FACTORS AFFECTING EXTENT OF HRIS ADOPTION AND ITS IMPACT …
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FACTORS AFFECTING EXTENT OF HRIS ADOPTION AND ITS IMPACT ON ORGANIZATION’S PERFORMANCE: MODERATING ROLE OF HR STAFF EXPERTISE By Nasim Qaisar (Registration No. F11C06P04004) Faculty of Management Sciences Riphah International University, Islamabad 2018
Transcript of FACTORS AFFECTING EXTENT OF HRIS ADOPTION AND ITS IMPACT …
FACTORS AFFECTING EXTENT OF HRIS ADOPTION AND ITS IMPACT ON
ORGANIZATION’S PERFORMANCE: MODERATING ROLE OF HR STAFF
EXPERTISE
By
Nasim Qaisar
(Registration No. F11C06P04004)
Faculty of Management Sciences
Riphah International University,
Islamabad
2018
FACTORS AFFECTING EXTENT OF HRIS ADOPTION AND ITS IMPACT ON
ORGANIZATION’S PERFORMANCE: MODERATING ROLE OF HR STAFF
EXPERTISE
By
Nasim Qaisar
Registration No. F11C06P04004
Supervised by
Prof. Dr. Khurram Shahzad
A thesis submitted in partial fulfilment of the requirements for the degree of
Doctor of Philosophy
In
Management Sciences
at
Riphah International University,
Islamabad, Pakistan
2018
RIPHAH INTERNATIONAL UNIVERSITY, ISLAMABAD
APPROVAL SHEET SUBMISSION OF HIGHER RESEARCH DEGREE THESIS
The following statement is to be signed by the candidates ‘supervisor (s), Dean/ HOD and must be received by the COE, prior to the dispatch of the thesis to the approved examiners. Candidate’s Name & Reg#: _______ Nasim Qaisar –& Registration No. F11C06P04004____
Programme Title: _______________ Ph.D.________________________________________
Faculty/Department: ____________ Management Sciences __________________________
Thesis Title: ___ Factors Affecting Extent of HRIS Adoption and its Impact on Organization’s Performance: Moderating Role of HR Staff Expertise ___
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Sign.____________________
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DECLARATION OF AUTHENTICATION
I certify that the research work presented in this thesis is to the best of my knowledge my own.
All sources used and any help received in the preparation of this dissertation have been
acknowledged. I hereby declare that I have not submitted this material, either in whole or in
part, for any other degree at this or any other institution.
Signature……………….
Plagiarism Undertaking by the PhD scholar
I solemnly declare that research work presented in this thesis titled “Factors Affecting Extent
of HRIS Adoption and its Impact on Organization’s Performance: Moderating Role of HR Staff
Expertise”
is solely my research work with no significant contribution from any other person. Small
contribution / help wherever taken has been duly acknowledged and that complete thesis has
been written by me.
I understand the zero tolerance policy of the HEC and Riphah International University
towards plagiarism. Therefore, I as an author of the above titled thesis declare that no portion
of my thesis has been plagiarized and any material used as reference is properly referred / cited.
I undertake that if I am found guilty of any formal plagiarism in that above titled thesis even
after award of PhD degree, the university reserves the right to withdraw/ revoke my PhD degree
and the HEC and the university has the right to publish my name on HEC/ University website
on which names of students are placed who submitted plagiarized thesis.
Student / Author Signature:__________________
Name: Nasim Qaisar
ACCEPTANCE CERTIFICATE
FACTORS AFFECTING EXTENT OF HRIS ADOPTION AND ITS IMPACT ON ORGANIZATION’S PERFORMANCE: MODERATING ROLE OF HR STAFF
EXPERTISE
By
Nasim Qaisar
Registration No. F11C06P04004
A thesis submitted in partial fulfilments of the requirements for the degree of
Doctor of Philosophy
In
Management Sciences
We accept this thesis as conforming to the required standard
Supervisor: Prof. Dr. Khurram Shahzad Sign. ______________________
External Examiner-1: Dr. Muhammad Razzaq Athar Sign. ______________________
External Examiner-2: Dr. Nadeem Ahmed Khan Sign. ______________________
HOD/Incharge: Prof. Dr. Khurram Shahzad Sign. ______________________
Dean: Prof. Muhammad Amanullah Khan Sign. ______________________
Acknowledgement
I would like to thank Allah Almighty for making this journey of mine possible. This has been
a long journey of exploring the gateways of knowledge. I encountered many upheavals and
experienced many satisfactions. A journey of research work can only be completed through the
consistent efforts and encouragements of supervisors, friends, and family members. I would
like to share some experience here, in my journey, there are some patches, where I lost control
but by the grace of Allah Almighty and prayers of loved ones, specially my colleague, Dr. Hafiz
Muhammad Ishaq, I was able to get back on track. My gratitude to all my friends, whom I
requested for guidance and I got sincere advice. My sincere thanks to my supervisor Prof. Dr.
Khurram Shahzad for guidance and support. In the end, I acknowledge those who prayed for
my success. May Allah bless them all.
Nasim Qaisar
Dedication
To my family, teachers & friends for genuine support
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CONTENTS
LIST OF TABLES ................................................................................................................ VI
LIST OF FIGURES/ILLUSTRATIONS ..............................................................................VIII
LIST OF EQUATIONS ........................................................................................................ IX
LIST OF ABBREVIATIONS ................................................................................................... X
ABSTRACT ......................................................................................................................... XI
1. INTRODUCTION ........................................................................................................ 1
1.1 BACKGROUND ..................................................................................................... 1
1.2 PROBLEM DEFINITION .......................................................................................... 5
1.3 RESEARCH QUESTIONS ......................................................................................... 8
1.4 RESEARCH OBJECTIVES ........................................................................................ 8
1.5 SIGNIFICANCE OF THE STUDY ............................................................................... 9
1.6 DEFINITION OF VARIABLES ................................................................................ 10
1.7 ORGANIZATION OF THESIS ................................................................................. 11
1.7.1 CHAPTER ONE: INTRODUCTION .......................................................................... 11
1.7.2 CHAPTER TWO: LITERATURE REVIEW ................................................................. 11
1.7.3 CHAPTER THREE: METHODOLOGY ...................................................................... 11
1.7.4 CHAPTER FOUR: FINDINGS ................................................................................. 11
1.7.5 CHAPTER FIVE: DISCUSSION AND CONCLUSIONS ................................................. 12
2. LITERATURE REVIEW .......................................................................................... 13
2.1 INTRODUCTION .................................................................................................. 13
2.1.1 HUMAN RESOURCE INFORMATION SYSTEM (HRIS) ............................................ 14
2.2 INNOVATION DIFFUSION THEORY (IDT) ............................................................. 16
2.2.1 INNOVATION CHARACTERISTICS ......................................................................... 18
2.2.1.1 RELATIVE ADVANTAGE ..................................................................................... 18
2.2.1.2 COMPATIBILITY ................................................................................................. 19
2.2.1.3 COMPLEXITY ..................................................................................................... 19
2.2.1.4 TRIAL-ABILITY .................................................................................................. 19
2.2.1.5 OBSERVABILITY................................................................................................. 20
2.2.2 TRI-CORE MODEL .............................................................................................. 21
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2.2.3 TECHNOLOGY ORGANIZATION ENVIRONMENT FRAMEWORK (TOE) .................... 22
2.2.4 DIFFUSION/ IMPLEMENTATION MODEL BY KWON AND ZMUD (1987).................... 23
2.3 ORGANIZATIONAL CHARACTERISTICS ................................................................ 24
2.3.1 TOP MANAGEMENT SUPPORT ............................................................................. 24
2.3.2 ORGANIZATION SIZE .......................................................................................... 25
2.4 ENVIRONMENTAL CHARACTERISTICS ................................................................. 26
2.5 HUMAN RESOURCE INFORMATION SYSTEM FUNCTIONS DISCUSSED BY DIFFERENT
AUTHORS IN LITERATURE. ................................................................................................. 27
2.6 EXTENT OF HUMAN RESOURCE INFORMATION SYSTEM ....................................... 37
2.6.1 STRATEGIC INTEGRATION .................................................................................. 39
2.6.2 PERSONNEL DEVELOPMENT ............................................................................... 40
2.6.3 COMMUNICATION AND INTEGRATION ................................................................. 40
2.6.4 RECORDS AND COMPLIANCE .............................................................................. 41
2.6.5 HUMAN RESOURCE ANALYSIS ............................................................................ 41
2.6.6 KNOWLEDGE MANAGEMENT .............................................................................. 42
2.6.7 FORECASTING AND PLANNING ............................................................................ 42
2.7 ORGANIZATION’S PERFORMANCE ....................................................................... 43
2.8 EXTENT OF HUMAN RESOURCE INFORMATION SYSTEM ADOPTION AND
ORGANIZATION’S PERFORMANCE ...................................................................................... 45
2.9 MODERATING ROLE OF HR STAFF EXPERTISE .................................................... 46
2.10 STUDY MODEL AND HYPOTHESES ...................................................................... 49
2.10.1 RESEARCH MODEL............................................................................................. 49
2.10.2 FORMULATION OF RESEARCH HYPOTHESES ........................................................ 50
2.11 CHAPTER SUMMARY .......................................................................................... 51
3. METHODOLOGY ..................................................................................................... 52
3.1 RESEARCH PHILOSOPHY AND PARADIGM ............................................................ 52
3.1.1 ONTOLOGY ........................................................................................................ 53
3.1.2 EPISTEMOLOGY ................................................................................................. 53
3.2 RESEARCH METHODS ......................................................................................... 54
3.3 RESEARCH APPROACHES .................................................................................... 55
3.4 RESEARCH DESIGN ............................................................................................ 55
3.4.1 TYPE OF STUDY ................................................................................................. 56
3.4.2 STUDY SETTING ................................................................................................. 56
3.4.3 EXTENT OF RESEARCHER INTERFERENCE ............................................................ 56
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3.4.4 TIME HORIZON .................................................................................................. 56
3.4.5 UNIT OF ANALYSIS ............................................................................................ 57
3.5 POPULATION AND SAMPLE .................................................................................. 57
3.5.1 POPULATION ...................................................................................................... 57
3.5.2 SAMPLING ......................................................................................................... 58
3.6 DEMOGRAPHICS OF RESPONDENTS ..................................................................... 58
3.6.1 CHARACTERISTICS OF THE RESPONDENTS ........................................................... 59
3.6.2 CHARACTERISTICS OF ORGANIZATIONS .............................................................. 63
3.7 SCALE AND MEASURES ...................................................................................... 66
3.7.1 INNOVATION CHARACTERISTICS ......................................................................... 68
3.7.2 ORGANIZATIONAL CHARACTERISTICS ................................................................ 68
3.7.3 ENVIRONMENTAL CHARACTERISTICS ................................................................. 68
3.7.4 EXTENT OF HUMAN RESOURCE INFORMATION SYSTEM ....................................... 68
3.7.5 HR STAFF EXPERTISE ........................................................................................ 69
3.7.6 ORGANIZATION’S PERFORMANCE ....................................................................... 70
3.8 PROCEDURE OF DATA COLLECTION .................................................................... 70
3.9 RESEARCH INSTRUMENT .................................................................................... 71
3.9.1 PILOT TESTING OF THE INSTRUMENT .................................................................. 71
3.9.2 RESPONSE RATE ................................................................................................ 73
3.9.3 DATA CODING AND DATA ENTRY ....................................................................... 73
3.9.4 NORMAL DISTRIBUTION (ASSUMPTION OF NORMALITY) ..................................... 73
3.9.5 EXAMINATION OF MULTICOLLINEARITY AMONG PREDICTORS ............................ 74
3.9.6 OUTLIER INFLUENCE CASES ............................................................................... 76
3.10 DATA ANALYSIS PROCEDURE............................................................................. 76
3.11 VALIDITY OF THE INSTRUMENT .......................................................................... 76
3.12 RELIABILITY OF THE INSTRUMENT ...................................................................... 77
3.13 CHAPTER SUMMARY .......................................................................................... 82
4. FINDINGS ................................................................................................................. 83
4.1 DESCRIPTIVE STATISTICS OF DATA ..................................................................... 83
4.2 ANALYSIS OF VARIANCE (ANOVA) ................................................................... 84
4.2.1 ANOVA: EXTENT OF HRIS ADOPTION BY DEMOGRAPHICS DATA ...................... 84
4.2.1.1 EXTENT OF HRIS ADOPTION BY GENDER ........................................................... 85
4.2.1.2 EXTENT OF HRIS ADOPTION BY EDUCATION ...................................................... 85
4.2.1.3 EXTENT OF HRIS ADOPTION BY AGE OF RESPONDENTS ...................................... 86
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4.2.1.4 EXTENT OF HRIS BY DESIGNATION .................................................................... 86
4.2.1.5 EXTENT OF HRIS ADOPTION BY EXPERIENCE IN CURRENT DESIGNATION ............ 87
4.2.1.6 EXTENT OF HRIS ADOPTION BY EXPERIENCE IN CURRENT ORGANIZATION ......... 87
4.2.1.7 EXTENT OF HRIS ADOPTION BY TOTAL PROFESSIONAL EXPERIENCE .................. 88
4.2.1.8 EXTENT OF HRIS ADOPTION BY ORGANIZATION INDUSTRY ................................ 89
4.2.1.9 EXTENT OF HRIS ADOPTION BY LIFE OF BUSINESS ............................................. 90
4.2.1.10 EXTENT OF HRIS ADOPTION BY NUMBER OF EMPLOYEES IN HR DEPARTMENT ... 90
4.2.1.11 EXTENT OF HRIS ADOPTION BY NUMBER OF COMPUTERS IN HR DEPARTMENT... 91
4.2.1.12 EXTENT OF HRIS BY AGE OF HRIS .................................................................... 92
4.3 CORRELATION ANALYSIS OF MAIN VARIABLES .................................................. 92
4.4 REGRESSION ANALYSIS COMBINED EFFECTS ...................................................... 94
4.4.1 REGRESSION ANALYSIS AND HYPOTHESES TESTING............................................ 95
4.4.2 HYPOTHESIS 1: INNOVATION CHARACTERISTICS AS PREDICTOR OF EXTENT OF
HRIS ADOPTION. .............................................................................................................. 95
4.4.3 HYPOTHESIS 2: ORGANIZATIONAL CHARACTERISTICS AS PREDICTOR OF EXTENT OF
HRIS ADOPTION ............................................................................................................... 96
4.4.4 ANALYSIS OF VARIANCE AND HYPOTHESIS TESTING. .......................................... 96
4.4.5 HYPOTHESIS 3: ENVIRONMENTAL CHARACTERISTICS AS PREDICTOR OF EXTENT OF
HRIS ADOPTION. .............................................................................................................. 97
4.4.6 HYPOTHESIS 4: EXTENT OF HRIS ADOPTION AS PREDICTOR OF ORGANIZATION’S
PERFORMANCE .................................................................................................................. 98
4.4.7 MULTIPLE REGRESSION ANALYSIS MODERATING EFFECT AND COMBINE EFFECT.
99
4.4.8 HYPOTHESIS 5: HR STAFF EXPERTISE AS PREDICTOR OF ORGANIZATION’S
PERFORMANCE. ................................................................................................................. 99
4.5 SUMMARY OF RESULTS .................................................................................... 101
5. DISCUSSION AND CONCLUSIONS ..................................................................... 102
5.1 DISCUSSION ON FINDINGS ................................................................................ 102
5.2 CONTRIBUTIONS OF THIS STUDY ....................................................................... 105
5.3 MANAGERIAL IMPLICATIONS ............................................................................ 106
5.4 LIMITATION OF STUDY ..................................................................................... 108
5.5 IMPLICATIONS FOR FUTURE RESEARCH ............................................................. 108
5.6 CONCLUSION ................................................................................................... 109
REFERENCES ................................................................................................................. 111
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APPENDIXES .................................................................................................................. 131
A- QUESTIONNAIRE .............................................................................................. 132
B- CODING SHEET ............................................................................................... 137
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LIST OF TABLES
Table 1: Functions of HRM used in HRIS ............................................................................. 29
Table 2: Gender of Respondents ........................................................................................... 59
Table 3:Education of Respondents ....................................................................................... 60
Table 4:Age of Respondents ................................................................................................. 60
Table 5:Designation of Respondents .................................................................................... 61
Table 6:Experience in current designation of respondents .................................................... 61
Table 7:Experience in current organization of respondents .................................................. 62
Table 8:Total professional experience of Respondents .......................................................... 62
Table 9:Organization industry of responding organization ................................................... 63
Table 10:No. of years in business of responding organization .............................................. 64
Table 11: No. of employees in HR department of responding organization ........................... 64
Table 12:No. of computers in HR department of responding organization ............................ 65
Table 13:Age of HRIS of responding organization ................................................................ 65
Table 14:Summary of Scales ................................................................................................ 67
Table 15:Skewness and Kurtosis .......................................................................................... 74
Table 16:Tolerance and VIF of the research model core variables ....................................... 75
Table 17: Analysis of person’s product moment.................................................................... 77
Table 18:Reliability of IC scale ............................................................................................ 78
Table 19:Reliability of OC scale........................................................................................... 79
Table 20:Reliability of EC scale ........................................................................................... 79
Table 21:Reliability EXT Scale ............................................................................................. 80
Table 22:Reliability of STFEXP Scale .................................................................................. 81
Table 23:Reliability OP scale ............................................................................................... 81
Table 24:Descriptive Statistics of study variables ................................................................. 84
Table 25: T stat extent of HRIS by gender ............................................................................ 85
Table 26: One-way ANOVA: extent of HRIS by education .................................................... 86
Table 27: One-way ANOVA: extent of HRIS adoption by age of respondents ........................ 86
Table 28: One-way ANOVA: extent of HRIS adoption by designation ................................... 87
Table 29: One-way ANOVA: extent of HRIS adoption by experience in current designation . 87
Table 30: One-way ANOVA: extent of HRIS adoption by experience in current organization88
Table 31: One-way ANOVA: extent of HRIS adoption by total professional experience ........ 88
Table 32: One-way ANOVA: extent of HRIS adoption by organization industry ................... 89
Table 33: One-way ANOVA: extent of HRIS adoption by life of business .............................. 90
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Table 34: One-way ANOVA: extent of HRIS adoption by number of employee in HR
department ........................................................................................................................... 91
Table 35: One-way ANOVA: extent of HRIS adoption by number of computers in HR
department. .......................................................................................................................... 91
Table 36: One-way ANOVA: extent of HRIS adoption by age of HRIS .................................. 92
Table 37:Correlations, and Reliabilities ............................................................................... 93
Table 38:Regression Analysis Direct Effects ........................................................................ 95
Table 39: One-Way ANOVA Organization size by extent of HRIS adoption .......................... 96
Table 40: Combined effect and moderating regression analysis of extent of HRIS adoption,
HR staff expertise and organization’s performance .............................................................. 98
Table 41:Combined effect and moderating regression analysis of extent of HRIS adoption, HR
staff expertise and organization’s performance .................................................................... 99
Table 42:Summary of results .............................................................................................. 101
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LIST OF FIGURES/ILLUSTRATIONS
Figure 1: HRIS Functions .................................................................................................... 39
Figure 2: Research model of the study .................................................................................. 49
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LIST OF EQUATIONS
Equation 2: Total response rate ........................................................................................... 73
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LIST OF ABBREVIATIONS
EC environmental characteristics
EHRM electronic human resource management
HRIS human resources information systems
HR human resources
HRM human resource management
IC innovation characteristics
ICT information & communication technologies
IDT innovation diffusion theory
IOE innovation organization environment
IT information technology
IS information systems
MIS management information systems
OC organizational characteristics
OP organization performance
TOE technology organization environment
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ABSTRACT
The human resource information system is a class of specialized applications that were designed
to improve management of an organization’s human assets. Human resource information
system supports the alignment of strategic outcomes which are essential for achieving sustained
competitive advantage. Resultantly, human resource information system plays a major role in
enhancing the organization’s performance, and impact its bottom line. The deployment of an
effective human resource system is part of a holistic approach, partial implementation does not
yield the same results.
The main construct of interest for this study was the “extent of HRIS adoption”. The model that
was developed and elaborated upon in this study incorporates the ideas of Mayfield, who
provided a functional perspective of human resource information system, going beyond
focusing on automating the various activities performed in human resources. The model then
tests this impact of the extent of HRIS adoption on organization’s performance. Furthermore,
the model developed for this study also incorporated the antecedents of the extent of HRIS
adoption. In order to an all-inclusive model, the moderating role of HR staff expertise was also
added to the model for the current study.
Data was collected through a self-administered questionnaire. The sample (n = 108) was drawn
from organizations in the capital city of Pakistan. One-way Analysis of Variance was used to
isolate the effect of contextual factors at the organizational and respondent level. Two
organizational and two respondent level factors caused a significant variation in extent of HRIS
adoption and one organizational factor caused variation in organization’s performance.
Correlation analyses indicated the presence of a significant positive association between the
antecedent and the outcome variable. Regression analysis was also performed and the results
from this also confirmed the positive influence of innovation and environmental characteristics
on the extent of HRIS. The extent of HRIS positive influence on organization’s performance.
The results of the moderation analysis of the effect of HR staff expertise was not confirmed,
although HR staff expertise was found to have a significant effect on organization’s
performance.
The results from this study contribute to the literature on extent of HRIS adoption in three ways
(a) provides a different operationalization of the construct of extent of HRIS, (b) it examines
the relationship between extent of HRIS, and its antecedents, (c) extent of HRIS adoption also
tended to predict organization’s performance and its implications for managers and researchers
have also been suggested.
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CHAPTER 1
INTRODUCTION
1.1 Background
Conventionally computer technology was used only as an information processing tool in
business organizations. With the passage of time, globalization, market competition and
requirements of fast information necessitated the transformation of traditional information
processing tools into computerized information systems (Ward & Peppard, 2002). Buzkan
(2016) expressed that nowadays organizations are facing challenges in performing their
functions and they are required to adopt innovations in their business processes.
In the 1960s, human resource (HR) department of an organization started using Information
Technologies (ITs) for managing their activities. However, their use was limited to maintaining
the record of personnel as part of a centralized Management Information System (MIS)
(DeSanctis, 1986; Tannenbaum, 1990). The inception of IT gets its root in various functions
and departments of an organization except the HR department, where IT was given less
attention in managing activities (Marler & Fisher, 2013). While it has been highlighted that IT
plays a key role in the organization in a day to day operations, and getting efficiency and
effectiveness in work activities (Fichman & Kemerer, 1993).
In organizations, information and human resources are two important strategic assets
(Martinsons, 1994), which required to be managed effectively with the use of ITs for getting
maximum benefits from them. But unfortunately, many organizations failed in assuming
benefits of IT applications in HR departments. One of the important reasons is the traditional
thinking of managers that HR departments are not a strategic player and having no role in
achieving organizational success, that is why the process of implementing technology in HR
was slow (Dunivan, 1991). But with the challenges of the globalized economy, organizations
are also required to bring innovation into their work operations. IT is an enabler of introducing
innovations in organizational processes (Hameed, Counsell, & Swift, 2012).
According to Ceric and Krivokapic-Skoko (2016) organizations introducing new technology in
their work process is treated as innovation, further, the author relating adoption of new
technology and innovation as interchangeably. Organizations who are incorporating IT in
managing their HR functions usually adopts Human Resource Information Systems (HRIS).
HRIS, an integrated framework of IT and HR functions, provides benefits not only as automated
HR functions but also provide organizations an opportunity to reducing the cost of functions
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performed and achieving organizational strategic outcomes which ultimately enhances the
organization’s performance.
HRIS allows organizations to manage numerous functions of the HR department with the use
of technology both in hardware and software forms (DeSanctis, 1986).
After IT’s the introduction in the HR process, HRIS gained popularity not only in organizations
but also among the academic researchers. HR practitioner and researchers have described HRIS
in numerous ways depending on the approaches to explore the system’s effectiveness, the
context of investigation and outcomes from the use of the system. According to Kavanagh and
Thite (2009), HRIS is a type of system which integrates HR management functions with IT
applications, or simply, it can be said that HRIS is an IT backed HRM system (Alam, Masum,
Beh, & Hong, 2016; Ruel, Magalhaes, & Chiemeke, 2011).
Buzkan (2016) in his study the role of HRIS in an organization, concluded that HR is an
important function in an organization that plays a significant role in achieving organizational
success. Organizations are required to manage HR resources in a way to achieve organizational
strategic outcomes. For this purpose, HRIS plays a vital role not only in maintaining
organizational HR information but it also focuses on achieving organizational strategic
outcomes. Specifically, HRIS was designed to support the HR functions in HR departments
within organizations (Dunivan, 1991).
HRIS implementation in organizations raised multiple issues in managing HR and IT itself.
Initially, in organizations, HR personnel were hesitant about the involvement of centralized
MIS staff in their work routine due to their lacking in use of IT. HR functions were performed
through a specialized information system personnel and a small group of IS experts was
managing the activities of the department (DeSanctis, 1986).
Moorthy and Polley (2010) also acknowledged that the knowledge about ICT plays important
role in the utilization of IS in organizations. Whereas, lack of IT expertise of HR staff can be a
major obstacle in the adoption of HRIS in breadth and depth. Therefore, it is important that HR
staff should have strong IT skills for use of HRIS in order to get maximum benefits from the
system (Troshani, Jerram, & Rao, 2011).
According to Moorthy and Polley (2010), knowledge about ICT play important role in
achieving a firm’s performance. Thong (1999) argued that all employees in HR departments
should have expertise and skills of HRIS to complete their tasks. Hence it can be summarized
that the reasons behind underutilization of HRIS for integrating all HRM functions may be due
to the hesitation of adoption of the systems. The low adoption rate can be due to lack of technical
professionals who can understand the use of HRIS, and realization of benefits which can be
achieved in terms of enhanced performance.
3
Numerous evidence are available where the research has been conducted on the utilization of
HRIS in different functions of HRM in isolation in the shape of different modules, for example
payroll & benefits, e-recruitment, e-training, e-learning (Tursunbayeva, Pagliari, Bunduchi, &
Franco, 2016; Keim & Weitzel, 2008; Parry & Wilson, 2009; Beulen, 2009). In spite of
extensive research on the context, researchers have highlighted a gap in the practices of HRIS
in multiple functions of HRM (Stone & Dulebohn, 2012) as well as support from top
management for implementing automated systems within HR departments (Kovach & Cathcart,
1999).
Literature also reported that many organizations are using computerized HR systems at limited
level due to the number of factors such as; complexity, fear of losing control over activities
during functionally and operationally maintained and managed by organizational centralized IS
department and confidentiality issues. Such issues can be minimized by the active involvement
of HR professionals and giving the control of HRIS to HR department personnel (Buzkan,
2016).
Since literature reported that HRIS is a form of an innovation in organizations (Ceric &
Krivokapic-Skoko, 2016; Buzkan, 2016). This innovation can have an impact on various
organizational functions such as innovation in HRM processes which can ultimately enhance
organization’s performance (Ruel, Bondarouk, & Looise, 2004).
Damanpour (1987) argued that managers are keen to improve the performance of their
organization, for this purpose they try to work effectively and efficiently for bringing innovation
in their work processes. Rogers (2004) has defined an innovation as “an idea perceived as new
spreads …” (p 13). However, it is not necessary that this perceived idea is new for everyone,
rather, it is new for the adopting organization.
Martinsons (1994) said that large organizations are more likely to adopt the use of IT resources
in HR at a greater extent. Buzkan (2016), Ball (2001), and Phahlane (2017) also endorsed that
HRIS adoption also depends on organization size. Whereas, some authors argue that
organization size does not impact the utilization of HRIS. These contradictory findings suggest
that the organization size need to further investigate with reference to the extent of HRIS
adoption. The HRIS applications and its extensive adoption lead to develop an opinion that the
purpose of using IT in HR management is to improve the efficiency of an organization by
providing quality information in time that helps ultimately in organizational decision making
(Ngai & Wat, 2006; Sadiq, Khan, Ikhlaq, & Mujtaba, 2013). Becker and Gerhart (1996),
Khashman and Khashman (2016) also, mentioned that timely and accurate HR decisions may
have an influence on organization’s performance.
4
HRIS is a combination of technology and HR processes to managing HRM. In literature
reviewed it can be seen that various names like e-HR, e-HRM, HR intranet, web-based HR,
computer-based human resource management systems (CHRIS), and HR portals have been
used to describe the IT implementation in HR functions (Marler & Fisher, 2013; Ruel,
Bondarouk, & Looise, 2004; Ruel, Bondarouk, & Van der Velde, 2007; Findikli & Beyza
Bayarcelik, 2015). HRIS is defined as “a system used to acquire, store, manipulate, analyze,
retrieve and distribute pertinent information about an organizational human resource”
(Tannenbaum, 1990, p.27).
Kavanagh and Thite (2009) express that these names like e-HR are a philosophy of delivering
the HR services without the involvement of HR professionals through the HR portal. Ruel,
Bondarouk, and Looise (2004) says that the distinction of HRIS with other variants are in term
of the system working like HRIS is limited to those individuals who are working in or with the
organization's HR function, whereas other variants are utilized by other members of the
organization as well as staff and managers.
The implementation of IT in HRM functions are challenging initiatives for management, it has
been observed that most of the time IT implementation remained unsuccessful because of
multiple organizational internal issues (Othman & Teh, 2003). Rogers (1995) argued that the
acceptance and adoption of new innovation in organizations in piecemeal are higher than the
implementation in one go. The success of the newly implemented IT systems depends on the
extent of its adoption. Likewise, the extent of HRIS adoption and acceptance depend on
different factors like, innovation, organizational, and environmental.
The factors affecting the extent of HRIS adoption may be categorized in innovation factors,
organizational factors, and environmental factors (Jeyaraj, Rottman, & Lacity, 2006). It has
been pointed out that these factors are the best predictors while exploring the “extent” of IT
implementations in organizations (Chong, Lin, Ooi, & Raman, 2009). These factors are based
on Innovation Diffusion Theory (IDT) proposed by Rogers (Rogers, 1995) and Technology-
Organization-Environment (TOE) Model proposed by Tornatzky (Tornatzky & Fleischer,
1990). The researcher has identified that more research is to be conducted to explore how these
factors that can predict the extent of HRIS adoption. Baker (2012) discussed that technology,
organization, and environmental factors may be used in conjunction with other theories in order
to predict factors affecting adoption of innovation.
This distinction makes the importance of HRIS as a strategic partner in achieving a strategic
outcome of an organization (Kovach, Hughes, Fagan, & Maggitti, 2002). Use of HRIS allows
the HR staff to become a strategic player in an organization (Hussain, Wallace, & Cornelius,
2007). In the same vein, this distinction realized the importance of HR staff expertise. Al-
5
Mobaideen, Allahawiah, and Basioni (2013) expresses that the HR staff expertise plays
important role in working of HRIS, if the HR manager and staff are competent then HRIS will
work well. So, it is important to explore the role of HR staff expertise for predicting whether it
has any role in relations of HRIS achieving the strategic outcome of any organization by using
the extent of HRIS adoption.
According to the DeCenzo and Robbins (2005) staffing, training, motivation, maintenance are
major functions performed in the domain of HRM. Staffing includes the strategic human
resource planning, recruiting and selecting; training includes: orientation, and employee
training; motivation include: performance appraisals, rewards and compensation, and employee
benefits; maintenance includes: safety and health, communications and employee relations.
Authors have studies different functions of HRIS (DeSanctis, 1986; Ngai & Wat, 2006; Beulen,
2009; Mishra & Akman, 2010; Teo, Soon, & Fedric, 2001; Mayfield, Mayfield, & Lunce,
2003). But still lacking guidance regarding HRIS theory and practice in cumulative literature
exist in the context of extent of HRIS adoption. To have an understanding about the concept of
extent of HRIS adoption and to provide strong guidance to practitioners by explaining the
concept of the extent of HRIS adoption, that needs to be addressed so that a guideline may be
proposed for the practitioners by explaining the concept of HRIS (Marler & Fisher, 2013). In
the literature of innovation, the dominant part has been discussed regarding factors affecting
the extent of adoption (Parry & Wilson, 2009) but little literature is available on the impact of
extent of adoption on organization’s performance.
1.2 Problem Definition
Utilization of IT in HR management in the past, the 1960s, was aimed initially to maintain a
record of personnel department (DeSanctis, 1986). However, the need for further improvement
in the systems is vogue necessitated gradual progression in the use of information technology
due to contemporary practices in the business process for achieving organization’s
performance, comes in the shape of human resource information system. HRIS is a type of IS
and it is relatively new concept inculcating information technology in the HR functions
(Kavanagh & Thite, 2009; Hussain, Wallace, & Cornelius, 2007; Alam, Masum, Beh, & Hong,
2016). According to Teo, Soon, and Fedric (2001) use of information technology in HRM
functions just improved the efficiency without effectiveness just because of lack of clarity of
the concept of HRIS and the functions involved in developing HRIS.
Globally the adoption of HRIS in organizations is satisfactory but the extent of HRIS adoption
varies in different contexts (Kovach & Cathcart, 1999). HRIS literature revealed that strategic
outcomes of organizations are linked with the full extent of adoption of HRIS. Lantara (2016)
6
argued that the organization’s performance is the strategic outcome, that can be achieved by
successfully implementing HRIS and its utilization at a large extent. The reasons for using
performance measure is because one of the conception and operationalization of this measure
is directly targeted to the profit of an organization which could be achieved through the adoption
of HRIS, that is the ultimate objective of the stakeholders and shareholders (Boselie, Dietz, &
Boon, 2005).
Crossan and Apaydin (2010), Mone, McKinley, and Barker (1998) supported that the use of
innovation in an organization is an important determinant of organization’s performance. The
use of IS/ IT in organizational functions is the best enabler for attaining this objective, whereas
HRIS is IT backed HRM (Townsend & Bennett, 2003; Ruel, Magalhaes, & Chiemeke, 2011).
Notwithstanding, the fact that technology-driven systems always pass through improvement
and value addition phases, still little evidence is available in the literature describing the extent
of HRIS adoption and lacking guidance how actually HRIS affects the organization’s
performance.
Few studies have been carried out in the Pakistani context, these studies have been focusing the
impact of HRIS in performance appraisal and adoption of HRIS for record keeping of staff
(Ahmer, 2013). No study found that explain the concept of HRIS in totality. In the same vein,
little evidence exists describing the extent of HRIS adoption and how actually HRIS adoption
affects the organization’s performance (Qaisar, Shahzad, & Arif, 2018). Crossan and Apaydin
(2010) highlighted the gap between the adoption of innovation and organization’s performance.
Literature on the use of information system in human resource reveals that the extent of HRIS
adoption varies organization to organization (Kovach & Cathcart, 1999; Parry, Tyson, Selbie,
& Leighton, 2007; Chae, Prince, Katz, & Kabst, 2012; Teo, Soon, & Fedric 2001), it is because
of lacking HR staff knowledge and expertise of using HRIS. IT skills of staff may help in using
HRIS to its full extent (Haines & Petit, 1997; Al-Mobaideen, Allahawiah, & Basioni, 2013).
So, it is required to address the factors responsible for the extent of HRIS adoption.
The extent of HRIS adoption is linked with the overall objective of information which is
deemed necessary. The germane of the issue revolves around the “extent of HRIS adoption”
which needs to be addressed besides enhancing the scope of HRIS entailing coverage of the
factors affecting the organization’s performance. Kassim, Ramayah, and Kurnia (2012),
Premkumar and Roberts (1999), Lantara (2016), Jeyaraj, Rottman, and Lacity (2006) described
that the extent of HRIS adoption depends on various factors, which includes innovation
characteristic, organizational characteristic, and environmental characteristic. These factors
studied in the context of developed countries (Premkumar & Roberts, 2005; Premkumar &
Roberts, 1999), whereas developing countries sharing different perspective. Chakraborty &
7
Mansor (2013) highlighted the importance to study these factors in the context of developing
countries.
Tansley and Watson (2000) also indicated that HRIS research lacks theoretical considerations.
To have an understanding about the concept of extent of HRIS adoption and to provide strong
guidance to practitioners by explaining the concept of the extent of HRIS adoption, the
importance of HR staff expertise, factors affecting HRIS adoption and how extent of HRIS
adoption affects the organization’s performance is to be investigated (Marler & Fisher, 2013).
According to Magalhaes and Ruel (2007) in concluding remarks on HRIS, there should be a
need to broaden and deepen the research of HRIS.
In Pakistani context, studies were conducted in HRIS in context of its impact on organizations
productivity (Awan & Sarwar, 2014), enhancing HR functions using HRIS use (Latif, Ullah,
Din, & Anjum, 2014; Hanif, 2011), factors influencing decision making process in HRIS
adoption (Hanif, et al., 2014) administrative and strategic impact of HRIS in Pakistan (Khan &
Anwar, 2012) HRIS as knowledge management (Kazmi & Naaranoja, 2014). Awan and Sarwar
(2014) also, highlighted that in Pakistani context research on HRIS has been conducted in case
studies approach only. Researchers have found out that in Pakistan there are very few
organizations which have implemented HRIS so this can be a reason of lack of research studies
on the topic (Ahmer, 2013).
Saleem (2012) in his article highlighted that the factors should be explored that become
impediments in the adoption of HRIS in Pakistan. Furthermore, this also needs to be explored
what is the relationship of HRIS and profitably of an organization. Keeping in view the current
status of research on HRIS in the Pakistani context, it is imperative to identify the factors
responsible for the HRIS adoption and its yielded benefits, hence this explanatory study is
designed to examine the relationship between extent of HRIS adoption and its impact on
organization’s performance in the context of Pakistan.
8
1.3 Research Questions
According to Leedy and Ormrod (2010), research questions may generally originate in sub-
problems, and have one to one relationship with sub-problem. According to Creswell (2013),
research questions deal with the relationship between variables of interest in a way to express
the purpose of the study. Research question doesn’t address the speculative answer but guides
the researcher’s efforts for selecting the proper data gathering and analysis techniques.
1. What is the effect of innovation characteristics, organization characteristics,
environmental characteristics on extent of HRIS adoption.
2. Is there statistically significant relationship between extent of HRIS and organization’s
performance? if so, what is it.
3. What is the effect of extent of HRIS adoption on Organization’s performance.
4. Does HR staff expertise moderate the relationship between extent of HRIS adoption and
organization’s performance?
1.4 Research Objectives
Research objectives followed by the research questions which expresses the researcher’s clarity
towards the purpose and direction of research (Saunders, Lewis, & Thornhill, 2016). The
objective of this study is to build a nexus between the factors affecting the extent of HRIS
adoption followed by the impact assessment. The study further explains the extent to which and
how the extent of HRIS has an impact on an organization’s performance. The explanation of
“how” will provide guidance to the practitioner to minimize the gaps between theory and
practice of extent of HRIS adoption. The relationship between the variables is illustrated in
figure 2.
Specific objectives of the study are as follows:
1. To examine the effect of innovation characteristics, organization characteristics,
environmental characteristics on extent of HRIS adoption.
2. To examine the impact of extent of HRIS adoption on organization’s performance.
3. To find whether HR staff expertise moderate the relationship of extent of HRIS adoption
and organization’s performance.
4. To have an understanding about the concept of extent of HRIS adoption.
In summary, the novelty and contribution of this thesis is distinctive contribution in the field of
HRIS by incorporating the approach of extent of HRIS with reference to the functional
description given by Mayfield (Mayfield, Mayfield, & Lunce, 2003). To the best of my
understanding, no previous study has operationalized extent of HRIS based on the functional
description proposed by (Mayfield, Mayfield, & Lunce, 2003). Furthermore, most of the
9
previous research on the extent of HRIS adoption was conducted from the context of developed
countries, whereas the sample for the present study was drawn from organizations in a
developing country. Further, determining to what extent, extent of HRIS adoption impacts the
organization’s performance in non-western sample.
1.5 Significance of the Study
In HR management, HRIS is treated an essential part, that has an influence on organizations. it
seems essential and has the impact on an organization’s performance. HRIS research is lacking
in theoretical consideration (Tansley & Watson, 2000) in term of adoption of HRIS in
organizations. The concept of extent of HRIS adoption is relatively new concept in HRIS
research. According to (Qadir & Agrawal, 2017) despite the importance of the HRIS, not all
organizations able to use HRIS optimally. This study makes valuable contribution in the field
of human resources information systems in general and specially explaining the concept of
HRIS in term of “extent of HRIS”. Previous studies of extent of HRIS, the authors differently
operationalized the concept like few studies carried out on extent of HRIS in term of No. of
computers allocated for use of HR staff, No. of applications used by an organization mainly
focused on no of application and no of computers ( Teo, Soon, & Fedric, 2001). Considerable
gaps in HRIS theory and practice in cumulative literature exist that needs to be addressed, in
order to provide strong guidance to practitioners by explaining the concept of HRIS and how
extent of HRIS affects organization’s performance (Marler & Fisher, 2013).
The research framework of this study was based on innovation adoption literature
predominantly influenced by Innovation diffusion theory (Rogers, 1995) which was utilized to
hypothesized that what factors affecting the extent of HRIS adoption. Many authors discussed
the adoption of HRIS as innovation, because it is a new idea in term of implementation of
information technology in HR department in the shape of HRIS. Jeyaraj, Rottman, and Lacity
(2006) discussed that innovation diffusion theory is used at individual level adoption of IS/ IT
as well as at organizational level adoption. The focus of the current study is adoption HRIS at
the organizational level. The reason for underpinning IDT is because it deals with both types of
adoptions i.e. individual and organization level. There has been no significant research with
regard to the use of IDT specifically with HRIS adoption and extent of HRIS adoption in
organizations (Parry & Wilson, 2009).
Although HRIS as a concept has been adopted globally, however on implementation side its
coverage remains partial in some functions of human resource and to a greater extent in large
organizations. However, its applicability is witnessed as marginal in the case of Pakistan.
Insufficient literature is available that describes the extent of HRIS adoption in a local context,
10
necessitating Pakistani context being explored to contribute to the international body of
knowledge.
In order to fill the gap in theory and to provide the strong guidance to the practitioners, it is
imperative to study the factors affecting the extent of HRIS adoption and how extent will affect
organization’s performance. Little evidence is available on adoption of HRIS in developing
countries. On the other hand the HRIS is heavily discussed area with different buzzwords, but
the evidence on extent of HRIS adoption from western and non-western counties is still limited.
Chakraborty and Mansor (2013) also suggest that the adoption of HRIS and its antecedent
factors should be studied in other parts of the world. This highlight the contextual importance
of the use of IS/IT in HR, so that it may contribute to the international body of knowledge on
extent of HRIS adoption, this is another significant accept of this study.
1.6 Definition of Variables
The operational definitions of independent, moderating and dependent variables depicted in
research framework Figure2. The operational definitions of under study variables are as under.
Human Resource Information System: A HRIS is defined as “a system used to acquire, store,
manipulate, analyze, retrieve and distribute pertinent information about an organizational
human resource” (Tannenbaum, 1990).
Innovation Characteristics: Rogers (1995) it refers to innovation characteristics suggested by
Rogers as an aggregated impact.
Organizational Characteristics: Premkumar and Roberts (1999) it includes top management
support, organization size. Organization size is measured as No. of full time employees and
estimated annual revenue.
Environmental Characteristics: Tornatzky and Fleischer (1990) it refers to the competitors,
rivals in the market with respect to industry.
Extent of HRIS adoption: It refers to what extent organization as a whole using HRIS
functionalities. HRIS functions includes strategic integration, personal development,
communication and integration, records and compliance, human resource analysis, knowledge
management, and forecasting and planning (Mayfield, Mayfield, & Lunce, 2003).
HR Staff Expertise: Thong (1999) and Panayotopoulou, Vakola, and Galanaki (2007) refers
as all employees in HR departments who have the expertise and skills of using HRIS to
complete their tasks.
11
Organization’s Performance: It refer to the subjective measures of organization’s
performance with respect to the rival in the industry. The organization’s performance was
measured by using four dimensions which includes market share, sales revenue, innovation and
profitability (Singh, Darwish, & Potocnik, 2016; Lee & Choi, 2003).
1.7 Organization of Thesis
The organization of the thesis includes five chapters along with references, glossary and
appendixes. The detail of each chapter is given below.
1.7.1 Chapter One: Introduction
This chapter includes the background of the study, problem definition and research gap,
research questions, research objectives, the significance of the study, definition of variables,
limitations of the study, ethical consideration, and organization of thesis.
1.7.2 Chapter Two: Literature review
The relevant literature review of this study is presented in this chapter. Starting from defining
the concept of HRIS prevailing in the domain use of information technology in human resources
highlighted by most published authors in top journals. Then, identify and discuss the theories/
models presented on the subject matters. Discussion of the factors like innovation, organization,
and environment characteristics with reference to the extent of HRIS adoption also presented.
Further, discussion on extent of HRIS adoption, organization’s performance and linkages with
organization’s performance, relevant literature on HR staff expertise and moderating role of
HR staff expertise presented as a part of the literature review. Followed by chapter 2, in the
end, the research framework and formulation of research hypotheses are presented.
1.7.3 Chapter Three: Methodology
Chapter 3 provides the details on the choice of research philosophy, research design, methods
and basic assumptions relating to underlying data. The chapter will present the demographics
of the respondents, and responding organizations. Scale and measures used for data collection,
a brief description of the constructs, procedure of data collection, a basic assumptions of the
data: validity and reliability of the instrument, response rate, and data analysis techniques.
1.7.4 Chapter Four: Findings
Chapter 4 presents the descriptive statistics of study variables, data analysis is carried out using
various statistical analysis including ANOVA, Correlation and regression analysis. Data and
the results are presented step by step according to the hypotheses of the study. At the end,
summary of hypotheses presented.
12
1.7.5 Chapter Five: Discussion and Conclusions
Chapter five presents the discussion on finding according to each research questions of the
study. After discussion, managerial implications are recommended for practitioners are marked,
limitations of the study are recorded along with the implications for future research. At the end
conclusion is presented.
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CHAPTER 2
LITERATURE REVIEW
2.1 Introduction
This chapter presents a review of the literature related to the current study variables which
include the antecedents of extent of HRIS adoption i.e. innovation characteristics (IC),
organizational characteristics (OC) and environmental characteristics (EC); the main study
variable extent of HRIS adoption, organization’s performance and HR staff expertise. The main
objective of reviewing the relevant literature is to establish theoretical foundations of a key
relationship among the variables presented in figure 2 and to explore the research questions of
this study.
The literature reviewed for this study is presented in different sections of this chapter. The first
section covers the relevant studies that introduce the concepts of Human resource information
system (HRIS), innovation theories and the factors affecting the extent of HRIS adoption, extent
of HRIS, organization’s performance in relation with extent of HRIS adoption and moderating
role of HR staff expertise. The second section covers the research model and hypotheses.
Chapter summary presented the last section of this chapter.
According to Kavanagh and Thite (2009), HRIS is a combines the HRM functions and IT. The
use of Information Technology (IT) in human resource functions is endless. IT is the enabler
for so many superior performances in different functions of business management. Some of the
organizations using IT for computerizing HR functions to achieve superior performance in
human resources department, whereas, information technology is not only used for gaining
superior performance but also has changed the processes and practices of HR. Nowadays HR
functions can be supported by information technology because the technology expedites the
speed of HR transactions. HR professionals, who realized that technology can play an important
role in changing insight HR in an environment where trends are changing at a fast pace. These
HR professionals are more relying on technology by equipping their HR with IT.
Human resource functions equipped with latest available IT resources form a shape called
HRIS, which is, now a day, treated an essential part of the human resource department. HRIS
has established an independent existence like other entities or systems working in organizations.
DeSanctis (1986) describes HRIS as an independent system which does not treat as a shared
part of centralized Management information systems (MIS). In relevant literature in the field of
management sciences, information technology management and human resource management,
14
various nomenclature have been used for equipping HR functions with IT resources i.e. e-HR,
EHRM, HRIS, HR intranet, web-based HR, computer-based human resource management
systems (CHRIS), and HR portals. All the variants used to describe the IT possibilities in HR
functions (Ruel, Bondarouk, & Looise, 2004; Ruel, Bondarouk, & Van der Velde, 2007). The
definition of HRIS given by different authors are presented as under.
2.1.1 Human Resource Information System (HRIS)
Kavanagh and Thite (2009), HRIS is a combines the human resource
management functions and information technology.
Kavanagh and Thite (2009) Synthesized the definition of HIRS as “A system
used to acquire, store, manipulate, analyze, retrieve, and distribute information
regarding an organization’s human resources to support HRM and managerial
decisions” (p. 17).
Ruel, Bondarouk, and Looise (2004) describes the HRIS as “automating the
system used by the HR function itself”.
(Hendrickson, 2003) briefly defined HRIS as “Integrated system used to gather,
store and analyzed information regarding an organization’s human resources”
(Tannenbaum, 1990) “A system used to acquire, store, manipulate, analyze,
retrieve and distribute pertinent information about an organizational human
resource”.
DeSanctis (1986). “HRIS is designed to support the planning, administration,
decision-making, and control activities of human resources management”(p. 15).
The definitions of HRIS focuses on the concept of “system”, which is proprietary in nature.
Which uses IT to support HR functions of an organization. The difference between Enterprise
Resource Planning (ERP) and HRIS is, ERP meet all informational need of an organization in
one software package like SAP and people soft, whereas, HRIS is not communicating with
other business systems (Hopkins & Markham, 2003). In order to equip the HR functions with
IT, it required the full support of IS expertise in all functional areas of technology.
Tannenbaum’s functional definition of HRIS is adopted in this study for defining HRIS
(Tannenbaum, 1990). The same definition is used for defining the HRIS in latest studies for
example (Qadir & Agrawal, 2017; Buzkan, 2016)
15
HRIS utilizing all functional areas of information technology which are necessary for the
information system. These functional areas are hardware technologies, software technologies,
it also included database and communication technologies. O'Brien and Marakas (2011) also
discussed four technology areas which are necessary for the adoption of any information
system. These technologies include hardware, software, databases, and communication.
In continuation of the definition of HRIS Ruel, Bondarouk, and Looise (2004) describes the
HRIS as “automating the system used by the HR function itself”. In this description of HRIS
author also distinguish the HRIS with its variants as the user of HRIS is employees working in
the human resource department rather than the general employees and managers of the
organization. The operational use of HRIS is confined within the domain of human resource
department.
The adoption of IT resources in the shape of information systems in organizations have different
perspective, some of the organizations have adopted at the individual level, whereas others
adopted at the organizational level. Mingers and Willcocks (2004) discussed that IS adoption
research at organization level become dominated part in literature than individual adoption.
However, Chakraborty and Mansor (2013) highlighted that the major portion of the research
has been carried out in Europe and outside Asia, whereas, a little research has been carried out
in developing countries. The current study focuses on the organizational level adoption of
HRIS. The relevant literature on adoption of the information system at the organizational level
is presented in the shape of HRIS is as under:
In the literature review, the adoption of IS at organizational level is underpinned by different
theories and models. The authors Swanson (1994), Oliveira and Martins (2010) discussed the
dominated theories and model underpinned in different studies at organizational level adoptions
of IS, which includes: Innovation diffusion theory by Rogers (Rogers, 1995), Diffusion/
implementation model by Kwon (Kwon and Zmud, 1987), Tri-Core model by Swanson
(Swanson, 1994) , and Technology-Organization-Environment (TOE) framework by Tornatzky
(Tornatzky & Fleischer, 1990).
This study deals with HRIS adoption at organization level. The aforementioned theories are
used for adoption of information system and information technology (IS/IT) at an organization
level. Ward and Peppard (2002) use the term “information system” and “information
technology” interchangeably. These theories discussed the antecedents of IS/IT adoption at
organization level for example (Rogers, 1995) identify the innovation characteristics as
predictor of IS adoption, (Kwon & Zmud, 1987) identifying five characteristics including
16
innovation, organizational, environmental, individual, and task characteristics that have the
influence on the decision of adoption of HRIS.
Tornatzky and Fleischer (1990) presented three characteristics of IS adoption framework,
which are technological, organizational and environmental, also known as the TOE framework.
Teo, Soon, and Fedric (2007) also studied three factors for HRIS adoption namely innovation,
organizational and environmental characteristics. Authors discussed different theories and
models for adoption of HRIS at an organizational level. However, Jeyaraj, Rottman, and Lacity
(2006) highlighted that the best predictors that have an influence on IS/IT adoption at
organizational level are innovation characteristics, organizational characteristics, and
environmental characteristics. Same is proposed by (Kwon & Zmud, 1987) in addition to that
also proposed two additional characteristics i.e. individual and task characteristics. Whereas in
the case of organizational adoption of IT/ IS, individual characteristics need not be examined,
so that it is not considered in this context (Jeyaraj, Rottman, & Lacity, 2006). The brief
overview of major theories discussed in IS/IT adoption at organization level is presented in the
following section.
2.2 Innovation Diffusion Theory (IDT)
Rogers (1995) introduces the theory of innovation diffusion. This theory predominantly used
to explain the adoption of information technology and diffusion at the organizational level. The
innovation theory of adoption and diffusion have been studied at different level of adoptions,
like it is underpinned at individual level for example (Sultan & Chan, 2000; Van Slyke, Lou, &
Day, 2002) and at organization level for example (Prescott & Conger, 1995; Venkatesh, Morris,
Davis, & Davis, 2003).
Hameed, Counsell, and Swift (2012 discussed that the adoption of IS/IT for example the
adoption of HRIS at the organizational level is treated as innovation by the adopting
organizations. For this purpose models/ theories related to adoption of innovation may be used
to underpinning the main construct of study variables. The innovation literature has been
dominated by innovation diffusion theory by Rogers (1995) along with other models discussed
previously. The literature revealed that the reasons for dominating innovation theory is because
of its two-distinctive feature, the theory deals with individual and organization level adoption.
Jeyaraj, Rottman, and Lacity (2006) also, highlighted that Rogers theory (Rogers, 1995) of
innovation that gives a comprehensive view of technology adoption at the individual level as
well as at the organization level.
Damanpour (1991) and Damanpour (1987) stated that this theory proposed two stages of IT
adoption at organization level i.e. initiation and implementations whereas other authors like
17
(Hameed, Counsell, & Swift, 2012; Pierce & Delbecq, 1977; Damanpour & Schneider, 2006;
Pierce & Delbecq, 1977; Zmud, 1982) highlighted the stages of innovation adoption at
organization level as: initiation, adoption, and implementation. This can be expressed as pre-
adoption, adoption and post-adoption (Pierce & Delbecq, 1977). According to the Frambach
and Schillewaert (2002), adoption of innovation decision at the organizational level takes place
between the stage of initiation and implementation. Kwon and Zmud (1987) in a framework of
IT implementation argued that the implementation stage is the final stage of innovation process
at the organizational level, cited by (Henriksen & Andersen, 2008). (Straub, 2009) suggests that
the IDT provides fundamentals understanding about the innovation adoption, it is not in term
of take the decision to adoption, but it is in term of use, in the context of extent of adoption.
The short description about these stages is as under.
Initiation stage
This stage of innovation adoption deals with Initiation thinking of the organization in which
organizations take part in such activates that leads the organization towards the decision in
which organization decided to adopt the innovation (Damanpour, 1991). In short, organization
just aware of the IS/IT innovation exist in the market but needs serious consideration to adopt
an innovation (Frambach & Schillewaert, 2002).
Adoption stage
In this stage of innovation adoption, the organizations are in process in which organizations are
willing to provide resources for adoption of IS/IT and this is a stage in which organization
formally decide that to adopt the IS/IT innovation (Thompson, 1965) cited in (Pierce &
Delbecq, 1977).
Implementation stage
Implementation stage in which organizations start using innovation and decided that the
organization will use it on a continual basis, the implementation stage brings a change in the
organization in term of initial utilization of IS/IT and continue to use this innovation
(Damanpour, 1991). In short, the organization just adopt the innovation and start using it.
According to Frambach and Schillewaert (2002), the organizational adoption of IS/IT started at
the beginning of the implementation stage.
Bondarouk and Schilling (2016) describe the diffusion of innovation theory (DOI) as the
decision to adopt the new idea and its further implementation in the organization is depends on
the five characteristics of innovation. Some of the author using reinvention as a component of
DOI but (Greenhalgh, Robert, Bate, Macfarlane, & Kyriakidou, 2008) says reinvention was not
18
added with the core list of innovation attributes. Similar many authors opted different
characteristic in their studies like (Teo, Soon, & Fedric, 2007; Tornatzky & Klein, 1982; Li,
2008) taken only three characteristics (Rogers, 1995; Parry & Wilson, 2009) taken five
characteristics. Many authors discussed the adoption of HRIS as innovation, because it is a new
idea in term of implementation of information technology in HR department in the shape of
HRIS. DOI theory provides the theoretical foundations of adoption of IS/IT in organizations
which are an enabler to transform the manual work activities and processes of the HR into
HRIS. The short description of each characteristics of DOI is as fellows. These characteristic
are interlinked with each other.
2.2.1 Innovation Characteristics
Tanoglu, Basoglu, and Daim (2010) Innovation is defined as an idea, practice or object
perceived as new by the organization and diffusion is spread of use of IS/IT utilization in term
of implementation of the concept at large extent. The adoption of IS/IT in organization,
innovation diffusion theory (Rogers, 1995) is helping in explaining how to IS/IT systems
adopted and extended in organizations.
HRIS adoption is taken as innovation by the organization which uses IT in their HR functions.
For this purpose, (Moore & Benbasat, 1991) has developed an instrument on information
technology innovation within the organization which is grounded on the IDT (Rogers, 1995).
The scale was developed for the measurement of adoption and diffusion of information
technology in organizations. (Moore & Benbasat, 1991) using (Rogers, 1995) theory suggested
five characters of innovation which predominantly affect the adoption of IS/IT, it includes
relative advantage, compatibility, complexity, trialability, and observability. The detail of each
characteristic is as under. These characteristics are interlinked with each other. The author
emphasised that these are the characteristics which have an influence on adoption of innovation.
According to Fichman (1992), these five characteristics of innovation determines the rate of
adoption and its extent of adoption.
2.2.1.1 Relative Advantage
Rogers (1995) “Relative advantage is the degree to which an innovation is perceived as being
better than the idea it supersedes”. Rogers discussed the relative advantages in two distinct
ways, economic profitability and social reorganization. Economic aspects in terms of cost
reduction and increase in profitability (Beulen, 2009; Dessler, Sutherland, & Cole, 2005) and
reorganization in terms of change as compared to existing practices of work processes. Using
the same idea to implement HRIS for change in the organization. The adoption of HIRS in
organization helped change in term of changing the traditional HR functions and process, which
19
ultimately help in reduction in cost and increase in organizational profit. HRIS helping
inefficient deployment of human resources with the help of utilizing information extracted from
this system. Relative advantage may be the most important predictor of adoption of
technological innovation in organizations. The innovation in terms of adoption of information
technology in human resource department in the key facet of HRIS.
2.2.1.2 Compatibility
Rogers (1995) “Compatibility is the degree to which an innovation is perceived as consistent
with the existing values, past experiences, and needs of potential adopters”. The literature on
information technology adoption revealed that high compatibility with existing experiences
regarded high acceptability and adaptability. Those innovations which have matched with needs
of potential adopter and with existing systems play a vital role in acceptance of new ideas in
organization (Kassim, Ramayah, & Kurnia, 2012), HRIS adoption is consistent with existing
values and past experiences because it not only simplifies the existing experiences but also add
the values in performing the duties. Compatibility of HRIS is necessary for adopting
organizations because of differing in the adoption of HRIS with organizational IS/ IT
infrastructure, and data needs to support existing practices, values and beliefs minimizing the
chances of acceptance, in contrast to this, high chance of acceptance. HRIS is treated as
innovation in which information technology is adopted in the human resources department.
2.2.1.3 Complexity
Simplicity in new ideas takes less time to implement and accept as compare with complexity.
How the organization perceived HRIS as a complex or simple process dependent on the
complexity of the system. Rogers (1995) “Complexity is the degree to which an innovation is
perceived as relatively difficult to understand and use”. The newness in any form may be rated
on the basis of a complexity-simplicity continuum. More complex system may have the less
chance of acceptances and integrate with the existing system than the simple one. The
innovation is in term of adoption of information technology in human resource department
requires to makes application simple. Complexity is also dependent on the skill set of the staff
working in the HR department. Higher the skills set makes system adoption easier and vice
versa.
2.2.1.4 Trial-ability
Rogers (1995) “Trial-ability is the degree to which an innovation may be experimented with on
a limited basis”. The trail ability reduces the uncertainty. The innovation is in term of adoption
of information technology in human resource department in the shape of HRIS. Fichman (1995)
20
in the adoption of new technologies, organizations hesitant because of a risk of failure. Trail
ability reduces the risk as HRIS is adopted in an organization where the user of HRIS is staff
working in the HR department, not employees and managers.
2.2.1.5 Observability
Rogers (1995) Observability is the degree to which the results of an innovation are visible to
others. The benefits of innovation may be realized in term of economic and social. Economic
and social benefits are more visible than others and easily recognizable. Visible reorganization
leads to greater adoption of innovation in term of adoption of information technology in human
resource department in the shape of HRIS. Now the question is how an implementation of
technology is viewed and experienced by the organization? Soft-systems have fewer
observabilities as compare to hardware installation. observability can be realized by the
information derived from HRIS, and would be shared with top management for aligning the
organization vision consistent with the human resources available in the organization.
The above-mentioned characteristics may be used to measure the innovation characteristics of
an organization. These characteristics may be viewed as antecedents of adoption of HRIS as
innovation in the organization. various studies have established the relationship of innovation
characteristics with the adoption of innovation for example (Kwon & Zmud, 1987; Teo, Soon,
& Fedric, 2007; Sonnenwald, Maglaughlin, & Whitton, 2001). Some of the studies using few
characteristics of innovation diffusion theory like (So & Sun, 2011; Parry & Wilson, 2009) used
relative advantage for adopting of information systems in a supply chain.
According to Rogers (1995), the five attributes of innovation may not the most important
characteristic of adoption of innovation that applicable in all cases. According to Fichman
(1992) innovation diffusion theory needs modifications and extensions in term of the addition
of more attributes. In the same lines, Tornatzky and Klein (1982) expressed that out of five
innovation attribute three have significant relationship whit innovation adoption. These
characters are the relative advantage, compatibility, and complexity.
In addition to Rogers (1995) work on innovation, various other model has been proposed by
different authors that elaborate upon how the innovation is implemented in organizations. The
advantage of Rogers (1995) theory with other models is it deals with both aspects of individual
adoption and organization adoption, whereas other theory / model deal with single adoption
like (Swanson, 1994; Rogers, 1995; Kwon & Zmud, 1987; Tornatzky & Fleischer, 1990) used
of organization adoption and (Rogers, 1983; Davis, 1989; Venkatesh et al. 2003; Fishbein &
Ajzen ,1975) used for individual adoption.
21
2.2.2 Tri-Core Model
Swanson (1994) proposed Tri-Core model that discussed in the literature of innovation, it
discussed the innovation adoption in the context of organizations. Swanson’s tri-core mode is
extended form of (Daft, 1978) dual core model which deals with two aspects of organization
innovation, which includes: (i) technical innovation, and (ii) administrative innovation, the
author explains the technical innovation as relating the use of technology in the organization.
Whereas, administrative innovation as relating to maintenance of social structure including
policies, allocation of resource, benefits, rewards etc. Swanson (1994) tri-core model has three
components which includes: technical core, administrative core and functional IS core.
Functional IS core is used to bridge the technical core and administrative core for IS innovation.
Swanson (1994) and Grover (1997) categorized the model into three subtypes namely Type 1a,
1b, type 2, and type 3a, 3b, 3c. The reasons for not opting the tri-core model for innovation
adoption is because of its results are very fragmented and it is not used as a dominated model
in innovation adoption at organization level (Grover, 1997).
22
2.2.3 Technology Organization Environment Framework (TOE)
Technology organization environment framework is developed by (Tornatzky & Fleischer,
1990), this framework is used for adoption technological innovation at organization level This
framework discussed the three important aspects of the organization that have the impact on
the adoption of information technology at the organization level. These aspects are technology,
organization, and environment.
The brief description of the TOE framework Tornatzky and Fleischer (1990) is as follows:
(a) Technological context: it refers the availability of technology for performing organizational
processes, organizations automating their business processes with the help of technology for
example use of Radio frequency identification (RFID) and Barcode reader is used for data
capturing. Zhu and Kraemer (2005) highlighted that the concept of availability of technology
in term of utilized by the organization internally and the same is available in the market. It also
includes the availability of expertise and knowledge of using technology.
(b) Organizational context: it refers to the demographic profile of organizations adopting a
technology, e.g.; the size of an organization, management structure (Zhu & Kraemer, 2005).
(c) Environmental context. It refers to the external factors that have an impact on the
organization, for example, the surroundings in which the business is conducted, like
competitors.
The competitors pressure is an external factor that influences the organization to adopt
information technology, several authors discussed competitors pressure in context to the
environment (Martins & Oliveira, 2009; Oliveira & Martins, 2010; Pan & Jang, 2008; Kuan &
Chau, 2001). TOE framework has been used by Troshani, Jerram, and Rao Hill (2011) for the
adoption of HRIS in public sector organization. This framework used for technology adoption
at the organizational level (Oliveira & Martins, 2010).
TOE framework deals with technological innovation in term of technological artifacts available
in the market that may be used by organizations like the use of Barcode reader in departmental
stores and radio frequency identification tags used in the tracking system for tracking
organizational assets (Baker, 2012). The author further discussed in term of theoretical linkages
with DOI, However, TOE framework may be used in conjoint with other theories where
innovation is adopted in organizations. DOI theory deals with innovation adoption within the
organization, many authors combined the innovation characteristics with organizational and
environmental characteristics (Thong, 1999; Prescott, 1995; Ahmer, 2013; Teo, Soon, & Fedric,
2007). Adoption of HRIS is not a technological artifact, it deals more with soft resources of the
23
organization. For these reasons, TOE framework would not be an appropriate choice for current
study in its normal setting. Based on the discussion and available literature three characteristics,
innovation, organization, and environment (IOE) may be used, which is formed by the
amalgamation of Rogers’s theory of diffusion of innovation (Rogers, 1995) and TOE
framework by (Tornatzky & Fleischer, 1990). This IOE model may be used for soft / processes
related innovations in organizations.
2.2.4 Diffusion/ Implementation model by Kwon and Zmud (1987)
Kwon and Zmud (1987) proposed a model which deals with information technology adoption.
This model is based on innovation diffusion theory. Kwon and Zmud (1987) describe the model
which integrates IDT with some of the other constructs from other theories it includes
innovation characteristics, organizational characteristics, environmental characteristics, task
characteristics, and individual characteristics. These components determine as predictors of
information technology adoption, which uses Roger’s theory. The model deals with
organizational level adoption of IS/IT. According to Swanson (1994) describes the information
system innovation as a use of information technology adoption in organizations and diffusion
means the extent to which the organization is benefiting from innovation by utilizing its features
and applications. Jeyaraj, Rottman, and Lacity (2006) in a review of the article states that
diffusion/ implementation model is used for individual-level adoption.
The aforementioned short description of theories/model used for adoption IS/IT has some
theoretical overlapping in term of different types of variables proposed by different authors.
Like Kwon and Zmud (1987) integrate some constructs from Roger’s theory to propose a
model. The current study deals with innovation adoption in term of soft resources of
organization i.e. adoption and extent of HRIS adoption at the organization level.
The study is based on IDT, in addition to that two other contextual constructs included from
TOE framework which is organizational and environmental. Technological context deals with
technological artifacts (Zhu & Kraemer, 2005) whereas HRIS is more deal with the soft
resource of the organization. So, the innovation characteristic of IDT deals with the adoption
of IS/IT. Jeyaraj, Rottman, and Lacity (2006) expressed that IDT and TOE model is used at
organization level adoption of technology. This IOE model is used for soft / processes related
innovations at the organization level. IOE characteristics are the predictor of IS/ IT adoption,
the same is used by (Premkumar & Roberts, 1999; Teo, Soon, & Fedric, 2007) studying
organization level adoption.
24
2.3 Organizational Characteristics
Organizational characteristics need to address while adopting IS/IT because IS/IT may be
adopted at different levels of organization like functional, departmental and at organization
(Premkumar & King, 1994), whenever information system is implemented at organization,
where the entire organization is considered, organizational characteristic should be taken into
account as contextual factors. Without the support of these characteristics, a success could not
be achieved. Soltan, Jusoh, Mardani, and Bagheri (2015) also highlighted the importance to
identify the antecedents that contribute to the success of ERP systems implementation.
Studies conducted in the field of human resources and information systems separately or
collectively proposed that these factors have a significant impact on the adoption of HR systems
and IT systems. Considerable literature exists Hameed, Counsell, and Swift (2012); Ruel and
Bondarouk (1997) that expresses different organizational characteristics from different parts of
the world at the individual level and at the organization level. Hameed, Counsell, and Swift(
2012) synthesize the best predictor at the organization level as top management support and
organization size. The author found top management support and organization size as a strong
predictor of IT adoption, further, expressed that top management support was found significant
predictor in 24 studies, and organization size found significant predictor in 28 studies. Karimi,
Somers, and Bhattacherjee (2007) state that organization characteristics have an impact on the
extent of IT adoption and implementations.
Teo, Soon, and Fedric (2007) Suggests three organizational characteristics, it includes top
management support, organization size, and HRIS expertise. Lantara (2016) hypothesis in his
article that organizational factors affect the adoption of HRIS, his results stats that the
organizational factors have positive effects on the adoption of HRIS. Chakraborty and Mansor
(2013) presenting the theoretical analysis synthesis that organizational characteristics like size,
management support having a major impact on the adoption of HRIS. Troshani, Jerram, and
Rao Hill (2011) also stated that top management support as antecedent of HRIS adoption. The
short description of above mentioned organizational characteristics is given below.
2.3.1 Top Management Support
The realization of the importance of information as an assets especially human resources
become a significant factor that encourages top management to adopt HRIS. The clarity about
this importance of information leads towards the adoption to its full extent. Organizations where
top management realized the benefit of using such information for placing right man at right
job facilitating the adoption of HRIS.
25
Tannenbaum (1990), Bondarouk, Schilling, and Ruel ( 2016), Fui-Hoon Nah, Lee-Shang Lau,
and Kuang (2001) discussed that the greater the support of top management will help to adopt
IS/IT to at large extent, furthers, the extent of HRIS adoption in organizations would only be
possible when top management actively encourages it adoption, and providing adequate
resources to human resource personnel for adoption and use of HRIS applications to its full
extent (Dong, 2008). Senior management should realize and extend their support in term of
providing the resource and promoting the IS adoption in human resources. The outcomes of top
management support towards the adoption of HRIS to its full extent has been found highly
significant (Chakraborty & Mansor, 2013). Hameed, Counsell, and Swift (2012), Lee and Xia,
2006, Lin (2010) has shown a positive association of IT adoption with top management support.
According to Bhattacherjee (1998) IT adoption at organization level is different as compared
to an individual level, individual level adoption of IT based on personal/ user levels
characteristics like belief, attitude and intention, but at organization level adoption of IT
depends on management support through encouragement and taking corrective action in the
right direction. Cheney, Mann, and Amoroso (1986), Weill (1992) highlighted the importance
of top management support in term of they recognize the importance of a system and realized
that, their involvement is necessary for success full implementation of system. Lack of support
of top management may be considered an impediment toward the adoption of HRIS (Bamel,
Kumar Bamel, Sahay, & Thite, 2014) ranked lack of top management support as a major
impediment. According to Remus (2007), top management support is treated critical success
factors of systems implementations at organizations level.
2.3.2 Organization Size
Organization size would be highly correlated with the availability of business resources and
treated as a platform that would be necessary for adoption IS/IT system (Thong, 1999).
Information technology is an enabler in managing large organizations in a successful fashion
and become a strategic partner. Different studies propose different measures for determining
organization size as a predictor that has an influence on HRIS adoption. Some propose the size
of organization can be measured in term of No. of full-time employees working in an
organization (DeTienne & Koberg, 2002; Gooding & Wagner III, 1985). Some linked
organization size with annual revenue of an organization (Lee & Xia, 2006; Mabert, Soni, &
Venkataramanan, 2003). It is a general tendency that large organization is more likely to go for
an adoption of HRIS as compare to small organizations because IT is an enabler to manage
things effectively and efficiently. The literature on the adoption of information technology in
an organization has shown mixed significance of organization size with the adoption of HRIS.
26
The major portion of these studies conducted in technologically advanced countries, whereas,
little literature is available in developing countries it highlights the importance of organization
size as a factor of organizational characteristics that may be studied because of organizations in
developing countries share different values (Kassim, Ramayah, & Kurnia, 2012). Tannenbaum
(1990) discussed that is the extent HRIS adoption is positively associated with the organization
size. According to the findings larger the organization size, the more chances to adopt HRIS to
its full extent. Lee and Xia (2006), Gremillion (1984), Raymond (1985) also highlights the
importance of organization size that it is one of the important predictor in IT innovation
adoption. Ball (2001) study found that the relationship exists between the organization size and
adoption of HRIS, the size of an organization influences the adoption of HRIS, greater the size
of organization is more likely to adopt HRIS (Chakraborty & Mansor, 2013). Troshani, Jerram,
and Rao (2011) findings support that organization size have an influence on HRIS adoption
because of the potential benefits observed in large organizations.
Youndt, Snell, Dean, and Lepak (1996), Bartram (2005) discussed that large organization has
more tendency to adopt more HR practices than small organizations. DeTienne and Koberg
(2002) in his study uses organization size in term of the number of employees and found this
as a most appropriate measure. Along with the No. of employees, another appropriate measure
of organization size, annual estimated revenue may also be used to measure organization size.
According to Thong and Yap (1995), organization size have a positive relationship with IT
adoption in organizations, organization size may be determined by No. of employees
(Raymond, 1990) and total sales revenue (Hameed, Counsell, & Swift, 2012). The adoption of
HRIS has largely been depending on the size of organization (Hendrickson, 2003; Gueutal,
Strohmeier, & Kabst, 2009), which could be a helpful factor for successful adoption, same is
confirmed by (DeLone, 1981). The next section discusses the third environmental
characteristics.
2.4 Environmental Characteristics
Environment refers to the external setup surroundings of an organization where the business is
performed. Competition of an organization is treated as environmental characteristics.
Generally, it is a tendency of organizations they use information technology as a competitive
advantage and gaining efficiency and effectiveness in organizational operations (O'Brien &
Marakas, 2011). With the help of IS/IT, organizations get timely information, availability of
information has been taken as a strategic resource, which could be used to gain competitive
advantage (Barney, 1995). Human resources and informational resources are taken as soft
resources of an organization, which needs to organize in a way to gain a competitive edge
27
(Karim & Rahman, 2018). Organizations not only managing human resources with the help of
HRIS but also adopting these systems to its greater extent to gain an edge over rivals.
Chakraborty and Mansor (2013), Thong (1999) describes the environmental characteristics as
the surrounding and whereabouts of the organization where the business is conducted. Al-
Dmour, Masa'deh, & Obeidat (2017) discussed and highlight the importance of environmental
factors, like competition have a significant impact on adoption HRIS. DeTienne and Koberg
(2002) considered the environment as one of the factors that has the impacts on the decision to
adopt innovation or otherwise. According to Barney (1995), technological artifacts are treated
as a competitive advantage in which the environment plays an important role to adopt these
artifacts. Teo, Soon, and Fedric (2007) argued that companies are facing competitive pressure,
to maintain the competitiveness which needs to adopt HRIS. Premkumar and Roberts (1999)
discussed that it is strategically necessary to use HRIS at the workplace for managing
organizational human assets, and putting pressure on competitors by an efficient deployment
of human resources through the right person at the right place by using HRIS. Ruel, Bondarouk,
and Looise (2004) discussed competition as environmental factors that have an influence on
adopting IS/IT systems in HR department. HRIS plays a pivotal role in competing in the market
by taking timely decisions based on the data of employees, then better utilizing of human
resources. Battisti, Hollenstein, Stoneman, and Woerter (2007) treated the environmental factor
like competitive pressure as a powerful drive that put the pressure on organizations in term of
adoption of IS/IT. According to Troshani, Jerram, and Rao Hill (2011) adoption of HRIS varies
across organizations, its adoption depends on the needs of the organizations. The external
environment became one of the strong motivators that encourages the organization to become
competitive by adopting HRIS to its greater extent.
The aforementioned discussion has been based on the components of IOE, that would be
considered as factors affecting the extent of HRIS adoption. In the upcoming section a brief
discussion on components of HRIS, that had been adopted by different authors across the
literature.
2.5 Human Resource Information System Functions Discussed by Different
Authors in Literature.
Troshani, Jerram, and Rao Hill ( 2011) discussed that the adoption of HRIS varies across
organizations, some of the organization using HRIS up to the availability of standard
functionality in HRIS applications. But at the same time, some of the organizations customized
these standard functionalities according to their needs. Organizations should not realize
maximum benefits of IS/IT systems until they adopt HRIS systems to its full extent, that would
28
be benefiting the organizations by enhancing organization’s performance. The HRIS is used to
support HRM functions, a brief history of HRIS functions used by different authors shown in
Figure 2. Mayfield, Mayfield, and Lunce (2003) discussed the functions of HRIS according to
the data needs that would require by managers for HR decision making. HRIS is beyond to
automating HR functions. A summary of the HRIS adoption in literature is shown in Table 1.
29
Table 1: Functions of HRM used in HRIS
Table1: Functions of HRM used in HRIS
Sr. No Title Author Year Components
1
Human Resource
Information Systems: A
Current Assessment
DeSanctis,
Gerardine 1986
Benefits Administration Applicant Flow, Collective Bargaining,
Compensation Administration, Employee Attendance, Equity Monitoring
(Eeo / Aa), Human Resource Control, Position Control, Recruiting &
Selection, Safety/Workers Compensation, Training & Development
2
Benchmarking Human
Resource Information
Systems in Canada and
Hong Kong
Martinsons, Maris
G 1994
Absence Records, Benefits Administration, Budgeting, Employee Records,
Manpower Planning, Payroll Administration, Performance Appraisal,
Planning & Control, Recruitment & Selection, Training & Development
3
Adoption and Impact of
Human Resource
Information Systems
(HRIS)
Teo, Thompson
SH; Soon, Lim
Ghee; Fedric,
Sherin Ann
2001
Benefits Management, Career Development, Compensation Management,
Employee Record-Keeping, Payroll, Performance Appraisal,
Recruitment/Selection, Succession Planning, Training & Development,
Turnover Tracking/Analysis
4
The use of human resource
information systems: a
survey
Ball, Kirstie S 2001 Benefits Management, Health & Safety, Payroll & Pensions, Personnel
Administration, Recruitment, Time & Attendance, Training
30
Sr. No Title Author Year Components
5
Implementation of Human
Resource Information
System in Pakistani
Organizations
Malik, Khusro P
and Rehman,
Dareema
2002
Basic Module Containing Basic, Benefits Module, Career Development
Module, Employee Self Service Module, Job Evaluation Module, Labour
Relations Module, Payroll Module, Position Control, Recruitment Module,
Safety Module, Tax Module, Training Module, Vital Information,
6
Technology for human
resources management:
seven questions and answers
Ashbaugh, Sam;
Miranda, Rowan 2002
Benefits Administration, Employee & Manager Self Service, Human
Resource Administration, Payroll, Time & Labour
7
Human Resource
Information Systems: A
Review and Model
Development
Mayfield, Milton;
Mayfield, Jackie;
Lunce, Steve
2003
Communication & Integration, Forecasting & Planning, Hr Analysis,
Knowledge Management, Personnel Development, Records & Compliance,
Strategic Integration
8
Human Resource
Information Systems:
Backbone Technology of
Contemporary Human
Resources
Hendrickson,
Anthony 2003
Benefits Administration, Compensation Analysis, Management
Development, Payroll & Pension, Performance Appraisals & Management,
Profit Sharing Administration, Recruiting & Retention, Reporting
&Compliance, Resume Processing, Skill Development & Inventory, Skills
Testing & Assessment & Development, Team & Project Management,
9 Human resource
management systems and
Rodriguez, Jesus
M; Ventura, Juan 2003 Compensation, Performance Appraisal, Staffing, Training & Development
31
Sr. No Title Author Year Components
organizational performance:
an analysis of the Spanish
manufacturing industry
10
The Impact of Human
Resource Information
Systems: An Exploratory
Study in the Public Sector
Beadles, N;
Lowery,
Christopher M;
Johns, Kim
2005 Communicating, Correcting Errors, Inputting Data, Making Staff
Decisions, Processing Paperwork, Recruiting, Training
11
Human Resource
Information Systems: A
Review and Empirical
Analysis
Ngai, EWT; Wat,
FKT 2006
Compensation, Corporate Communication, Employee Opinion Survey,
Employment Verification, General Information, Payroll Service,
Recruitment, Selection, Training
12
E-Hr Adoption and The
Role of Hrm: Evidence
from Greece
Panayotopoulou,
Leda; Vakola,
Maria; Galanaki,
Eleanna
2007
Career Management, Communication, Compensation & Benefits, Hr
Planning, Performance Appraisal, Recruitment & Selection, Training &
Development
13 The use and impact of
human resource information
Hussain, Zahid;
Wallace, James; 2007
Assessment & Training Needs, Employment Benefits, Hr Planning,
Industrial Relations, Performance Management, Recruitment, Salary
Advice
32
Sr. No Title Author Year Components
systems on human resource
management professionals
Cornelius,
Nelarine E
14
The Enabling Role of
Information Technology in
the Global War for Talent:
Accenture’s Industrialized
Approach
Beulen, Erik 2008
Compensation & Benefits, Education & Training, Hr Administration &
Payroll, Performance Management & Talent Management, Recruitment &
Selection, Scheduling
15
The contribution of a global
service provider’s Human
Resources Information
System (HRIS) to staff
retention in emerging
markets
Beulen, Erik 2009 Benefits Administration, Human Resource Planning, Performance
Appraisal, Staff Development & Regulatory Compliance
16
Information Technology in
Human Resource
Management: An Empirical
Assessment
Mishra, Alok;
Akman, Ibrahim 2010 Maintenance & Development, Management & Planning, Recruitment
33
Sr. No Title Author Year Components
17 Role of HRIS in Improving
Modern HR Operations
Chauhan,
Akansha; Sharma,
Sanjeev Kr;
Tyagi, Tarun
2011 E- Payroll, E-Benefits, E-Recruitment/Applicant Tracking, E-Self-Service
E-Time & Labour Management., E-Training
18
Human Resource
Information System and Its
Impact on Human Resource
Planning: A Perceptual
Analysis of Information
Technology Companies
Khera, Shikha N;
Gulati, Ms
Karishma
2012
Absenteeism Analysis, Applicant Tracking, Benefit Administration,
Compensation Management, Cost of Salary Benefit Per Employee, Cost of
Selection Per Employee, Grievance Management, Manpower Planning,
Performance Management, Personal Information Identification, Salary
Planning, Succession Planning, Training, Turnover Analysis, Union
Negotiation, Work Scheduling
19
Impact of adopting HRIS on
three tiers of HRM:
Evidence from Developing
Economy
Saleem, Irfan 2012
Career Development, Compensation Management, Employee Record-
Keeping, Hr Planning, Payroll Preparation, Performance Appraisal,
Recruitment & Selection, Strategic Decision Making, Training Needs
Assessment, Turnover Tracking Analysis
20
The Relationship between
Human Resource
Information System (HRIS)
Functions and Human
Obeidat, Bader
Yousef 2012
Communication & Integration, Forecasting & Planning, Hr Analysis,
Knowledge Management, Personnel Development, Records & Compliance,
Strategic Integration
34
Sr. No Title Author Year Components
Resource Management
(HRM) Functionalities
21
The Relationship Between
Innovation Diffusion and
Human Resource
Information System(HRIS)
Obeidat, Bader
Yousef 2013
Communication & Integration, Forecasting & Planning, Hr Analysis,
Knowledge Management, Personnel Development, Records & Compliance,
Strategic Integration
22
Integrated Role of HRIS &
SHRM (SHRIS) In Banking
Sector of Pakistan
Awan, Abdul
Ghafoor; Sarwar,
Ghulam Haider
2014
Communication & Integration, Forecasting & Planning, Hr Analysis,
Knowledge Management, Personnel Development, Records & Compliance,
Strategic Integration
23
Usage, benefits and barriers
of human resource
information system in
universities
Bamel, Nisha;
Kumar Bamel,
Umesh; Sahay,
Vinita; Thite,
Mohan
2014
Absence Monitoring, Compensation Management, Disciplining
Procedures, Employees’ Information, Employment Reward, Job Analysis
& Work Design, Performance Appraisal, Promotion Management, Training
& Development
24
Exploring the Outcomes of
Electronic Human Resource
Management (E-Hrm)?
Findikli, Mine
Afacan; beyza
Bayarccelik, Ebru
2015 Career Planning, Learning & Training, Performance Appraisal, Planning,
Recruitment, Salary System
35
Sr. No Title Author Year Components
25
Human Resource
Information System and
Competitive Advantage of
Companies Listed on
Nairobi Securities Exchange
in Kenya
Kariuki, Margaret
Muthoni 2015
Communication & Integration, Forecasting & Planning, Hr Analysis,
Records & Compliance, Strategic Integration
26
Impact of Human Resource
Information Systems on
Firms’ Financial
Performance
Bhuiyan, Faruk;
Rahman,
Muhammad
Mahbubur; Gani,
Mohammad
Osman
2015
Compensation & Benefits, Employee & Labour Relation, Equal
Employment, Health, Hr Development, Hr Planning & Analysis, Safety &
Security, Staffing
27
The Impact of Human
Resource Information
System (HRIS)
Applications on
Organizational Performance
(Efficiency and
Khashman, Iyad
Mohammad Ali;
Khashman, Aysar
Mohammad
2016 Communication, Job Analysis, Performance Appraisal, Recruitment,
Selection
36
Sr. No Title Author Year Components
Effectiveness) in Jordanian
Private Hospitals
28
The Role of Human
Resource Information
System (HRIS) in
Organizations: A Review of
Literature
Buzkan, Halil 2016 Benefit & Compensation, Employee Labour Relations, Equal Employment,
Hr Development, Hr Planning & Analysis, Staffing
29
What does it take to
implement Human Resource
Information System (HRIS)
at scale? Analysis of the
Expected Benefits and
Actual Outcomes
Tursunbayeva,
Aizhan; Pagliari,
Claudia;
Bunduchi,
Raluca; Franco,
Massimo
2016 Business Intelligence, Payroll & Benefits Administration, Performance
Management, Service Delivery, Workforce Management
37
2.6 Extent of Human Resource Information System
Human resource information systems have been adopted and utilized by various organizations
to manage their HR related data. The implementation of HRIS varies with respect of HR
functionalities in a system and its utilization. The philosophy behind the adoption of every
system is, the system should provide information about the organization. Literature on HRIS
revealed that, some studies describing HRIS as it has some functions in it that were performed
manually in traditional human resource management practices, these practices converted into
computerized applications for example (Ball, 2001; Ashbaugh & Miranda, 2002; Rodriguez &
Ventura, 2003; Mishra & Akman, 2010; Khashman & Khashman, 2016). Some of these studies
describing HRIS as, it is a system that is based on traditional HR functions by automating these
functions like (Martinsons, 1994; Malik, 2002; Hendrickson, 2003; Khera, 2012; Bamel,
Kumar Bamel, Sahay, & Thite, 2014).
According to the Bharadwaj (2000), information technology can be used as a strategic resource
of an organization that helps the organization to develop IT-based business processes. Mayfield,
Mayfield, and Lunce (2003) proposed a comprehensive model of HRIS which address the
management accepts of the HR functions with the strategic importance of HRIS. According to
Bharadwaj (2000) and Barney (1995), IT resources of a firm are homogeneous in nature and
can easily be accessed from an open market. In the same lines, HRIS systems are available in
the market that can easily be implemented by any organization. However, organizations can
only get the benefits from these systems provided the organization create unique IT mix of
adoption of these applications, to its greater extent through a best mix. According to Qadir &
Agrawal (2017) organizations develop HRIS in piecemeal despite the importance of it in
organization.
According to Teo, Soon, and Fedric (2007) the term extent of HRIS is described in two different
ways, first hard/physical resources allocated by the organization like provisioning of more
workstations and other accessories, second, soft resources adopted by the organization like
more and more applications adopted by human resource department. Another author describes
the extent of ERP in term of its implementation and benefits derived from that system. The
quantity of implementation of IT systems into three areas like the extent of system
implementation in a functional, departmental or entire organization, the number of benefits
derived in a way by getting better business outcome (Karimi, Somers, & Bhattacherjee, 2007).
In the context of the extent of HRIS, some author like (DeSanctis, 1986; Teo, Soon, & Fedric,
2007; Teo, Soon, & Fedric, 2001) argued that the extent of HRIS adoption requires the
38
availability of resources, which could help to adopt more HRIS applications. Availability of
resources could be managed through the alignment of HR management and top management.
This alignment would be helpful for top management in term of facilitation in decision making
with respect to human resources. Ruel, Bondarouk, and Van der Velde (2007) says HRIS plays
strategic role provided the processes of services are increased. Tye and Chau (1995), Gremillion
(1984) reported that few studies deal with extensive use of HRIS which deem necessary to
address.
Teo, Soon, and Fedric (2001), Tye and Chau (1995), Thong (1999) discussed the extent of
HRIS in two ways, first, the computer resources dedicated for the use of human resource
department, second, the application level utilization of HRIS across the organization. The extent
of HRIS is measured by the application level adoption of HRIS. In the same lines, the extent of
HRIS adoption is linked with the degree to which HRIS has been adopted with reference to the
model proposed by Mayfield. The model describes the functions of HRIS as strategic
integration, personal development, communication and integration, records and compliance,
human resource analysis, knowledge management, and forecasting and planning. Table 1 is
adopted from the article describing the functions of HRIS.
Beadles, Lowery, and Johns (2005) discussed the HRIS in comparison with public and private
sector organizations, the impact of HRIS in public sector seem satisfactory, the working
environment of public sector organizations varies in comparison with private sector in different
functional accepts like public sector organization does not participate in competition, they are
not designed for profit maximization. The findings of the author suggest that the HR staff
believed that organization should adopt HRIS to its full extent because of limited use of HRIS
functions should not provide full benefits until the full extent of HRIS is adopted.
Teo, Soon, and Fedric (2001) argued that the extent of HRIS varies across organizations
because of organizations lacking HRIS application level knowledge and expertise. The HRIS
expertise possessed by staff demanding more and more applications which provide the extent
of HRIS adoption.
After the detailed literature review, it is concluded that the model proposed by Mayfield
(Mayfield, Mayfield, & Lunce, 2003) provide a comprehensive view of HRIS with respect of
definitions proposed by different authors like (Tannenbaum, 1990) and it covers all
organizational essential areas relating to HRIS for the management of human resources.
According to (Kariuki, 2015) the functions of Mayfield model serve the purpose of strategic
and administrative HRIS.
39
Figure 1: HRIS Functions
Source: Mayfield (2003)
The detail description of these of HRIS functions along with the major activities performed are
presented in upcoming section.
2.6.1 Strategic Integration
Strategic Integration is taken as a liaison of the HR department with the top management in
term of meeting long-term strategic needs of human personnel. The adoption of HRIS is treated
as a strategic partner because it creates a link with top management by providing relevant
information. Mayfield, Mayfield, and Lunce (2003) describing the strategic integration as it is
used to aid top management in making long-term HR planning. Sheehan (2005) expressed that
strategic integration could be possible provided that HR become part of the senior decision-
making process by showing representation in a strategic decision. This could be achieved by
sharing HR-related information with top management while planning HR requirements. For
this purpose, HRIS enabled the HR department to become a strategic partner in decision
making. In a similar fashion (Kovach, Hughes, Fagan, & Maggitti, 2002; Parry, 2011) second,
the arguments proposed earlier that HRIS is not only used for the administrative purpose, but it
40
can also be used for strategic decision making. The author explaining strategic integration as a
function of HRIS where the system helps top management in strategy formulation and strategic
implementation (Obeidat, 2013). According to Lawler III ( 2005), HRIS can also be used to
serve the needs of the strategic partner by delivering the HR services. HRIS helps the executive
that they should focus on developing the capabilities of HR staff to become a strategic partner.
Ulrich (1997) suggests that capabilities required to become business partner include the person
should possess business acumen, which would be developed through a broader career
background. HRIS enables top management to become a strategic partner by getting aid in HR
planning.
2.6.2 Personnel Development
Personnel development is an ongoing process that helps organizations to train and develop their
staff to meet short-term and long-term HR needs. The HR department is responsible to develop
the skills and abilities of existing staff in order to meet the current needs and also cater for the
future talent needed by enhancing human resources abilities. Wiblen, Grant, and Dery (2010)
expressed that HRIS would be helpful by providing data to develop talent that meets future
needs. Some of the HR managers think that their staff may not have the capability to perform
certain duties lacking personnel development in their organizations (Torrington & Hall, 1996).
Mayfield, Mayfield, and Lunce (2003), describe the personnel development as used to enhance
worker’s skills and ability. Training and development improve the quality of work life. Obeidat
(2013) explaining the personnel development in his article as to prepare the employee for future
in a way to enhance the employee’s personality and abilities.
2.6.3 Communication and Integration
Information systems helping in improving communication between departments and
designations. The flow of information within an organization considered as a pivotal for
enforcing organization policies and regulations. In context with human resources of an
organization, it is important to establish coordinating among human assets of an organization.
The effectiveness of an organization can be improved by organizational communication by
establishing the human networks with the help of IS/IT (Magalhaes & Ruel, 2007). This
communication among designations also encourages integration between different activities
performed in the organization. Connecting one entity with others helps to get the optimal mix,
this is only possible with the help of communication within the organization. Mayfield,
Mayfield, and Lunce (2003), describe communication, and integration as Inter organization
communication, support and coordination of different organizational activities. In the same
lines, (Obeidat, 2013) further elaborate communication and integration in two different aspects.
41
Communication means to deliver the necessary information to organize human resources within
organization and integration means sharing the information for establishing linkages with other
functions activities of the organization. These linkages resultantly helping the organization to
gain a strategic outcome.
2.6.4 Records and Compliance
Information system managing organization transactional data in general, and HRIS particularly
managing human resource functions related transactions. According to O'Brien and Marakas
(2011), the function of HRIS is to store the records of employees. The record management helps
the organization to perform internal activities with the help of information generating through
these records. It also helps the organization to use these records for different compliance
externally, for example to meet the requirements established by industry, regulators, and govt.
The record management of employees may help in meeting legal obligations. Mayfield,
Mayfield, and Lunce (2003), describing this function of HRIS as to managing organizational
human resource related information and meeting governmental compliances. The author
describes this function as to takes records for retention of employee data and compliance deals
with meeting legal requirements (Obeidat, 2013).
2.6.5 Human Resource Analysis
According to Siddique (2004), HR analysis gives an emerging view of human resource which
contributes in an organization’s performance. HRIS become an integral part of analyzing
human resources data. Organizational HR is considered as soft resources. According to Barney
(1995), among other organizational resources, human resources play important role in
competing with other organizations in the industry. Human resource analysis provides help in
exploiting the opportunities for enhancing the productivity of an organization by analyzing the
available HR knowledge, skills, abilities (KSA). Further, the author associate KSA with
available positions, and how these available expertise’s meets the needs of these positions.
According to (O'Brien & Marakas, 2011) HRIS is used for analyzing the use of personnel
positioned in a different operation of an organization. Mayfield, Mayfield, and Lunce, (2003)
describes human resource analysis as an analytical tool by means of gathering and diagnosing
human resource needs. HRIS improves decision making with the help of availability of the
better information about the personnel and positions (Broderick & Boudreau, 1992) . The author
Obeidat (2013) further explained the human resource analysis as it is a process that helps the
management to find out what position is available in the organization, and what kind of KSA
required to fill that particular position to improve organization’s performance.
42
2.6.6 Knowledge Management
According to O'Brien and Marakas (2011), the uses of information technology at strategic level
can be viewed as knowledge management. These systems helping an organization in the
creation of new knowledge that enhances the organization’s performance. HRIS performing the
function of knowledge management by managing business know-how and make that
knowledge available to the organization. Computerized systems continuously monitor and
record the work processes and activities and also providing feedback on activities and processes
performed in the organization. A quick feedback on work-related activities helps the
organizations to enhance organizational learning and utilize that learning in future as best
practices. These processes and activities are the amalgamations of theory and practice,
Organizations needs to document this knowledge. Mayfield, Mayfield, and Lunce (2003)
describe the knowledge management as to facilitates, develop, and retain information about
human resource practices that are beneficial for the organization. To preserving the
organizational learning is beneficial for achieving a high organization’s performance. Obeidat
(2013), explaining knowledge management as it is important for the organization and is a source
of important organizational knowledge which needed to document. Nwankpa (2015) discussed
that knowledge management enables the organization to acquire knowledge and implement it
in various functional areas for better collaboration and performance. According to O'Brien and
Marakas (2011), knowledge management is a collaborate work management activity that helps
organizations to accomplish group work activities, these group work activities enable HR
managers to collaborate with other managers and aid top management for collaborative decision
making for gaining strategic outcomes.
2.6.7 Forecasting and Planning
IS/IT systems used for forecasting and planning, decision supports system deals with
organizational forecasting and planning. O'Brien and Marakas (2011), say forecasting and
planning function as a part of HRIS and it became an integral part of other systems used in the
organization. Information stored in HRIS is related to HR skills and abilities help the
organization to predict the future trends in human resources requirements. The availability of
skills and predictive growth in skills helps to determine the organization’s future HR needs.
Planning deals with collecting HR-related information from all sources, which includes internal
sources and external sources. Forecasting deals the estimation of future demand for human
resources with respect of skills and ability. Mayfield, Mayfield, and Lunce (2003) explaining
forecasting and planning functions to access organizational future HR needs. Obeidat (2013)
43
expressed forecasting and planning as it is useful in a way to determine what type of skills
required in future to meet the expected HR needs of an organization.
These factors are not fully adopted by the organizations because of lacking empirical evidence.
In order to study the factors affecting the extent of HRIS adoption in term of functions adopted
by organizations as part of HRIS, the literature leads that the innovation, organizational, and
environmental characteristics may impact the extent of HRIS adoption. The literature on
adoption of HRIS theoretical support that the adoption has an impact on the organization’s
performance. The current study empirically test that, is there any statistically significant
relationship exist between the extent of HRIS and organization’s performance? if so, what is
it? It is further stated that greater the extent has greater the impact on the organization’s
performance. The functions proposed by Mayfield, Mayfield, and Lunce (2003) is treated as an
aggregate mix that measured extent of HRIS adoption. The extent of system adoption is
measured through means value of all functions adopted by the organization in term of their
functional level of utilization. This is in accordance with the guidelines suggested by (Becker
& Huselid, 1998), and the same is adopted by (Guest, Michie, Conway, & Sheehan, 2003).
2.7 Organization’s Performance
Organization’s performance is always a dominant area of interest for management
professionals. A growing body of evidence revealed that human resources of an organization is
treated as an asset for an organization that has a major contribution in enhancing organization’s
performance. Some of the researchers emphasised that technological innovation in human
resource management significantly contributing in organization’s performance (Li, Zhao, &
Liu, 2006; Phahlane, 2017). Crossan and Apaydin (2010) , Mone, McKinley, and Barker (1998)
also, supported that the use of innovation in an organization is an important determinant of the
organization’s performance. Klomp and Van Leeuwen (2001), Calantone, Cavusgil, and Zhao
(2002) found a significant relationship between innovation adoption and organization’s
performance. The adoption of HRIS is studied globally, but much focus of the research on
technological innovation in HR has been studied in western context. Whereas, other parts of
the world got little attention specifically developing countries. The adoption of HRIS with
reference to enhancing organization’s performance highlights the contextual importance of the
use of IS/IT in HR functions. According to Weill (1992), IT is used as an enabler of success in
achieving the organization’s performance. IT provides the information for implementing the
best available human resources in the organization. These practices in HR enables the HR to
implement an ideal set of HR practices, which leads towards achieving high performance.
According to Youndt, Snell, Dean, and Lepak (1996), the literature shows that the HR practices
44
have a direct impact on an organization’s performance. Organizations opting and implementing
best practices in HR have found a direct relationship with organization’s performance and these
relationships would be stronger enough to become competitive requirements for the firm.
Lawler III (2005) says organizations should treat HR practices as HR services to all employee
of the organization, that would helpful for senior people for achieving strategic outcomes
through these practices. Providing HR services to employees could be implemented with the
help of HRIS adoption.
Dyer and Reeves (1995) relate the organization’s performance in a way that it could be derived
as a result of a synergetic set of HR practices and strategies. These strategies can be formulated
in three ways: (i) financial outcomes, (ii) operational outcomes, and (iii) HR outcomes.
According to Jiang, Lepak, Hu, and Baer (2012), these outcomes may vary in term of impact
on an organization’s performance by adopting HR practices and innovations. However, among
these measures, most of the research has been considering the impact of HR systems on
financial outcomes. Roos, Fernstrom, and Pike (2004) argued that innovative HR practices can
contribute to enhancing an organization’s performance. IT and innovation are highly correlated
and IT provide a positive contribution to achieving superior performance. Among these
measures, the author Boselie, Dietz, and Boon (2005) discussed that the word “performance”
and financial performance predominately used in literature. The reasons for opting financial
measure is because it directly targets the profit of an organization which is the ultimate goal of
the stakeholders and shareholders. IT/ IS in HRM as innovation is the best enabler to attaining
the profit of an organization (Townsend & Bennett, 2003; Moore & Benbasat, 1991). Guest,
Michie, Conway, and Sheehan (2003) discussed that the organization’s performance can be
measured objectively as well as subjectively. The author draws the conclusion that subjective
measure of an organization’s performance is strongly associated with HRM. Youndt, Snell,
Dean, and Lepak (1996) also, implied self-reported measure due to the non-availability of
objective financial numbers. The under-study sample also using the same procedure of
measuring the organization’s performance.
The literature on HRIS reveal that the use of HRIS allows the HR staff to become strategic
player in organization (Hussain, Wallace, & Cornelius, 2007), and also linking with the
adoption of greater number of HRIS applications is due to more strategic roles of HRIS in
organization (Teo, Soon, & Fedric 2001). Rodriguez and Ventura (2003)also, indicated that the
strategic orientations of HRIS have a positive impact on the organization’s performance.
Kaplan and Norton (1992) elaborated the organization in both ways: financial and non-financial
measures. Both can be implied for determining the organization’s performance.
45
Rodriguez and Ventura (2003) discussed that the adoption of human resource systems is always
positively related to the organization’s performance. The authors used the perceived measure
of organization’s performance, and has taken data on three parameters of organizations: firm
return on assets (ROA), firm total sales growth, overall firm performance. For subjective
measures, the author has used data in comparison with the rival of organizations in the industry.
According to Yeh-Yun Lin (2007) current year data may be used for comparison with a rival
in industry. In the same vein, Youndt, Snell, Dean, and Lepak (1996) current year performance
can be measured with respect to a competitor in the industry.
Likewise, other authors Singh, Darwish, and Potocnik (2016), Richard, Devinney, and Johnson
(2009), Aragon-Correa, Garcia-Morales, and Cordon-Pozo (2007) discussed that organization’s
performance can be measured by using subjective measure and objective measure. The authors
further discussed that both measures can be employed to determine that organization’s
performance, both measures are consistent and reliable. In accessing the firm’s subjective
performance, the organization’s performance is measured with comparison with the rivals.
According to the study of Boselie, Dietz, and Boon (2005), Yeh-Yun Lin (2007) also supported
that many of studies used the perceptual measure to measuring organization’s performance
because of it is difficult to obtain data of objective measure. Subjective organization’s
performance is made on following parameters i.e. (1) market share, (2) sales revenue, (3)
innovation and (4) profitability. Lee and Choi (2003), Venaik, Midgley, and Devinney (2005)
measured the organization’s performance in term of subjective measure that includes the overall
success of the organization in term market share, profitability, and innovation.
2.8 Extent of Human Resource Information System Adoption and Organization’s
Performance
According to Ravichandran and Lertwongsatien (2005) extent of IT adoption has an impact on
the organization’s performance. Bharadwaj (2000) IT systems enhancing organization
capabilities which leads to achieving superior organization’s performance by utilizing IT
capabilities as innovation. The objective of the study is to examine the relationship of HRIS
adoption with the organization’s performance and impact of extent of HRIS adoption on the
organization’s performance. Tye and Chau (1995) highlights the importance of HRIS and
expressed that it is one of the areas in which IT is used most extensively. Hitt and Brynjolfsson
(1996), Palmer and Markus (2000) expressed that IT adoption contributes in organization’s
performance. According to Jain and Kanungo (2016) extent of IS used in organizations has a
positive impact with IS enabled performances. Khalil Darwish and Singh (2013) explained that
human resource practices directly impact the organization’s performance. The authors observed
46
that the greater the use of HR applications has a greater impact on an organization’s
performance. Chand and Katou (2007), Schuler and Jackson (1999), has also found that the HR
system has a direct relationship with the organization’s performance. According to Bharadwaj
(2000) use of IT skills in management organization administratively help the organizations to
deploy human resources in a way to get strategic objectives which improve organizations’
performance. Organizations adopting HRIS, or similar system adopted by a competitor could
not achieve the superior performance unless they opt extent of HRIS adoption, that will
contribute in organization’s performance by utilization the right application to its full extent.
Nwankpa (2015) discussed the ERP implementation in organizations, according to author, the
extent of ERP implementation leads to adopting more application modules to extend the scope
of the system. Larger the use of application enhancing the performance of the organizations.
2.9 Moderating Role of HR Staff Expertise
A vast literature in the field of information systems revealed that the success and failure of
information systems are largely depending on the capabilities of the staff who is using the
system (Bamel, Kumar Bamel, Sahay, & Thite, 2014). In the same lines, the extent of adoption
of information system in an organization depends on the expertise of the staff. Skilled staff
demanding more and more applications and using these available applications to its full extent
and vice versa. Human resource department is a key department in organization whose
responsibility is to provide right man at the right place, it could be possible with the help of
swift processing and availability of information, so that organization can get benefits of its full
extent (Wiblen, Grant, & Dery, 2010). Markham (2017) further, highlights the importance of
HR staff’s expertise, who’s responsibility is to adopt HRIS.
Troshani, Jerram, and Rao Hill (2011) discussed that human capabilities are the predictor of
HRIS adoption. The author discussed the human capabilities in term of strong IT skilled
possessed by HR staff. Thong (1999), Nguyen and Nguyen (2016) expressed that HR staff
should have the working knowledge of using HRIS. They indicate that all employees in the HR
department should have the expertise and skills of using HRIS to complete their tasks. In
literature, it has been found that the extent of HRIS varies across organizations because of
organizations lacking HR staff’s ability and expertise in using HRIS. HR staff’s knowledge and
expertise demanding more applications which provide the uniformity in the HRIS (Teo, Soon,
& Fedric, 2001). According to Lau and Hooper (2008), Wiblen, Grant, and Dery (2010)
technical skills of HR staff are important during the adoption of HR systems. If the HR staff
lacking knowledge of HRIS, the staff is unable to clearly explain the concept of HRIS.
According to Bharadwaj (2000), staff’s IT skills help them in using IS functions more
47
effectively to get the intangible benefits. Organization has the capabilities to utilize the IT
capabilities for gaining superior performance and increasing profitability. This could be
achieved by deploying HR staff who have IT skills for developing application in a way to
leveraging intangibles benefits, like the successful deployment of human resources and other
resources. Lack of IT expertise of HR staff become a major factor of underutilizing the HRIS
and low implementation of HRIS modules (Krishnan & Singh, 2007). Panayotopoulou, Vakola,
and Galanaki (2007) argued that HR professional needs training of using HRIS, further
discussed that in the adoption of HRIS, HR professional training plays a critical role. HRIS
expertise is essential for adoption of human resource systems in organization. Teo, Soon, and
Fedric (2001) discussed that the HRIS knowledge and expertise are the main hindrances that
causes low adoption of HRIS in organizations.
Al-Mobaideen, Allahawiah, and Basioni (2013) expressed that the HR staff’s competency is
important for working of HRIS, if the HR manager is competent than HRIS works well.
Beadles, Lowery, and Johns (2005) argued that without the proper training of human resource
staff, the staff is unable to take full advantage of HRIS capabilities. In some of the cases due to
lack of competency of staff HRIS is underutilized. Haines and Petit (1997) expressed that IT
skills are a predictor of high adoption of HRIS.
Hussain, Wallace, and Cornelius (2007), (Moussa (2014) expressed that the use of HRIS allows
the HR staff to become the strategic player in organization, the use of HRIS allow HR
professional to become a strategic partner in term of providing support in strategic decision
making. HRIS is an enabler to enhance the professional standing of HR professionals by using
HRIS (Hussain, Wallace, & Cornelius, 2007). Igbaria and Nachman (1990) expressed that
employees having computer skills are more satisfied with using the system, the satisfaction
relationship is significant with system utilization. Thus, more computer skills lead the more
system utilization. Computer skills are the core determinants of application adoption and use
(Kasper & Cerveny, 1985; Palvia, Means, & Jackson, 1994). The relationship between extent
of use of software application and organizational profitability has a positive correlation, high
skills of staff leads more utilization of software application, high utilization of software
application leads high profitability (Palvia, Means, & Jackson, 1994; DeLone, 1988).
Panayotopoulou, Vakola, and Galanaki (2007) argued that HR professional need training of
using e-system, further discussed that the adoption of HRIS, HR professionals training plays a
critical role. Moussa (2014) aruged that it never worthless where organizations make
investment in the IS/IT training of their HR staff. This includes all employees in HR
departments who have the expertise and skilled in using HRIS to complete their tasks. HRIS
48
expertise are essential for adoption of human resource systems in organization. HRIS expertise
means that staff should have the working knowledge of HRIS (Troshani, Jerram, & Rao Hill,
2011; Thong, 1999).
Teo, Soon, and Fedric (2001) discussed that HRIS knowledge and expertise are the
impediments for adopting the HRIS. Al-Mobaideen, Allahawiah, and Basioni (2013) expressed
that the HR staff competency plays important role in working of HRIS, if the HR manager is
competent than HRIS works well. Beadles, Lowery, and Johns (2005) argued that without the
proper training of Human resource staff, the staff is unable to take full advantage of HRIS using
capabilities. In some of the cases due to lack of competency of the HR staff, the system is
underutilized and organizations realizing no benefits.
Hussain, Wallace, and Cornelius (2007) express that the use of HRIS allows the HR staff to
become the strategic player in organization. The use of HRIS allow to HR professional to
become a strategic partner in term of providing support in strategic decision making (Moussa,
2014). HRIS is an enabler to enhance the Professional standing of HR professionals by utilizing
HRIS (Hussain, Wallace, & Cornelius, 2007).
49
2.10 Study Model and Hypotheses
2.10.1 Research Model
Factors affecting the extent of HRIS adoption and its impact on organization’s performance: moderated role of HR staff expertise
Figure 2: Research model of the study
Innovation Characteristics
Organizational Characteristics
Environmental Characteristics
Extent of HRIS adoption Organization’s Performance
HR Staff Expertise
50
2.10.2 Formulation of Research Hypotheses
A comprehensive review of literature in the field of human resource management and
information systems were conducted because of the nature of the topic. HRIS is a multi-
disciplinary topic that falls in management studies and information systems domain. The
concept of HRIS has introduced in literature in the 1960s the purpose was only to maintain the
records of personnel as a part of centralized MIS. In this regard, gathered a rich collection of
literature, a strategy was formatted for searching of literature based on keywords and phrases
used for IT possibilities in human resource department. For this purpose, selected keywords
and phrases were used, for example, HRIS, extent of HRIS, ehrm, web based hrm, HR portal
etc. for searching the relevant literature in fields like Title, Abstract, and keywords of an article.
Different digital libraries and database were used for current study for collection of relevant
literature which includes: Scopus, Elsevier, JSTOR, Ebscohost, IEEE, Emerald, Science Direct,
Springer link, Sage, ProQuest and Google scholar. Along with databases, personal web pages
of selected authors were also visited to gather related articles.
The selected literature was reviewed and found that various naming conventions were used,
like e-HR, e-HRM, HR intranet, web-based HR, computer-based human resource management
systems (CHRIS), and HR portals. All Jorgen and buzzwords used in literature have a consensus
on the definition of HRIS given by (Tannenbaum, 1990). The reviewed literature revealed that
studies have been conducted in different functions areas of HRM. Some of the authors worked
on adoption of HRIS as a system in different function of HRM. Some of the authors worked on
antecedents of HRIS adoption. The literature also revealed that a major portion of the HRIS
research has been carried out in developed countries like America and Europe. Little research
has been carried out in Asian context in general and in Pakistan particularly. Studies using
various theories and models in the adoption of IS/IT, and IS/IT is treated as innovation at the
individual level and at the organization level. Predominately innovation diffusion theory is
employed in HRIS adoption. The theme of the current study is extent of HRIS adoption. In this
theme, authors differently operationalized the concept like few studies carried out on the
concept of extent of HRIS in term of No. of computers allocated for use of HR staff, No. of
applications used by an organization, and the benefits derived HRIS. No one discussed the
concept of extent of HRIS adoption according to its functional approach. The current study
explains the concept of extent of HRIS adoption in accordance with its functional description
as proposed by Mayfield, Mayfield, & Lunce, 2003).
51
The research hypotheses based on proposed design i.e. innovation organization environment
(IOE) to investigate the factors affecting the extent of HRIS adoption. Five research hypotheses
of the study have been investigating the factors affecting the extent of HRIS adoption and its
impact on organization’s performance. moderating role of HR staff expertise between the extent
of HR adoption and the organization’s performance.
H1. Innovation characteristics have positive impact on extent of HRIS adoption.
H2. Organization characteristics (2a top management support, 2b organization size) will
have significant positive impact on extent of HRIS adoption.
H3. Environment characteristics have positive impact on extent of HRIS adoption.
H4. Extent of HRIS adoption has positive impact on organization’s performance.
H5a. HR staff expertise’s has positive impact on organization’s performance.
H5b. HR staff expertise’s moderate the relationship between extent of HRIS adoption
and organization’s performance.
2.11 Chapter Summary
This chapter described the available literature on the topic. The researcher establishes the
relationships between the variables with the help of academic reasoning and theoretical
underpinning. In this chapter literature is discussed and summarized on logical conclusion of
all variables exists in research framework.
52
CHAPTER 3
METHODOLOGY
The aim of this study was to investigate the factors affecting the extent of HRIS adoption, and
its impact on organization’s performance. Further, the study also observed the moderating
effect of HR staff expertise was also tested. The following chapter explains the research
philosophy, research design and methodological approaches including the basic assumptions
pertaining to different components used which include population, and selection of sample. The
chapter also introduces the data collection instrument, and related concepts like pilot study,
reliability and validity. At the end, the data collection procedure, data analysis techniques, and
underlying data analysis methods will be discussed.
3.1 Research Philosophy and Paradigm
Prior to any research endeavor its prudent that a researcher sets out his/her research philosophy.
This allows the consumer of research to separate the voice of the researcher from the many
views contained in the research output and to understand the context in which the researcher
has approached the research (Saunders, Lewis, & Thornhill, 2016). A research philosophy
reflects the researcher’s assumptions on the nature of knowledge, and how knowledge is
created. The old adage “beauty lies in the eye of the beholder” is representative of how
researchers view the reality around them from the perspective of their own understanding of
what that reality represents. Consequently, the philosophical assumptions help to chalk out
strategy and methods to understand the reality under observation. To achieve the objectives of
the research, careful selection of research philosophies and related assumptions are important
so that results of the study can be interpreted in a true sense and allows for reproducibility and
generalizability. According to Saunders, Lewis, and Thornhill (2016), there are three sets of
philosophical assumptions, e.g. (i) ontology, (ii) epistemology, and (iii) axiology related to the
creation of knowledge. Mingers and Willcocks (2004) also highlighted these terms i.e.
ontology, epistemology, methodology, methods as a philosophical assumption. These
assumptions are useful in developing better research approaches. Most of the research
conducted in the field of business and management is based on existing theories in a way of
modifying these theories or building new ones. The current study follows the same approach it
will be building upon the theory of innovation known as innovation diffusion theory,
Technology Organization Environment (TOE) framework i.e. Innovation Organization and
Environment (IOE) and further, explain the concept of the extent of HRIS adoption.
The subject matter of the current study falls in the domain of IT adoption by organizations in
general and in the HR department in particular. Previous studies conducted in this field have
53
employed the positivistic paradigm (e.g., Orlikowski & Baroudi, 1991; DeSanctis, 1986;
Nguyen & Nguyen, 2016; Fichman, 2004).
A brief description of the aforementioned philosophical assumptions as follows.
3.1.1 Ontology
Ontology means nature of reality (Iivari, Hirschheim, & Klein, 1998). According to Saunders,
Lewis, and Thornhill (2016) there are two key ontological assumptions that can be adopted.
These assumptions are objectivism and subjectivism. The objectivism assumes that social
constructs exist independent of the social actors, whereas the subjectivism assumes that social
constructs are created from the interaction of social actors with each other and with their
surroundings. Based upon the ontologically assumption, the current study follows in
objectivism in which the constructs of the study are independent to human intervention.
3.1.2 Epistemology
Epistemological assumptions deal with the nature of knowledge which will in turn determine
what is viewed as acceptable knowledge and how that knowledge can be acquired in a field of
study (Iivari, Hirschheim, & Klein, 1998). Sekaran and Bougie (2016) discussed approaches
for the development of acceptable knowledge, the first being that reality is objective, and that
the researcher has no influence on the reality. This approach is referred as positivism. Second,
that reality is subjective and that the researcher is a part of the reality and thus can influence the
reality. This approach referred as constructionism. This approach focuses on the relationship
between theory and practice. In the context of organization and technology adoption, the
philosophy of current study is positivistic, which explore the factors affecting the extent of
HRIS adoption.
According to Orlikowski and Scott (2008) discussed that how new technology has had an
impact on human action and thoughts normally using positivist paradigm, in which technology
is used as independent variable that has impact on organization. The current study also deals
with extent of HRIS adoption and its impact on organization’s performance. Positivistic
approach is typically associated with quantitative techniques of data collection. These
techniques are highly structured in a way that all efforts involve to operationalization the study’s
constructs, build specific instrument to measure each construct. The quantitative data is
collected from a sizeable sample of the target population to achieve the objectives, empirically
prove the relationships between constructs that would be replicable and generalizable.
54
Positivist epistemology was deemed appropriate for the current study considering that the goal
of the study which was objectively determine the impact of extent of HRIS adoption on
organization’s performance where organizations adopting HRIS.
The extent of HRIS adoption was operationalized in quantitative terms. According to Olivas-
Lujan and Rousseau (2010), the positivistic viewpoint promulgates knowledge through
empirical validation. Similarly, (Bondarouk, Ruel, & Looise, 2011; Orlikowski & Baroudi,
1991) are also in the view that research conducted on the use of IT in HR is dominated by
positivistic approach. Positivistic research is credited with enhancing the view of different
organizational phenomena. According to Ruel, Magalhaes, and Chiemeke (2011) positivist
paradigm has had a significant influence on shaping our understanding with regards to how
organizations adopt and develop their IT infrastructure.
Axiological assumptions deal with the judgments regarding values, or the considerations about
what is right and wrong (Mingers, 2003). According to Berger and Kuckertz (2016) researchers
employing the positivistic approach will view themselves as independent of the reality that s/he
is studying and will take steps to not pass any value judgments on the reality they observed.
Positivism is the dominate paradigm used in business and management research, therefore, for
these reasons, the most of management research is based on survey design. Saunders (2016)
notes that this approach is appropriate for theory or model building. Positivistic approach is
deductive in nature and employing survey research. Survey research is economical which
covers large population, and useful in generating generalizable research. The research on use
of information systems in human resources are dominated by the use of self-reported survey
(Ngai & Wat, 2006 ; Haines & Petit, 1997).
3.2 Research Methods
Orlikowski and Baroudi (1991) are of the view that large scale survey based research is the
suitable methodology while opting for positivist approaches. Two research methods used to
answer the research question i.e. quantitative and qualitative studies.
3.2.1 Quantitative research
Quantitative research methods deals with analyzing and explaining data (Berger & Kuckertz,
2016), According to Creswell (2013) survey is good for quantitative description and
explanation of data from a large population. According to Orlikowski and Baroudi (1991) , 49%
of the research conducted in the field of IT adoption in organizations is based on survey design
and quantitative in nature. According to Orlikowski and Scott (2008), the new technology has
had an impact on human action and thoughts normally using positivist paradigm, in which
55
technology is used as independent variable that has impact on organization. The extent of HRIS
adoption was operationalized in quantitative terms. According to Olivas-Lujan and Rousseau
(2010), the positivistic viewpoint promulgates knowledge through empirical validation.
3.2.2 Qualitative research
Qualitative research deals with non-quantitative data to examine social phenomena. Qualitative
research methods are subjective in nature (Pratt, 2008). In qualitative research, the data is
collected in the form interviews, focus group discussion and case study. The date in qualitative
research is gather in a form of informal discussion (Sekaran & Bougie, 2016). Creswell (1998)
defines qualitative research as an inquiry that explore social and human problems by observing,
analyzing words, reports and detail interviews of informants. The author mentioned five
common methods for conducting qualitative research i.e. Biography, Phenomenology, Grounded
theory, Ethnography and Case study.
3.3 Research Approaches
The purpose of conducting research is twofold either theory development or testing of existing
theories. These approaches normally named as deductive and inductive. According to (Sanders,
Cogin, & Bainbridge, 2013) natural sciences uses scientific methods to find the solution of a
problem. In scientific methods, the author discussed seven steps for getting solution of
problems. Deductive methods are normally used for theory testing, generally it moves from
general to specific . Whereas, other approach is inductive, which is used for theory generation,
generally it moves from specific to general. The current research is deductive in nature.
Deductive approaches normally examines the relationship between variables employing survey
research. Survey research is economical which covers large population, and useful in generating
generalizable research.
3.4 Research Design
This study is relational/ casual in nature. Casual studies normally express the relationships
between variables called explanatory studies. The purpose of these studies is to explain the
relationships between variables (Sanders, Cogin, & Bainbridge, 2013). The study used mono
method approach in contrast to multi method approach. Multi method approach employed more
than one procedures to answer the research questions. Mono method research uses different
research techniques including the survey design, structured interview, and structure
observations. Survey design has become the dominant choice, because it allows researchers to
gather data from a large population. According to Orlikowski and Baroudi (1991) , 49% of the
research conducted in the field of IT adoption in organizations is based on survey design.
56
In this study, the questionnaire based cross sectional survey strategy was used. The current
study aims to determine the relationship between the antecedents of the extent of HRIS
adoption, the extent of HRIS adoption and its impact on organization’s performance, and
moderating role of HR staff expertise between the extent of HRIS adoption and organization’s
performance. The survey designed was deemed appropriate for the current study, as similar
studies also employed the research method (Mishra & Akman, 2010; Hsieh & Wang, 2007;
Ball, 2001; Teo, Soon, & Fedric, 2007; Martinsons, 1994).
3.4.1 Type of Study
To measures the organization’s response for this study, survey design has been considered.
Relevant literature revealed that the majority of studies conducted used the survey for example
(Panayotopoulou, Galanaki, & Papalexandris, 2010; Yang, Lee, & Lee, 2007; Ahmer, 2013;
Ball, 2001). The reasons for using the survey design is due to its effectiveness for collecting
data in quantitative studies which are exploratory in nature. According to Creswell (2013)
survey is good for quantitative description and explanation of data from a large population.
Additionally, Evans and Mathur (2005) highlighted the benefits of survey design in a way that
its appeared same for everyone, having variety of questions and adoptability as compare to
other designs which eliminate the researcher bias.
3.4.2 Study Setting
The study is conducted in a natural setting to collect data in a real time working environment.
The managers of the concerned organizations were contacted to fill the questionnaire. There
was no artificial setting created for any variable and none of the study variable is neither
controlled nor manipulated. The extent of researcher interference is low.
3.4.3 Extent of Researcher Interference
The study is conducted with normal work flow in a real working environment. The extent of
researcher interference is low because the researcher has no interference with normal flow of
the work during performing deities.
3.4.4 Time Horizon
The data from organizations using HR systems were collected in four months of time span,
starting from October 2016 to January 2017. The data were cross-sectional in nature, collected
from organizations based in Islamabad, the capital territory of the country. The reason for
collecting data at the end of year is because of at that time period HR staff is actively involved
in utilizing the HRIS systems. furthermore, at the same time organization’s performance is in
57
concluding phase and HR managers are finalizing the incentives to staff. The manager has an
active eye on organization’s performance figures.
3.4.5 Unit of Analysis
The unit of analysis for this study is organizations using any sort of computerize systems in
their HR department. Since the research was exploring the factors affecting the extent of HRIS
adoption in organizations and what is the relationship between extent of HRIS adoption and
organization’s performance. Further, the study also investigates what is the role of HR staff
expertise towards the extent of HRIS adoption in those organizations.
3.5 Population and sample
This section discuss the population of the study and sampling technique employed for drawing
the sample.
3.5.1 Population
According to Sekaran and Bougie (2016) population referred to the entire set of cases or objects
from which the sample is to be drawn, and to which the researcher intends to generalize research
in the given domain. The key characteristics of a population are its: availability, accessibility,
quantifability, and its relatedness to the research. According to Polit (2013) the portion of
population which is directly accessible to the researcher is classified as the accessible
population.
The population of the current study comprises private sector organizations. According to
Securities & exchange commission of Pakistan around 12150 companies listed in private sector
in capital Territory (SECP, 2016) not all companies are operative and not all companies using
computerised system in their HR department. According to Ahmer (2013) 60 companies were
using HRIS applications in Pakistan. It shows low adoption of HRIS. So, the population of
current study was all those organizations they have computerized system in their HR
departments. The reasons for selecting the private sector organizations is twofold: (i) the sector
is more dynamic, and adopt innovation proactively (Troshani, Jerram, & Gerrard, 2010;
Troshani, Jerram, & Rao Hill, 2011). (ii) the accessible population was the private sector
organizations located in Islamabad where head offices of the organizations are based in the city.
Data were collected from organizations that had implemented HRIS systems, regardless of the
extent of use, the types of modules implemented, and the vendor of the HRIS in case of off-the-
shelve solutions.
58
3.5.2 Sampling
The purpose of sampling is to select a representative sub-set of the overall accessible
population. The purpose is to collect data from the sample and then to generalize the results to
entire population. Sampling is considered important when it is not feasible to study the entire
accessible population. According to Willcocks, Sauer, and Lacity (2015) it is not necessary that
the responses of population would be more useful than just collecting responses from a sample.
The sampling frame of current study was those organizations they have any sort of
computerized system in their HR departments and they are using HRIS to any extent. The
sample unit was HR department of an organization. Sampling is generally of carry two
alternative methods: (i) probability and (ii) non-probability. In probability sampling, the
population is known, each individual in the population has the same chance to be selected as a
member of the sample. Whereas, in non-probability sampling, the population is unknown, and
participants may be selected on convenience basis. Judgmental sampling was used to select the
sample. The judgment is based upon the factors such as HR department of organizations using
any sort of computerizations to any extent. Managers working in HR department of the different
organizations were approached through professional acquaintances. Judgmental sampling
approach was employed because of computerized systems had not been adopted by
organizations widely. In contrast to organizations in developed countries, developing countries,
such as Pakistan, are characterized as lacking the formal implementation of HR functions. The
typical functions of HR department are normally performed by the personnel and administration
department. These departments mostly operated manual, without using soft technological
artefacts. Managers were explained about survey and ensured the confidentiality and privacy.
A total of 250 survey distributed, 108 returned comprised 43.2 % response rate. Judgmental
sampling approach was used in similarly types of studies for example (Mishra & Akman, 2010;
Tye & Chau, 1995; Premkumar & Roberts, 1999; Teo, Soon, & Fedric, 2001). In the local
context, the judgmental sampling would be appropriate for organizational level studies in the
field of ICT (Ahmer, 2013).
3.6 Demographics of Respondents
This section describes the personal demographic and organizational demographic information
of the survey sample. The personal demographics includes gender, education, age, designation,
experience in current designation, current organization, and total professional experience.
Whereas the organizational demographics includes organization industry, life span of business,
employees in HR department, number of computers in HR department, and age of HRIS.
59
A short description of personal demographics, gender included two options male and female.
The qualification of the respondents measured the education level such as bachelor, master,
MS/ MPhil and PhD. The age of the respondents having six option included less than 25 years,
25-34 years, 35-44 years, 45-54, 55-64, 65 years and above. The designation of the respondents
of HR department included deputy manager / director, manager / director, senior manager /
director, and others. The experience on current designation option includes less than 1 year, 1
to 3 years, 4 to 7 years, 8 years or more. The experience in current organization covers options
less than 3 years, 3 to 6 years, 7 to 10 years, 11 to 14 years, and more than 14 years. At the end
total professional experience of respondents which have option less than 5 years, 5 to 9 years,
10 to 14 years, 15 to 20 years, and 21 years or more.
The organization demographic information captured included one: the nature of industry
architecture/ engineering, banking and finance, computers / IT, education, health / hospital,
manufacturing, services, trading, travel / hotel, and others. Two: No. of years in business having
option less than 3 years, 4 to 6 years, 7 to 9 years, 10 to 12 years, 13 to15 years, and more than
15 years. Three: No. of employees in HR department having options included 1 to 3 employees,
4 to 6, 7 to 9, 10 to 12, 13 to 15, and more than 15 employees. Four: number of computers
dedicated for HR department have options 1 to 3 computers / laptops, 4 to 6, 7 to 9, 10 to 12,
and more than 12 computers / laptops. Five: age of human resource information system included
options less than 1 year, 1 to 3 years, 4 to 6 years, 7 to 9 years, 10 to 12 years, and more than
12 years.
3.6.1 Characteristics of the Respondents
Gender: Table 2 presents the characteristics of the respondents. Among the responding sample,
76.9% (83) respondents were male and 23.1% (25) were female. The low ration of female
managers in human resource departments is in accordance with local ration of females
professional working in industry.
Table 2: Gender of Respondents
Table 2: Gender of Respondents
Frequency Percent Cumulative Percent
Valid Male 83 76.9 76.9
Female 25 23.1 100.0
Total 108 100.0
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Education: Table 3 The educational qualification was measured in four categories as minimum
entry level qualification is bachelor. Upon receiving responses, 9.3% respondents were
bachelor degree means 14 years of education qualification, 59.3% were master, 28.7% means
16 years of qualification and 28.4 % were MS/ MPhil. equivalent to 18 years’ qualification, and
2.8% were Ph.D. The analysis revealed that the majority of respondents 88% was 18 years of
qualification (Table 3).
Table 3:Education of Respondents
Table 3 Education of Respondents
Frequency Percent Cumulative Percent
Valid Bachelor 10 9.3 9.3
Master 64 59.3 68.5
MS/ M.Phil. 31 28.7 97.2
Ph.D. 3 2.8 100.0
Total 108 100.0
Age: In term of the age of HR managers, the respondents includes, 6.5 % were less than 25
years of age, 61.1 % were between 25-34 years, 21.3% were between 35-44 years, 7.4% were
between 45-54, 2.8% were between 55-64 whereas 0.9% were above 65 years of age. Majority
of the respondents were young and belongs to 25-34 years’ age bracket (Table4).
Table 4:Age of Respondents
Table 4: Age of Respondents
Frequency Percent Cumulative Percent
Valid Less than 25 7 6.5 6.5
25-34 66 61.1 67.6
35-44 23 21.3 88.9
45-54 8 7.4 96.3
55-64 3 2.8 99.1
65 + 1 0.9 100.0
Total 108 100.0
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Designation: The analysis of the designation of the responding managers included, 36.1% of
Deputy managers/ Directors, 31.5% were Managers/ Directors, 5.6% were Senior managers/
directors and 26.9% were fall in other titles in same department and managerial ladder. The
reasons for selecting middle and higher-level management of HR department is because of they
are good informants and due to their role in management and their involvement in decision
making. These characteristics enabling them to realize the benefits of system used in their
department. Table 5 describe the characteristics of respondents by designation.
Table 5:Designation of Respondents
Table 5: Designation of Respondents
Frequency Percent Cumulative Percent
Valid Deputy Manager / Director 39 36.1 36.1
Manager / Director 34 31.5 67.6
Senior Manager / Director 6 5.6 73.1
Others 29 26.9 100.0
Total 108 100.0
Experience in current designation: The experience of respondents in current designation was
10.2 % were less than one year, 37% were between 1 to 3 years, 31.5% were between 4 to 7
years and 21.3% were 8 years or more. Majority of the respondents working on current positions
long time reveals that they are managing system in well-mannered. (Table6).
Table 6:Experience in current designation of respondents
Table 6: Experience in current designation of respondents
Frequency Percent Cumulative Percent
Valid Less than 1 Year 11 10.2 10.2
1 to 3 years 40 37.0 47.2
4 to 7 years 34 31.5 78.7
8 years or more 23 21.3 100.0
Total 108 100.0
62
Experience in current organization: In term of employees experience in the current
organization, 31.5%% having less than 3 years, 31.5%% were between 3-6 years, 19.4 %
between 7-10 years, 8.3 % were between 11-14 years and 8.3% were more than 14 years of
experience in the current organization (table7).
Table 7:Experience in current organization of respondents
Table 7: Experience of the respondents in current organization
Frequency Percent Cumulative Percent
Valid Less than 3 years 34 31.5 31.5
3 to 6 years 35 32.4 63.9
7 to 10 years 21 19.4 83.3
11 to 14 years 9 8.3 91.7
More than 14 years 9 8.3 100.0
Total 108 100.0
Professional experience: As for as total professional experience was concerned, 21.3%
respondents were fall in less than 5 years of category, 32.41% were between 5-9 years, 25.9%
between 10-14 years, 10.2% were between 15-20 years, and 10.2% were more than 21 years of
total professional experience (table 8).
Table 8:Total professional experience of Respondents
Table 8: Total professional experience of the respondents
Frequency Percent Cumulative Percent
Valid Less than 5 Years 23 21.3 21.3
5 to 9 years 35 32.4 53.7
10 to 14 years 28 25.9 79.6
15 to 20 years 11 10.2 89.8
21 years or more 11 10.2 100.0
Total 108 100.0
63
3.6.2 Characteristics of Organizations
Organization Industry: The distribution of the respondent’s organization by industry revealed
that, 9.3 % of organization were from architecture/ engineering, 23.1, were from banking and
finance, 13.9 % were computers / IT, 4.6% of organizations were from education, 6.5% of
organization from health / hospitals, 6.5 % of organization were from manufacturing, 23.1% of
organizations were from services industry, 2.8% were from trading, travel/ hotels and 7.4% of
organizations were from other categories such as consultancy firms, law firms etc.
Table 9:Organization industry of responding organization
Table 9: Types of the responding Organizations.
Frequency Percent Cumulative Percent
Valid Architecture/Engineering 10 9.3 9.3
Banking & Finance 25 23.1 32.4
Computers / IT 15 13.9 46.3
Education 5 4.6 50.9
Health / Hospital 7 6.5 57.4
Manufacturing 7 6.5 63.9
Services 25 23.1 87.0
Trading 3 2.8 89.8
Travel / Hotel 3 2.8 92.6
Others 8 7.4 100.0
Total 108 100.0
Organization’s Business Experience: The distribution of respondent’s organization explains
number of years in business. The responding organization was 2.8% were less than three years,
6.5% were between 4 to 6 years, 2.8% were between 7 to 9 years, 13.9% were 10 to 12 years,
13.9% were 13 to 15 years and 60.2% were more than 15 years or more. Majority of the
organizations having long standing in business in term of experience (table 10) the analysis
describes that majority, of the organization having experience over ten years.
64
Table 10:No. of years in business of responding organization
Table 10: Years of business of the responding organizations
Frequency Percent Cumulative Percent
Valid Less than 3 years 3 2.8 2.8
4 to 6 years 7 6.5 9.3
7 to 9 years 3 2.8 12.0
10 to 12 years 15 13.9 25.9
13 to15 years 15 13.9 39.8
More than 15 years 65 60.2 100.0
Total 108 100.0
Employees in HR department: Distribution of respondent’s organization by number of
employees in HR department was 11.1% between 1 to 3. 14.8% between 4 to 6, 15.7% between
7 to 9, 9.3% between 10 to 12, 12% between 13 to 15, and 37% between more than 15% were
serving in HR department. (Table 11)
Table 11: No. of employees in HR department of responding organization
Table 11: Number of employees in HR department of the responding organizations
Frequency Percent Cumulative Percent
Valid 1 to 3 12 11.1 11.1
4 to 6 16 14.8 25.9
7 to 9 17 15.7 41.7
10 to 12 10 9.3 50.9
13 to 15 13 12.0 63.0
More than 15 40 37.0 100.0
Total 108 100.0
Number of Computers in HR Department: Number of computers/ laptops dedicated for the
used in HR department. No of computers/ laptops provided to HR department for using HRIS
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was 15.7% between 1 to 3. 10.2% between 4 to 6, 12% between 7 to 9, 14.8% between 10 to
12, and 47.2% 12 or more computers were dedicated in HR department for using HRIS
application Table 12.
Table 12:No. of computers in HR department of responding organization
Table 12: Computers/ laptops in HR department of the responding organizations
Frequency Percent Cumulative Percent
Valid 1 to 3 17 15.7 15.7
4 to 6 11 10.2 25.9
7 to 9 13 12.0 38.0
10 to 12 16 14.8 52.8
More than 12 51 47.2 100.0
Total 108 100.0
Age of HRIS: The age of HRIS application in responding organization was less than one year
were 5.6%. 11.1% were between 1 to 3 years, 23.1% were between 4 to 6 years, 18.5% were 7
to 9 years, 16.7% were 10 to 12 years and 25.0% were more than 12 years. Table 13.
Table 13:Age of HRIS of responding organization
Table 13: Age of HRIS of the responding organizations
Frequency Percent Cumulative Percent
Valid Less than 1 year 6 5.6 5.6
1 to 3 years 12 11.1 16.7
4 to 6 years 25 23.1 39.8
7 to 9 years 20 18.5 58.3
10 to 12 years 18 16.7 75.0
More than 12 year 27 25.0 100.0
Total 108 100.0
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3.7 Scale and Measures
The research variables were measured on five point Likert scale type starting from strongly
disagree to strongly. List of the scales is given below that was used to measure the variables.
(i) Innovation characteristics, Moore and Benbasat (1991) scale
(ii) Organizational Characteristics, Premkumar and Roberts (1999) scale
(iii) Environmental Characteristics, Premkumar and Roberts (1999) scale
(iv) Extent of HRIS adoption scale access the level of adoption of HRIS in term of
utilization of functional description given by Mayfield, Mayfield, and Lunce (2003)
(v) HR staff expertise Thong (1999) scale
(vi) Organization’s performance, Lee and Choi (2003) scale
(vii) Demographics (personal and organizational) self-items, and Teo, Soon, and Fedric
(2001)
67
A summary of the scales used in the study’s instrument is given below.
Table 14:Summary of Scales
Table14: Summary of Scales
Variables Author of scale Sub scale No of Items
Innovation characteristics
Moore and Benbasat (1991)
22
Organization characteristics
Premkumar and Roberts (1999)
6
Environmental Characteristics
Premkumar and Roberts (1999)
3
Extent of HRIS
Items based on functional description given by Mayfield, Mayfield, and Lunce (2003)
13
HR staff expertise Thong (1999) 3
Organization’s performance Lee and Choi (2003)
5
Demographics
Personal
Organization
Self, Teo, Soon, and Fedric (2001)
Gender Education
Age Designation
Experience in current designation Experience in current organization Total professional experience.
Organization industry
Life span of business Employees in HR department
No. of computers in HR dept. Age of HRIS
7
5
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3.7.1 Innovation Characteristics
The innovation characteristics has been measured as aggregate variable. The innovation
characteristics was used by different authors in five different attributes. Rogers (1995) takes
these attributes as highly interrelated with each other but at the same time expresses that these
attributes are conceptually distinct with each other. The relevant literature reveled that
characteristics of innovation varies among theories of innovations (Jeyaraj, Rottman, and
Lacity, 2006). In this study, these attributes were taken as aggregated as these are interrelated
with each other, the scale is used having 22 items. Becker and Huselid (1998) suggests that the
measuring the coherent impact of construct by combining means across all functions may be
used. The attributes of innovation characteristics will be measured by the scale developed by
(Moore & Benbasat, 1991), using five Likert point starting from “Strongly disagree” to
“Strongly agree”. This scale has 22 items. All items were taken as aggregate, the average value
of these attributes was taken. The reported reliability of the innovation characteristics was 0.92.
3.7.2 Organizational Characteristics
Organizational characteristics refers to top managements support, was measured using five
Likert point starting from “Strongly disagree” to “Strongly agree”, and organization size in term
of the number of full time employees and estimated annual revenue. The items of this scale
were measured by the scale used by (Premkumar & Roberts, 1999), having 6 items, the scale
has been previously empirically validated by (Lin, 2010; Bradford & Florin, 2003; Premkumar
& Ramamurthy, 1995). The reported reliability of the organizational characteristics was 0.916.
3.7.3 Environmental Characteristics
Environmental characteristics refers to competition, will be measured using five point Likert
type scale starting from “Strongly disagree” to “Strongly agree”, the items of this scale were
adopted by the scale used by (Premkumar & Roberts, 1999), having 3 items in it. The scale was
previously empirically validated by (Teo, Soon, & Fedric, 2007; Thong, , 1999) and they found
positive associations with extent of HRIS adoption. The reported reliability of the scale was
0.791
3.7.4 Extent of Human Resource Information System
It refers to the extent of HRIS functions adopted by organization in terms of utilization level of
HRIS functions. HRIS functions includes strategic integration, personal development,
communication and integration, records and compliance, human resource analysis, knowledge
management, and forecasting and planning (Mayfield, Mayfield, & Lunce, 2003). Various
studies measure the adoption of HRIS in term of number of application adopted by
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organizations using dichotomous variable i.e. “Yes” “No” and number of computers dedicated
for the use of HRIS (Teo, Soon, & Fedric, 2001 ; Altarawneh, 2010; Teo, Soon, & Fedric,
2007). The extent of HRIS adoption of current study measures by extent to which each
functional area is adopted by organization. The scale of extent of HRIS was used keeping in
view the adoption level of HRIS functionality in terms of its utilization in organizations. The
scale access the level of adoption of HRIS, the level of adoption was based on the functional
description given by (Mayfield, Mayfield, & Lunce, 2003). Thirteen questions were asked to
measured extent of HRIS adoption. The adoption was measured using five point Likert type
scale where starting from “Not at all” to “a great extent” as the same procedure was adopted by
(Altarawneh, 2010; Powell & Dent-Micallef, 1997 ; Premkumar & Ramamurthy, 1995) for
measuring the extent of HRIS adoption. The aggregate score of all HRIS function were taken
as extent of HRIS adoption. Becker and Huselid (1998) suggests that the measuring the coherent
impact of construct by combining means across all functions may be used. The same was
implied by Guest, Michie, Conway, and Sheehan (2003) for HR practices in organizations as
well as (Grover & Goslar, 1993) for extent of technologies adoption in organization. Hence, the
extent of HRIS was measured based on combine means of seven functions of HRIS. The items
used to measure the extent of HRIS adoption were (1) In my organization HRIS is used to aid
top management. (2) In my organization HRIS is used to making long term HR planning. (3)
In my organization HRIS is used to enhance worker’s skills and ability. (4) In my organization
HRIS is used to enhance quality of work life (5) In my organization HRIS is used for inter
organizational communication. (6) In my organization HRIS is used for change management.
(7) In my organization HRIS is used to manage organizational information. (8) In my
organization HRIS is used to ensure governmental compliance. (9) In my organization HRIS is
used for gathering HR needs. (10) In my organization HRIS is used for identifying HR needs.
(11) In my organization HRIS is used to develop knowledge. (12) In my organization HRIS is
used to store HR practices. and (13) In my organization HRIS is used to forecast long term HR
needs. The reported coefficient of alpha was 0.952 which would be good enough in comparison
with the parameters given in literature.
3.7.5 HR Staff Expertise
The authors Thong (1999), Panayotopoulou, Vakola, and Galanaki (2007) refers HR staff
expertise as all employees in HR department who have the expertise and skills of using HRIS
to complete their tasks. The scale of HR staff expertise, comprised three items was adopted
from the study of (Thong, 1999). The data is measured through Likert scale starting from
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“Strongly disagree” to “Strongly agree”. The measures used by Teo, Soon, and Fedric (2007)
reported 0.67 alpha reliability. The alpha reliability of this scale is 0.74.
3.7.6 Organization’s Performance
The organization’s performance refers subjective measures of financial performance of an
organization. The scale of OP was measured using four parameters given in the literature which
were: (i) market share,(ii) sales revenue, (iii) innovation and (iv) profitability (Singh, Darwish,
& Potocnik, 2016 ; Lee & Choi, 2003). The scale of OP was adopted from Lee (Lee & Choi
2003). The scale used to measure perceptual organization’s performance comprised five items,
these measures access the performance of an organization with reference to other organizations
in industry. The data were measured in five Likert points starting from “Strongly disagree” to
“Strongly agree”. The managers of HR department were asked to respond with respect to their
competitors in industry. According to Bradford and Florin (2003) performance related
responses taken from key informants would be consistent because of active involvement of the
manager in their area of IS adoption. In past, alpha reliability reported by (Galbreath & Galvin,
2008) was 0.77. The reliability of scale in current study was 0.911. The reason for opting for
perceptual measures was non-availability of financial figures, organizations hesitant to share
financial information. The authors Law and Ngai (2007) , Bradford and Florin (2003) also,
opted perceptual measure of organization’s performance in studying ERP system adoption by
organizations. The same was employed by Beard and Dess (1981) for measuring organization’s
performance. Dess and Robinson (1984) equating the perceived organization’s performance
measure with objective measure. The author suggested that in a condition where financial
figures would be inaccessible, researcher may employ subjective measures to measuring
organization’s performance. The subjective measures would be appropriate to measuring
organization’s performance.
3.8 Procedure of Data Collection
Data for research were collected through self-administered questionnaire. A three-page
questionnaire along with covering statement was delivered to managers working in HR
department of organizations through personal acquaintance (Attached in appendix “A” The
covering statement explaining the purpose of study and a promise to maintained confidentially
of the data including identity of respondent and organization name. the questionnaire was also
sent through email to HR managers of the accessible population. The data were collected in
four months, owing the facts that data collected at organizational level in which one
organization filled only one survey instrument. A total of 250 survey distributed, 108 returned
comprised 43.2 % response rate. According to Baruch and Holtom (2008) organizational level
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studies specially collecting data from higher level management, 35% response rate would be
appropriate. The high response rate helps to enhanced the credibility of research finding.
Cycyota and Harrison (2006) suggests some techniques to enhance the response rate, such as
choosing a research area that has some meaning for the participants, giving an advance notice,
using social networks, and following-up etc. An inherent advantage of the present study was
that it focused on a research topic that had gained prominence among HR practitioners who are
constantly in search of information that would help them to improve the functioning of their
departments. As an added attraction, the managers were given the option to record their emails
in order to receive the findings of this research. This information was placed in the introduction
portion of the questionnaire. The positive responses were received in this regard, which
confirmed the interest of the HR practitioners in the research area.
To enhance response rate follow up requests for participation are essential (Yammarino,
Skinner, & Childers, 1991). For this purpose, after a month of initial delivery of survey
questionnaire, soft reminders were sent to the respondents using the available communication
channels like email, phone calls, and short messaging (SMS). This resulted in 18 number of
additional responses.
Second follow-up: to enhance further response, a second reminder was sent to the remaining
non-respondents through the available communication channels. Finally this effort helped to
get additional 9 responses, the analysis of the data is based on 108 properly filled
questionnaires.
3.9 Research Instrument
A self-administered questionnaire was used for this study. The data is cross sectional in nature.
According to Orlikowski and Baroudi (1991) 90% of research conducted in the field of IS/IT
implementation and adoption by organizations has employed cross sectional data.
3.9.1 Pilot Testing of the Instrument
Several authors Polit (2013), Baker (1994) and Van Teijlingen and Hundley (2002) elaborated
the functions of pilot testing in social sciences such as : (i) pilot testing is a mini version of full
scale study, and (ii) it is pre-testing of a particular instrument. De Vaus (2001) also, suggested
to conduct a pilot study before stating the actual research. Van Teijlingen and Hundley (2002)
proposed a step wise procedure for conducting pilot study which includes steps like, conducting
interviews with experts in the field of study, after the discussion with experts the wording and
sequence of question may be altered in deemed beneficial, and finally, test the research process
thorough pilot distribution of questionnaire. The use of experts allows to resolve issues related
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to the clarity of the concept, the quality of language used, and the general reliability of the
instrument.
Keeping in line with the advice given above, a pilot study was conducted . The scale used for
this survey was adopted and it was a well-established scale. Minor changes in wording were
made to make it cleared for respondents in the context of HRIS. The scale of one variable is
measured the utilization level of HRIS, that deals with extent of HRIS adoption. The design of
scale was based on the functions of HRIS explained by (Mayfield, Mayfield, & Lunce, 2003).
All necessary measures were taken to test the reliability and validity of this variable. After the
development of the study instrument, the questionnaire rigorously evaluated by experts in the
field who have rich relevant experience. According to De Vaus (2001) pre-testing should be
performed before the final administration of questionnaire. For this purpose the instrument was
first vetted from two professors of HRM. Both the gentlemen had PhDs in HRM and had vast
research expertises. The details of current study were discussed which includes research
objectives, research questions and hypotheses. The purpose of this activity was to seek insight
by evaluating the instrument with respect to field of study and statistical measures. Finally, the
instrument was shared with two professionals in industry, who were actively involved in using
HRIS have given their affirmative opinion about the instrument.
To perform pilot testing, target accessible population was selected on the basis of opinion given
by the experts and professionals who were engaged in using HRIS and actively involved in the
process of adoption of HRIS in organizations. On the basis of recommendations proposed by
the experts, minor modifications in the flow of writing and formatting were made. Generally
speaking, experts form academic and industry have the consciences that scale is valid.
Final draft of the questionnaire was distributed to 30 organizations. All the organizations were
approached through professional acquaintance, and questionnaire is distributed to HR
departments of the organizations to get the responses from managerial carder. In response 13
organizations responded the survey, yielded 43.33%. All the filled survey were found valid and
data were entered into SPSS-Ver. 24. The reliability of the instrument was found in accordance
to the parameters prescribed in literature. According to Connelly (2008), 10% sample is
appropriate in pilot testing and considered good for getting initial reliability of the scale items.
The reported reliability of all measures were in accordance with the parameters prescribed in
literature. The respondents of the pilot study organizations indicated that comprehended the
scale items. They also allowed to use the questionnaire in English language because most of
the managerial cadre managers had master degree. Hence, no need to translate questionnaire
into local language was felt.
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3.9.2 Response Rate
According to Rogelberg and Stanton (2007) , high response rate in survey research would be
appreciated and give high confidence too. In this study, 43.2% (108) response achieved. The
response rate is in accordance to the similar type of studies conducted in Pakistan and other part
of the world reported in the literature (Ahmer, 2013; Sadiq, Khan, Ikhlaq, & Mujtaba, 2013;
Karimi, Somers, & Bhattacherjee, 2007; Kariuki, 2015; DeSanctis, 1986; Kassim, Ramayah, &
Kurnia, 2012). According to Saunders, Lewis, and Thornhill (2016), the following formula
calculate the response rate can be used:
Equation 1: Total response rate
!"#$%'()*"+)('$#( = !"#$%+-./('"0'()"+)()!"#$%+-./('1+)$.*%( − 1+(%131/%('()*"+()
The response rate of this study was found adequate to run quantitative tests for hypotheses
testing. The population for this study comprises the organization using any sort of computerized
system in their HR department to any extent and of any vendor. A sample of 250 was selected
through judgmental sampling technique from the target population. In. order to get maximum
response of the survey, recommended techniques suggested in literature were used. Resultantly,
108 valid responses were received. The response rate was 43.2 % and the respondents belongs
to 10 different industries.
3.9.3 Data Coding and Data Entry
Data analysis through software packages requires data codding. In this regard, first data were
coded and then entered into statistical package. In first step, all the filled survey responses
assigned code starting from 001 for example 001, 002, 003, and so on. In second step, all
questions in survey response assigned code according to measured group, for example first
section of instrument was personal demographic and first question in is related to gender of
respondents. The code assigned to this item was PDG1. In third sept, code is assigned to item
response categories, for example (Gender: male =1, female =2). The detail coding sheet of
survey instrument is attached in Annexure B. After codification of the instrument, data is
entered into a statistical package of IBM SPSS-Ver. 24.
3.9.4 Normal Distribution (Assumption of Normality)
Normality test on the sampled data is necessary before applying parametric tests, the test of
normality means that data is distributed normally. It can be tested by quantitative measures that
is the value of skewness and Kurtosis and graphically by drawing the normal curve.
Statistical tests are applied to test the normality of data, which includes skewness, and kurtosis.
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Table 15:Skewness and Kurtosis
Table 15: Skewness and Kurtosis
Skewness Kurtosis
Statistic Std. Error Statistic Std. Error
V_IC -1.066 0.233 1.029 0.461
V_OC -1.011 0.233 0.665 0.461
V_EC -0.923 0.233 0.658 0.461
V_Ext_of_HRIS -0.934 0.233 0.128 0.461
V_Stf_Exp -1.050 0.233 0.621 0.461
V_OP -0.829 0.233 0.291 0.461
George and Mallery (2010) refers that the value of skewness and kurtosis falls between -2 to
+2. The value of skewness and kurtosis as shown in table 15 reveals that the data is normal
distributed. Field (2009) expresses the rule of thumb for normal distribution of data for large
sample, the sample greater than 30, that found normal in distribution.
In first step, first part of the model, multiple regression was performed between the independent
variables (IV) (IC, OC, EC) and dependent variable (DV) (extent of HRIS adoption) to check
the direct impact with significance value (p < 0.05). In second step, other part of the model,
simple regression was performed between the IV (extent of HRIS adoption) and DV
(organization’s performance). In step three, multiple regression was performed to check the
moderating effect of HR staff expertise between extent of HRIS adoption and organization’s
performance was performed. Moderating effect of HR staff expertise was tested through
interaction term as proposed by (Baron & Kenny, 1986), in which the author described that
interaction term (moderating variable * independent variable) have the effect on relationship
between IV and DV.
3.9.5 Examination of Multicollinearity Among Predictors
According to Marcoulides (1998) multicollinearity refers when two or more independent
variables correlate with each other. If the correlation between IV is greater than 0.90. this means
correlations exist. According to Hair, Anderson, Babin, and Black (2010) another statistical test
is used to check the multicollinearity i.e. the value of the variance inflation factor (VIF). The
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value of VIF on both extremes, low and high i.e. very small less than 0.10 and very large greater
than 10 indicates that multicollinearity exits.
In order to test any chance of multicollinearity among predictors, a further examination of
multicollinearity between IC and OC, IC and EC, and OC and EC was tested by using the value
of tolerance and VIF (variance inflation factor). Both values was calculated by a statistical
package of SPSS ver. 24. Both value of tolerance, and VIF is calculated by using formula as
follows
(i) Tolerance = 1 – R2
(ii) VIF = 1 / tolerance
The conditions for the presence of multicollinearity between predictors are: (i) tolerance value
should not be very low, (ii) VIF value should be >= 1. The value of VIF on both extremes, low
and high i.e. very small less than 0.10 and very large greater than 10 indicates that
multicollinearity exits (Allahawiah, 2013).
• VIF < 3-- not a problem
• VIF > 3 -- potential problem
• VIF > 5-- very likely problem
• VIF > 10 -- definitely problem
VIF value less than 3 indicates that there is no multicollinearity exits between the predictors. In
the current study VIF value of predictors fall below the generally accepted value where there is
no chance of multicollinearity exits. The values of table 16 given below show that there is an
issue of multicollinearity in this data.
Table 16:Tolerance and VIF of the research model core variables
Table16: Tolerance and VIF of the research model core variables
Predictor Tolerance VIF
V_IC 0.437 2.286
V_OC-TMS 0.509 1.965
V_EC 0.425 2.350
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3.9.6 Outlier Influence Cases
Outlier are the cases in the sample data that are significantly different from normal trend of the
date in both sides of very small or very large values. Using SPSS option box and whisker plot
to identify the outlier, a test was run to identify the influenced cases. Outlier can be checked by
calculating the standardised residual of each item of a variable.
3.10 Data Analysis Procedure
Data analysis was performed using the statistics package of IBM SPSS (Ver. 24). All
appropriate statistical tests were performed to analyzed the collected data. The detail of each
test is given in following sections.
As a first step, the reliability and validity of scale items was tested. The Cronbach’s alpha for
all the variables of interest are presented as follows:
3.11 Validity of the Instrument
The validity would be the second measure to evaluate instrument. In broader terms, validity
deals with correct choice of a measuring scale. Polit (2013) defines validity as “degree to which
it measures what it is supposed to measure” (p.609). Saunders, Lewis, and Thornhill (2016)
mentioned different types of validities, which deem necessary for evaluating measuring
instrument. Content validity also called face validity deals with the questions used in scale were
essential and provide adequate coverage of the specific content area on which one can draw
meaningful inference (Creswell, 2013). Face validity is performed by the judgment of experts
in the field and through careful definition. The instrument developed for the current study
included measures adopted from various sources, these included: innovation characteristics,
organization characteristics, environment characteristics (Moore & Benbasat, 1991), HR staff
expertise (Thong, 1999) , organization’s performance (Lee & Choi, 2003). These scales were
well-established. The original scales were used during the pilot testing process, as a result the
wording of some of the items were changed in order to improve their comprehension. The final
instrument was again presented to experts in the field and also HR practitioners who confirmed
the content validity of the items. The scales used for this survey were adopted and were well-
established scales. Generally speaking, experts form academic and industry have the
consciences that scale is valid The validity would be used to evaluate the instrument to establish
that the instrument used to measure the concept is correct for a measuring scale.. The validity
was measured using person’s product moment. The tabular r value for n= 108 was 0.189 The
analysis shows all items valid.
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Table 17: Analysis of person’s product moment.
Table 17: The analysis results of Pearson’s product moment
Item r p Item r p Item r p
IC1 .616** 0.000 IC18 .253** 0.008 EXT6 .709** 0.000
IC2 .625** 0.000 IC19 .399** 0.000 EXT7 .674** 0.000
IC3 .684** 0.000 IC20 .615** 0.000 EXT8 .599** 0.000
IC4 .611** 0.000 IC21 .665** 0.000 EXT9 .704** 0.000
IC5 .607** 0.000 IC22 .613** 0.000 EXT10 .730** 0.000
IC6 .668** 0.000 OC1 .672** 0.000 EXT11 .673** 0.000
IC7 .577** 0.000 OC2 .662** 0.000 EXT12 .728** 0.000
IC8 .679** 0.000 OC3 .652** 0.000 EXT13 .782** 0.000
IC9 .769** 0.000 OC4 .697** 0.000 STFEXP1 .730** 0.000
IC10 .704** 0.000 EC1 .704** 0.000 STFEXP2 .574** 0.000
IC11 .701** 0.000 EC2 .623** 0.000 STFEXP3 .718** 0.000
IC12 .632** 0.000 EC3 .726** 0.000 OP1 .620** 0.000
IC13 .577** 0.000 EXT1 .731** 0.000 OP2 .620** 0.000
IC14 .582** 0.000 EXT2 .741** 0.000 OP3 .609** 0.000
IC15 .441** 0.000 EXT3 .750** 0.000 OP4 .670** 0.000
IC16 .330** 0.000 EXT4 .755** 0.000 OP5 .621** 0.000
IC17 .323** 0.001 EXT5 .702** 0.000
n= 108, Cronbach’s alphas presented in parentheses
**. Correlation is significant at the 0.01 level (2-tailed).
*. Correlation is significant at the 0.05 level (2-tailed).
3.12 Reliability of the Instrument
In statistical analysis, reliability would be used to evaluate the scales. This statistical test
generally used in quantitative studies called Cronbach’s alpha (a) coefficient. The value of the
scale indicates a close bound between the items of a scale, higher the value indicates more
satiability of the measuring instrument. According to Polit (2013), the generally acceptable
value of Cronbach’s alpha (a) coefficient is 0.70, however, the value greater than 0.80 is
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perfect. The alpha value of all measures scale of current study were above 0.50. The details of
Cronbach’s alpha (a) coefficient of main variables are presented in Table 37.
Reliability of Innovation Characteristics
Cronbach alpha coefficient for innovation characteristics scale was .0919 with 22 items. Alpha
reliability is adequate and need not to delete any item, Alpha values if other items deleted are
shown below in table 18.
Table 18:Reliability of IC scale
Table 18: Reliability of IC scale
Items (22)
Alpha 0.921
Cronbach's Alpha if Item Deleted
IC1 0.918
IC2 0.917
IC3 0.917
IC4 0.917
IC5 0.917
IC6 0.916
IC7 0.918
IC8 0.917
IC9 0.915
IC10 0.916
IC11 0.916
IC12 0.917
IC13 0.917
IC14 0.918
IC15 0.920
IC16 0.921
IC17 0.922
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IC18 0.923
IC19 0.921
IC20 0.917
IC21 0.916
IC22 0.916
IC = Innovation characteristics
Reliability of Organizational Characteristics
In current study, Cronbach alpha for organizational characteristics-top management support
scales was 0.915 with 4 items. The alpha value is in an acceptable range and there is no need to
remove any item from original scale. Alpha’s if item deleted is shown in table 19
Table 19:Reliability of OC scale
Table 19: Reliability of OC scale
Items (4)
Alpha 0.916
Cronbach's Alpha if Item Deleted
OC1 0.891
OC2 0.893
OC3 0.881
OC4 0.898
OC = Organizational characteristics
Reliability of Environmental Characteristics
In the current study, Cronbach alpha for environmental characteristics was 0.786 with 3 items.
The overall alpha value is an acceptable range so there is no need to remove any item from
original scale. Alpha’s if item deleted is shown in table 20
Table 20:Reliability of EC scale
Table 20: Reliability of EC scale
Items (3) Cronbach's Alpha if Item Deleted
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Alpha 0.791
EC1 0.788
EC2 0.666
EC3 0.676
EC = Environmental characteristics
Reliability of extent of HRIS adoption
The Cronbach alpha for value for extent of HRIS adoption was 0.951 with 13 items. The overall
alpha value is adequate and is in acceptable range so there is no need to remove any item from
original scale. Alpha’s if item deleted is shown in table 21
Table 21:Reliability EXT Scale
Table 21: Reliability EXT Scale
Items (13)
Alpha 0.952
Cronbach's Alpha if Item Deleted
EXT 1 0.950
EXT 2 0.948
EXT 3 0.947
EXT 4 0.947
EXT 5 0.949
EXT 6 0.948
EXT 7 0.950
EXT 8 0.950
EXT 9 0.949
EXT 10 0.948
EXT 11 0.949
EXT 12 0.949
EXT 13 0.947
EXT = extent of HRIS adoption
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Reliability of HR staff expertise
The Cronbach alpha for value HR staff expertise was 0.734 with 3 items. The overall alpha
value is adequate and is in an acceptable range and there is no need to remove any item from
original scale. Alpha’s if item deleted is shown in table 22
Table 22:Reliability of STFEXP Scale
Table 22: Reliability of STFEXP Scale
Items (3)
Alpha 0.741
Cronbach's Alpha if Item Deleted
STFEXP1 0.668
STFEXP2 0.728
STFEXP3 0.578
STFEXP1= HR staff expertise
Reliability of Organization’s Performance
The alpha value, 0.907, with 5 items scale of organization’s performance is well above the
acceptable range of 0.70. As a result of this adequacy, no need to delete any item from the
original scale. Alpha’s if item deleted is shown in table 23.
Table 23:Reliability OP scale
Table 23: Reliability OP scale
Items (5)
Alpha 0.911
Cronbach's Alpha if Item Deleted
OP 1 0.892
OP 2 0.886
OP 3 0.881
OP 4 0.888
OP 5 0.906
OP = Organization’s performance
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It is concluded that all the scales used in this study having high internal consistency and
reliability. The scales of innovation characteristics, organizational characteristics,
environmental characteristics, extent of HRIS adoption and organization’s performance show
a high reliability as suggested by (Nunnally & Bernstein, 1994) , i.e. a minimum acceptable
standard of 0.70.
To test the hypotheses a multiple linear regression was performed. Before applying parametric
test on the data, the basic assumptions of the regression was tested. For regression analysis, the
basic assumptions such as: (i) normal distribution (measured by using Skewness and Kurtosis)
(ii) multicollinearity (as indicated by Tolerance and VIF), and (iii) correlation (using the
person’s measure of correlation). The descriptive statistics of the tests are also discussed in the
next section, Ch. 4.
3.13 Chapter Summary
This chapter described the methodological description, assumptions and justifications of the
scale items. Moreover, the chapter highlights the research design, methodology, population,
sampling, data collection, codding steps, and data analysis. The steps in instrument
development and statistical criteria for reliability and validity were also discussed.
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CHAPTER 4
FINDINGS
This study is aimed to explore the factors affecting the extent of HRIS adoption and its impact
on the organization’s performance. The study also highlights the moderating role of HR staff
expertise between the relationship of extent of HRIS adoption and organization’s performance
by adopting diffusion of innovation theory in the Pakistani context.
This chapter is comprised of three parts. Firstly, descriptive analysis is performed using mean,
standard deviation, minimum and maximum to explore the characteristics of study variables. In
the second part, t-Test, ANOVA and correlation have been applied to find out the difference
among the groups and the relationship among variables. In the last part, regression analysis has
been performed to analyze the impacts of study independent variables on the extent of HRIS
adoption. The results interpretation including (a) factor affecting the extent of HRIS adoption,
(b) extent of HRIS and organization’s performance, and (c) moderating role of HR staff
expertise.
4.1 Descriptive Statistics of Data
In this section, descriptive statistics has been applied on factors affecting extent of HRIS usage;
innovation characteristics, organizational characteristics, environmental characteristics, extent
of HRIS, HR staff expertise and organization’s performance. The values of mean, standard
deviation, minimum and maximum has been shown in table 24.
The mean values of innovation characteristic were 3.65 (SD=0.666), organizational
characteristics was 3.95 (SD=0.960), environmental characteristics was 3.82 (SD=0.951),
extent of HRIS adoption was 3.72 (SD=0.898), HR staff expertise was 3.87 (SD=0.942), and
organization’s performance was 3.81 (SD=0.892) (table24). The mean and standard deviation
values indicated that innovative, organizational and environmental characteristics and HR staff
expertise supported the extent of HRIS, and extent of HRIS contributes into organization’s
performance.
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Table 24:Descriptive Statistics of study variables
Table 24: Descriptive Statistics of study variables
Minimum Maximum Mean Std. Deviation
Innovation characteristics * 1 5 3.65 0.666
Organizational characteristics * 1 5 3.95 0.960
Top management support * 1 5 3.95 .960
Organizational size ** 1 6 4.26 1.704
Environment characteristics* 1 5 3.82 0.951
Extent of HRIS*** 1 5 3.72 0.898
HR staff expertise* 1 5 3.87 0.942
Organization’s performance * 1 5 3.81 0.892
n=108 *1=strongly disagree, 2= somewhat disagree, 3= neither agree nor disagree, 4= somewhat agree, 5= strongly agree. ** 1= less than 50, 2= 50-99, 3=100-199, 4= 200-499, 5=500-999, 6= 1000 or more. *** 1= not at all, 2= a small extent, 3= some extent, 4= moderate extent, 5= a great extent
4.2 Analysis of Variance (ANOVA)
One-way analysis of variance (ANOVA) was applied to find out the impact of personal and the
organizational demographic on key dependent variables i.e. Extent of HRIS adoption in
relation. Demographic having significant impact will be treated as control variables in
regression analysis of the main study variable.
4.2.1 ANOVA: Extent of HRIS Adoption by Demographics Data
The following sub section will explain the difference on extent of HRIS adoption in the context
of personal demographics.
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4.2.1.1 Extent of HRIS Adoption by Gender
Table 25 shows the t-test result of t-Test for extent of HRIS adoption by the male and female
managers. The analysis revealed that there was no difference between the extent of HRIS
adoption between male and female managers.
Table 25: T stat extent of HRIS by gender
Table 25: T stat extent of HRIS by gender.
Levene's Test for
Equality of Variance
t-test for Equality of Means
F Sig. t df Sig. (2-
tailed)
Mean
Differe
nce
Std.
Error
Differen
ce
95% Confidence
Interval of the
Difference
Lower Upper
Equal
variance
assumed
0.24
4
0.6
22
-
1.58
6
106 0.116 -0.323 0.203 -0.726 0.081
Equal
variance
not
assumed
-
1.54
0
37.8
97
0.132 -0.323 0.210 -0.747 0.102
*Note. Significant ≤ .05
4.2.1.2 Extent of HRIS Adoption by Education
Table 26 shows that ANOVA results of extent of HRIS use by manager with different education
level. The p-value (p=.168) indicates that there was no significant difference exists among the
opinion of different education level groups in respect of extent of HRIS use. As the education
level is not significantly predicting any change in extent of HRIS adoption, Hence this variable
will not be controlled in regression analysis in relation of variables with extent of HRIS
adoption.
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Table 26: One-way ANOVA: extent of HRIS by education
Table 26: One-way ANOVA: extent of HRIS by education
Mean F Sig.
Bachelor Master MS/MPhil PhD
4.12 3.72 3.53 4.41 1.716 0.168*
*Note. Significant ≤ .05
4.2.1.3 Extent of HRIS Adoption by Age of Respondents
One-way analysis of variance of extent of HRIS adoption by age was performed. This factor
having different age groups, indicates that there is a significant difference in the mean value of
extent of HRIS adoption and age group. F value of 2.806 was found significant at p = .020 as
shown below in Table 27. P < 0.05 shows that age causes significant variation in extent of HRIS
adoption. So, age will be entered as control variable in first step of regression analysis in relation
of IV with extent of HRIS adoption.
Table 27: One-way ANOVA: extent of HRIS adoption by age of respondents
Table 27: One-way ANOVA: extent of HRIS adoption by age of respondents
Mean F Sig.
Less than 25 years
25-34
years
35-44
years
45-54
years
55-64
Years
65 and above
years
4.31 3.66 3.47 4.31 4.51 2.46 2.760 0.022*
*Note. Significant ≤ .05
4.2.1.4 Extent of HRIS by Designation
Table 28 shows that ANOVA results of extent of HRIS adoption by manager with different
designations. The p-value (p=.963) indicates that there was no significant difference exists
among the opinion of managers with a different designation in respect of extent of HRIS use.
As designation is not significantly predicting any change in extent of HRIS adoption , hence
this variable will not be controlled in regression analysis in relation of variables with extent of
HRIS adoption.
87
Table 28: One-way ANOVA: extent of HRIS adoption by designation
Table 28: One-way ANOVA: extent of HRIS adoption by designation
Mean F Sig.
Deputy Manager/Director Manager/Director Senior
Manager/Director Others
3.71 3.78 3.59 3.71 0.094 .963
*Note. Significant ≤ .05
4.2.1.5 Extent of HRIS Adoption by Experience in Current Designation
Table 29 shows that ANOVA results of extent of HRIS adoption by manager with experience
in current designation. The p-value (p=.482) indicates that there was no significant difference
exists among the opinion of managers with experience in current position respect of extent of
HRIS adoption. As professional experience of managers is not significantly predicting any
change in extent of HRIS adoption, hence this variable will not be controlled in regression
analysis in relation of variables with extent of HRIS adoption.
Table 29: One-way ANOVA: extent of HRIS adoption by experience in current designation
Table 29: One-way ANOVA: extent of HRIS adoption by experience in current
designation
Mean F Sig.
Less than 1years
1-3 years
4-7 years
8 years or more
3.66 3.61 3.70 3.98 0.827 0.482
4.2.1.6 Extent of HRIS Adoption by Experience in Current Organization
Table 30 shows that ANOVA results of extent of HRIS adoption by a manager with different
professional experience. The p-value (p=.229) indicates that there was no significant difference
exists among the opinion of managers with different professional experience in current
organization with respect of extent of HRIS adoption. As professional experience of managers
is not significantly predicting any change in extent of HRIS adoption, hence this variable will
not be controlled in regression analysis in relation of variables with extent of HRIS adoption.
88
Table 30: One-way ANOVA: extent of HRIS adoption by experience in current organization
Table 30: One-way ANOVA: extent of HRIS adoption by experience in current
organization
Mean F Sig.
Less than 3years
3-6 years
7-10 years
11-14 years
more than 14
years
3.47 3.94 3.63 3.92 3.86 1.431 0.229
4.2.1.7 Extent of HRIS Adoption by Total Professional Experience
One-way ANOVA of was performed with extent of HRIS adoption and total professional
experience of the respondents. The result shows that there was a significant difference in the
mean value of extent of HRIS adoption with total professional experience. The result shows in
table 31: F value of 3.324 was found significant at p = .013. A significant p-value (p < 0.05)
implies to opt total professional experience as control variable while regressing IV on extent of
HRIS adoption in step 1.
Table 31: One-way ANOVA: extent of HRIS adoption by total professional experience
Table 31: One-way ANOVA: extent of HRIS adoption by total professional experience
Mean F Sig.
Less than 5years
5-9 years
10-14 years
15-20 years
21 years or more
years
3.57 3.51 4.06 3.37 4.24 3.272 0.014*
*Note. Significant ≤ .05
89
4.2.1.8 Extent of HRIS Adoption by Organization Industry
Organization chrematistics i.e. industry will be tested to check any significant variation in the mean value of extent of HRIS adoption. It shows a
significant result where F value was 3.440 for extent of HRIS adoption is significant with p-value 0.001 (p<0.05). This indicated that extent of HRIS
adoption varies in different industries. Thus, organization industry will be treated as a control variable for extent of HRIS adoption.
Table 32: One-way ANOVA: extent of HRIS adoption by organization industry
Table32: One-way ANOVA: extent of HRIS adoption by organization industry
Mean F Sig.
Architecture/ Engineering
Banking &Finance
Computers/IT
Education Health/Hospital
manufacturing
services
Trading Travel others
4.08 3.90 3.06 2.97 3.68 4.22 3.94 2.41 4.31 3.67 3.427 0.001*
*Note. Significant ≤ .05
90
4.2.1.9 Extent of HRIS Adoption by Life of Business
One-way ANOVA of was performed with the extent of HRIS adoption and life of business.
The result shows that there was no significant difference in the mean value of extent of HRIS
adoption with a life of business. The result shows in table 33: F value of .908 was found not
significant at p = 0.479. Hence this variable will not be controlled in regression analysis in
relation of variables with extent of HRIS adoption.
Table 33: One-way ANOVA: extent of HRIS adoption by life of business
Table 33: One-way ANOVA: extent of HRIS adoption by life of business
Mean F Sig.
Less than 3 years
4-6
years
7-9
years
10-12
years
13-15
years
More than 15 years
2.87 3.57 4.26 3.79 3.59 3.77 0.908 0.479*
*Note. Significant ≤ .05
4.2.1.10 Extent of HRIS Adoption by Number of Employees in HR Department
One-way ANOVA of was performed with extent of HRIS adoption and number of HR staff
members. The result shows that there was no significant difference in the mean value of extent
of HRIS adoption with the difference in the number of staff members in the HR department.
The result shows in table 34: F value of .1.099 was found not significant at p = .366. Hence this
variable will not be controlled in regression analysis in relation of variables with extent of HRIS
adoption.
91
Table 34: One-way ANOVA: extent of HRIS adoption by number of employee in HR
department
Table 34: One-way ANOVA: extent of HRIS adoption by number of employee in HR department.
Mean F Sig.
1-3 employees
4-6 employees
7-9 employees
10-12 employees
13-15 employees
More than 15 employees
3.33 3.86 3.50 3.58 3.88 3.87 1.099 .366*
*Note. Significant ≤ .05
4.2.1.11 Extent of HRIS Adoption by Number of Computers in HR Department.
One-way ANOVA was performed with extent of HRIS adoption and number of computers in
HR departments. The result shows that there was no significant difference in the mean value of
extent of HRIS adoption with the difference in the number of computers in the HR department.
The result shows in table 35: F value of .568 was found not significant at p = .686 Hence this
variable will not be controlled in regression analysis in relation of variables with the extent of
HRIS adoption.
Table 35: One-way ANOVA: extent of HRIS adoption by number of computers in HR
department.
Table 35: One-way ANOVA: extent of HRIS adoption by number of computers in HR
department.
Mean F Sig.
1-3 computers
4-6 computers
7-9 computers
10-12 computers
More than 12
computers
3.49 3.97 3.85 3.79 3.70 .568 .686*
*Note. Significant ≤ .05
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4.2.1.12 Extent of HRIS by Age of HRIS
The age of HRIS causes significant variation in mean value of extent of HRIS adoption. The
table given blows shows F value 3.605 significant at p = 0.005 (p < 0.05) depicts that there are
significant differences in age of HRIS with extent of HRIS adoption. The age of HRIS need to
be controlled when regressing the independent variable on extent of HRIS adoption.
Table 36: One-way ANOVA: extent of HRIS adoption by age of HRIS
Table36: One-way ANOVA: extent of HRIS adoption by age of HRIS
Mean F Sig.
Less than 1 year
1-3 years
4-6 years
7-9 years
10-12 years
More than 12 years
2.69 3.42 3.64 3.79 4.26 3.76 3.580 .005*
*Note. Significant ≤ .05
In conclusion of one-way ANOVA of extent of HRIS adoption was checked on both personal
demographics, seven factors, and organization demographics, five factors. In a personal
demographic only age of respondents and total professional experience were found significant
in showing difference among opinion of managers that causes significant variation on extent of
HRIS adoption. In organizational demographics only two factors i.e. organization industry and
age of HRIS caused significant variation in extent of HRIS adoption. As a result of the
aforementioned tables of ANOVA, these factors will be treated as control variables during
regressing the independent variable i.e. IC & OC and EC and DV i.e. extent of HRIS adoption.
4.3 Correlation Analysis of Main Variables
Pearson’s correlation coefficient analysis was used to determine the relationship between
innovation characteristic, organizational characteristics, environmental characteristics, extent
of HRIS adoption, HR staff expertise and organization’s performance variables. The purpose
of correlation is to explain how the variables are related over the range of +1.0 (a perfect
positive relationship) through 0.0 (no correlation between the variables) to -1.0 (a perfect
negative relationship) (Cooper & Schindler, 2008; Swanson & Holton, 2005). Alpha
reliabilities for all measures were above .70 level. All correlations above 0.50 in magnitude are
significant at p<0.01.
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Table 37:Correlations, and Reliabilities
Table 37: Correlations, and Reliabilities
Variable 1 2 3 4 5 6 7 8 9 10 11 12
1 Education 1
2 Age .234* 1
3 Total professional experience 0.128 .603** 1
4 Organization Industry -0.010 -0.089 0.021 1
5 Age of HRIS -0.123 0.094 0.105 -0.008 1
6 V_IC -.225* -0.101 0.098 0.150 .219* 1 (.92)
7 V_OC -0.041 0.033 0.094 0.033 .233* .637** 1 (.91)
8 No. of Employees -0.158 0.026 0.074 0.020 .370** 0.071 0.134 1
9 V_EC -0.069 -0.026 0.090 0.041 0.189 .713** .645** 0.011 1(.79)
10 Extent of HRIS. -0.090 0.017 0.189 0.016 .268** .705** .583** 0.051 .666** 1 (.95)
11 HR staff expertise -0.059 -0.014 -0.044 0.000 0.157 .703** .621** 0.042 .675** .681** 1 (.74)
12 V_OP -0.079 -0.022 0.030 -0.005 0.144 .514** .540** 0.139 .600** .647** .685** .1 (0.91)
n= 108, Cronbach’s alphas presented in parentheses
**. Correlation is significant at the 0.01 level (2-tailed).
*. Correlation is significant at the 0.05 level (2-tailed).
94
4.4 Regression Analysis Combined Effects
After running the ANOVA and correlation coefficient analysis, the last step of data analysis is
regression analysis. In the first step, main effects and combine effects were tested. The model
of the current study also included the moderation effect between predictor extent of HRIS
adoption and dependent variable organization’s performance and same was hypothesized in
hypotheses of this study. Baron and Kenny (1986) states the procedure of moderation analysis
to check if the moderator moderates the relationship. For this purpose, multiple linear regression
will be carried out in which predictors are IV, moderator and interaction term. Interaction term
is calculated by multiplying the IV and moderator. The dependent variable of this regression
analysis is OP. The procedure carried out to test the moderation effect as prescribe in literature.
At first step, the control variables were identified that shows the significate variation with a
mean value of the predictor and DV. Add controls in the first step of regression analysis. Then,
in step two, predictors added, then in the third step, the interaction term is added. Interaction
term is created by multiplying the predictor with a moderator. According to the Baron and
Kenny (1986) a significant interaction term means moderation is supported. The results of the
direct effects of predators with DV and multiple regression of moderated analysis was presented
in table 38 and 40.
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4.4.1 Regression Analysis and Hypotheses Testing
Table 38:Regression Analysis Direct Effects
Table 38: Multiple Regression Analysis
Predictor Dependent Variable: Extent of HRIS adoption
ß R2 ∆R2
Step 1.
Control variables .115
Step 2.
Innovation Characteristics 0.561*** .585
Organizational Characteristics 0.108
Environmental Characteristics 0.255*** .470***
n=108, ns=not significant, control variables for Extent of HRIS adoption: Age, Total professional experience, Organization industry, and Age of HRIS. ***p <.001, **p<.05
4.4.2 Hypothesis 1: Innovation Characteristics as Predictor of Extent of HRIS
Adoption.
The first hypothesis of this study was “H1. Innovation characteristics have positive impact on
extent of HRIS adoption”.
In order to test the first hypothesis of the study, the statistical package SPSS ver. 24 was used
for analysis. Regression analysis was carried to formally test the direct effect of innovation
characteristics (IC) on extent of HRIS adoption. For this purpose, first, identify the control
variables that have significant variations in extent of HRIS adoption. In regression, age, total
professional experience, organization industry, and age of HRIS age were used as control
variables. Control variables were entered in the first step of regression option in SPSS. In step
2, innovation characteristics, organizational characteristics and environmental characteristics
were entered as a predictor and then extent of HRIS adoption as a dependent variable. The
analysis results show that the change in R2 was .470 (p < .000). The result is significant, it
revealed that there are significant variations in the dependent variable extent of HRIS adoption
by IC. 47.% variation in extent of HRIS adoption is explained by IC. The beta value ß =.561, p
<.000 of IC is also significant. These results support the first hypothesis. Hence, innovation
96
characteristics are a significant factor that affects the extent of HRIS adoption and positively
related with the outcome variable.
4.4.3 Hypothesis 2: Organizational Characteristics as Predictor of Extent of HRIS
Adoption
Second hypothesis of this study was “Organizational characteristics (2a top management
support) will have significant positive impact on extent of HRIS adoption.”
In order to test the second hypothesis of the study, the statistical package SPSS ver. 24 was
used for analysis. Regression analysis was carried out to test the direct effect of organization
characteristics (OC) i.e. top management support for this purpose, first identify the control
variables that have significant variations in extent of HRIS adoption. In regression, age, total
professional experience, organization industry, and age of HRIS age were used as control
variables. Control variables entered in the first step of regression option in SPSS. In step 2,
innovation characteristics, organizational characteristics and environmental characteristics was
entered as predictor and extent of HRIS adoption as a dependent variable. The analysis results
show that the change in R2 was .470 (p < .000). The result is not significant, The beta value ß
=.108, p <.206 was not significant. These results does not support the 2a hypothesis. Hence,
organizational characteristics insignificant factor that does not any affects the extent of HRIS.
4.4.4 Analysis of Variance and Hypothesis Testing.
Table 39: One-Way ANOVA Organization size by extent of HRIS adoption
Table 39: One-Way ANOVA Organization size by extent of HRIS adoption
Sum of Squares
df Mean Square
F Sig.
Extent of HRIS adoption
Between Groups
4.428 5 0.886 1.104 0.363
Within Groups 81.834 102 0.802
Total 86.262 107
Second hypothesis of this study was “Organizational characteristics (2b organization size) will
have significant positive impact on extent of HRIS adoption..”
In order to test the second hypothesis of the study, statistical package SPSS ver. 24 was used
for analysis. Analysis of variance was carried out to test the significant differences in extent of
HRIS adoption and organizational characteristics i.e. organization size, the organization size is
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in term of No. of employees working in the organization on extent of HRIS adoption. The result
is not significant at p=<0.05, it shows that extent of HRIS adoption is insignificant regardless
of organization size. Hence, hypothesis 2b not supported.
4.4.5 Hypothesis 3: Environmental Characteristics as Predictor of Extent of HRIS
Adoption.
The third hypothesis of this study was “H3. Environment characteristics have positive impact
on extent of HRIS adoption”
In order to test the third hypothesis of the study, the statistical package SPSS ver. 24 was used
for analysis. Regression was performed to formally test the direct effect of environmental
characteristics on extent of HRIS adoption. For this purpose, first, identify the control variables
that have significant variations in extent of HRIS adoption. In regression, age, total professional
experience, organization industry, and age of HRIS age were used as control variables. Control
variables entered in the first step of regression option in SPSS. In step 2, innovation
characteristics, organizational characteristics and competitor pressure as environmental
characteristics was entered as predictor and extent of HRIS adoption as a dependent variable.
The analysis results show that the change in R2 was .470 (p < .000). The results are significant,
it revealed that there is significant variation in the dependent variable extent of HRIS adoption
by EC. 47% variation in extent of HRIS adoption is explained by EC. The beta value ß =.255,
p <.007 was also significant. These results support the third hypothesis. Hence, environmental
characteristics positively affects the extent of HRIS adoption and have a significant impact on
outcome variable.
98
Table 40: Combined effect and moderating regression analysis of extent of HRIS adoption,
HR staff expertise and organization’s performance
Table 40: Combined effect of extent of HRIS adoption and organization’s performance
Predictor Dependent variable: OP
b R2 ∆R2
Step 1
Control Variables .006
Step 2
Extent of HRIS .317**
.530 .524***
n=108, ns=not significant, control variable for organization’s performance: education
***p <.001, **p<.05
4.4.6 Hypothesis 4: Extent of HRIS Adoption as Predictor of Organization’s
Performance
The fourth hypothesis of this study was “H4. Extent of HRIS adoption has positive
impact on organization’s performance.”
In order to test the fourth hypothesis of the study, the statistical package SPSS ver. 24 was used
for analysis. Linear regression was performed to formally test the direct effect of extent of HRIS
adoption on organization’s performance. For this purpose, first, identify the control variables
that cause significant variations with the organization’s performance. In regression, education
level of respondent were used as control variables. Before performing regression data centering
were performed, Control variables entered in the first step of regression option in SPSS. In step
2, extent of HRIS adoption as predictor and organization’s performance as DV is entered.
The extent of HRIS adoption showed a positive impact with organization’s performance (b=
.317*, p<.05). The result confirmed hypothesis 4. The results support the fourth hypothesis.
Hence, extent of HRIS adoption has a positive impact on the organization’s performance. higher
the level of adoption of HRIS greater the organization’s performance.
99
4.4.7 Multiple Regression Analysis Moderating Effect and Combine Effect.
Multiple regression analysis was performed to test the direct and moderating effects of
predictors on organization’s performance which is a dependent variable. First, it is tested that
there is no multicollinearity exists in two predictors i.e. extent of HRIS adoption and HR staff
expertise. The absence of multicollinearity means their combined effect can also be examined.
Table 41:Combined effect and moderating regression analysis of extent of HRIS adoption, HR staff expertise and organization’s performance
Table 41: Combined effect and moderating regression analysis of extent of HRIS adoption, HR staff expertise and organization’s performance
Predictor Dependent variable: OP
b R2 ∆R2
Step 1
Control Variables .006
Step 2
Extent of HRIS .317**
HR staff expertise .401** .530 .524**
Step 3
Extent of HRIS adoption x HR staff expertise -.110 (ns) .538 .008(ns)
n=108, ns=not significant, control variable for organization’s performance: education ***p <.001, **p<.05
4.4.8 Hypothesis 5: HR Staff Expertise as Predictor of Organization’s Performance.
The fifth hypothesis of the study was “H5a. HR staff expertise has positive impact on
organization’s performance.” and “H5b. HR staff expertise moderate the relationship
between extent of HRIS adoption and organization’s performance”
In order to test the fifth hypothesis of the study, the statistical package SPSS ver. 24 was used
for analysis. Moderated multiple regression was performed to test the direct effect of extent of
HRIS adoption and HR staff expertise on an organization’s performance as well as moderating
effect of HR staff expertise on organization’s performance. For this purpose, first, identify the
control variables that have significant variations on organization’s performance. In moderated
regression, education level of the responded were used as control variables. Before performing
moderated regression analysis, data were standardize i.e. first independent variable, then
100
moderating variable after that interaction effect is created. Control variables entered in first step
of regression analysis option in SPSS. In step 2, extent of HRIS adoption and HR staff expertise
as a predictor is entered. In step 3, the interaction effect is entered, the interaction effect is
created by multiplying independent variable extent of HRIS adoption with moderating variable
HR staff expertise as the moderation analysis suggested by (Baron & Kenny, 1986).
Organization’s performance is added as a dependent variable.
HR staff expertise showed a positive relationship with the organization’s performance (b= .401,
p<.05). The result is significant and confirmed hypothesis 5a. The results support the 5a
hypothesis. Hence, HR staff expertise positively affects the organization’s performance. The
moderating role of HR staff expertise on the extent of HRIS adoption and organization’s
performance was not supported. The results of moderation analysis explained that extent of
HRIS and HR staff expertise interaction was not significant thus, hypothesis 5b was not
supported.
101
4.5 Summary of Results
The result of hypotheses of current study is presented in table given below in summarized
form.
Table 42:Summary of results
Table 42: Summary of results
No. Hypotheses statement Result
H1 Innovation characteristics are positively related with the
extent of HRIS adoption and have significant impact on extent
of HRIS adoption.
Supported
H2 Organization characteristics (2a top management support, 2b
organization size) will have significant positive impact on
extent of HRIS adoption.
Not
Supported
(2a,2b)
H3 Environment characteristics have positive impact on extent of
HRIS adoption. Supported
H4 Extent of HRIS adoption has positive impact on
organization’s performance. Supported
H5a HR staff expertise has positive impact on organization’s
performance. Supported
H5b HR staff expertise moderate the relationship between extent
of HRIS adoption and organization’s performance.
Not
supported
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CHAPTER 5
DISCUSSION AND CONCLUSIONS
5.1 Discussion on Findings
This section of the study presents the discussion on research findings discussed in previous
chapter of current study. The discussion on research findings followed by the research questions
that were based on research objectives of this study. The discussion on research questions one
by one are presented in upcoming sections of this chapter, discussion on research finding also
satisfied the study objectives.
Research Question 1: The first research question of the study was “What is the effect of
innovation characteristics, organization characteristics, and environmental characteristics on
extent of HRIS adoption”
Innovation is an idea, practice or object perceived as new by the adopting organizations
(Tanoglu, Basoglu, & Daim, 2010). The results of research shown in table 37 of correlation
analysis indicates that the innovation characteristics, organizational characteristics and
environmental characteristics have a significant positive correlation with extent of HRIS
adoption. These variables are highly correlated with the main construct of the study i.e. extent
of HRIS adoption. The correlations values were 0.705, 0.583, and 0.666 respectively.
The findings revealed that if the organizations are rich towards adoption of innovation
supported by internal and external characteristics i.e. organizational characteristics and
environmental characteristics then there will be a chance of adoption of enhanced application,
i.e. extent of HRIS adoption. Fichman (1992) also supported that the characteristics of
innovation determine the extent of adoption. Other important factors for HRIS adoption
includes innovation, organizational and environmental characteristics (Teo, Soon & Fedric,
2007). Al-Dmour, Masa'deh, & Obeidat (2017) supported environment characteristics. The
findings of this research suggest that innovation and environment pressure play a supportive
role in the adoption of HRIS to a greater extent.
In order to answer the first research question, three hypotheses was developed to find out the
impact of innovation characteristics, organizational characteristics, environmental
characteristics on extent of HRIS adoption. Hypothesis 1 tested the impact of innovation
characteristic on extent of HRIS adoption. The hypothesis was supported that innovation
characteristics have impact on the extent of HRIS adoption. Innovative characteristics
explained that new technology is being diffused in organizations by having getting relative
advantage over existing systems, observability and trialability. Mustonen-Ollila and Lyytinen
103
(2003), also highlighted that these factors have strongly influence on IS adoption in
organizations.
The organizational innovativeness leads towards the high level of HRIS adoption.
Organizations encouraging innovation are more likely to adopt IS systems. The findings of this
study are in lines with the findings of (Kamal, 2006; Cooper & Zmud 1990). Mustonen-Ollila
and Lyytinen (2003), Oliveira and Martins (2011) also supported the role of innovation
characteristics in identifying its impact on HRIS adoption. The variance explained (.470) is
higher which indicate that the organization’s innovation characteristics is an indicator towards
the adoption of IS to its greater extent. In the same vein, these characteristics lead towards
extent of HRIS adoption to its greater extent. The scope of the current study is organizational
level, innovation characteristics confirm that it has significant support and encouragement for
the organization to the adoption of HIRS systems at large extent. According to Rockart and
Short (1989) implementation of IS/IT become an enabler of ensuring the innovations in
organizations
In continuation of answering the first research question, the second hypothesis says that
Organizational characteristics (2a top management support, 2b organization size) will have
significant positive impact on extent of HRIS adoption. The hypothesis was not supported that
organizational characteristics affects the extent of HRIS adoption. The organization
characteristics (organization size) is also insignificant. (Al-Dmour, Masa'deh, & Obeidat, 2017)
also confirms that organizational size does not help in adoption of HRIS. Regardless of the
organizations, the No. of full time employees have no influence on adoption HRIS to its greater
extent. Organizations where they have top management support are insignificant for adoption
of extent of HRIS. The findings of this study are contradictory with the findings of (Lin, 2010),
which indicates that organizational characteristics, top management support are the enablers
towards the more and more adoption of HRIS by the organizations. So, top management support
would not be dominates the adopting HRIS to its greater extent.
In order to answer the first research question, the third hypothesis says that environmental
characteristic has a positive impact on extent of HRIS adoption. The hypothesis was supported
that says environmental characteristics affects the extent of HRIS adoption. The findings of this
study are in line with the findings (Cooper & Zmud, 1990). The variance explained (.470) is
higher which indicate that environmental characteristics in term of the pressure of competitor
in the industry push the organization towards the adoption of HRIS to its greater extent.
According to Rockart & Short (1989) IS/IT enables organizations to gain a competitive
advantage, (O'Brien & Marakas, 2011) also supported that information system may be used as
104
a competitive edge, it put pressure on the organization to adopt information system. (Al-Dmour,
Masa'deh, & Obeidat, 2017) also confirms that the environmental factors become a significant
predictor of adoption of HRIS. In order to meet the first objective of the study i.e. to examine
the effect of innovation characteristics, organization characteristics, environmental
characteristics on extent of HRIS adoption, research question 1 satisfy the first objective of this
study. According to the findings of the study, IC and EC are the factors that need encourage the
organizations to adopt HRIS to its greater extent. Whereas OC found insignificant in local
context.
Research Question 2: The second research question of the study was “Is there statistically
significant relationship between extent of HRIS and organization’s performance? if so, what is
it. ” The results shown in table 37 of correlation analysis between extent of HRIS adoption and
the organization’s performance indicates that the extent has a significant positive correlation
with the organization’s performance. The correlation value was 0.647. This shows relative
strong correlation. As an organization’s performance is the strategic outcome, that can be
achieved by successfully implementing HRIS and its utilization at large extent (Lantara, 2016).
Hence this relationship indicates that extent of HRIS adoption is successfully contributing
towards the performance of the organization. Higher the adoption of HRIS contributes to
achieving high level organization’s performance.
Research Question 3: The third research question of the study was “What is the effect of extent
of HRIS adoption on Organization’s performance.”
In order to answer the third research question, the fourth hypothesis says extent of HRIS
adoption has a positive impact on the organization’s performance. The hypothesis was
supported that revealed that extent of HRIS adoption has significant impact on an organization’s
performance, greater the extent of HRIS, higher the organization’s performance. The findings
of the study are in lines with the findings of (Ravichandran & Lertwongsatien, 2005). However,
the variance explained is higher which indicate that extent of HRIS adoption is an indicator
towards the enhancing the organization’s performance. The extent of HRIS adoption enables
the organization in term of high provisioning of human resources data which leads towards
efficiency and effectiveness, resultantly organization getting elevated performance. So, the
extent of HRIS has a direct impact with organization’s performance. hence, the objective two
of the study is satisfied in research question 3.
Research Question 4: In order to address fourth research question, “Does HR staff expertise
moderate the relationship between extent of HRIS adoption and organization’s performance?
The HR staff has a significant role in adoption of HRIS in organizations. With the help of HRIS,
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HR staff now able to perform HR functions efficiently and effectively. The role of HR staff
expertise is helpful for enhancing organization performance. In this regard, the question of
What is the role of HR staff expertise between extent of HRIS adoption and the organization’s
performance?” addressed by developing two hypotheses i.e. 5a and 5b.
The fifth (a) hypothesis says HR staff expertise has positively impacted the organization’s
performance. The hypothesis has been supported as the results are significant. HR staff
expertise has a positive impact on the organization’s performance. Higher the HR staff expertise
towards the utilization of HRIS leads towards high impact on the organization’s performance.
The performance is considered as the organizations achieving high performance in term of
profitability. HR staff expertise explains the 50% of the variance in the organization’s
performance. The role of HR staff expertise towards organization’s performance also confirmed
previously by (DeLone, 1994).
Fifth (b) hypothesis test the moderating effect of HR staff expertise in the relationship between
extent of HRIS adoption and the organization’s performance. This hypothesis has not been
supported. The findings of this hypothesis is contradictory with the findings of (Bamel et al.,
2014; Nguyen & Nguyen, 2016). The result is due to the Pakistani environment of IS
implementation. Ahmer (2013) also reported the limited implementation of HRIS in a local
context. In addition to that, the author also highlighted that HRIS would not be used as the first
system in the organization. The respondents of the study possibly perceive their expertise as an
outcome of HRIS utilization while serving in the HR department instead of extent of HRIS
adoption. fourth research question satisfy the third objective of the study.
5.2 Contributions of this Study
This study makes valuable contribution in the field of human resources information systems in
general and specially explaining the concept of HRIS in term of “extent of HRIS”. This
explanation of functional description is based on the description given by Mayfield (2003). In
addition to that the extension is proposed in the model proposed Kwon and Zmud (1987), a
model which deals with information technology adoption. The components of the model
determine as predictors of information technology adoption, which uses Roger’s theory. The
proposed extension is IOE, Innovation, Organizational, and Environment characteristics which
may be used as predictor for adopting soft systems at organization level. Whereas this research
validate only two components of this model i.e. innovation and environmental. The samples
used in this study is from developing country like Pakistan. As in Pakistan the adoption of HRIS
is in early stage. The literature also support that the applicability HRIS is witnessed as marginal
in the case of Pakistan. Insufficient literature is available that describes the extent of HRIS
106
adoption in a local context, this study contribute to the international body of knowledge. Most
of the research in conducted in western context. So, local context also added in the body of
knowledge.
5.3 Managerial Implications
There is a growing realization among practitioners that organization’s capability to effectively
deploy its human assets determines its chances of survival in the current competitive
environment. The management of human capital has come, very far, from the days of merely
record keeping regarding the various aspects of human assets. The contemporary successful
organizations leverage complex data analysis techniques to ensure that they have the
professionals performing the most important jobs within the organization . The same data are
used to project different important statistic, such as turnover ratios, and are used to project
future HR needs of the organizations. This growing importance of HR data analyses has led to
the emergence of the specialized positions of HR analysts within organizations. Most of this
advancement in HR analyses can only be performed, if an organization has an extensive HRIS
implementation.
This findings of this research work satisfy the fourth objective of this study by provide guidance
to managers and policymakers who want to introduce HRIS into the organizations, or who want
to extend its adoption beyond its record keeping functions and tracking employees attendance.
The managers should take heart from the results presented in this study which indicates a
significant relationship between the extent of HRIS adoption and the organization’s
performance. The study may also be seen as a guideline for managers who intended to introduce
HRIS in their organizations, as it describes the relationship between the extent of HRIS
adoption and its key antecedents. Increasing the extent of HRIS adoption within an organization
is also important from the perspective of achieving strategic integration. An effective HRIS
implementation is essential for the vertical integration of the organizational strategic plan with
the functional level HR plans. Extensive HRIS adoption also allows for the horizontal
integration of the various HR functions, which previously were catered through isolated
modules in piecemeal. According to Qadir & Agrawal (2017) organizations develop HRIS in
piecemeal despite the importance of it to the organization, still organizations optimally use of
HRIS.
The results of the present study also indicate a positive relationship between the HR staff
expertise and the organization’s performance. This should be sufficient evidence for managers
and decisions makers to staffing their HR staff with individuals who have the required HRIS
competencies. Individuals who have expertise in working with HRIS will be in a better position
107
to contribute to the goals that the organization has set for its HR function. This evidence should
also encourage to added investments should be made in training and development interventions
focused on HR staff’s capacity building.
A growing trend among successful organizations is prevailed that all decision made within the
organizations should be based on sound evidence, also called evidence-based decision making.
The adoption of an extended HRIS can help the decision makers acquire, record, and analyze
the important data relating to the human assets of the organization, and to base their decisions
on the evidence, that is gleaned from this data. HRIS enhances the managers’ abilities to fine-
tune their control over their HR assets and allows them to introduce important interventions
relating to HR such as knowledge management, personnel development, HR analysis,
forecasting and Planning, strategic integration etc. Information gathered through these systems
helps in achieving organizational effectiveness and efficiency. According to O'Brien and
Marakas (2011), HRIS is used for effective and efficient deployment of HR of an organization.
An extensive adoption of HRIS enables the HR managers to take up a higher strategic role in
the organization and not become a business partner. This also helps to enhance the relationship
of the HR department with the other departments in the organization. The close integration
between the HR team and the line managers is an important step towards the implementation
of effective HR policies and procedures which could be achieved through extensive HRIS
adoption.
Another important point with regards to the adoption of HRIS, as alluded in this thesis, is the
separate roles played by the IS expert and the HR manager. Both of these positions play an
important role in the extensive adoption of HRIS systems. IS implementer may use the finding
of this thesis for implementing other similar systems using by different departments in the
organization. The objective of every system implemented in an organization is to contribute in
strategic decision making for enhancing organization’s performance. So, the finding of this
thesis suggests that IS implementer should first focus on the antecedents of proper
implementing an information system in a specific department. They have to focus on whether
the context they are working is favoring, to what extent they can get maximum benefits and
how they can contribute to organizations success. Without the involvement of the departmental
staff neither full benefits of the system can be realized, nor can the system achieve its goals.
The role of the IS manager has to be a facilitator and rather becoming the dominant partner.
The guidelines provided to the practitioner and managers satisfied the fourth objective of the
study. The findings of this study contribute to the body of knowledge on HRIS implementation
in context developing and emerging countries such as Pakistani (Asian), as previous studies
108
have mostly focused on western and developed country contexts (Chakraborty and Mansor
(2013).
5.4 Limitation of Study
The present study specifically focuses on a single class of information systems that constitute
the HRIS. Because there are much functional difference in term of system used by the HR
department and other departments in an organization, the findings from this study should be
very cautiously generalized to information systems that cater to the needs of other departments.
The use of HRIS in Pakistan is still at nascent stage, this hindered the selection of a wider
sample of participants for the current study. Future research might benefit from extending the
sample by including data from other developing and emerging countries. Organizational
revenue was not added in the final analysis as approximately 50 % of respondent did not provide
response against the statement.
5.5 Implications for Future Research
Organizations typically adopt different IS modules over time. For example, an organization
may adopt an accounting information system before implementing an HRIS. Organizations
learn through experiences over time. As a direction of future research, the study may be
conducted that determines whether the effects of the antecedents of HRIS remain constant or it
varies across organizations where organizations have different learning experiences of
implementing information system in different functional areas of the organization.
The analysis of the data gathered for the current study revealed that the staff working in the HR
department have strong influence on utilizing the HRIS that have an impact on the
organization’s performance. This relationship merits a further investigation. Also, it would be
worthwhile to investigate the differing effect of HR staff expertise and IS staff expertise on
extent of HRIS adoption. This study does not target the individuals, the future researcher may
target individual end users of HRIS systems to ascertain their satisfaction with extent of
adoption of HRIS. Furthermore, the mediating mechanism like the creativity of implementer
and innovativeness of the organization may be investigated. Moreover, the impact of senior
management teams (SMT) decision regarding the adoption of HRIS can also be investigated as
a moderating factor.
The findings of the thesis contribute to the existing body of knowledge on extent of HRIS
adoption with a context of Pakistan, as a developing country. Pakistan shares different cultural
values than western countries. Future researchers may investigate the cultural aspects including
109
western context to investigate how different cultures have an influence on factors affecting
extent of HRIS adoption.
This study also adds value to the methodologic approach used for conceptualizing the concept
of extent of HRIS adoption which is different from previous conceptualizations by different
authors. The concept of extent of HRIS is conceptualize based on the functional description
that was proposed by (Mayfield, 2003) needs further explorations. Researchers may get benefits
of this approach to construct the best combination of these functions for different organizations
across industries.
5.6 Conclusion
The present study contributes to the body of knowledge in the domain of extent of HRIS
adoption by investigating in the context of emerging and developing countries like Pakistan.
The sample of this study was drawn from organizations that had introduced some level of
computerization to their HR department. The novel aspect of the current study was its
operationalization of the construct of extent of HRIS adoption. This reconceptualization was
based on the functional aspects of HR as recommended by (Mayfiled, 2003). The model
developed by this study incorporated this reconceptualised view of extent of HRIS adoption,
its antecedents, and organization’s performance was included as an outcome variable. To have
an understanding about the concept of extent of HRIS adoption, this study helps the
practitioners and managers to understand the concept of extent of HRIS. The result reveled that
innovation and environmental factors had a significant influence on extent HRIS adoption.
These findings are in line with previous studies, however, it has exhibited a differing context
of a developing country. With regards to the influence of the extent of HRIS adoption on
organization’s performance, the present study confirms that there is a positive relationship
between these two factor when considering subjective measures of organization’s performance.
The implications of the results from the current study are the organizations that adopted HRIS
to a greater extent have better chances to improve their organization’s performance.
Another objective of this study was the role of HR staff expertise. This study also investigated
the role of the HR staff expertise in relation to the extent of HRIS adoption and the
organization’s performance. All hypothesized effects were proved except organizational
characteristics, whereas the effect of HR staff expertise was only proved in relation with the
organization’s performance, no significant moderating effect was discovered.
The findings of this study make a valuable contribution to the literature of information systems
adoption. Specifically, with reference to the concept of extent; the results from the current study
110
indicates that organizations that adopt a holistic system of HRIS will reap its benefits.
Organizations that are best placed to reap the benefits of HRIS are those that completely map
their HR functions onto their HRIS (Qadir & Agrawal, 2017). If the various components of
HRIS are not interlinked, it then does not matter how many of HR systems are mapped to
individual applications, or how many computers are dedicated to these packages, and how much
time end-user spend on these detached applications. Researchers and practitioners in the field
of information system and human resource who are interested to successfully implement the
information system should pay serious consideration of this aspect of the extent of HRIS
adoption.
The sample used in this study was drawn from organizations based in a developing country like
Pakistan. This aspect of the study helps to extend the body on knowledge of IS adoption and
implementation by going beyond the samples from the developed countries. This also addresses
of the shortage of empirical evidence with regards to the extent of HRIS adoption in developing
countries as expressed (Chakraborty & Mansor, 2013; Ahmer, 2013).
111
REFERENCES
Ahmer, Z. (2013). Adoption of Human Resource Information Systems Innovation in Pakistani
Organizations. Journal of Quality and Technology Management, 9(2), 22-50.
Alam, M. G., Masum, A. K., Beh, L.-S., & Hong, C. S. (2016). Critical Factors Influencing
Decision to Adopt Human Resource Information System (HRIS) in Hospitals. PloS one,
11(8).
Al-Dmour, R. H., Masa'deh, R., & Obeidat, B. Y. (2017). Factors influencing the adoption and
implementation of HRIS applications: are they similar? International Journal of
Business Innovation and Research.
Allahawiah, S. R. (2013). Factors affecting the use of E-services from user perspectives: a case
study of Al-Balqa'Applied University. Journal of Management Research, 5(2), 45.
Al-Mobaideen, H., Allahawiah, S., & Basioni, E. (2013). Factors Influencing the Successful
Adoption of Human Resource Information System: The Content of Aqaba Special
Economic Zone Authority. Intelligent Information Management, 5, 1-9.
Altarawneh, I. a.-S. (2010). Human resource information systems in Jordanian universities.
International Journal of Business and Management, 5(10), 113.
Aragon-Correa, J. A., Garcia-Morales, V. J., & Cordon-Pozo, E. (2007). Leadership and
organizational learning's role on innovation and performance: Lessons from Spain.
Industrial marketing management, 36(3), 349-359.
Ashbaugh, S., & Miranda, R. (2002). Technology for human resources management: Seven
questions and answers. Public Personnel Management, 31(1), 7-20.
Awan, A. G., & Sarwar, G. H. (2014). Integrated Role of HRIS & SHRM (SHRIS) in Banking
Sector of Pakistan. Global Journal of Human Resource Management, 3(1), 45-61.
Baker, J. (2012). The technology-organization-environment framework. Information systems
theory, 231-245.
Baker, T. L. (1994). Doing social research (3 rd. ed.). McGraw-Hill New York, NY.
Ball, K. S. (2001). The use of human resource information systems: a survey. Personnel review,
30(6), 677-693.
112
Bamel, N., Kumar Bamel, U., Sahay, V., & Thite, M. (2014). Usage, benefits and barriers of
human resource information system in universities. The journal of information and
knowledge management systems, 44(4), 519-536.
Barney, J. B. (1995). Looking inside for competitive advantage. The Academy of Management
Executive, 9(4), 49-61.
Baron, R. M., & Kenny, D. A. (1986). The moderator--mediator variable distinction in social
psychological research: Conceptual, strategic, and statistical considerations. Journal of
personality and social psychology, 51(6), 1173.
Bartram, T. (2005). Small firms, big ideas: The adoption of human resource management in
Australian small firms. Asia Pacific Journal of Human Resources, 43(1), 137-154.
Baruch, Y., & Holtom, B. C. (2008). Survey response rate levels and trends in organizational
research. Human relations, 61(8), 1139-1160.
Battisti, G., Hollenstein, H., Stoneman, P., & Woerter, M. (2007). Inter and intra firm diffusion
of ICT in the United Kingdom (UK) and Switzerland (CH) an internationally
comparative study based on firm-level data. Economics of Innovation and New
technology, 16(8), 669-687.
Beadles, N., Lowery, C. M., & Johns, K. (2005). The impact of human resource information
systems: an exploratory study in the public sector. Communications of the IIMA, 5, 39-
46.
Beard, D. W., & Dess, G. G. (1981). Corporate level strategy, business leve strategy and firm
performance. Academy of management journal, 24, 663-688.
Becker, B. E., & Huselid, M. A. (1998). High performance work systems and firm performance:
A synthesis of research and managerial implications. Research in Personnel and Human
Resource Management, 16, 53-101.
Becker, B., & Gerhart, B. (1996). The impact of human resource management on organizational
performance: Progress and prospects. Academy of management journal, 39, 779-801.
Berger, E. S., & Kuckertz, A. (2016). Complexity in entrepreneurship, innovation and
technology research: applications of emergent and neglected methods. Springer.
Beulen, E. (2009). The contribution of a global service provider's Human Resources
Information System (HRIS) to staff retention in emerging markets: Comparing issues
and implications in six developing countries. Information Technology & People, 22(3),
270-288.
113
Bharadwaj, A. S. (2000). A resource-based perspective on information technology capability
and firm performance: an empirical investigation. MIS quarterly, 169-196.
Bhattacherjee, A. (1998). Managerial Influences on Intraorganizational Information
Technology Use: A Principal-Agent Model. Decision Sciences, 29(1), 139-162.
Bondarouk, T., Ruel, H., & Looise, J. (2011). Electronic HRM in theory and practice (Vol. 6).
Emerald Group Publishing.
Bondarouk, T., Schilling, D., & Ruel, H. (2016). eHRM adoption in emerging economies: The
case of subsidiaries of multinational corporations in Indonesia. Canadian Journal of
Administrative Sciences.
Boselie, P., Dietz, G., & Boon, C. (2005). Commonalities and contradictions in HRM and
performance research. Human resource management journal, 15(3), 67-94.
Bradford, M., & Florin, J. (2003). Examining the role of innovation diffusion factors on the
implementation success of enterprise resource planning systems. International journal
of accounting information systems, 4(3), 205-225.
Broderick, R., & Boudreau, J. W. (1992). Human resource management, information
technology, and the competitive edge. The academy of managment executive, 6(2), 7-
17.
Buzkan, H. (2016). The Role of Human Resource Information System (HRIS) in Organizations:
A Review of Literature. Academic Journal of Interdisciplinary Studies, 5(1), 133.
Calantone, R. J., Cavusgil, S. T., & Zhao, Y. (2002). Learning orientation, firm innovation
capability, and firm performance. Industrial marketing management, 31(6), 515-524.
Campbell, D. T., & Fiske, D. W. (1959). Convergent and discriminant validation by the
multitrait-multimethod matrix. Psychological bulletin, 56(2), 81.
Ceric, A., & Krivokapic-Skoko, B. (2016). Applying QCA and Cross-impact Analysis to the
Study on ICT Adoption and Use by Croatian SMEs. In E. S. Berger, & A. Kuckertz,
Complexity in Entrepreneurship, Innovation and Technology Research (pp. 349-370).
Springer.
Chae, B. K., Prince, J. B., Katz, J., & Kabst, R. (2012). An Exploratory Cross-National Study
of Information Sharing and Human Resource Information Systems. Human Resources
Management: Concepts, Methodologies, Tools, and Applications.
Chakraborty, A. R., & Mansor, N. N. (2013). Adoption of human resource information system:
A theoretical analysis. Procedia-Social and Behavioral Sciences, 75, 473-478.
114
Chand, M., & Katou, A. A. (2007). The impact of HRM practices on organisational
performance in the Indian hotel industry. Employee Relations, 29(6), 576-594.
Cheney, P. H., Mann, R. I., & Amoroso, D. L. (1986). Organizational factors affecting the
success of end-user computing. Journal of Management Information Systems, 3(1), 65-
80.
Chong, A. Y.-L., Lin, B., Ooi, K.-B., & Raman, M. (2009). Factors affecting the adoption level
of c-commerce: An empirical study. Journal of Computer Information Systems, 50(2),
13-22.
Connelly, L. M. (2008). Pilot studies. Medsurg Nursing, 17(6), 411-413.
Cooper, R. B., & Zmud, R. W. (1990). Information technology implementation research: a
technological diffusion approach. Management science, 36(2), 123--139.
Creswell, J. W. (2013). Research design: Qualitative, quantitative, and mixed methods
approaches (4th ed.). Sage publications.
Crossan, M. M., & Apaydin, M. (2010). A multi-dimensional framework of organizational
innovation: A systematic review of the literature. Journal of management studies, 47(6),
1154-1191.
Cycyota, C. S., & Harrison, D. A. (2006). What (not) to expect when surveying executives: A
meta-analysis of top manager response rates and techniques over time. Organizational
Research Methods, 9(2), 133-160.
Daft, R. L. (1978). A dual-core model of organizational innovation. Academy of management
journal, 21(2), 193-210.
Damanpour, F. (1987). The adoption of technological, administrative, and ancillary
innovations: Impact of organizational factors. Journal of management, 13(4), 675-688.
Damanpour, F. (1991). Organizational innovation: A meta-analysis of effects of determinants
and moderators. Academy of management journal, 34(3), 555-590.
Damanpour, F., & Schneider, M. (2006). Phases of the adoption of innovation in organizations:
Effects of environment, organization and top Managers1. British Journal of
Management, 17(3), 215-236.
De Vaus, D. A. (2001). Research design in social research. Sage.
DeCenzo, D. A., & Robbins, S. P. (2005). Fundamentals of human resource management .
Hoboken.
115
DeLone, W. H. (1981). Firm size and the characteristics of computer use. Mis Quarterly, 65-
77.
DeLone, W. H. (1988). Determinants of success for computer usage in small business. Mis
Quarterly, 51-61.
DeSanctis, G. (1986). Human resource information systems: a current assessment. MIS
Quarterly, 15-27.
Dess, G. G., & Robinson, R. B. (1984). Measuring organizational performance in the absence
of objective measures: the case of the privately-held firm and conglomerate business
unit. Strategic management journal, 5(3), 265-273.
Dessler, G., Sutherland, G., & Cole, N. D. (2005). Human resources management in Canada.
Pearson Education Canada.
DeTienne, D. R., & Koberg, C. S. (2002). The impact of environmental and organizational
factors on discontinuous innovation within high-technology industries. IEEE
Transactions on engineering management, 49(4), 352--364.
Dong, L. (2008). Exploring the impact of top management support of enterprise systems
implementations outcomes: Two cases. Business Process Management Journal, 14(2),
204-218.
Dunivan, L. (1991). Implementing a user-driven human resource information system. Journal
of Systems Management, 42(10), 13-15.
Dyer, L., & Reeves, T. (1995). Human resource strategies and firm performance: what do we
know and where do we need to go? International Journal of human resource
management, 6(3), 656--670.
Evans, J. R., & Mathur, A. (2005). The value of online surveys. Internet research, 15(2), 195-
219.
Fichman, R. G. (1992). Information technology diffusion: a review of empirical research. ICIS,
195-206.
Fichman, R. G. (1995). The assimilation and diffusion of software process innovations.
Massachusetts Institute of Technology.
Fichman, R. G. (2004). Going beyond the dominant paradigm for information technology
innovation research: Emerging concepts and methods. Journal of the association for
information systems, 5(8), 11.
116
Fichman, R. G., & Kemerer, C. F. (1993). Adoption of software engineering process
innovations: The case of object orientation. Sloan management review, 34(2), 7.
Field, A. (2009). Discovering Statistics using SPSS (3rd ed.). Sage.
Findikli, M. A., & Beyza Bayarcelik, E. (2015). Exploring the Outcomes of Electronic Human
Resource Management (E-HRM). Procedia-Social and Behavioral Sciences, 207, 424-
431.
Frambach, R. T., & Schillewaert, N. (2002). Organizational innovation adoption: A multi-level
framework of determinants and opportunities for future research. Journal of Business
Research, 55(2), 163-176.
Fui-Hoon Nah, F., Lee-Shang Lau, J., & Kuang, J. (2001). Critical factors for successful
implementation of enterprise systems. Business process management journal, 7(3), 285-
-296.
Galbreath, J., & Galvin, P. (2008). Firm factors, industry structure and performance variation:
New empirical evidence to a classic debate. Journal of business research, 61(2), 109-
117.
George, D., & Mallery, P. (2010). SPSS for Windows Step by Step: A Simple Guide and
Reference 18.0 Update. Prentice Hall Press.
Gooding, R. Z., & Wagner III, J. A. (1985). A meta-analytic review of the relationship between
size and performance: The productivity and efficiency of organizations and their
subunits. Administrative science quarterly, 462-481.
Greenhalgh, T., Robert, G., Bate, P., Macfarlane, F., & Kyriakidou, O. (2008). Diffusion of
innovations in health service organisations: a systematic literature review. John Wiley
& Sons.
Gremillion, L. L. (1984). Organization size and information system use: An empirical study.
Journal of Management Information Systems, 1(2), 4-17.
Grover, V. (1997). An extension of the tri-core model of information systems innovation:
strategic and technological moderators. An extension of the tri-core model of
information systems innovation: strategic and technological moderators, 6(4), 232-242.
Grover, V., & Goslar, M. D. (1993). The initiation, adoption, and implementation of
telecommunications technologies in US organizations. Journal of Management
Information Systems, 10(1), 141-164.
117
Guest, D. E., Michie, J., Conway, N., & Sheehan, M. (n.d.). Human resource management and
corporate performance in the UK. British journal of industrial relations, 41(2), 291-
314.
Gueutal, H. G., Strohmeier, S., & Kabst, R. (2009). Organizational adoption of e-HRM in
Europe: An empirical exploration of major adoption factors. Journal of Managerial
Psychology, 24(6), 482-501.
Haines, V. Y., & Petit, A. (1997). Conditions for successful human resource information
systems. Human Resource Management, 36(2), 261-275.
Hair, J. F., Anderson, R. E., Babin, B. J., & Black, W. C. (2010). Multivariate data analysis: A
global perspective (Vol. 7). Pearson Upper Saddle River, NJ.
Hameed, M. A., Counsell, S., & Swift, S. (2012). A conceptual model for the process of IT
innovation adoption in organizations. Journal of Engineering and Technology
Management, 29(3), 358-390.
Hameed, M. A., Counsell, S., & Swift, S. (2012). A meta-analysis of relationships between
organizational characteristics and IT innovation adoption in organizations. Information
& management, 49(5), 218-232.
Hanif, F. (2011). Impact of Human Resource Information System (HRIS): Substituting or
Enhancing HR Function. Available at SSRN 1425905.
Hanif, M. I., Yunfei, S., Hanif, M. S., ullah Muhammad, Z., Ahmed, K. T., & Xiu-Yin, B.
(2014). Explore the Adoption of HRIS in Telecom Sector in Pakistan. International
Journal of Economics & Management Sciences.
Hayes, A. F. (2013). Introduction to mediation, moderation, and conditional process analysis:
A regression-based approach. New York, USA.
Hendrickson, A. (2003). Human resource information systems: Backbone technology of
contemporary human resources. Journal of Labor Research, 24(3), 382-394.
Henriksen, H. Z., & Andersen, K. V. (2008). Electronic records management systems
implementation in the Pakistani local government. Records Management Journal,
18(1), 40-52.
Hitt, L. M., & Brynjolfsson, E. (1996). Productivity, business profitability, and consumer
surplus: three different measures of information technology value. MIS quarterly, 121-
142.
118
Hopkins, B., & Markham, J. (2003). E-HR: using intranets to improve the effectiveness of your
people. Gower Publishing, Ltd.
Hsieh, J. P.-A., & Wang, W. (2007). Explaining employees' extended use of complex
information systems. European Journal of Information Systems, 16(3), 216-227.
Hussain, Z., Wallace, J., & Cornelius, N. E. (2007). The use and impact of human resource
information systems on human resource management professionals. Information &
Management, 44, 74-89.
Igbaria, M., & Nachman, S. A. (1990). Correlates of user satisfaction with end user computing:
an exploratory study. Information & Management, 19(2), 73-82.
Iivari, J., Hirschheim, R., & Klein, H. K. (1998). A paradigmatic analysis contrasting
information systems development approaches and methodologies. Information Systems
Research, 9(2), 164-193.
Jain, V., & Kanungo, S. (2016). Working smarter or working harder? Complementary
relationship between extent of IS use and nature of IS use. International Journal of
Business Information Systems, 21(4), 512-540.
Jeyaraj, A., Rottman, J. W., & Lacity, M. C. (2006). A review of the predictors, linkages, and
biases in IT innovation adoption research. Journal of Information Technology, 21, 1-23.
Jiang, K., Lepak, D. P., Hu, J., & Baer, J. C. (2012). How does human resource management
influence organizational outcomes? A meta-analytic investigation of mediating
mechanisms. Academy of management Journal, 55(6), 1264-1294.
Kamal, M. M. (2006). IT innovation adoption in the government sector: identifying the critical
success factors. Journal of Enterprise Information Management, 19(2), 192-222.
Kaplan, R., & Norton, D. (1992). The Balanced Scorecard-Measures That Drive Performance.
Harvard Business Review, 1(70).
Karim, Z., & Rahman, M. H. (2018). Practices of Human Resource Information Systems: A
Study on Some Private Business Enterprises in Bangladesh. Global Journal of
Management And Business Research.
Karimi, J., Somers, T. M., & Bhattacherjee, A. (2007). The impact of ERP implementation on
business process outcomes: A factor-based study. Journal of Management Information
Systems, 24(1), 101-134.
119
Kariuki, M. M. (2015). Human Resource Information System and Competitive Advantage of
Companies Listed on Nairobi Securities Exchange in Kenya. European Journal of
Business and Management, 7(21).
Kasper, G. M., & Cerveny, R. P. (1985). A laboratory study of user characteristics and decision-
making performance in end-user computing. Information & Management, 9(2), 87-96.
Kassim, N. M., Ramayah, T., & Kurnia, S. (2012). Antecedents and outcomes of human
resource information system (HRIS) use. International Journal of Productivity and
Performance Management, 61(6), 603--623.
Kavanagh, M. J., & Thite, M. (2009). Human resource information systems: Basics,
applications, and future directions. Sage.
Kazmi, S. A., & Naaranoja, M. (2014). HRIS-An Effective Knowledge Management Solution.
GSTF Journal on Business Review (GBR), 13(2).
Keim, T., & Weitzel, T. (2008). An adoption and diffusion perspective on HRIS usage.
Encyclopedia of Human Resources Information Systems: Challenges in e-HRM:
Challenges in e-HRM.
Khalil Darwish, T., & Singh, S. (2013). Does strategic human resource involvement and
devolvement enhance organisational performance? Evidence from Jordan. International
Journal of Manpower, 34(6), 674-692.
Khan, A. S., & Anwar, F. (2012). An Exploratory Study of Appraisal Techniques from Pakistan
Telecommunication Company Limited (PTCL). Arabian Journal of Business and
Management Review (OMAN Chapter), 7, 51-70.
Khashman, I. M., & Khashman, A. M. (2016). The Impact of Human Resource Information
System (HRIS) Applications on Organizational Performance (Efficiency and
Effectiveness) in Jordanian Private Hospitals. Journal of Management Research, 8(3),
31-44.
Khera, S. N. (2012). Human resource information system and its impact on human resource
planning: A perceptual analysis of information technology companies. Journal of
Business and Management, 3(6), 6-13.
Kimberly, J. R. (1976). Organizational size and the structuralist perspective: A review, critique,
and proposal. Administrative Science Quarterly, 21, 571--597.
Klomp, L., & Van Leeuwen, G. (2001). Linking innovation and firm performance: a new
approach. International Journal of the Economics of Business, 8(3), 343-364.
120
Komiak, S. Y., & Benbasat, I. (2006). The effects of personalization and familiarity on trust
and adoption of recommendation agents. MIS quarterly, 941-960.
Kovach, K. A., & Cathcart, C. E. (1999). Human Resource Information Systems (HRIS):
Providing Business with Rapid Data Access, Information Exchange and Strategic
Advantage. Public Personnel Management, 28(2), 275.
Kovach, K. A., Hughes, A. A., Fagan, P., & Maggitti, P. G. (2002). Administrative and strategic
advantages of HRIS. Employment Relations Today, 29(2), 43-48.
Krishnan, S. K., & Singh, M. (2007). Issues and Concerns in the Implementation and
Maintenance of HRIS. Management and Labour Studies, 32(4), 522-540.
Kuan, K. K., & Chau, P. Y. (2001). A perception-based model for EDI adoption in small
businesses using a technology--organization--environment framework. Information &
management, 38(8), 507--521.
Kwon, T. H., & Zmud, R. W. (1987). Unifying the fragmented models of information systems
implementation. Critical issues in information systems research, 227-251.
Lantara, N. F. (2016). The Use of Human Resources Information System for Organization and
Motivation of South Sulawesi Gubernatorial Office Staffs. International Business
Management, 10(4), 385-390.
Latif, A., Ullah, R., Din, M. S., & Anjum, Z. A. (2014). THE FUTURE OF HUMAN
RESOURCE PROFESSIONALS. City University Research Journal, 208-222.
Lau, G., & Hooper, V. (2008). Adoption of e-HRM in large New Zealand organizations.
Encyclopedia of Human Resources Information Systems: Challenges in e-HRM:
Challenges in e-HRM, 31-41.
Law, C. C., & Ngai, E. W. (2007). ERP systems adoption: An exploratory study of the
organizational factors and impacts of ERP success. Information & Management, 44(4),
418-432.
Lawler III, E. E. (2005). From Human Resource Effectiveness to Organization Effectiveness.
Human Resource Management, 44(2), 165-169.
Lee, G., & Xia, W. (2006). Organizational size and IT innovation adoption: A meta-analysis.
Information & Management, 43(8), 975-985.
Lee, H., & Choi, B. (2003). Knowledge management enablers, processes, and organizational
performance: An integrative view and empirical examination. Journal of management
information systems, 20(1), 179-228.
121
Leedy, P. D., & Ormrod, J. E. (2010). Practical Research Planning and Design. New Jersey:
Pearson Education.
Li, Y., Zhao, Y., & Liu, Y. (2006). The relationship between HRM, technology innovation and
performance in China. International journal of manpower, 27(7), 679--697.
Li, Y.-h. (2008). An empirical investigation on the determinants of e-procurement adoption in
Chinese manufacturing enterprises. Management Science and Engineering, 2008.
ICMSE 2008. 15th Annual Conference Proceedings., International Conference on (pp.
32-37). IEEE.
Lin, H.-F. (2010). An investigation into the effects of IS quality and top management support
on ERP system usage. Total Quality Management, 21(3), 335-349.
Mabert, V. A., Soni, A., & Venkataramanan, M. A. (2003). The impact of organization size on
enterprise resource planning (ERP) implementations in the US manufacturing sector.
Omega, 31(3), 235--246.
Magalhaes, R., & Ruel, H. (2007). Human Resource Information Systems: An Integrated
Research Agenda. Workshop on Human Resource Information Systems embedded in the
9th International Conference on Enterprise Information Systems (ICEIS).
Maier, C., Laumer, S., Eckhardt, A., & Weitzel, T. (2013). Analyzing the impact of HRIS
implementations on HR personnel’s job satisfaction and turnover intention. The Journal
of Strategic Information Systems.
Malik, K. P. (2002). Implementation of Human Resource Information System in Pakistani
Organizations. Pakistan's Seventh International Convention on Quality Improvement
(ICQI'2002), 01-10.
Marcoulides, G. A. (1998). Modern methods for business research. Lawrence Erlbaum
Associates, Inc., New Jersey.
Markham, J. (2017). E-hr-Using Intranets to Improve the Effectiveness of Your People. Taylor
& Francis Limited.
Marler, J. H., & Fisher, S. L. (2013). An evidence-based review of e-HRM and strategic human
resource management. Human Resource Management Review, 23, 18-36.
Martins, M., & Oliveira, T. (2009). Determinants of e-commerce adoption by small firms in
Portugal. In Proceedings of the 3rd European conference on information management
and evaluation (pp. 328-338).
122
Martinsons, M. G. (1994). Benchmarking human resource information systems in Canada and
Hong Kong. Information & Management, 26(6), 305-316.
Mayfield, M., Mayfield, J., & Lunce, S. (2003). Human resource information systems: A review
and model development. Advances in Competitiveness Research, 11, 139.
Mayfield, M., Mayfield, J., & Lunce, S. (2009). Increasing tacit knowledge sharing with an
HRIS. In Encyclopedia of human resources information systems: Challenges in e-HRM
(pp. 518-524). IGI Global.
Mingers, J. (2003). A classification of the philosophical assumptions of management science
methods. Journal of the Operational Research Society, 54(6), 559-570.
Mingers, J., & Willcocks, L. (2004). Social theory and philosophy for information systems.
John Wiley & Sons Ltd.
Mishra, A., & Akman, I. (2010). Information technology in human resource management: an
empirical assessment. Public Personnel Management, 39(3), 271-290.
Mone, M. A., McKinley, W., & Barker, V. L. (1998). Organizational decline and innovation:
A contingency framework. Academy of Management Review, 23(1), 115-132.
Moore, G. C., & Benbasat, I. (1991). Development of an Instrument to Measure the Perceptions
of Adopting an Information Technology Innovation. Information Systems Research,
2(3), 192-222.
Moorthy, S., & Polley, D. E. (2010). Technological knowledge breadth and depth: performance
impacts. Journal of Knowledge Management, 14(3), 359-377.
Moussa, M. (2014). A Review of Human Resource Information Systems (HRISs) in
Organizations. SIU Journal of Management.
Mustonen-Ollila, E., & Lyytinen, K. (2003). Why organizations adopt information system
process innovations: a longitudinal study using Diffusion of Innovation theory.
Information Systems Journal, 13(3), 275-297.
Ngai, E., & Wat, F. (2006). Human resource information systems: a review and empirical
analysis. Personnel Review, 35(3), 297-314.
Nguyen, D. N., & Nguyen, M. H. (2016). Factors Influencing the Use of HRIS: Case Study
from SMEs in Vietnam. SGBED wishes to recognize the following sponsors, 378.
Nunnally, J. C., & Bernstein, I. H. (1994). Psychological theory. New York, NY: MacGraw-
Hill.
123
Nwankpa, J. K. (2015). ERP system usage and benefit: A model of antecedents and outcomes.
Computers in Human Behavior, 45, 335-344.
Obeidat, B. Y. (2012). The Relationship between Human Resource Information System (HRIS)
Functions and Human Resource Management (HRM) Functionalities. Journal of
Management Research, 4, 192-211.
Obeidat, B. Y. (2013). The Relationship between Innovation Diffusion and Human Resource
Information System (HRIS). Business and Management, 5.
O'Brien, J. A., & Marakas, G. (2011). Management information systems. McGraw-Hill, New
York, NY.
Olivas-Lujan, M. R., & Florkowski, G. W. (2008). Diffusion of HR-ICTs, an innovations
perspective. Technology, Outsourcing & Transforming HR, 231-256.
Olivas-Lujan, M. R., & Rousseau, D. M. (2010). Can the Evidence-Based Management
Movement Help e-HRM Bridge the Research-Practice Gap? Evidence-Based e-HRM?
On the way to rigorous and relevant research., 3-13.
Oliveira, T., & Martins, M. F. (2010). Firms patterns of e-business adoption: evidence for the
European Union-27. The Electronic Journal Information Systems Evaluation, 13(1), 47-
56.
Oliveira, T., & Martins, M. F. (2010). Information technology adoption models at firm level:
review of literature. European Conference on Information Management and Evaluation,
312.
Oliveira, T., & Martins, M. F. (2011). Literature review of information technology adoption
models at firm level. Electronic Journal of Information Systems Evaluation, 14(1), 110.
Orlikowski, W. J., & Baroudi, J. J. (1991). Studying information technology in organizations:
Research approaches and assumptions. Information systems research, 2(1), 1-28.
Orlikowski, W. J., & Scott, S. V. (2008). Sociomateriality: challenging the separation of
technology, work and organization. The academy of management annals, 2(1), 433-474.
Othman, R., & Teh, C. (2003). On developing the informated work place: HRM issues in
Malaysia. Human Resource Management Review, 13(3), 393-406.
Palmer, J. W., & Markus, M. L. (2000). The performance impacts of quick response and
strategic alignment in specialty retailing. Information Systems Research, 11(3), 241-
259.
124
Palvia, P., Means, D. B., & Jackson, W. M. (1994). Determinants of computing in very small
businesses. Information & Management, 27, 161-174.
Pan, M.-J., & Jang, W.-Y. (2008). Determinants of the adoption of enterprise resource planning
within the technology-organization-environment framework: Taiwan's communications
industry. Journal of Computer information systems, 48(3), 94-102.
Panayotopoulou, L., Galanaki, E., & Papalexandris, N. (2010). Adoption of electronic systems
in HRM: Is national background of the firm relevant? New Technology, Work and
Employment, 25(3), 253-269.
Panayotopoulou, L., Vakola, M., & Galanaki, E. (2007). E-HR adoption and the role of HRM:
evidence from Greece. Personnel Review, 36(2), 277-294.
Parry, E. (2011). An examination of e-HRM as a means to increase the value of the HR function.
The International Journal of Human Resource Management, 22(5), 1146-1162.
Parry, E., & Wilson, H. (2009). Factors influencing the adoption of online recruitment.
Personnel Review, 38(6), 655-673.
Parry, E., Tyson, S., Selbie, D., & Leighton, R. (2007). HR and technology: Impact and
advantages. London: Charted Institute of Personnel and Development.
Peansupap, V., & Walker, D. (2005). Exploratory factors influencing information and
communication technology diffusion and adoption within Australian construction
organizations: a micro analysis. Construction Innovation: Information, Process,
Management, 5(3), 135-157.
Phahlane, M. M. (2017). A conceptual research framework for human resource information
systems adoption and use in universities. Information Communication Technology and
Society (ICTAS), Conference on (pp. 1-6). IEEE.
Pierce, J. L., & Delbecq, A. L. (1977). Organization structure, individual attitudes and
innovation. Academy of management review, 2(1), 27-37.
Polit, D. F. (2013). Essentials of nursing research: Appraising evidence for nursing practice (8
th ed.). Lippincott Williams & Wilkins.
Powell, T. C., & Dent-Micallef, A. (1997). Information technology as competitive advantage:
The role of human, business, and technology resources. Strategic management journal,
375-405.
Premkumar, G., & King, W. R. (1994). Organizational characteristics and information systems
planning: An empirical study. Information Systems Research, 5(2), 75--109.
125
Premkumar, G., & Ramamurthy, K. (1995). The role of interorganizational and organizational
factors on the decision mode for adoption of interorganizational systems. Decision
sciences, 26(3), 303-336.
Premkumar, G., & Roberts, M. (1999). Adoption of new information technologies in rural small
businesses. Omega, 27, 467-484.
Prescott, M. B. (1995). Diffusion of innovation theory: borrowings, extensions, and
modifications from IT researchers. ACM SIGMIS Database, 26(2), 16-19.
Prescott, M. B., & Conger, S. A. (1995). Information technology innovations: a classification
by IT locus of impact and research approach. 26(2), 20--41.
Qadir, A., & Agrawal, S. (2017). HR Transformation through Human Resource Information
System: Review of Literature. Journal of Strategic Human Resource Management, 6(1).
Qaisar, N., Shahzad, K., & Arif, M. (2018). Extent of HRIS Adoption and Its Impact on
organization's performance: moderating role of HR staff expertise. Abasyn University
Journal of Social Sciences.
Ravichandran, T., & Lertwongsatien, C. (2005). Effect of information systems resources and
capabilities on firm performance: a resource-based perspective. Journal of management
information systems, 21(4), 237--276.
Raymond, L. (1985). Organizational characteristics and MIS success in the context of small
business. MIS quarterly, 37-52.
Raymond, L. (1990). Organizational context and information systems success: a contingency
approach. Journal of Management Information Systems, 6(4), 5-20.
Remus, U. (2007). Critical success factors for implementing enterprise portals: A comparison
with ERP implementations. Business process management journal, 13(4), 538--552.
Richard, P. J., Devinney, T. M., & Johnson, G. (2009). Measuring organizational performance:
Towards methodological best practice. Journal of management.
Rockart, J. F., & Short, J. E. (1989). IT in the 1990s: Managing organizational interdependence.
MIT Sloan Management Review, 30(2), 7.
Rodriguez, J. M., & Ventura, J. (2003). Human resource management systems and
organizational performance: an analysis of the Spanish manufacturing industry.
International Journal of Human Resource Management, 14, 1206-1226.
126
Roehling, M., Boswell, W., Caligiuri, P., Feldman, D., Graham, M., Guthrie, J., . . . Tansky, J.
(2005). The future of HR management: Research needs and directions. Human Resource
Management, 44(2), 207-216.
Rogelberg, S. G., & Stanton, J. M. (2007). Understanding and dealing with organizational
survey nonresponse. Organizational Research Method, 10, 195–209.
Rogers, E. M. (1995). Diffusion of Innovations. (4th, Ed.) New York, NY.: The Free Press.
Rogers, E. M. (2004). A prospective and retrospective look at the diffusion model. Journal of
Health Communication, 9(S1), 13-19.
Roos, G., Fernstrom, L., & Pike, S. (2004). Human resource management and business
performance measurement. Measuring Business Excellence, 8(1), 28--37.
Ruel, H. J., Bondarouk, T. V., & Van der Velde, M. (2007). The contribution of e-HRM to
HRM effectiveness: Results from a quantitative study in a Dutch Ministry. Employee
Relations, 29, 280-291.
Ruel, H., & Bondarouk, T. (2014). E-HRM research and practice: facing the challenges ahead.
In Handbook of strategic e-Business management (pp. 633-653). Springer.
Ruel, H., Bondarouk, T., & Looise, J. K. (2004). e-HRM: innovation or irritation: an explorative
empirical study in five large companies on web-based HRM. Management Revue, 15,
364-380.
Ruel, H., Magalhaes, R., & Chiemeke, C. C. (2011). Human Resource Information Systems:
An Integrated Research Agenda. Electronic HRM in theory and practice, 21-39.
Sadiq, U., Khan, A. F., Ikhlaq, K., & Mujtaba, B. G. (2013). The Impact of Information Systems
on the Performance of Human Resources Department.  Strategic Human Resource
Management at Tertiary Level, 31.
Saleem, I. (2012). Impact of Adopting HRIS on Three Tries of HRM: Evidence from
Developing Economy. Business Review, 7(2), 96-105.
Sanders, K., Cogin, J. A., & Bainbridge, H. T. (2013). Research methods for human resource
management. Routledge.
Saunders, M., Lewis, P., & Thornhill, A. (2016). Research methods for business students. (7th,
Ed.) Pearson Education.
Schuler, R. S., & Jackson, S. E. (1999). Linking competitive strategies with human resource
management practices. Strategic human resource management, 159-176.
127
SECP. (2016). Data and Statistics. Retrieved from Securities & Exchange Commission of
Pakistan: https://www.secp.gov.pk/data-and-statistics/corporates/
Sekaran, U., & Bougie, R. (2016). Research methods for business: A skill building approach.
John Wiley & Sons.
Sheehan, C. (2005). A model for HRM strategic integration. Personnel Review, 34(2), 192-209.
Siddique, C. (2004). Job analysis: A strategic human resource management practice. The
International Journal of Human Resource Management, 15(1), 219-244.
Singh, S., Darwish, T. K., & Potocnik, K. (2016). Measuring Organizational Performance: A
Case for Subjective Measures. British Journal of Management, 27(1), 214-224.
So, S., & Sun, H. (2011). An extension of IDT in examining the relationship between electronic-
enabled supply chain integration and the adoption of lean production. International
Journal of Production Research, 49(2), 447-466.
Soltan, E. K., Jusoh, A., Mardani, A., & Bagheri, M. M. (2015). Successful enterprise resource
planning post-implementation: Contributions of technological factors. Journal of Soft
Computing and Decision Support Systems, 2(4), 17-25.
Sonnenwald, D. H., Maglaughlin, K. L., & Whitton, M. C. (2001). Using innovation diffusion
theory to guide collaboration technology evaluation: Work in progress. Enabling
Technologies: Infrastructure for Collaborative Enterprises, 2001. WET ICE 2001.
Proceedings. Tenth IEEE International Workshops on, (pp. 114-119).
Stone, D. L., & Dulebohn, J. H. (2012). Emerging issues in theory and research on electronic
human resource management (eHRM). Human Resource Management Review.
Straub, E. T. (2009). Understanding technology adoption: Theory and future directions for
informal learning. Review of educational research, 79(2), 625-649.
Sultan, F., & Chan, L. (2000). The adoption of new technology: the case of object-oriented
computing in software companies. IEEE transactions on Engineering Management,
47(1), 106-126.
Swanson, E. B. (1994). Information systems innovation among organizations. Management
science, 40(9), 1069-1092.
Tabachnick, B. G., & Fidell, L. S. (2013). Using multivariate statistics. (6th, Ed.) USA: Pearson
Education, Inc.
128
Tannenbaum, S. (1990). Human resource information systems: User group implications.
Journal of Systems Management, 41, 27–32.
Tanoglu, I., Basoglu, N., & Daim, T. (2010). Exploring technology diffusion: Case of
information technologies. International Journal of Information Technology & Decision
Making, 9(2), 195-222.
Tansley, C., & Watson, T. (2000). Strategic exchange in the development of human resource
information systems (HRIS). New Technology, Work and Employment, 15(2), 108-122.
Teo, T. S., Soon, L. G., & Fedric, S. A. (2001). Adoption and impact of human resource
information systems (HRIS). Research and Practice in Human Resource Management,
9, 101-117.
Teo, T. S., Soon, L. G., & Fedric, S. A. (2007). The adoption and diffusion of human resources
information systems in Singapore. Asia Pacific Journal of Human Resources, 45, 44-
62.
Thompson, V. A. (1965). Bureaucracy and innovation. Administrative science quarterly, 1-20.
Thong, J. Y. (1999). An integrated model of information systems adoption in small businesses.
Journal of management information systems, 15, 187-214.
Thong, J. Y., & Yap, C.-S. (1995). CEO characteristics, organizational characteristics and
information technology adoption in small businesses. Omega, 23(4), 429-442.
Tornatzky, L. G., & Fleischer, M. (1990). Processes of technological innovation. New York:
Lexington Books.
Tornatzky, L. G., & Klein, K. J. (1982). Innovation characteristics and innovation adoption-
implementation: A meta-analysis of findings. IEEE Transactions on engineering
management(1), 28-45.
Torrington, D., & Hall, L. (1996). Chasing the rainbow: how seeking status through strategy
misses the point for the personnel function. Employee Relations, 18(6), 81-97.
Townsend, A. M., & Bennett, J. T. (2003). Human resources and information technology.
Journal of Labor Research, 24(3), 361-363.
Troshani, I., Jerram, C., & Gerrard, M. (2010). Exploring the organizational adoption of human
resources information systems (HRIS) in the Australian public sector. Proceedings of
the 21st Australasian Conference on Information Systems (ACIS2010), Brisbane,
Australia, December.
129
Troshani, I., Jerram, C., & Rao Hill, S. (2011). Exploring the public sector adoption of HRIS.
Industrial Management & Data Systems, 111(3), 470-488.
Tursunbayeva, A., Pagliari, C., Bunduchi, R., & Franco, M. (2016). What does it take to
implement Human Resource Information System (HRIS) at scale? Analysis of the
Expected Benefits and Actual Outcomes.
Tye, E. M., & Chau, P. Y. (1995). A study of information technology adoption in Hong Kong.
Journal of information science, 21(1), 11-19.
Ulrich, D. (1997). Human Resource Champions. The next agenda for adding value and.
Harvard Business School Press, Boston, Massachusetts, USA.
Van Slyke, C., Lou, H., & Day, J. (2002). The impact of perceived innovation characteristics
on intention to use groupware. Information Resources Management Journal (IRMJ),
15(1), 1-12.
Van Teijlingen, E., & Hundley, V. (2002). The importance of pilot studies. Nursing Standard,
16(40), 33-36.
Venaik, S., Midgley, D., & Devinney, T. M. (2005). Dual paths to performance: The impact of
global pressures on MNC subsidiary conduct and performance. Journal of International
Business Studies, 36(6), 655-675.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of
information technology: Toward a unified view. MIS quarterly, 425-478.
Ward, J., & Peppard, J. (2002). Strategic planning for information systems. (3, Ed.) John Wiley
& Sons Ltd.
Weill, P. (1992). The relationship between investment in information technology and firm
performance: A study of the valve manufacturing sector. Information systems research,
3(4), 307--333.
Wiblen, S., Grant, D., & Dery, K. (2010). Transitioning to a new HRIS: The reshaping of human
resources and information technology talent. Journal of Electronic Commerce
Research, 11(4), 251.
Willcocks, L. P., Sauer, C., & Lacity, M. C. (2015). Formulating Research Methods for
Information Systems. Palgrave Macmillan.
Yamane, T. (1967). Elementary sampling theory. NJ, Prentice-Hall.
130
Yammarino, F. J., Skinner, S. J., & Childers, T. L. (1991). Understanding mail survey response
behavior a meta-analysis. Public Opinion Quarterly, 55(4), 613-639.
Yang, K. H., Lee, S. M., & Lee, S.-G. (2007). Adoption of information and communication
technology: impact of technology types, organization resources and management style.
Industrial Management & Data Systems, 107(9), 1257--1275.
Yeh-Yun Lin, C. a.-C. (2007). Does innovation lead to performance? An empirical study of
SMEs in Taiwan. Management Research News, 30(2), 115--132.
Youndt, M. A., Snell, S. A., Dean, J. W., & Lepak, D. P. (1996). Human resource management,
manufacturing strategy, and firm performance. Academy of management Journal, 39(4),
836-866.
Zhu, K., & Kraemer, K. L. (2005). Post-adoption variations in usage and value of e-business
by organizations: cross-country evidence from the retail industry. Information systems
research, 16(1), 61-84.
Zmud, R. W. (1982). Diffusion of modern software practices: influence of centralization and
formalization. Management science, 28(12), 1421-1431.
131
APPENDIXES
132
A- Questionnaire
Dear Sir / Madam:
I am a Ph.D. Scholar at Faculty of Management Sciences, Riphah International University (RIU) Islamabad. I am conducting research on the topic of “FACTORS AFFECTING EXTENT OF HUMAN RESOURCE INFORMATION SYSTEM (HRIS) ADOPTION AND ITS IMPACT ON ORGANIZATION PERFORMANCE MODERATED BY HR STAFF EXPERTISE”. Data collected will only be used for research purpose. Your responses will be kept confidential and will not be used for any other purpose. Your participation is valuable for the completion of this research. Thank you for helping me in my research. If you would like to have findings of this research, please provide your email at the end of this questionnaire.
Nasim Qaisar
03335165656
Please answer the following questions with respect to yourself. Please Tick the relevant box.
Gender: Male Female
Education:
Bachelor Masters MS/ M.Phil Ph.D.
Age:
Less than 25 25-34 35-44
45-54 55-64 65 or more
Designation:
Deputy Manager / Director
Manager / Director Senior Manager / Director
Other
Experience in current designation:
Less than 1 year 1 to 3 years 4 to 7 years 8 years or more
Experience in current organization:
Less than 3 years
3 to 6 years 7 to 10 years 11 to 14 years More than 14 years
Total professional experience:
Less than 5 years
5 to 9 years 10 to 14 years 15 to 20 years 21 years or more
133
Answer the following question with respect to your organization and its HR department.
What is nature of your organization:
Architecture/Engineering
Banking & Finance
Computers / IT
Education
Health / Hospital
Manufacturing
Services
Trading
Travel / Hotel
Others_____ ____
Since how long your organization is in business:
Less than 3 years
4 to 6 years
7 to 9 years
10 to 12 years
13 to15 years
More than 15 years
How many employees are working in HR department of your organization?
1 to 3 4 to 6 7 to 9 10 to 12 13 to15 More than 15
How many computers / laptops are available in your HR department:
0 1 to 3 4 to 6 7 to 9 10 to 12 More than 12
Since how long HRIS is being used in your organization:
Less than 1 year
1 to 3 years
4 to 6 years
7 to 9 years
10 to 12 years
More than 12 years
Answer the following statements by keeping your organization and Human Resource Information System (HRIS) in your mind.
Strongly disagree
Somewhat disagree
Neither agree nor disagree
Somewhat agree
Strongly agree
1 2 3 4 5
HRIS enables human resource personnel to accomplish tasks more quickly.
1 2 3 4 5
HRIS improves the quality of the work of human resource personnel
1 2 3 4 5
HRIS makes it easier for human resource personnel to do their work
1 2 3 4 5
HRIS enhanced the job effectiveness of human resource personnel
1 2 3 4 5
HRIS provides timely information for decision making
1 2 3 4 5
HRIS enables my organization to cut costs in operations
1 2 3 4 5
HRIS increased the profitability of my organization
1 2 3 4 5
134
The changes introduced by HRIS are compatible with existing operating practices
1 2 3 4 5
Adoption of HRIS is consistent with my organization’s values and beliefs
1 2 3 4 5
HRIS is compatible with my organization’s IT infrastructure
1 2 3 4 5
HRIS is compatible with my organization’s computerized data resources
1 2 3 4 5
I have seen what others do using their HRIS
1 2 3 4 5
It is easy for me to observe others using the HRIS
1 2 3 4 5
I can see many individuals using the HRIS
1 2 3 4 5
HRIS is complex to use
1 2 3 4 5
HRIS development is a complex process
1 2 3 4 5
HRIS is hard to learn
1 2 3 4 5
Integrating HRIS into our current work practices will be very difficult
1 2 3 4 5
I want to be able to use a HRIS on a trial basis long enough to see what it can do
1 2 3 4 5
I am able to satisfactorily try out various uses of HRIS
1 2 3 4 5
I have had opportunities to try out various HRIS applications
1 2 3 4 5
Before deciding whether to use any HRIS applications, I would want to be able to try them.
1 2 3 4 5
Top management enthusiastically supports the adoption of HRIS
1 2 3 4 5
Top management has allocated adequate resources for the adoption of HRIS
1 2 3 4 5
Top management is aware of the benefits of HRIS
1 2 3 4 5
Top management actively encourages human resource personnel to use HRIS in their daily tasks
1 2 3 4 5
Number of employees in the organization
Less than 50
50 to 99
100 to
199
200 to
499
500 to
999
1000 or
more
Annual revenue (PKR in million)
Less than
1
1 to 10
11 to
100
101 to
300
301 to 500
Don’t know
Strongly disagree
Somewhat disagree
Neither agree nor disagree
Somewhat agree
Strongly agree
1 2 3 4 5
It is a strategic necessity to use HRIS in the workplace
1 2 3 4 5
Competitors’ adoption of HRIS places pressure on my organization to adopt HRIS
1 2 3 4 5
135
My organization actively keeps track of new and innovative uses of technology by competitors
1 2 3 4 5
Answer the following statements with respect to the extent of HRIS adoption in organization.
Not at
all A small extent
Some extent
A moderate extent
A great extent
1 2 3 4 5
In my organization HRIS is used to aid top management
1 2 3 4 5
In my organization HRIS is used to making long term HR planning
1 2 3 4 5
In my organization HRIS is used to enhance worker’s skills and ability
1 2 3 4 5
In my organization HRIS is used to enhance quality of work life
1 2 3 4 5
In my organization HRIS is used for inter organizational communication
1 2 3 4 5
In my organization HRIS is used for change management
1 2 3 4 5
In my organization HRIS is used to manage organizational information
1 2 3 4 5
In my organization HRIS is used to ensure governmental compliance
1 2 3 4 5
In my organization HRIS is used for gathering HR needs
1 2 3 4 5
In my organization HRIS is used for identifying HR needs
1 2 3 4 5
In my organization HRIS is used to develop knowledge
1 2 3 4 5
In my organization HRIS is used to store HR practices
1 2 3 4 5
In my organization HRIS is used to forecast long term HR needs
1 2 3 4 5
Answer the following statements with respect to HR staff expertise.
Strongly
disagree Somewhat disagree
Neither agree nor disagree
Somewhat agree
Strongly agree
1 2 3 4 5
All human resources personnel are computer-literate and have expertise of HRIS
1 2 3 4 5
There is at least one computer expert in the human resources department that can use HRIS
1 2 3 4 5
Human resources personnels’ understanding of computers is good as compare to other organizations in the industry
1 2 3 4 5
Answer the following statements with respect to organization’s performance by using HRIS.
As compare to key competitors, our organization is more successful.
1 2 3 4 5
As compare to key competitors, our organization has a greater market share.
1 2 3 4 5
136
As compare to key competitors, our organization is growing faster.
1 2 3 4 5
As compare to key competitors, our organization is more profitable.
1 2 3 4 5
As compare to key competitors, our organization is more innovative.
1 2 3 4 5
Email(Optional) _______ _______________________________________________________ to get findings of this research work.
Thank You very much for your valuable input.
137
B- Coding Sheet
Code Variable 1 2 3 4 5 6
PDG1 Gender: Male Female
PDE2 Education: Bachelor Masters MS/ M.Phil Ph.D.
PDA3 Age: Less than 25 25-34 35-44 45-54 55-64 65 +
PDD4 Designation: Deputy Manager / Director
Manager / Director
Senior Manager / Director
others
PDECD5 Experience in current designation: Less than 1 year
1 to 3 years 4 to 7 years 8 years or more
PDECO6 Experience in current organization: Less than 3 years
3 to 6 years 7 to 10 years 11 to 14 years more than 14 years
PDTE7 Total professional experience: Less than 5 Years
5 to 9 years 10 to 14 years 15 to 20 years 21 years or more
ODOI1 What is nature of your organization: Architecture/Engineering
Banking & Finance
Computers / IT Education Health / Hospital
Manufacturing
Services Trading Travel / Hotel Others_______
ODYIB2 Since how long your organization is in business: Less than 3 years
4 to 6 years 7 to 9 years 10 to 12 years 13 to15 years more than 15 years
ODEHRD3 How many employees are working in HR
department of your organization?
1 to 3 4 to 6 7 to 9 10 to 12 13 to15 more than 15
ODCHRD4 How many computers / laptops are available in
your HR department:
0 1 to 3 4 to 6 7 to 9 10 to 12 more than 12
ODAHRIS5 Since how long HRIS is being used in your
organization:
Less than 1 year
1 to 3 years 4 to 6 years 7 to 9 years 10 to 12 years more than 12 years
Strongly disagree
Somewhat disagree
Neither agree nor disagree
Somewhat agree
Strongly agree
IC 1 HRIS enables human resource personnel to accomplish tasks more quickly.
1 2 3 4 5
138
IC 2 HRIS improves the quality of the work of human resource personnel
1 2 3 4 5
IC 3 HRIS makes it easier for human resource personnel to do their work
1 2 3 4 5
IC 4 HRIS enhanced the job effectiveness of human resource personnel
1 2 3 4 5
IC 5 HRIS provides timely information for decision making
1 2 3 4 5
IC 6 HRIS enables my organization to cut costs in operations
1 2 3 4 5
IC 7 HRIS increased the profitability of my organization
1 2 3 4 5
IC 8 The changes introduced by HRIS are compatible with existing operating practices
1 2 3 4 5
IC 9 Adoption of HRIS is consistent with my organization’s values and beliefs
1 2 3 4 5
IC 10 HRIS is compatible with my organization’s IT infrastructure
1 2 3 4 5
IC 11 HRIS is compatible with my organization’s computerized data resources
1 2 3 4 5
IC 12 I have seen what others do using their HRIS 1 2 3 4 5
IC 13 It is easy for me to observe others using the HRIS 1 2 3 4 5
IC 14 I can see many individuals using the HRIS 1 2 3 4 5
IC 15 HRIS is complex to use 1 2 3 4 5
IC 16 HRIS development is a complex process 1 2 3 4 5
IC 17 HRIS is hard to learn 1 2 3 4 5
IC 18 Integrating HRIS into our current work practices will be very difficult
1 2 3 4 5
IC 19 I want to be able to use a HRIS on a trial basis long enough to see what it can do
1 2 3 4 5
IC 20 I am able to satisfactorily try out various uses of HRIS
1 2 3 4 5
IC 21 I have had opportunities to try out various HRIS applications
1 2 3 4 5
139
IC 22 Before deciding whether to use any HRIS applications, I would want to be able to try them.
1 2 3 4 5
OCTMS1
Top management enthusiastically supports the adoption of HRIS
1 2 3 4 5
OCTMS2
Top management has allocated adequate resources for the adoption of HRIS
1 2 3 4 5
OCTMS3
Top management is aware of the benefits of HRIS 1 2 3 4 5
OCTMS4
Top management actively encourages human resource personnel to use HRIS in their daily tasks
1 2 3 4 5
OCNOE1
Number of employees in the organization Less than 50 50 to 99 100 to 199 200 to 499 500 to 999 1000 or more
OCAR1 Annual revenue (PKR in million) Less than 1 1 to 10 11 to 100 101 – 300 301 to 500 Don’t know
Strongly disagree
Somewhat disagree
Neither agree nor disagree
Somewhat agree
Strongly agree
ECC1 It is a strategic necessity to use HRIS in the workplace
1 2 3 4 5
ECC2 Competitors’ adoption of HRIS places pressure on our organization to adopt HRIS
1 2 3 4 5
ECC3 Our organization actively keeps track of new and innovative uses of technology by competitors
1 2 3 4 5
Not at all A small extent
Some extent A moderate extent
A great extent
EXT1 In my organization HRIS is used to aid top management
1 2 3 4 5
EXT2 In my organization HRIS is used to making long term HR planning
1 2 3 4 5
EXT3 In my organization HRIS is used to enhance worker’s skills and ability
1 2 3 4 5
EXT4 In my organization HRIS is used to enhance quality of work life
1 2 3 4 5
EXT5 In my organization HRIS is used for inter organizational communication
1 2 3 4 5
EXT6 In my organization HRIS is used for change management
1 2 3 4 5
EXT7 In my organization HRIS is used to manage organizational information
1 2 3 4 5
EXT8 In my organization HRIS is used to ensure governmental compliance
1 2 3 4 5
140
EXT9 In my organization HRIS is used for gathering HR needs
1 2 3 4 5
EXT10 In my organization HRIS is used for identifying HR needs
1 2 3 4 5
EXT11 In my organization HRIS is used to develop knowledge
1 2 3 4 5
EXT12 In my organization HRIS is used to store HR practices
1 2 3 4 5
EXT13 In my organization HRIS is used to forecast long term HR needs
1 2 3 4 5
Strongly disagree
Somewhat disagree
Neither agree nor disagree
Somewhat agree
Strongly agree
HRSE1 All human resources personnel are computer-literate and have expertise of HRIS
1 2 3 4 5
HRSE2 There is at least one computer expert in the human resources department that can use HRIS
1 2 3 4 5
HRSE3 Human resources personnels’ understanding of computers is good as compare to other organizations in the industry
1 2 3 4 5
OP1 As compare to key competitors, our organization is more successful.
1 2 3 4 5
OP2 As compare to key competitors, our organization has a greater market share.
1 2 3 4 5
OP3 As compare to key competitors, our organization is growing faster.
1 2 3 4 5
OP4 As compare to key competitors, our organization is more profitable.
1 2 3 4 5
OP5 As compare to key competitors, our organization is more innovative.
1 2 3 4 5
