PROMOTING UNCOMMON KNOWLEDGE USE WITHIN IS

DEPARTMENT: HUMAN RESOURCE MANAGEMENT

PERSPECTIVE

Shih-Yu Wang, Department of Information Management, National Sun Yat-Sen University,

Kaohsiung, Taiwan, R.O.C., d014020006@student.nsysu.edu.tw

Jack Shih-Chieh Hsu, Department of Information Management, National Sun Yat-Sen

University, Kaohsiung, Taiwan, R.O.C., jackshsu@mis.nsysu.edu.tw

Tung-Chin Lin, Department of Information Management, National Sun Yat-Sen University,

Kaohsiung, Taiwan, R.O.C., tclin@mis.nsysu.edu.tw

Yu-Wen Hung, Department of Information Management, National Sun Yat-Sen University,

Kaohsiung, Taiwan, R.O.C., d004020004@student.nsysu.edu.tw

Abstract

Employing new IT to react to external changes and developing IS effectively and efficiently are

critical for IS department in contemporary business environment. In order to solve wicked problems

that are never faced before, IS department needs to use knowledge uncommonly through twisting

current knowledge slightly or analogizing from other areas. In addition to understand its impact on

performance, this study also explores the antecedents of uncommon knowledge use from a human

resource management perspective. Specifically, we hypothesize that uncertainty avoidance culture,

communication, shared decision making, team style work design, and human resource policies are

critical antecedents of knowledge augmentation and adaptation, which in turns lead to better IS

performance. The results show that while knowledge adaptation can be enhanced by uncertainty

avoidance culture and communication, knowledge augmentation is a function of shared decision-

making, use of team, and innovation-based policies. The results serve as guidance for managers to

choose needed HRM practices to boost desired uncommon knowledge use style.

Keywords: Uncommon knowledge use, Human resource management practices, Information system

department.

1 INTRODUCTION

Nowadays technology and business environment changes rapidly. Organizations have to change their

business strategies, process, and structure frequently so that they can effectively use knowledge and

utilize decision-making strategies to cope with the changing environment (Jones & Mahon 2012).

External changes in the business context often lead to changes in user requirements of the information

system that developed by information system (IS) department (Lee & Xia 2005). Therefore, the IS

department has to have sufficient capability to respond to changing needs and help firms to achieve

their goals. For example, IS department should be able to employ new information technology (IT) to

react to external changes and develop IS effectively and efficiently. Given that IS development is a

knowledge intensive process, the final performance of ISD is a function of effective knowledge

management (Joshi et al. 2007; Ko et al. 2005; Patnayakuni et al. 2007; Pee et al. 2010).

Indeed, previous knowledge management studies have demonstrated that performance is related to the

extent to which organization can create, acquire, and apply knowledge effectively (Chang Lee et al.

2005; Choo 1996; Gold et al. 2001; Janz & Prasarnphanich 2003; Lee & Choi 2003). Early literatures

in knowledge management area emphasize the importance to store knowledge effectively and be able

to retrieve it when needed. However, under a turbulent environment, being able to retrieve and apply

existing knowledge may not be sufficient. Solutions generated through simply applying accumulated

experiences in the same way may not be sufficient to solve problems never facing before. Researchers

suggest that organizations need to acquire new knowledge from external (Cohen & Levinthal 1990;

Matusik & Hill 1998; Tsai 2001). The following studies therefore shift their focus to clarify the role

of knowledge acquisition, such as absorptive capacity (Jansen et al. 2005; Lichtenthaler 2009; Zahra

& George 2002). However, simply applying existing knowledge, accumulated within organization or

acquired from external, is not sufficient for organizations in such a turbulent environment. Recently,

researchers further highlight the need to utilize existing knowledge uncommonly, through twisting

current knowledge slightly or analogizing from other areas, in order to solve wicked problems to gain

advantage. Nag and Gioia (2012) classify the way to adopt uncommon knowledge use into two types:

knowledge adaption and knowledge augmentation. While the former refers to applying knowledge to

modify and improve specific operational activities the later is defined as criticizing what are known so

as to generate new understandings on problem solving.

Nag and Gioria (2012), through case studies, demonstrate the critical role of uncommon knowledge

use under a turbulent environment. Analogizing the same concept to IS area, IS department may also

need to use knowledge uncommonly to improve the development process and to create innovative

information systems. However, a lack of systematic analysis leaves this question unanswered.

Therefore, the first purpose of this study is to understand the impact of uncommon knowledge use on

the outcomes of IS department. Furthermore, if using knowledge uncommonly does allow IS

department to perform better, we are also interested in knowing the ways to encourage members to

use knowledge uncommonly within IS department. The drivers of behavior include motivation or

capability (Vroom 1964). Human Resource Management (HRM) practices are frequently adopted to

motivate or provide employees sufficient capability (Bowen & Ostroff 2004). For example, HRM

practices can foster innovation and improve firm’s ability to sustain competitive advantage

(Beugelsdijk 2008; Gupta & Singhal 1993). However, even though past studies have demonstrated the

relationship between HRM practices and outcome variables, how effectively HRM practices can lead

to better outcomes (such as innovation) in such a turbulent environment is not clear. We suspect that

HRM practices may motivate or provide employees capability to use knowledge uncommonly.

Therefore, the second purpose of this study is to understand what HRM practices can enhance the

performance of IS department, through promoting uncommon knowledge use within the department.

Through achieving the above purposes, this study contributes to knowledge management literature by

highlighting the importance of uncommon knowledge use and illustrating ways to enhance it.

Furthermore we also contribute to HRM literatures by showing how effective HRM practices can

enhance unit performance indirectly through promoting uncommon knowledge use.

This paper is organized as follows. In the next section, we introduce uncommon knowledge use and

the role of HRM practice to two modes of uncommon knowledge use. In the third section, we describe

the method used to collect data and examine the proposed model. The fourth section presents the

analysis results. Last, conclusion and implication are provided.

2 LITERATURE REVIEW

2.1 Effectiveness of IS department

Contemporary business environment requires effective IS department to be innovative while

maintaining sufficient performance. One the one hand, the dramatic change of information technology

and economic make being innovative as a critical factor for organizations to success in the

competitive environment (Cardozo et al. 1993; Frambach & Schillewaert 2002). IS department often

need to introduce new technology quickly to accommodate the turbulent environment. Since

organizations often need to employ new technologies to empower their business function and increase

their competitive capability (Dewett & Jones 2001; Sambamurthy et al. 2003), being innovative

therefore refers to implementing new IT, adopting new methodology, or developing new IS to enable

new product or service or improve business operation.

On the other hand, the performance of IS department is defined as the extent to which IS department

can plan, develop, and operate information system effectively and efficiently. IS department is

responsible for developing or implementing information system to support organization operation, e.g.

to provide useful information that can solve organization’s business problem and improve the

efficiency and effectiveness of decision-making. However, the variation in the business context often

leads to changes in user requirements of the information system that is developed or implemented by

IS department. High failure rate of IS/IT projects is one significant issue in IS area and enhancing IS

department’s performance is therefore cannot be neglected.

2.2 From Common to Uncommon Knowledge Use

Insufficient knowledge has been identified as one critical problem in information system (IS)

development (Sakthivel 2007). IS department performance suffers when needed capability cannot be

constructed because of lacking sufficient knowledge resources (Nelson & Cooprider 1996).

Effectively acquiring, storing, and retrieving knowledge has been emphasized by knowledge

management literatures (Alavi & Leidner 2001; Nemati et al. 2002). Recent studies further highlight

the need to acquire needed knowledge from external (Cohen & Levinthal 1990; Matusik & Hill 1998;

Tsai 2001). However, Nag and Gioia (2012) pointed out that many firms feel no interest in generate

novel knowledge generally, but only focus on following what they used to do in the past and

maintaining the status quo. For example, firms prefer to continue with current approach even though

there are other more efficient ways to do things. Those firms value knowledge mainly for maintaining

responsiveness to current customers. Nag and Gioia referred this situation as common knowledge use.

According to Nag and Gioia (2012), strategic leaders have to transform common knowledge into

uncommon knowledge to create distinctive capabilities and sustain competitive advantage. They

further proposed two modes of uncommon knowledge use: knowledge augmentation and knowledge

adaptation. Knowledge adaptation emphasizes on utilize existing knowledge to figure out new

solution to modify or improve the process of specific operational activities. Knowledge augmentation

encourages employees to question existing knowledge to generate new understanding for future

activities. The process of information system development is knowledge intensive and it is critical to

acquire knowledgeable IS developers for effective system development and implementation (Tesch et

al. 2009). In addition, there is no two identical projects within IS department. Members need to

generate effective solutions for various problems. Since many problems are unique, IS department

therefore need to use knowledge uncommonly to improve the development process and to create

innovative information systems. However, limited efforts in IS area have been entered to understand

the role of uncommon knowledge use. The goal of this study is therefore to introduce two types of

uncommon knowledge use and explore their impact on the outcomes of IS department.

2.3 Human Resource Management Practices

The importance of employing effective HRM practices has long been emphasized in organization

studies. For example, many studies investigate the relationship between HRM practices and firm

performance (e.g. Becker & Huselid 2006; Boselie et al. 2005; Collins & Clark 2003; Evans & Davis

2005) or innovative outcome (e.g. Beugelsdijk 2008; Chen & Huang 2009; Oke et al. 2012). Some

scholars also explore the impact of HR practices on knowledge sharing (e.g. Cabrera & Cabrera 2005;

Collins & Smith 2006). While few studies attempt to explore the link between HRM practices and

performance or innovative outcome (Laursen & Foss 2003), limited effort has been entered to

understand what transfers the effect of HRM to outcome variables. Wright et al. (2001) suggested that

people management practices impact the knowledge creation, transfer, and integration of firms. We

believe that effective HRM practices can improve the performance of IS department through

promoting uncommon knowledge use. Managers can use effective HRM practices to create an

environment that encourage members to use knowledge uncommonly. In this study, we introduce

common HRM practices, including uncertainty avoidance culture, communication, shared decision-

making, work design (e.g. use of team), and innovation-based policies as the factors impacting

uncommon knowledge use.

Given the importance of being innovative and having high performance, this study addresses these

issues from a knowledge perspective. Specifically, we propose that different modes of uncommon

knowledge use can help IS department to utilize their expertise creating more effective performance

and innovative solutions. The research model is shown in Figure 1.

Figure 1. Research Model

HRM Practices Uncommon

Knowledge Use

IS Department

Effectiveness

Innovation-based

Policy

Communication

Shared DM

Work Design

(Use of Team)

Uncertainty

avoidance

Adaptation

Augmentation

Performance

Innovation

3 HYPOTHESIS DEVELOPMENT

3.1 From Uncommon Knowledge Use to Outcome

3.1.1 Knowledge Adaptation

Knowledge adaptation is a way to use knowledge which can be described as an ability to apply

knowledge to modify and improve specific operational activities (Nag & Gioia 2012). Knowledge

adaptation emphasizes “tweaking” knowledge already known to create novel solutions to specific

problems but not innovation. According to literature, with accumulated knowledge, an IS department

can draw from its experiences to quickly figure out what need to do to match organization’s objective

as firm’s strategy changing. However, performance remains the same if only applying the same

solution on the same problems. Therefore, Nag and Gioia proposed that, strategic leaders should focus

on how to tweak existing knowledge so as to improve operational efficiency. This implies that, by

keeping tweaking existing knowledge (knowledge adaptation), IS department continuously refines its

existing resources and processes of daily work. As an outcome, better performance can be expected.

Thus, we hypothesized:

H1: Knowledge adaptation has a positive impact on performance.

3.1.2 Knowledge Augmentation

Different from knowledge adaptation focuses on solving the same problem with slightly tweaked

knowledge, knowledge augmentation style uncommon knowledge use encourages members of a firm

to reflect upon, criticize, questioning what they have known, and generate new understandings to

solve problems (Nag & Gioia 2012). Knowledge augmentation style uncommon knowledge use

doesn’t focus on a particular problem but analyse problems to figure out how these solutions apply to

other problems. It emphasizes on using existing expertise and skills of the firm to develop new

understandings and principles for future action to benefit the firm’s competitiveness. Based on these

experience, the members of IS department can quickly apply the solution to similar situation. Then,

they can solve problem more effectively and efficiently during the development or implementation.

Therefore, we proposed:

H2a: Knowledge augmentation has a positive impact on performance.

For example, managers who choose knowledge augmentation as their strategy for developing

uncommon knowledge believe that new technological knowledge enabled them to find new insights

and develop a richer understanding of customer needs. In a rapidly changing environment, IS

department has to respond to the changing business strategy and user requirements effectively. While

some problems are predictable, some problems are wicked and unpredictable at all. It is not likely for

IS department to only tweak existing knowledge slightly to solve those problem never faced before.

Instead, innovative approaches are needed. Members should challenge what have known and develop

unique insights. They can apply these ideas to other problems in the future and meet changing user

needs more easily. Since members are encouraged to challenge existing knowledge, they are more

likely to generate some novel insights during this process and also be more willing to adapt new

technologies or new ways to perform work. With effective knowledge augmentation, IS department

can then be able to improve the ability to support the organizational strategy. Therefore, we proposed:

H2b: Knowledge augmentation has a positive impact on innovation.

3.2 From Human Resource Management Practices to Uncommon Knowledge Use

3.2.1 Uncertainty avoidance culture

Members in a society with uncertainty avoidance culture prefer to work through rules, budgets, and

standard operating procedures (Shane et al. 1995). The company with high uncertainty avoidance

culture invest more time and effort on planning and designing their program (Javidan et al. 2005). In

our context, culture of department has significant impact on the intention to change. If an IS

department has clear norm and procedure for employees to follow, employees are constrained with

standard operational procedure to avoid risks. The members of IS department will focus on the

existing process, hence, we proposed:

H3a: Uncertainty avoidance culture is positively related to knowledge adaptation.

On the other hand, members are more willing to break the rules and norms to innovation in the society

with uncertainty accepting culture (Shane et al. 1995). Javidan et al. (2005) also indicated that the

company with low uncertainty avoidance culture is more willing to explore opportunities to adapt

quick changes and develop new ideas. In other words, employees in the IS department with

uncertainty avoidance culture are not allowed to question existing knowledge and unlikely to change

and innovate as well. Therefore, we proposed:

H3b: Uncertainty avoidance culture is negatively related to knowledge augmentation.

3.2.2 Communication

Smith and Rupp (2002) define communication as “human interaction through oral conversations and

the use of body language” and considered that communication is fundamental in encouraging

knowledge transfer. Communication can be classified into two types: formal and informal

communication. Formal communication refers to communication that flows through written modes,

like official meetings, manuals and procedure and rule books. On the other hand, informal

communication is based on social relationship among employees. Employees can share work-relevant

information and create collaboration opportunities outside the formal channels (Mohr & Nevin 1990;

Smith et al. 1994). In this study, we primarily focus on informal communication among IS department

members. Informal communication can facilitate the knowledge flows among members (Smith et al.

1994). Frequent informal communication between department members enables members to learn

from others and exchange ideas and information with each other. Moreover, informal communication

can facilitate the collaborative work between members and further figure out more effective solution.

Therefore we proposed:

H4a: Communication is positively related to knowledge adaptation.

Through the process of communication, the members of the IS department can build a sharing belief

and express new ideas to increase the quality of knowledge creation (Henderson et al. 1997;

Patnayakuni et al. 2007). Senge (1997) also proposed that organizational knowledge is created

through communication of individual learning among co-workers. The communication among

members can arouse them to find the problem of process and generate new ideas. Therefore, we

proposed:

H4b: Communication is positively related to knowledge augmentation.

3.2.3 Shared-decision making

Shared decision making refers to “seeking team members’ input in decision making” (Patnayakuni et

al. 2007). Shared decision making has effect on uncommon knowledge use for the following two

reasons. First, previous studies have indicated that employees are more like to accept the decision if

they are involved in the decision making process. Employees feel that they are recognized by the

organization when involving in decision making. Employees also sense more responsibilities toward

the outcomes if they are included in the decision making process (Driscoll 1978). By viewing

themselves as critical members in the department, employees are more willing to spend efforts and,

more importantly, adjust themselves to reach a better outcome. So they may pay more attention on

how to improve operational efficiency. Therefore, we proposed:

H5a: Shared-decision making is positively related to knowledge adaptation.

Second, in the process of shared-decision making, members have to collect various perspectives in

order to make more comprehensive decision and get better performance. This action would encourage

members to understand others’ expertise and share their knowledge with each other (Patnayakuni et al.

2007). Thus, empowering the members of department to make decision increase opportunities and

need of knowledge sharing to solve problems (Srivastava et al. 2006). They need to expand their

knowledge and acquire new skills. Knowledge creation and innovation are more likely to result if

team members are allowed to make decision, solve problem, and identify opportunities by themselves

(Bligh et al. 2006). Therefore we proposed:

H5b: Shared-decision making is positively related to knowledge augmentation.

3.2.4 Teamwork Design

Teamwork design refers to use teams for performing activities of information system development

(Patnayakuni et al. 2007). Using team as work design provides members of department opportunities

to work closely with others. Teamwork is a process to integrate individual knowledge into collective

knowledge and realize the value of integrated knowledge (Okhuysen & Eisenhardt 2002). An

information system team usually includes members from different department or expertise, such as

users, programmers, and project managers. Since each member has different background, they have

their own opinion and viewpoint to understand the existing process. They may find different problems

that should be solved based on their unique background. Therefore, we proposed:

H6a: Teamwork design is positively related to knowledge adaptation.

The use of teams can not only bring better use of local knowledge, but also be positively related to

innovation performance (Laursen & Foss 2003). Integrating individual’s perspectives and unique

skills of team members into collective knowledge of team can contribute to team creativity – using

different ways to develop information systems (Tiwana & Mclean 2005). So the use of team can

integrate knowledge of team members to create more value and innovation. Thus, we hypothesized:

H6b: Teamwork design is positively related to knowledge augmentation.

3.2.5 Innovation-based Policies

Empirical studies have shown that including “being innovative” as a requirement in recruitment,

compensation, and promotion of employees are important to promote innovations in firms (Atuahene‐Gima 1996; Khazanchi et al. 2007). In this study, we move further and argue that innovation-based

policies, such as hiring creative employees and rewarding innovative initiates, are expected to have

positive impacts on uncommon knowledge. The policies allow organization to successfully hire

employees who have required expertise to solve difficult problems and find novel ideas (Amabile

1998; Seijts & Latham 2005). Therefore, we proposed:

H7a: Innovation-based Policies is positively related to knowledge adaptation.

Rewarding and recognizing being innovative encourage employees to generate new ideas, break rules

(Khazanchi et al. 2007), and also motivate employees’ willingness to achieve innovative outcomes

(Seijts & Latham 2005). The innovation-based HR policies are also likely to facilitate an innovative

organizational culture (Oke et al. 2012). Specific policies foster the climate, such as psychological

safety, that drives employees to learn and be innovative (Edmondson 1999). Individuals are more

willing to challenge existing process and try out new ideas. Therefore, we proposed:

H7b: Innovation-based Policies is positively related to knowledge augmentation.

4 RESEARCH METHOD

4.1 Data Collection

We conducted a survey to examine the proposed hypotheses. The target sample of this study is the

manager of IS department. The data were collected from the members of the Information

Management Association (IMA) in Taiwan. IMA is an association aims to improving IT usage and

enhancing communication among IS professionals. Members of this organization are either IS seniors

or IS manager. First, we contacted members of the IMA to introduce the purpose of this study and

obtain their willingness to participate. A total of 750 survey packages were then sent to managers who

agree to participate. We received 133 survey packages, yielding a valid response rate of 17.73%.

Table 1 provides the detailed information.

Variables Categories # % Variables Categories # %

Industry type Information

Technology

47 35.3 # of company

employee

<30 15 11.3

Financial 2 1.5 30-50 7 5.3

Manufacturing 39 29.3 50-100 11 8.3

Service 8 6.0 100-500 26 19.5

Medical 13 9.8 500-1000 15 11.3

Hospitality 1 0.8 1000-5000 26 19.5

Retailing 1 0.8 >5000 33 24.8

Government 10 7.5 # of IS employee <5 21 15.8

School 9 6.8 5-10 18 13.5

Others 3 2.3 10-15 15 11.3

Position Senior member 62 46.6 15-20 14 10.5

Manager 20 15 20-50 14 10.5

Senior manager 12 9 50-100 12 9

Administrator 38 28.6 >100 39 29.3

Others 1 0.8

Table 1. Sample demographics (N=133)

4.2 Constructs and Measurement

All constructs of our research model were measured using multiple items. Most of measurement items

were adapted from past studies. Due to the research of Nag and Gioia (2012) was conducted by

interview, the measurement items of adaptation and augmentation were developed by the authors. The

questionnaire adopted Likert scales ranging from 1 (strongly disagree) to 7 (strongly agree). The

definitions of the constructs are shown in Table 2.

Construct Definition Source of items

Performance of IS

department

the efficiency of IS department to develop and

implement information system

Adapted from DeLone and

McLean (1992);

Ravichandran and

Lertwongsatien (2005)

Innovation the extent to innovation activities of IS

department

Song et al. (2006)

Knowledge adaptation the mode of uncommon knowledge use that

focuses on applying knowledge to modify and

improve specific operational activities

Developed by authors

Knowledge augmentation the mode of uncommon knowledge use that

represents an orientation toward using existing

expertise and skills to reflecting upon, critiquing,

and questioning for problem solving and

generating new insights

Developed by authors

Uncertainty avoidance the extent that the members of a culture feel

threatened by uncertain or unknown situations

Hwang (2005)

and try to avoid them

Communication the extent of informal interaction among members

of IS department

Patnayakuni et al. (2007)

Shared decision-making sharing of decision-making authority among IS

employee

Patnayakuni et al. (2007)

Work design use of teams for ISD activities Patnayakuni et al. (2007)

Innovation-based policy the extent to which a firm adopts people-focused

policies including recruitment and selection, and

reward systems that foster the development of

innovation

Oke et al. (2012)

Table 2. Construct definition and source of items

4.3 Common Method Variance

Common method variance (CMV) might be a concern in this study, because both independent and

dependent variables are collected simultaneously from the same respondent. We implemented the

Harman’s single factor to ensure there was no significant method effect on the predefined causal

relationship. The result shows that the first factor explains 16.52% of variance through the exploratory

factor analysis process. Besides, we followed Liang et al. (2007) to test the impact of common method

variance in the PLS model. There are 33 indicators and only 6 method factor loadings are significant.

The summation of substantively explained variance of the indicators is 25.1, while the average

method based variance is 0.46. The ratio of substantive variance to method variance is approximately

54:1. Therefore, CMV is unlikely to be a problem in this study.

4.4 Reliability and Validity

We used PLS (Partial Least Squares) to evaluate the item reliability, convergent validity, and

discriminant validity of measurement model. The reliability was ensured through composite reliability,

Cronbach’s alpha and factor loading. Convergent validity should be examined by item-to-total

correlation (ITC), composite reliability, and average variance extracted (AVE) by constructs (Fornell

& Larcker, 1981). For discriminant validity, the correlation between construct pairs should be lower

than 0.90 and the square root of AVE should be higher than the inter-construct correlation coefficients

(Fornell & Larcker 1981). All validity requirements are met, as shown in Tables 3 and 4. Table 4

shows the descriptive statistics.

Constructs Items Loadings ITC Uncertainty

avoidance

culture

Alpha: 0.91 ;

AVE:0.84 ;

CR:0.94

It is important to have job requirements and instructions spelled

out in detail so that employees always know what they are

expected to do.

0.930 0.828

Rules and regulations are important because they inform

employees what the organization expects of them.

0.910 0.807

Standard operating procedures are helpful to employees on the

job.

0.912 0.802

Communication

Alpha: 0.85 ;

AVE:0.76 ;

CR:0.91

There is extensive informal communication among IS employees

at the same level.

0.865 0.675

There is extensive informal communication among IS employees

at different level.

0.908 0.773

There is extensive informal communication between IS

employees and employees in other departments.

0.848 0.691

Shared decision

making

Alpha: 0.87 ;

AVE:0.80 ;

CR:0.92

Participative decision-making is broadly used in these

development projects.

0.916 0.769

Decision-making authority rests with managers as opposed to

development staff. (R)

0.878 0.744

Joint-decision making by managers and analysts/programmers is

the norm in our ISD.

0.884 0.758

Work design - All projects are managed by autonomous teams. 0.832 0.594

team

Alpha: 0.78 ;

AVE:0.69 ;

CR:0.87

System development is team based. 0.873 0.678

Project team performance is evaluated rather than individual

performance.

0.794 0.576

Innovation-

based Policies

Alpha: 0.94 ;

AVE:0.80 ;

CR:0.95

Our human resource policies support a culture of innovation. 0.870 0.784

The rewards and recognition systems encourage innovation. 0.877 0.811

Innovation is a key criterion in our recruitment and selection

process.

0.939 0.899

Innovation forms part of our training and development programs. 0.907 0.851

Clear innovation targets are set for all employees. 0.868 0.801

Knowledge

augmentation

Alpha: 0.84 ;

AVE:0.76 ;

CR:0.91

We encourage everyone to question what they think they know,

to generate new understanding.

0.897 0.680

We analyze problems to figure out how solutions apply to other

problems.

0.875 0.756

We use new technical knowledge to find unique insights. 0.844 0.690

Knowledge

adaptation

Alpha: 0.78 ;

AVE:0.61 ;

CR:0.86

We capable of refining and extending our existing knowledge

and technologies to enhance the efficiency of firm.

0.743 0.476

We usually change the operation processes (development,

implementation, maintenance process) we use slightly to gain

better performance.

0.870 0.694

We regularly recombine and integrate existing technologies in

new products or services process.

0.798 0.639

Our innovation comes through small steps rather than giant

leaps.

0.691 0.542

Performance

Alpha: 0.92 ;

AVE:0.76 ;

CR:0.94

Information quality providing by our IT department has met our

firm’s objectives

0.865 0.772

The quality of information system developing or implementing

by our IT department has met our firm’s objectives.

0.883 0.816

The efficiency of developing or implementing information

system by our IT department has been successful.

0.876 0.806

The efficiency of introducing information system by our IT

department has been successful.

0.855 0.786

The efficiency of maintaining information system by our IT

department has been successful.

0.866 0.776

Innovation

Alpha: 0.89 ;

AVE:0.76 ;

CR:0.93

The overall performance of developing innovative information

system program has met our objectives.

0.819 0.703

From an overall profitability standpoint, implementing new

information system program has been successful.

0.888 0.779

We successfully use innovative method to plan and manage

information systems and launch novel development process.

0.855 0.748

We successfully use innovative information technology to

support business operations.

0.911 0.814

Note: ITC-Item-Total Correlation

Table 3. The results of factor analysis

Correlation matrix

Mean Std M3 M4 INN IBP SDM PE WD AD AUG COM UAC

INN 4.19 1.404 -0.291 -0.647 0.87

IBP 4.21 1.370 -0.282 -0.253 0.56 0.89

SDM 4.25 1.317 -0.308 -0.276 0.44 0.61 0.89

PE 4.62 1.013 -0.590 0.412 0.54 0.35 0.26 0.87

WD 4.83 1.250 -0.390 0.403 0.39 0.64 0.59 0.40 0.83

AD 5.13 0.988 -0.213 -0.273 0.34 0.40 0.43 0.53 0.45 0.78

AUG 4.34 1.224 -0.297 -0.049 0.63 0.65 0.57 0.42 0.57 0.53 0.87

COM 4.71 1.205 -0.128 -0.325 0.36 0.65 0.55 0.46 0.59 0.55 0.48 0.87

UAC 5.35 1.195 -0.634 0.607 0.24 0.43 0.40 0.37 0.54 0.59 0.36 0.57 0.92

Note: INN-innovation; IBP-Innovation-based Policies; SDM-Shared decision making; PE-Performance; WD-

Work design; AD-Adaptation; AUG-Augmentation; COM-Communication; CUL- Uncertainty avoidance

culture.

The boldfaced data on diagonal of the correlation matrix represent the squared root of AVE.

Table 3. Descriptive statics and correlation matrix

5 RESULTS

Test results are shown in Figure 2. The path coefficients from knowledge adaptation to department

performance and from knowledge augmentation to innovation are positively significant (β = 0.430, p

< 0.001; β = 0.630, p < 0.001; respectively). Therefore, H1 and H2a are supported. But knowledge

augmentation was partially related to department performance (β = 0.193, p < 0.1). Knowledge

adaptation and knowledge augmentation total explains a 31.3% variance of performance. Knowledge

augmentation explains a 39.7% variance of innovation. The path coefficients from uncertainty

avoidance culture and communication to knowledge adaptation are positively significant (β = 0.378, p

< 0.001; β = 0.268, p < 0.01; respectively), indicating that uncertainty avoidance culture and

communication contribute to knowledge adaptation. The path coefficient from shared decision

making to knowledge adaptation is partially significant (β = 0.135, p < 0.1, but from shared decision

making, work design, and innovation-based policy to knowledge adaptation are not significant (β =

0.036, p > 0.1; β = -0.046, p > 0.1; respectively). Thus, H3a and H4a are supported but H5a, H6a, and

H7a are not. The path coefficients from uncertainty avoidance culture and communication to

knowledge augmentation are not significant (β = 0.009, p < 0.1; β = -0.023, p > 0.1; respectively), but

from shared decision making, work design, and innovation-based policy are all positively significant

(β = 0.216, p < 0.05; β = 0.191, p < 0.05; β = 0.411, p < 0.001; respectively). Therefore, H5b, H6b,

H7b are all supported, but H3b and H4b are not. There five HR practices in total explain the 42.6%

and 49.2% variance of knowledge adaptation and knowledge augmentation respectively.

Figure 2. Results of hypotheses testing

Innovation-

based Policy

Communication

Shared DM

Work Design

(Use of Team)

Uncertainty

avoidance

Adaptation

R2=0.426

Augmentation

R2=0.492

Performance

R2=0.313

Innovation

R2=0.397

***: p < 0.001; **: p < 0.01; *: p < 0.05; +: p < 0.1

0.378***

0.268**

0.135+

0.216*

0.191*

0.411***

0.430***

0.193+

0.630***

-0.023

0.036

-0.046

0.009

6 DISCUSSION

The results show that (1) knowledge adaptation has a significant effect on department performance,

and knowledge augmentation is more important to innovation than department performance; (2)

uncertainty avoidance and communication can enhance knowledge adaptation, and shared decision

making, work design (use of team), and innovation-based policy are important to promote knowledge

augmentation.

First, two types of uncommon knowledge use have different impact on performance and innovation.

Knowledge augmentation is more important for innovation than for performance of the department.

The relationship from knowledge augmentation to performance is not significant. We suspect that

augmentation focuses on generating new understandings to solve problems for future actions. Hence

the effects of improving performance probably are not obvious immediately. Second, we found that

uncertainty avoidance and communication do not have effect on knowledge augmentation. For

uncertainty avoidance culture, although we argue that employees are less creative under this condition,

it is also reasonable that member may be able to apply one procedure to different problems after

having clearly understanding toward the detail parts. For communication, although members

communicate with each other and come out some creative ideas, but how to implement these ideas

might be another problem. It probably needs to break rules or make some changes. Third, work team

design and innovation-based policy were found to affect augmentation but have limited effects on

adaptation only. Team is a combination of individuals with diversified expertise. Information

exchange in problem analysis stage allows members to generate novel insight. However, many

activities in IS department are not in teamwork style, especially those routines works. Since

adaptation focuses on change the current way of doing things, it is then reasonable that teamwork

style has limited effect on adaptation. In addition, innovation-based policy leads to strong innovative

culture in which critical innovation is emphasized more than incremental innovation. Therefore,

augmentation is highlighted instead of adaptation.

6.1 Implications to Academia

Nag and Gioia (2012) proposed the concept of uncommon knowledge use and illustrate the idea with

several cases. This study introduces these two modes of uncommon knowledge use into the discipline

of project management and empirically validates its antecedents and consequences. In addition to

showing its effect on IS department outcomes, we also explore possible ways can be used to foster

uncommon knowledge use from the HRM perspective. We contribute to HRM literature by

introducing possible mediators that transfer the effect of HRM practices to innovation and

performance. While most of past studies investigated the relationship between HRM practices and

outcome variable, we further demonstrate that knowledge adaptation and knowledge augmentation

might be important mediators of HRM practices and performance or innovation.

6.2 Implications to Practitioners

According to the result of this study, knowledge adaptation is associated with performance positively

and knowledge augmentation leads to innovation. More important, this study identifies possible

antecedents from a HRM perspective. Based on our results, managers of IS department can choose

appropriate HRM practices to achieve the desired style of uncommon knowledge use. To promote

knowledge adaptation, managers should pay attention on fostering open department culture and

encourage communication between members. To boost augmentation, managers can empower

members to make decision, form teams to integrate different expertise to promote creative ideas of

members. In addition, managers should pay attention on member selection to select members with

innovative characteristic. They may provide adequate reward to promote uncommon knowledge use

or offer needed training to encourage members to think differently.

7 CONCLUSION

The objectives of our study are (1) examine the relationship of uncommon knowledge use between IS

performance and innovation and (2) explore the factors that are important to foster uncommon

knowledge use from the HRM perspective. Performance and innovation outcome represent the work

result of IS department. To achieve organization’s goal and meet user’s need, IS department have to

apply new method of knowledge use, which includes two modes of uncommon knowledge use. The

results indicate that uncertainty avoidance culture and communication have significant impact on

adopting knowledge adaptation; shared-decision making, work design (use of team), and innovation-

based policy impact the use of knowledge augmentation. Some limitations of this study should be

mentioned. First, the generalizability of the result might be limited because the sample pool of this

study is only in Taiwan. Thus, the future study may collect western-culture based data to verify the

generalizability of our results. Second, we validated our proposed model through cross-sectional data.

It is very likely that poor performance may reversely drive IS department to use knowledge

commonly in order to promote their performance. Finally, to maintain the parsimonious of our

research model, we explored the antecedents of uncommon knowledge use from an HRM practices

perspective only. We believe that exploring factors other than HRM practices allow us to know the

way to boost uncommon knowledge use, given its positive impact on IS performance.

References

Alavi, M., & Leidner, D. E. (2001). Review: Knowledge management and knowledge management

systems: Conceptual foundations and research issues. MIS Quarterly, 107-136.

Amabile, T. M. (1998). How to kill creativity: Harvard Business School Publishing.

Atuahene‐Gima, K. (1996). Differential potency of factors affecting innovation performance in

manufacturing and services firms in Australia. Journal of Product Innovation Management,

13(1), 35-52.

Becker, B. E., & Huselid, M. A. (2006). Strategic human resources management: where do we go

from here? Journal of management, 32(6), 898-925.

Beugelsdijk, S. (2008). Strategic human resource practices and product innovation. Organization

Studies, 29(6), 821-847.

Bligh, M. C., Pearce, C. L., & Kohles, J. C. (2006). The importance of self-and shared leadership in

team based knowledge work: A meso-level model of leadership dynamics. Journal of

Managerial Psychology, 21(4), 296-318.

Boselie, P., Dietz, G., & Boon, C. (2005). Commonalities and contradictions in HRM and

performance research. Human Resource Management Journal, 15(3), 67-94.

Bowen, D. E., & Ostroff, C. (2004). Understanding HRM–firm performance linkages: The role of the

“strength” of the HRM system. Academy of management review, 29(2), 203-221.

Cabrera, E. F., & Cabrera, A. (2005). Fostering knowledge sharing through people management

practices. The International Journal of Human Resource Management, 16(5), 720-735.

Cardozo, R., McLaughlin, K., Harmon, B., Reynolds, P., & Miller, B. (1993). Product-market choices

and growth of new businesses. Journal of Product Innovation Management, 10(4), 331-340.

Chang Lee, K., Lee, S., & Kang, I. W. (2005). KMPI: measuring knowledge management

performance. Information & Management, 42(3), 469-482.

Chen, C.-J., & Huang, J.-W. (2009). Strategic human resource practices and innovation

performance—The mediating role of knowledge management capacity. Journal of Business

Research, 62(1), 104-114.

Choo, C. W. (1996). The knowing organization: how organizations use information to construct

meaning, create knowledge and make decisions. International journal of information

management, 16(5), 329-340.

Cohen, W. M., & Levinthal, D. A. (1990). Absorptive capacity: a new perspective on learning and

innovation. Administrative science quarterly, 35(1), 128-152.

Collins, C. J., & Clark, K. D. (2003). Strategic human resource practices, top management team social

networks, and firm performance: The role of human resource practices in creating

organizational competitive advantage. Academy of management journal, 46(6), 740-751.

Collins, C. J., & Smith, K. G. (2006). Knowledge exchange and combination: The role of human

resource practices in the performance of high-technology firms. Academy of management

journal, 49(3), 544-560.

DeLone, W. H., & McLean, E. R. (1992). Information systems success: the quest for the dependent

variable. Information Systems Research, 3(1), 60-95.

Dewett, T., & Jones, G. R. (2001). The role of information technology in the organization: a review,

model, and assessment. Journal of management, 27(3), 313-346.

Driscoll, J. W. (1978). Trust and participation in organizational decision making as predictors of

satisfaction. Academy of management journal, 21(1), 44-56.

Edmondson, A. (1999). Psychological safety and learning behavior in work teams. Administrative

science quarterly, 44(2), 350-383.

Evans, W. R., & Davis, W. D. (2005). High-performance work systems and organizational

performance: The mediating role of internal social structure. Journal of management, 31(5),

758-775.

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable

variables and measurement error. Journal of Marketing Research, 18(1), 39-50.

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.

Gold, A. H., Malhotra, A., & Segars, A. H. (2001). Knowledge management: an organizational

capabilities perspective. Journal of Management Information Systems, 18(1), 185-214.

Gupta, A. K., & Singhal, A. (1993). Managing human resources for innovation and creativity.

Research Technology Management, 36, 41-41.

Henderson, J. C., Sussman, S. W., & Thomas, J. (1997). Creating and exploiting knowledge for fast-

cycle organizational response: the center for army lessons learned. Advances in Applied

Business Strategy, 5(4), 103-128.

Hofstede, G., Hofstede, G. J., & Minkov, M. (1991). Cultures and organizations: McGraw-Hill

London.

Hwang, Y. (2005). Investigating enterprise systems adoption: uncertainty avoidance, intrinsic

motivation, and the technology acceptance model. European Journal of Information Systems,

14(2), 150-161.

Jansen, J. J. P., Van Den Bosch, F. A. J., & Volberda, H. W. (2005). Managing potential and realized

absorptive capacity: how do organizational antecedents matter? Academy of management

journal, 48(6), 999-1015.

Janz, B. D., & Prasarnphanich, P. (2003). Understanding the Antecedents of Effective Knowledge

Management: The Importance of a Knowledge‐Centered Culture*. Decision Sciences, 34(2),

351-384.

Javidan, M., Stahl, G. K., Brodbeck, F., & Wilderom, C. P. (2005). Cross-border transfer of

knowledge: Cultural lessons from Project GLOBE. The Academy of Management Executive,

19(2), 59-76.

Jones, N. B., & Mahon, J. F. (2012). Nimble knowledge transfer in high velocity/turbulent

environments. Journal of knowledge management, 16(5), 774-788.

Joshi, K. D., Sarker, S., & Sarker, S. (2007). Knowledge transfer within information systems

development teams: Examining the role of knowledge source attributes. Decision Support

Systems, 43(2), 322-335.

Khazanchi, S., Lewis, M. W., & Boyer, K. K. (2007). Innovation-supportive culture: The impact of

organizational values on process innovation. Journal of Operations Management, 25(4), 871-

884.

Ko, D.-G., Kirsch, L. J., & King, W. R. (2005). Antecedents of knowledge transfer from consultants

to clients in enterprise system implementations. MIS Quarterly, 29(1), 59-85.

Laursen, K., & Foss, N. J. (2003). New human resource management practices, complementarities

and the impact on innovation performance. Cambridge Journal of economics, 27(2), 243-263.

Lee, G., & Xia, W. (2005). The ability of information systems development project teams to respond

to business and technology changes: a study of flexibility measures. European Journal of

Information Systems, 14(1), 75-92.

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.

Liang, H., Saraf, N., Hu, Q., & Xue, Y. (2007). Assimilation of enterprise systems: The effect of

institutional pressures and the mediating role of top management. MIS Quarterly, 31(1), 59-

87.

Lichtenthaler, U. (2009). Absorptive capacity, environmental turbulence, and the complementarity of

organizational learning processes. Academy of management journal, 52(4), 822-846.

Matusik, S. F., & Hill, C. W. (1998). The utilization of contingent work, knowledge creation, and

competitive advantage. Academy of management review, 23(4), 680-697.

Mohr, J., & Nevin, J. R. (1990). Communication strategies in marketing channels: A theoretical

perspective. Journal of Marketing, 54(4), 36-51.

Nag, R., & Gioia, D. A. (2012). From common to uncommon knowledge: foundations of firm-specific

use of knowledge as a resource. Academy of management journal, 55(2), 421-457.

Nelson, K. M., & Cooprider, J. G. (1996). The Contribution of Shared Knowledge to IS Group

Performance. MIS Quarterly, 20(4), 409-432.

Nemati, H. R., Steiger, D. M., Iyer, L. S., & Herschel, R. T. (2002). Knowledge warehouse: an

architectural integration of knowledge management, decision support, artificial intelligence

and data warehousing. Decision Support Systems, 33(2), 143-161.

Oke, A., Walumbwa, F. O., & Myers, A. (2012). Innovation Strategy, Human Resource Policy, and

Firms' Revenue Growth: The Roles of Environmental Uncertainty and Innovation

Performance*. Decision Sciences, 43(2), 273-302.

Okhuysen, G. A., & Eisenhardt, K. M. (2002). Integrating knowledge in groups: How formal

interventions enable flexibility. Organization science, 13(4), 370-386.

Patnayakuni, R., Rai, A., & Tiwana, A. (2007). Systems development process improvement: A

knowledge integration perspective. Engineering Management, IEEE Transactions on, 54(2),

286-300.

Pee, L. G., Kankanhalli, A., & Hee-Woong, K. (2010). Knowledge Sharing in Information Systems

Development: A Social Interdependence Perspective. Journal of the Association for

Information Systems, 11(10), 550-575.

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.

Sakthivel, S. (2007). Managing risk in offshore systems development. Communications of the ACM,

50(4), 69-75.

Sambamurthy, V., Bharadwaj, A., & Grover, V. (2003). Shaping agility through digital options:

Reconceptualizing the role of information technology in contemporary firms. MIS Quarterly,

237-263.

Seijts, G. H., & Latham, G. P. (2005). Learning versus performance goals: When should each be used?

The Academy of Management Executive, 19(1), 124-131.

Senge, P. M. (1997). The fifth discipline. Measuring Business Excellence, 1(3), 46-51.

Shane, S., Venkataraman, S., & MacMillan, I. (1995). Cultural differences in innovation championing

strategies. Journal of management, 21(5), 931-952.

Smith, A. D., & Rupp, W. T. (2002). Communication and loyalty among knowledge workers: a

resource of the firm theory view. Journal of knowledge management, 6(3), 250-261.

Smith, K. G., Smith, K. A., Olian, J. D., Sims Jr, H. P., O'Bannon, D. P., & Scully, J. A. (1994). Top

management team demography and process: The role of social integration and

communication. Administrative science quarterly, 39(3), 412-438.

Song, M., Dyer, B., & Thieme, R. J. (2006). Conflict management and innovation performance: An

integrated contingency perspective. Journal of the Academy of Marketing Science, 34(3),

341-356.

Srivastava, A., Bartol, K. M., & Locke, E. A. (2006). Empowering leadership in management teams:

Effects on knowledge sharing, efficacy, and performance. Academy of management journal,

49(6), 1239-1251.

Tesch, D., Sobol, M. G., Klein, G., & Jiang, J. J. (2009). User and developer common knowledge:

Effect on the success of information system development projects. International Journal of

Project Management, 27(7), 657-664.

Tiwana, A., & Mclean, E. R. (2005). Expertise integration and creativity in information systems

development. Journal of Management Information Systems, 22(1), 13-43.

Tsai, W. (2001). Knowledge transfer in intraorganizational networks: Effects of network position and

absorptive capacity on business unit innovation and performance. Academy of management

journal, 44(5), 996-1004.

Vroom, V. H. (1964). Work and motivation.

Wright, P. M., Dunford, B. B., & Snell, S. A. (2001). Human resources and the resource based view

of the firm. Journal of management, 27(6), 701-721.

Zahra, S. A., & George, G. (2002). Absorptive capacity: A review, reconceptualization, and extension.

Academy of management review, 27(2), 185-203.