Understanding the Impact of ERP System Implementation on Firm … · 2017. 10. 28. ·...

International Journal of Software Engineering and Its Applications

Vol. 10, No. 9 (2016), pp. 87-104

http://dx.doi.org/10.14257/ijseia.2016.10.9.09

ISSN: 1738-9984 IJSEIA

Copyright ⓒ 2016 SERSC

Understanding the Impact of ERP System Implementation on

Firm Performance – Focused on Vietnamese SMEs

Minh Duc Le1 and Kyeong Seok Han

2*

1Dept. of Business Administration, Graduate School of Soongsil University, Korea

2Professor of MIS, School of Business Administration, Soongsil University, Korea

[email protected],

[email protected]

Abstract

As Enterprise Resource Planning (ERP) is highly constructive for any augmenting

organization, identifying which determinants of ERP System Implementation impact on

the performance of firms is important. This study aims to examine the dimensions of

successful implementation of ERP systems, and how the ERP implementation affects firm

performance as focusing on Small and Medium-sized Enterprises (SMEs) in Vietnam is a

good case in point. We proposed a modified framework based on the IS Success Model

and developed our hypotheses. The results from an online survey of 402 respondents

revealed that ERP system implementation successfully enhanced the firm performance

indirectly through the effects of organizational capability and competitive advantage, in

which individual impact showed the strongest effect. We further found that, business

sector and firm age were found to have moderating effects in the conceptual framework.

Keywords: ERP implementation, IS Success Model, firm performance, SMEs

1. Introduction

In period of growing global competition, information technology (IT) and information

system (IS) have changed the lives of both individuals and organizations, and play a

crucial role in today’s business world. The wave of new information system adoption has

evolved around the use of Enterprise Resource Planning (ERP) systems. An ERP system

“comprises of a commercial software package that promises the seamless integration of

all the information flowing through the company–financial, human resources, supply

chain and customer information” [4]. ERP systems attempt to integrate all business

processes into one synchronized suite of applications, procedures, and metrics to improve

data homogeneity and integration of modular applications [13]. Once implemented in an

organization, ERP systems remain operational for a long period of time, because they

often serve as a basis to advance an organization’s information infrastructure and allow

future expansion [14]. ERP systems are propitious to accomplish goals concerning

organizational, managerial, strategic, operational, and IT infrastructure. ERP systems are

expected to improve firm performance primarily owing to redesigned business processes,

expanded information capabilities, and integrated managerial functions. As a result, the

need to test the impact of ERP implementation on firm performance represents an

important motivation for this study.

Notwithstanding the fact that ERP solutions have been introduced into the business

environment in Vietnam for approximately 15 years, the success rate of ERP

implementation is still very low and several years behind developed countries. The

number of failed ERP system implementations in Vietnam most prevails over successful

ones. Although an ERP system acts as an effective tool that provides a continuous

* Dr. Kyeong Seok Han is a corresponding author.


Vol. 10, No. 9 (2016)

88 Copyright ⓒ 2016 SERSC

competitive advantage and enhances firm performance, numerous studies reported that

the status of applying ERP solutions in Vietnam is still relatively limited.

While few earlier researches examined some practices of the assumed dimensional

structure of ERP implementation, to the best of our knowledge, no study has been found

to have interrogated the ERP system’s successful implementation on the performance of

Vietnamese SMEs, which occupy 97% in total 402,326 active enterprises and play a vital

role for Vietnam’s economic development, and tested the construct’s dimensionality

using structural equation modelling [17]. To gain a better insight into the dimensional

structure of ERP implementation construct, this study intends to figure out which success

factors influence the ERP system implementation, and how the implementation of ERP

systems can impact on the firm performance of SMEs in Vietnam by testing its

dimensionality using higher order factor model, and one factor model on a set of data

collected from 402 Vietnamese SMEs. Answering these issues fills the gap in the

literature on the business value of ERP systems. In theoretical terms, the objective of this

study is (1) to clarify the interplay between ERP implementation and it indicators

drawing from the DeLone and McLean (hereafter D&M) IS Success Model [5], and (2)

to enhance our understanding of the mechanisms by which the successful implementation

of ERP systems contributes to the performance of a firm. Empirically, the aim is to

develop conceptual tools in order to analyze the influence from ERP implementation of

the SMEs in Vietnam, and thus to offer guidelines for both researchers and practitioners.

This paper will proceed as follows: We start by reviewing the related literature in

Section 2. Thereafter, in Section 3 our proposed model and hypotheses will be discussed.

In the section of research methodology, details of the approach and measurement

instruments chosen to conduct the study are explained. Then data analysis and the main

results will be presented in Section 5. Finally, we will put forward the conclusion

condensed from this research, and discuss some of its deficiencies. We will also

designate what we see as feasible routes for further research.

2. Background and Related Works

2.1. Review of ERP Implementation

ERP systems are designed to console both functional and operational processes of the

value chain of a firm, including human resources, accounting and finance, customer and

sales, and supply chain management [4]. Thereupon, the signified benefits of ERP

systems are to streamline the workflow across various business units, ensure a smooth

transition and quicker completion of processes, and enable all inter-departmental

activities to be properly tracked and none of them to be “missed out”.

To date, prior studies have documented mixed evidence on addressing the critical

factors for ERP success. Factors which are unique to ERP implementation consist of

understanding corporate cultural change, reengineering business processes, and using

business analysts on the project team. D&M (1992) determined the factors that may

impact on the success of an ERP system under six main categories namely system

quality, information quality, system usage, user satisfaction, individual effect and

organizational impact [5]. Nevertheless, Ifinedo (2007) asserted that individual impact

and organizational impact are unrelated in the context of ERP systems [10]. Edward

(2008) reformulated the D&M IS Success Model, and examined it in ERP context [6].

Likewise, many empirical studies tested the IS Success Model, and confirmed it to be a

robust and parsimonious model with high explanatory power of the variance in IS success

across a broad variety of contexts including ERP, SCM practices, e-government, e-

commerce, etc.

In considering the evidence donated by experimental researches as well as the

observations reported in the literature, this study examines the determinants of ERP

implementation by revising the dimensions of IS Success Model.


Vol. 10, No. 9 (2016)

Copyright ⓒ 2016 SERSC 89

2.2. ERP Implementation and Firm Performance

An ERP system is an integrated system in that it promotes cooperation among groups,

teamwork, process expertise and business knowledge, and helps devolve authority and

responsibility from management to front lines [4]. Therefore, the nature of an ERP

system is to capture the organizational impact that is in line with the use of that system. It

is widely reported that ERP systems influence on the firm performance, for instance,

Hunton et al. (2003) tested the impact of ERP adoption on the performance by making a

comparative analysis of firms which did and did not use ERP systems [9].

In developing countries, ERP systems are typically implemented as part of an

enterprise’s effort to renovate and discriminate itself, not to replace legacy systems. ERP

systems are adopted by enterprises to support an integrated, packaged solution to their

information needs. Aside from the fact that enterprises anticipate significant benefits

from the implementation of their ERP systems, problems within the implementation

process can restrain an enterprise from realizing those predicted benefits, or even

recovering the cost of the implementation effort. To address these issues, numerous

studies have been explored. Poston and Grabski (2001) reported that ERP adoption leads

to an efficiency increase in terms of a decline in the number of employees and in the ratio

of employees to revenue in each year following the ERP implementation [13]. Also, ERP

implementation helps enterprises gain a competitive advantage. Additionally, Wier et al.

(2007) claimed that joint adoption of ERP systems and non-financial performance

incentives (NFPI) will gain better firm performance than either ERP or NFPI alone [15].

However, the literature argues that little attention has been given to research on ERP in

SMEs, as the majority of the ERP studies are based on findings from large enterprises.

2.3. SMEs and ERP Status in Vietnam

SMEs in Vietnam act jointly approximately all sorts of industries, in view of that they

have a variation in their range and significance. SMEs are business establishments that

have registered their business pursuant to law, and are classified into three levels in line

with the sizes of their total capital or the number of employees (under the Decree No.

56/2009/ND-CP by The Vietnamese Government).

Table 1. SME Definition In Terms of Sector in Vietnam

Types of SMEs

Sector

Micro

enterprises

Small-sized

enterprises

Medium-sized

enterprises

Number of

laborers

Capital

(Billion

VND)

Number

of

laborers

Capital

(Billion

VND)

Number

of

laborers

Agriculture, forestry, fishery ≤ 10 ≤ 20 10 - 200 20 - 100 200 - 300

Industry and construction ≤ 10 ≤ 20 10 - 200 20 - 100 200 - 300

Trade and service ≤ 10 ≤ 10 10 - 50 20 - 50 50 - 100 Source: Decree No. 56/2009/ND-CP dated 30

th June, 2009 by The Vietnamese Government

According to data released by the General Statistics Office of Vietnam, the majority of

active businesses are SMEs as defined in the Government’s Decree mentioned above.

The number of SMEs grew steadily from 2009 to 2014 (see Table 2). SMEs accounted

for around 97% of total enterprises, contributed 47% GDP and nearly 40% of the state

budget [17]. SMEs play an important role to support the nation’s economy – strengthen

Vietnam’s industrial base as well as provide the necessary supports to enhance Vietnam’s

development across the economic sectors.


Vol. 10, No. 9 (2016)


Table 2. Number of Acting Enterprises by Labor Size (annual 31th Dec)

Year Micro

Enterprises

Small

Enterprises

Medium

Enterprises

Large

Enterprises Total

2009 162,785 74,658 5,010 6,389 248,842

2010 187,580 79,085 5,618 7,077 279,360

2011 216,732 93,356 6,853 7,750 324,691

2012 225,037 93,036 6,735 7,864 332,672

2013 252,291 104,499 7,838 8,585 373,213

2014 271,971 112,650 8,449 9,256 402,326 Source: Business performance of enterprises by Vietnamese standard industrial classification, Statistical

Yearbook, 2015, General Statistics Office of Vietnam GSO

In the early 2000s, ERP solutions were first entered in the Vietnamese companies

which were prospecting for ways to help their business more efficient and effective. A

survey carried out by the Vietnam Chamber of Commerce and Industry reported that, by

the middle of 2006, only 1.1% of the Vietnamese enterprises successfully implemented

ERP solutions. Based on a report released by the Ministry of Industry and Trade, the rate

of enterprises using ERP packages was 17% in 2014 [20]. When comparing to many

developed countries, the IT implementation among Vietnamese SMEs is considered to be

at a basic level, and the degree of ERP implementation remains a relatively low rate.

While opting for a business software application in general and an ERP solution in

particular is not quite simple, Vietnam’s SMEs suffer more problems than most in this

regard. A noticeable challenge is that the cost spending for an ERP system is still

extremely high for many Vietnamese SMEs. Issues and lags in ERP implementation

might be a major problem interfering the long-term success of ERP adoption. Thus,

ensuring a quality ERP system after being implemented is markedly important to SMEs

in Vietnam.

3. Research Model and Hypotheses

3.1. Research Model

Figure 1 presents the conceptual framework that serves the purpose of our study. In

this study, stemming from the D&M IS Success Model, the authors assume that ERP

implementation variable is a second-order construct composed of five first-order latent

constructs: System quality, information quality, user fulfillment, individual impact, and

organizational impact. The five arrows leading from the five first-order constructs show

that the ERP implementation variable is comprised of the five latent constructs. Hence,

this variable is totally latent, unobservable, and not directly measurable. Each of the first-

order constructs constitutes a number of measurable characteristics, each of which is also

listed in details in the next section. The research model suggests that ERP implementation

influences on both organizational capability and competitive advantage which in turn

enhance firm performance. Especially, the research model also examines that through

which path type, business sector, age and size of enterprises exert moderating effects on

the relationship between the successful implementation of ERP systems and firm

performance.


Vol. 10, No. 9 (2016)


3.1.1. Antecedents of ERP Implementation: Previous studies have identified several

determinants for implementation of ERP systems. Our research focuses only on five

frequently factors grounded on the IS Success Model. The D&M’s model is employed as

theoretical foundation to appraise ERP implementation for its integrity and much

empirical support for the conceptual framework [5]. Each antecedent notion is as follows:

Hypothesized Relationship

Moderating Relationship

Figure 1. Conceptual Framework

System quality: System quality can be understood as the technical level involvement

the ERP’s characteristics including data accuracy, system accuracy, system efficiency,

database content and response time.

Information quality: Information quality refers to the extent to which user perception

of measuring the characteristics of the information is produced by the ERP system.

User fulfillment: User fulfillment reflects the degree to which a subjective user

evaluates various consequences after using ERP system.

Individual impact: Individual impact can be defined in broad terms as the user

perception of elevating in personnel performance, task effectiveness, and productivity.

Organizational impact: Organizational impact invokes as the dimension that measures

the effectiveness of the information performance on the organization.

3.1.2. Organizational Capability and Competitive Advantage: Organizational

capability is defined as an organization’s ability to perform a set of tasks using resources

in terms of product variety, information access, process advancement, and financial

flexibility [14]. These identified capabilities are the most harmonious capabilities to the

size-restricted firms, and they reflect a vital perspective of business issues in the ERP-

specific context. Prior studies showed that IT investment and organizational capability

Moderators

Enterprise Type

(Type)

Business Sector

(Sector) Enterprise size

(Size)

Enterprise Age

(Age)

H7

H8

H9

H10

System

Quality

(SQ)

Information

Quality

(IQ)

Competitive

Advantage

(CAD)

User

Fulfillment

(UF)

Firm

Performance

(FPE)

H2

+ H6

H3 +

H4 +

+ Individual

Impact

(IIM)

Organizational

Impact

(OIM)

ERP

Implementation

(ERPI)

Organizational

Capability

(OCA)

+ H1 H5


Vol. 10, No. 9 (2016)


are considerable factors, drive differences in firm performance, and a specific system of

organizational capability strengthens the performance effects of IT application.

Regarding competitive advantage, the pursuit itself has been systematically stated and,

to date, remains poorly defined and operationalized. Competitive advantage in this model

is defined as the positional superiority to compete with the rivals based on the

combination of disparity, cost superiority, or through operating [2]. The attainment of a

competitive advantage position can lead to a firm’s significant performance, being

regularly measured in conventional terms such as market-share and profitability.

3.1.3. Firm Performance: Firm performance refers to the degree to which a firm

achieves in comparison with its intended outputs based on financial criteria and market

criteria [7]. Indeed, the issue of heterogeneous firm performance is a key issue in the field

of management, and an effective performance measurement system should be disposed to

capture not only the financial edge of business performance but also the non-financial

aspects so as to assess a more explicit and comprehensive notion of performance.

3.2. Hypotheses

As noted above, ERP systems provide a mechanism by which firms can process,

deliver, and seize a wide array of key performance indicators in (near) real-time, and

through which managers can coordinate and control their decisions across the enterprise.

Implementing an ERP system generally composes a firm’s grandest IS investment in its

development and, in most cases, the greatest corporate project [4]. A successfully

implemented ERP system enables firms to flexibly assemble requisite assets, knowledge,

and business relationships, and allows firms to apprehend environmental changes by

assembling organizational resources. Thus, a successful implementation of ERP systems

magnifies organizational capabilities. Moreover, changes in technology are essential if

they can give prosperity to the competitive advantage. Abdinnour-Helm et al. (2003)

stated that ERP systems do not offer competitive advantages in themselves, but have to

be coupled with social and intellectual capital within the firm [1]. Yet, other researchers

have argued that ERP can be part of making a competitive advantage in some situations

[3]. To provide further empirical evidences, the hypotheses are developed as follows:

Hypothesis H1: ERP implementation has a positive impact on organizational capability.

Hypothesis H2: ERP implementation has a positive impact on competitive advantage.

Earlier learnings have shown that there is a significant relationship between

organizational capability and competitive advantage [2]. Organizational capability plays

an important role in renewing competitive advantage over time. As this area of

competitive advantage has been lacking in empirical research, it would be potentially

contributive to investigate the relationship between organizational capability and

competitive advantage. Based on the above arguments, it is predicted that:

Hypothesis H3: Organizational capability has a positive impact on competitive advantage.

Organizational capability and firm performance are two different constructs having an

apparently complex relationship. Information systems enable firms to yield better

performance with new customized products that have notable features and better quality.

Newbert (2008) suggested that to produce a product with more benefits, a firm must

exploit a set of capabilities greater than that of its rivals. It is hypothesized that no matter

what processes of capabilities are, they affect performance. Additionally, competitive

advantage provides chances to develop their own business performance and ability to

compete with the competitors. Although the investigation of competitive advantage in the

ERP context has limited studies, existing literature provides support that the relationship,

while anecdotic, is logical. It is expected that competitive advantage would have a


Vol. 10, No. 9 (2016)


positive effect on performance, and mediate the relationship between organizational

capabilities and firm performance. Thus, following hypotheses are proposed:

Hypothesis H4: Organizational capability has a positive impact on firm performance.

Hypothesis H5: Competitive advantage has positive impact on firm performance.

Recent studies have found evidence that ERP systems affect a firm’s performance [13]

[15]. Poston and Grabski (2001) investigated the effect of ERP implementation on firm

performance during an analysis window of 3 years pre- and post-implementation. The

results pointed no significant improvements in the financial ratios. From another aspect,

the market and the managers perceive value in ERP announcements and ERP

implementations, respectively [9]. Nicolaou and Bhattacharya (2006) indicated that once

an ERP system is implemented in a firm, it will continue to run well in the future, reduce

time lags in production processes, and improve the ability of firms to meet demands

which translate to higher firm performance [12]. From these assertions, in the sense that

in order for a firm to harvest the anticipated benefits, it is critical to start with an

implementation of an ERP system. Relied on these ideas, confirming a positive impact of

ERP implementation on performance is expected:

Hypothesis H6: ERP implementation has a positive impact on firm performance.

Additionally, as of moderating effects, empirical research in the literature of SMEs

context is rare and fragmented. Previous studies have discussed the roles of some

environment variables on ERP implementation such as time and nature of system

transformation, change and knowledge management, organizational culture, etc. [12]. In

light of this background, the current study will empirically dispute the influences of

enterprise profiles to test their moderating effects on the relationship between a firm’s

successful ERP implementation and performance. Among the potential moderators in the

relationships are the enterprise’s features, namely type, age, size and business sector. By

having information on such potential moderating impacts, decisions related to ERP

systems can be guided toward improvements in the firms’ position. Therefore, this study

advances the following hypotheses:

Hypothesis H7~H10: Type, business sector, age and size of enterprises have

moderating effects on firm performance.

4. Research Methodology

4.1. Instrument Design and Refinement

A web-based survey using a four-part questionnaire was designed to obtain responses

from the participants. The first part included 5 topic questions, each had several items

used to operationalize the constructs related to the ERP implementation. The second part

covered a set of questions regarding organizational capability and competitive advantage

whereas the third dealt with the performance outcomes. All scale items were measured

using a 7-point Likert-type scale, ranging from 1 = “strongly disagree” to 7 = “strongly

agree”. The last part involved nominal and/or ordinal scale items used to collect basic

information about demographic characteristics of the enterprises taking part in the survey.

To ensure that an inclusive list of items was covered in the questionnaire, all items

respecting the measurement of factors were adapted from prior scales and rephrased with

appropriate modifications in case of need to make them specifically relevant to the ERP

systems of SMEs context in Vietnam. The pool of items with regards to these constructs’

domain was compiled by the authors due to the lack of information from past findings.

Thence, the further validity of them should be justified by later research study. The final

questionnaire contained 31 items for eight constructs, and 6 questions pertaining to

business entity type, industry, number of employees, the number of years enterprise has


Vol. 10, No. 9 (2016)


been engaged in exporting operations, the number of months and years since the ERP

system initiatives, and the type of ERP related package used.

For measuring ERP implementation, our constructs were largely revised from D&M

scale [5]. The measurement included five items for each scale. Some items, however,

were removed as they loaded in two different factors or showed a weak loading. En

masse, 22 items were applied to measure. Organizational capability and competitive

advantage were redrawn based on the instrument developed by Law and Ngai 2007 [11].

Organizational capability was measured by three items and a similar number for

competitive advantage. To capture firm performance, three items were used and reformed

stemmed from the instrument of Ellinger et al. (2008) [7]. Each construct made at least

three items up to assure adequate reliability, as assigned by Nunnally (1978).

In advance of the hypothesized variables, each parity incorporated four moderators

(business type, sector, age and size). The age of enterprise was measured by the number

of years the company had been in operation, and the size was measured by the

enterprise's number of employees currently in employment. The type and business sector

were classified in accordance with criteria cited in the Enterprise Law (2014) of Vietnam.

The constructs have all been used in prior empirical studies, and the four moderating

variables are particularly pertinent to the context of an inspection of ERP implementation

as quoted above. Since all the measurements used in this study were from current

literature, it was judged that running a pilot study would be unnecessary.

4.2. Sample Selection and Data Collection

The data used to test the hypotheses were seized via a self-administered survey that

was essentially relied upon validated apprehension taken from the ERP-related literature.

This research was conducted among enterprises publicly declaring the implementation of

ERP systems for the first time within the period 2008-2014. This is adequate population

referring to ERP implementation, since several studies provide evidence that earnings

accrued from ERP-implementing firms are noticeable only after a lag of time from the

date of initial rollout [12].

Table 3. Summary of Sample Characteristics

Classification Category Frequency Ratio (%)

Business entity

Private companies 9 2.24

Limited liability 196 48.76

Joint-stock 140 34.83

Partnership 38 9.45

Foreign-invested 19 4.73

Industry sector

Agriculture/Fisheries 19 4.73

Manufacturing 99 24.63

Construction 114 28.36

IT/Communication 47 11.69

Wholesale/Retail 41 10.20

Transportation & Storage 28 6.97

Finance/Real estate 34 8.46

Others 20 4.98

Firm Age

1-5 years 115 28.61

5-10 years 152 37.81

> 10 years 135 33.58

Firm Employee < 50 33 8.21


Vol. 10, No. 9 (2016)


50-100 108 26.87

100-200 138 34.33

200-300 123 30.60

As our unit of analysis is the “firm”, the original sample included a summed quantity

of 672 enterprises, residing in Ho Chi Minh, Ha Noi and Da Nang City which represent

the largest economic centers in the south, north and middle of Vietnam, respectively. The

enterprises were randomly selected and contacted from the database stemmed from

Vietnam Chamber of Commerce and Industry. At the outset, there were 413 out of 672

enterprises contacted being agreed to feedback the survey. Yet, within the 413 returns, 11

invalid responses were discarded due to large portions of missing and discrepant

information. The remaining 402 questionnaires were retained as the usable sample size

for data analysis, yielding a complete response rate of 59.8%.

The demography of our respondents is summarized in Table 3. Aside from 11

incomplete responses, 402 out of 413 survey responses were analyzed. With regards to

the entity statistics, approximately 50% of the ERP firms came from limited liability

companies - LLCs (196 firms), 35% came from joint-stock companies (140 firms) and

the rest occupied 15%, showed that most of the respondents were LLCs and joint-stock

companies, which are the most popular forms of investment vehicle in Vietnam, in other

words, this rate is entirely appropriate to the Vietnamese enterprise structure. As for the

industry statistics, the sector of industry being made of construction and manufacturing

firms represented the highest proportion of the sample (more than 50%). The distribution

of enterprises’ age and size was nearly equal for all groups except group of less than 50

employees which was more likely to apply separate software packages more than a

complicated software required high-level structure of enterprises.

4.3. Analytical Methods

Data analysis was done in several steps by using three statistical software: SPSS 22,

AMOS 21.0.0 and Microsoft Excel 2013. Initially, we used SPSS to input survey data

and produce a basic description so as to ascertain the level of sample representative. Next,

we ran the reliability analysis, and conducted Exploratory Factor Analysis. Finally, the

proposed framework was tested through Structural Equation Modelling by the maximum

likelihood method using AMOS. The data were analyzed through a two-step approach.

Confirmatory Factor Analysis was primarily processed to identify if the measured

variables reflected the hypothesized latent variables. Then, Structural Equation Modelling

was explored to estimate overall model fit, path coefficients and explanatory power of the

proposed model. During this phase, Excel was performed to calculate the composite

reliability and variance extracted to test the convergent validity.

5. Results

5.1. Evaluation of Measurement Scales

5.1.1. Descriptive Statistics: In case each measured variable in structural equation

modeling does not have a normal distribution, we would get biased estimates and an

inaccurate model. Thus, descriptive statistics analysis using the mean score of each

measurement scale was tested to confirm normality in the multivariate distribution. If the

skewness of variables is less than 3, and kurtosis is below 10, a normal distribution can

be assumed. Descriptive analysis showed that the mean and standard deviations were

within the expected ranges, skewness ranged from -0.43 to -0.11, and kurtosis ranged

from -0.18 to 0.22. The results were well within the robustness thresholds for normality.

As a result, the univariate normality was evidenced in the dataset which may result in the


Vol. 10, No. 9 (2016)


fact that we can execute the maximum likelihood estimation in testing the structural

model.

5.1.2. Reliability Assessment: Reliability was estimated by performing the internal

consistency of the scale factors using Cronbach’s Alpha. This study used an Alpha value

of above 0.7 as a benchmark to check whether the scales are reliable [18]. The reliability

for each construct ranged from 0.802 to 0.870, satisfied the recommended threshold, or

that is to say, reflected acceptable reliability levels (see Table 4). Therefore, our items

have a high internal consistency in each scale.

Table 4. Cronbach’s Alpha Reliability Test Result

Construct name Construct

identifier

Initial

number

of items

Number of items

carried forward

to the analysis

Cronbach's

alpha

System quality SQ 5 5 0.850

Information quality IQ 5 5 0.859

User fulfillment UF 5 4 0.862

Individual impact IIM 5 3 0.802

Organizational impact OIM 5 5 0.858

Organizational capability OCA 3 3 0.815

Competitive advantage CAD 3 3 0.870

Firm performance FPE 3 3 0.869

5.1.3. Exploratory Factor Analysis: Exploratory factor analysis (EFA) was performed

to check whether the proposed factor structures are well-consistent with the actual data.

Kaiser’s criterion (Eigenvalue value of 1-point cutoff), percentage of variance (60% of

satisfactory cutoff point), and scree plot (identifying the plot to detect a point at which the

curve shape changes path and turns into horizontal) were used to assist in the decision

regarding the number of factors to maintain [18].

The results revealed that the factor structures evoked by EFA matched the one

designed in the research model. The outcomes of EFA using the principal components

factor extraction approach with Varimax rotation showed an eight-factor solution. This

was supported by the scree plot test. The eight-factor structure was recommended using

the criteria of all Eigenvalue greater than 1, and the extracted factors accounted for

71.26% of the variance. Besides, factor loadings were all above 0.6 on their own factors

as suggested by Hair et al. (2005). These findings suggest that those domains have a good

construct. However, EFA is a poor ending point for testing the scale dimensionality. It is

thence necessary to test the multidimensional nature of the measure to ensure that the

scale is accurate and does not cause defective conclusions. Consequently, Confirmatory

Factor Analysis would be employed to check the dimensional structure of the construct.

5.2. Measurement Model Assessment

CFA was conducted to assess the factorial structure of the entire scale, and to test the

reliability and validity of the measurement model through the convergent and

discriminant validity to ensure unidimensionality of the multiple-item constructs [16].

Convergent validity was assessed by testing Composite Reliability (CR) and Average

Variance Extracted (AVE) from the measures [18]. For a construct to possess good

consistency reliability, whereas a value higher than 0.70 is acceptable for CR, an AVE

value should exceed the threshold of 0.5 in all cases [8]. As shown in Table 5, CR values

were more than 0.7 (0.782 ~ 0.844), and AVE values were above 0.5 (0.506 ~ 0.637). In


Vol. 10, No. 9 (2016)


addition, all values of standardized factor loadings exceeded the cutoff point 0.7 (0.701 ~

0.901), which indicated a high degree of a positive relationship among items developed

to measure proposed constructs. The critical ratios associated with the other indicators

were found to be significant at the 0.001 level. Therefore, the convergent validity results

confirmed that the measures in our model are in reality related.

Table 5. Convergent Validity of the Measurement Model

Latent

constructs Items

Std.

Weights S.E. C.R. P CR AVE

Service quality

SQ1

SQ2

SQ3

SQ4

SQ5

0.701

0.746

0.793

0.703

0.705

-

0.083

0.086

0.085

0.084

-

13.401

14.110

12.699

12.733

-

***

***

***

***

0.806 0.517

Information

quality

IQ1

IQ2

IQ3

IQ4

IQ5

0.756

0.770

0.704

0.776

0.713

-

0.063

0.063

0.067

0.069

-

15.333

13.921

15.474

14.122

-

***

***

***

***

0.837 0.506

User fulfillment

UF1

UF2

UF3

UF4

0.791

0.853

0.797

0.702

-

0.060

0.059

0.061

-

18.247

16.907

14.268

-

***

***

***

0.835 0.560

Individual

impact

IIM1

IIM2

IIM3

0.743

0.756

0.777

-

0.074

0.078

-

12.855

12.996

-

***

***

0.782 0.545

Organizational

impact

OIM1

OIM2

OIM3

OIM4

OIM5

0.704

0.703

0.848

0.790

0.722

-

0.088

0.103

0.095

0.094

-

11.688

13.497

12.91

12.063

-

***

***

***

***

0.844 0.523

Organizational

capability

OCA1

OCA2

OCA3

0.723

0.863

0.739

-

0.082

0.081

-

15.093

13.578

-

***

***

0.823 0.609

Competitive

advantage

CAD1

CAD2

CAD3

0.788

0.901

0.812

-

0.059

0.056

-

19.198

17.363

-

***

***

0.840 0.637

Firm

performance

FPE1

FPE2

FPE3

0.826

0.796

0.890

-

0.065

0.056

-

17.918

20.341

-

***

***

0.822 0.606

Furthermore, we verified the discriminant validity of the measurement model by

comparing the AVE value of each latent construct to the squared correlation between this

construct and none of the squared correlations surpassed the AVE. As showed in Table 6,

the square roots of every AVE value associated with each latent construct exceeded the

levels of correlations among any pair of latent constructs. The test indicated that the

discriminant validity is supported for the measurement model.

Table 6. Discriminant Validity Analysis Results

Constructs SQ IQ UF IIM OIM OCA CAD FPE

SQ 0.719

IQ 0.656 0.711

UF 0.576 0.652 0.748

IIM 0.223 0.297 0.205 0.738


Vol. 10, No. 9 (2016)


OIM 0.288 0.355 0.244 0.390 0.723

OCA 0.532 0.614 0.601 0.280 0.375 0.780

CAD 0.599 0.644 0.631 0.349 0.419 0.629 0.798

FPE 0.528 0.647 0.604 0.385 0.349 0.664 0.638 0.778 Note: Square roots of AVE are on the diagonal; Correlations between constructs are off-diagonal

5.3. Higher-order Factor Model Assessment

We then tested a higher factor order model, where the five factors were measures of

one single determinant of ERP implementation. As establishing the second-order model,

the index changes according to the direction of the arrow between measurement variables

and factors, called Reflective Indicators. The same number of items was used to measure

each factor as in prior model. The only discrepancy between these models is that the

factors are now correlated to be measures of one higher factor - ERP implementation.

The five latent constructs, lower-order factors, formed the structure model. These factors

were correlated insofar as they measured one higher-order dimension. The second-order

factor model’s adoption is acceptable in case of being found to have a good fit to the data.

Figure 2 presents the analysis results. The goodness-of-fit measures in the acceptable

range showed that this model fit the data, and the measurement items converged on their

relevant variables, in other words, each measure represented a distinct latent variable.

Figure 2. Higher-order Confirmatory Factor Analysis

The analysis output also demonstrated that all parameter estimates were positive and

within the logical expected range of values. More specifically, the path coefficient from

each indicator to the observed variables was found to be significant, and the standardized

regression weights ranged from 0.754 to 0.961, which upheld the validity and reliability

of the items. Consequently, lower-order factors were measured, and items were summed

up to examine the higher-order factor analysis.

5.4. Structural Model Analysis

From literature review and findings in previous sections, the framework was tested

using Structural Equation Modeling (SEM). Bollen (1989) asserted that SEM is a

comprehensive statistical approach to test hypotheses between observed and latent

variables [16]. As our objective is to identify the causal relationship between ERP

implementation and firm performance, SEM would properly be the most appropriate

analysis way. SEM was executed in order to identify which ERP determinants generate

the performance outcomes. Fitness estimates of structural model are summarized in Table

7. Goodness-of-fit statistics indicated that the RMSEA score (0.066) was close fit. The

GFI and AGFI score (0.933 and 0.901, respectively) were close to good fit. The IFI, TLI,

Fit

Indices

Results Level of Acceptance

Absolute

Fit

χ2/df 2.402 1.0 ≤ χ2/df≤2.0~3.0

RMSEA 0.059 ≤ 0.05 ~ 0.08

RMR 0.077 ≤ 0.08

GFI 0.896 ≥ 0.8 ~ 0.9

AGFI 0.871 ≥ 0.8 ~ 0.9

Incremental

Fit

IFI 0.934 ≥ 0.8 ~ 0.9

TLI 0.925 ≥ 0.8 ~ 0.9

CFI 0.933 ≥ 0.8 ~ 0.9

Parsimonious

Fit

PNFI 0.788 ≥ 0.6

PCFI 0.824 ≥ 0.5 ~ 0.6

System

Quality

Information

Quality

User

Fulfillment

+

+

+

Individual

Impact

Organizational

Impact

ERP

Implementation

+

+


Vol. 10, No. 9 (2016)


and CFI score (0.959, 0.948 and 0.959, respectively) were all above 0.9, suggesting a

good fit between the structural model and the data. The parsimony-adjusted measures of

the model PNFI and PCFI scores were 0.732 and 0.748, which were significantly above

the suggested value of 0.60, indicating highly acceptable levels of parsimony. The

relative Chi-square (χ2 = 195.353 (df = 71, p = 0.000)) was within the suggested range

with the value of 2.751. All of these fit indices were adequate, supporting that the

structural model exhibits a good fit to the data after taking account into the sample size.

Table 7. Fit Indices of Structural Model

Fit Indices Results Level of

Acceptance

Source

Absolute Fit

χ2/df 2.751 1.0 ≤ χ2/df≤2.0~3.0 Carmines and McIver, 1981

RMSEA 0.066 ≤ 0.05 ~ 0.08 Browne and Cudeck, 1993

RMR 0.048 ≤ 0.08 Hair et al., 2005

GFI 0.933 ≥ 0.8 ~ 0.9 Jöreskog and Sörbom, 1984

AGFI 0.901 ≥ 0.8 ~ 0.9 Hair et al., 2005

Incremental

Fit

IFI 0.959 ≥ 0.8 ~ 0.9 Bentler and Bonett, 1980

TLI 0.948 ≥ 0.8 ~ 0.9 Bentler and Bonett, 1980

CFI 0.959 ≥ 0.8 ~ 0.9 Bentler and Bonett, 1980

Parsimonious

Fit

PNFI 0.732 ≥ 0.6 James et al., 1982

PCFI 0.748 ≥ 0.5 ~ 0.6 James et al., 1982

The Squared Multiple Correlation values, another goodness-of-fit indicator, indicate

the proportion of variance in the endogenous observed variables accounted for by the

exogenous latent variables in structural equations. In terms of explanatory power, this

model explained 31.7% of the variance in organizational capability, 43.3% of the

variance in competitive advantage, and 60.7% of the variance in organizational

performance construct. All hypothetical paths except the one between ERP

implementation and firm performance were positively significant. The results indicated

that there is no direct causal relationships from ERP implementation to firm performance.

The nature of this link appeared to be indirect, the relation might be mediated through

organizational capability and/or competitive advantage. Next, we present the summary of

path analysis results as showed in Table 8, and compare our results to past findings.

Table 8. Path Analysis Results

Hypotheses Path Path

Coefficient C.R. p_value Result R

2

H1 OCA <--- ERPI 0.620 9.840 *** Supported 0.317

H2 CAD <--- ERPI 0.402 5.826 *** Supported 0.433

H3 CAD <--- OCA 0.249 3.762 *** Supported

H4 FPE <--- ERPI 0.104 1.724 0.085 Not Supported

0.607 H5 FPE <--- OCA 0.301 5.047 *** Supported

H6 FPE <--- CAD 0.477 8.086 *** Supported Note: *** p < 0.001, ** p < 0.01, * p < 0.05 level of significance

Hypotheses H1 and H2 were strongly supported (β = 0.620 and 0.402, p < 0.001)

showing that the ERP implementation positively impacts on both organizational

capability and competitive advantage, in which individual impact had a higher effect in

comparison with service quality, information quality, user fulfillment, and organizational

impact. This result can be interpreted to mean that those items of constructs enhance the

organizational capability and competitive advantage of the enterprises surveyed, and

individual impact, regarding the joining in the adoption and implementation process of


Vol. 10, No. 9 (2016)


the ERP system by the delegates of the target users, is referred as the most important

determinant in magnifying the capabilities and attaining the competitive position.

In contrast to the proposed hypothesis, hypothesis H4 was found to be non-significant

(β = 0.104; p = 0.085), which indicates that there is no direct relationship between ERP

implementation and firm performance. This contradicts the results of other researchers

which showed that adoption and implementation of IT substantially impact on

performance outcomes [4] [13]. To further examine this relationship, the coefficients of

both total and indirect effects are calculated and discussed later in this section.

Hypotheses H5 and H6 were evidenced through highly significant coefficients at β =

0.301 and 0.477, p < 0.001. The results demonstrate that there are strong direct effects of

both organizational capability and competitive on firm performance. Also, organizational

capability was found to have a positive relationship with competitive advantage (β =

0.249, p < 0.001), as hypothesis H3 was supported. These findings are in line with the

ideas that firms possessing rare resources and capabilities will attain competitive

advantage, which thereby might lead to improved firm performance as they incarnate

dynamic routines to make their product distant, and investments in specific IT system

explain performance differences consistent with their strategic purpose [2].

Insofar as not anticipated, the ERP implementation construct had no direct effect on

the main endogenous variable, in this case – firm performance, the bootstrap test was

then performed to examine whether or not there occurred one or more potential

intervening effects in the baseline model. The significance of the indirect path was

evaluated from 5000 bootstrap samples; a bias-corrected and accelerated confidence

interval (CI) at 95% level was created for significance tests of the indirect path shown in

Table 9.

Table 9. Mediating Testing Results

Path Total effect Direct effect Indirect effect P value Result

CAD <--- ERPI 0.682 0.402 0.280 0.010 Supported

FPE <--- ERPI 0.519 0.104 0.415 0.010 Supported

FPE <--- OCA 0.558 0.301 0.257 0.010 Supported Note: 95% CI from 5000 bootstrapped samples

The results showed that organizational capability partially mediated the relationship

between ERP implementation and competitive advantage (β = 0.280 [0.192; 0.380])

which in turn intervened between organizational capabilities and performance (β = 0.257

[0.173; 0.352]). Interestingly, full mediation occurred between ERP implementation and

performance (β = 0.415 [0.307; 0.538]). The relationships were statistically significant at

the 0.01 level. These findings are momentous to the results of the hypothesis test where

individual impact is considered as the most basic criteria of implementing ERP system

which sequentially intensify the firm performance through indirect effect.

As mentioned above, responses to four sample characteristic questions were used as

moderators. A series of hierarchical hypotheses were tested using the critical ratios for

differences between parameters (DBP) to identify if the parameter estimate differs across

the groups suggested by Bollen (1989) [16]. The business sector was divided into 8

groups, and we reorganized into 2 groups: industry group, comprising manufacturing and

construction enterprises, and non-industry group. The similar reclassification occurred to

other moderators: 402 subjects were categorized into “≤ 10 year-age” group and “> 10

year-age” group. Enterprise type was classed into LLCs and non-LLCs group. For the

size of enterprises, the number of 200 employees was the point to divide groups. Table 10

presents the results of all pairwise parameter comparisons between groups of models

which verifies whether some of the paths reveal significant differences between delimited

groups. There were 4 out of 6 hypotheses being influenced by business sector due to the

absolute value of DBP which were higher than the critical value of 1.96. Thus, business


Vol. 10, No. 9 (2016)


sector would be defined as a moderator. The similar finding found in this test suggested

that the enterprise age would moderate the relationships in the model. Nevertheless, the 2

moderator, namely business type and size were found not to affect the relations between

ERP implementation and other endogenous variables as only 2 out of 6 hypotheses were

proved to be affected by these variables so as to be eliminated from the model.

The final research model, illustrated in Figure 3, represents a comprehensive set of

factors that affect the successful implementation of ERP systems which in turn strengthen

firm performance in SMEs in Vietnam based on the authors’ presented findings.

Table 10. Multiple Group Analysis Results

Effects

Enterprise Type Business Sector

Coefficients

DBP Result

Coefficients

DBP Result LLCs

Non-

LLCs Industry

Non-

industry

OCA <--- ERPI 0.309

***

0.466

*** 1.201

No

difference

0.301

***

0.445

*** 2.408 Difference

CAD <--- ERPI 0.385

***

0.179

* -3.600 Difference

0.196

**

0.414


CAD <--- OCA 0.694

***

0.755

*** 0.376

No

difference

0.628

***

0.806

*** 1.078

No

difference

FPE <--- ERPI 0.048 0.062 0.101 No

difference

0.124

* 0.048 -1.979 Difference

FPE <--- OCA 0.443

***

0.661

*** 1.231

No

difference

0.410

***

0.761

* 1.906

No

difference

FPE <--- OCA 0.521

***

0.156

* -2.802 Difference

0.487

**

0.177

* -2.362 Difference

Effects

Enterprise Age Enterprise Size

Coefficients DBP Result

Coefficients DBP Result

≤ 10yrs > 10yrs ≤ 200 EEs > 200 EEs

OCA <--- ERPI 0.378

***

0.382

*** 0.028

No

difference

0.321

***

0.515

*** 1.292

No

difference

CAD <--- ERPI 0.365

*** 0.154 -2.280 Difference

0.324

***

0.220

* -0.707

No

difference

CAD <--- OCA 0.723

***

0.783


0.831

***

0.587

*** -1.527

No

difference

FPE <--- ERPI 0.137 0.059 -1.996 Difference 0.114

* 0.023 -2.589 Difference

FPE <--- OCA 0.527

***

0.713

*** 0.198

No

difference

0.642

***

0.465

*** -0.994

No

difference

FPE <--- OCA 0.324

***

0.369


0.343

***

0.357

** 2.201 Difference

Note: *** p < 0.001, ** p < 0.01, * p < 0.05 level of significance


Vol. 10, No. 9 (2016)


Supported

Hypothesized Relationship Not Supported

Moderating Relationship Not Supported

Figure 3. Structural Model Result

6. Conclusions

6.1. Implications

The purpose of this study is to extend the empirical evidence regarding the effect of

ERP system implementation on firm performance across SMEs in Vietnam. We also

sought to identify whether enterprise characteristics moderate associations of these

variables with ERP implementation. The overall explanatory power of our research

model has an R-square of 60.7% for the firm performance, suggesting that the proposed

model is capable of explaining a relatively high proportion of variation of firm

performance. We primarily determined the effect of five constructs reviewed from the IS

Success Model on the implementation of ERP system. It is generally accepted that

individual impact exhibits the strongest association with ERP implementation in this

study. These findings support our conceptual model, and offer a managerial implication

that individual impact plays a critical role to implement ERP systems.

Also, the successful implementation of ERP systems is anticipated to boost firm

performance. We discovered that ERP implementation was not significantly directly

related to firm performance but had positive effects on organizational capability and

competitive advantage which would ultimately enhance the performance outcomes. The

non-significant relationship between the main exogenous and endogenous variable may

be explained by the following: First, given the nature of an ERP investment, the time for

completing an ERP system drives the time-to-benefit concerning the time horizon that an

organization needs to synchronize with the new system and train its users so as to

visualize the expected benefits. Second, organizations may initially have implemented

ERP systems, not because of the motivation to improve outcomes but because of the

pressure from smoothing synchronize business processes and information technologies,

and enhancing integration and coordination between business units. In consequence, firm

performance, after the adoption and on-going stage of an ERP system, would be probably

Moderators

Enterprise Type Business Sector Enterprise size Enterprise Age

System

Quality

Information

Quality

User

Fulfillment

Firm

Performance

0.758 0.477***

0.249*** 0.791

0.104 0.801

0.839 Individual

Impact

Organizational

Impact

ERP

Implementation

Organizational

Capability

0.716

R2 = 0.433

0.620*** 0.301***

R2 = 0.317

R2 = 0.607

0.402***

Competitive

Advantage


Vol. 10, No. 9 (2016)


vary from its own performance anterior to the investment of the system. These results

replicate a consistent finding in the literature.

From another aspect, mediating test was performed to advance our understanding of

ERP implementation on its consequences. This study discovered that organizational

capability and competitive advantage play a crucial intervening role in the relationships

in our model. Noticeably, we found that there is a full mediation effect in the relationship

between ERP implementation and firm performance. It can be inferred that firms seeking

to gain a higher competitive advantage need to build collaborative relationships with

capabilities to implement an ERP system, and once enterprises make sure what they do to

implement successfully, they can magnify the firm performance.

Returning to an earlier theme, in multi-group analyses, we found no evidence of

moderation by type and size of enterprises. Yet, there were noteworthy differences

between industry and non-industry groups, and between new and old enterprise groups

regarding the number of ten years in operation. This is an aspect that needs to be

addressed when implementing an ERP solution especially in the context of SMEs in

Vietnam. Thus, providers of ERP packages should recognize the importance of designing

solutions relied on sector-based enterprises for successful implementation.

In conclusion, drawing on the D&M IS Success Model, the results shed light on some

important issues related to firm performance which have not been addressed by previous

studies. This study is one of the few so far that includes ERP implementation as a second-

order construct while determining the relation to firm performance. This study can be

applied in other countries, especially emerging economies where integrated technology

solutions are not really popular, to provide a comprehensive overview of the

implementation of ERP systems residing in a particular country.

6.2. Limitations and Future Research

As with any archival research, our research findings need to be interpreted in light of

the following limitations. First, this study suffers from a major drawback, that is, firms

might report that they have implemented ERP systems, yet the extent of implementation

can vary considerably across firms. Hence, for expanding further, the measurement of

ERP implementation calculated an overall ERP impact score which contains the product

of level of ERP system functionality implemented, and degree of business process

redesign pursued should be to refined to unravel this mysterious paradox.

Second, the sample size in this study is relatively small compared to the total active

enterprises, and sample only focuses on firms in three big cities of Vietnam. This is

mainly due to the small number of firms that disclose the implementation of ERP

systems. Thus, finding a sample of firms that claimed the successful implementation was

quite restrictive. Thereby, the results might reflect only the process from these regions

rather than the whole SMEs. It should be further investigated with respondents from other

location to obtain a far more clear insight picture for the literature.

Third, we only examine organizational capability and competitive advantage whereas,

some other dimensions of socio-technical infrastructures that have been confirmed to

have impact on firm performance were not mentioned in this study. Future study should

attempt to more closely determine the specific features of operational environment to

better examine and understand the apparent synergetic relationship between ERP

implementation and outcomes.

Last but not least, only studying the moderating role of some firm features, naming the

type of entity and industry, firm age and size, this study does not mention other

characteristics of enterprises in current research framework. Therefore, the results may

get the discrepancy which are caused from different demographic groups that influence

the firm performance. An interesting issue for further research is to include some

contextual variables such as culture learning and knowledge, or the time using ERP


Vol. 10, No. 9 (2016)


systems in the firms as moderators to measure the degree of integration and configuration

in ERP implementation toward firm performance.

References

[1] Abdinnour-Helm S., Lengnick-Hall M. and Lengnick-Hall C., “Pre-implementation Attitudes and

Organizational Readiness for Implementing an Enterprise Resource Planning System”, European

Journal of Operational Research, vol. 146, no. 2, (2003), pp. 258-273.

[2] Barney J., “Firm Resources and Sustained Competitive Advantage”, Journal of Management, vol. 17,

no. 1, (1991), pp. 99-120.

[3] Beard J. W. and Sumner M., “Seeking Strategic Advantage in the Post-Net Era: Viewing ERP Systems

from the Resource-Based Perspective”, Journal of Strategic Information Systems, vol. 13, no. 2, (2004),

pp. 129-150.

[4] Davenport T. H., “Putting the Enterprise into the Enterprise System”, Harvard Business Review, vol. 76,

no. 4, (1998), pp. 121-131.

[5] DeLone W. H. and McLean E. R., “Information Systems Success: The Quest for the Dependent

Variable”, Information Systems Research, vol. 3, no. 1, (1992), pp. 60-95.

[6] Edward W. N., “IT Governance for Enterprise Resource Planning Supported by the DeLone-McLean

Model of IS Success”, Information and Management, vol. 45, no. 5, (2008), pp. 257-269.

[7] Ellinger A. E., Ketchen D. J. Jr, Hult G. T. M., Elmadag A. B. and Richey R. G. Jr., “Market

Orientation, Employee Development Practices, and Performance in Logistics Service Provider Firms”,

Industrial Marketing Management, vol. 37, no. 4, (2008), pp. 353-366.

[8] Fornell C. and Larcker D. F., “Evaluating Structural Equation Models with Unobservable Variables and

Measurement Error”, Journal of Marketing Research, vol. 18, no. 1, (1981), pp. 39-50.

[9] Hunton J. E, Lippincott B. and Reck J., “Enterprise Resource Planning Systems: Comparing Firm

Performance of Adopters and Non-Adopters”, International Journal of Accounting Information Systems,

vol. 4, (2003), pp. 165–84.

[10] Ifinedo P., “An Empirical Study of ERP Success Evaluations by Business and IT Managers”,

Information Management and Computer Security, vol. 15, no. 4, (2007), pp. 270 – 282.

[11] Law C. C. and Ngai E. W., “An Investigation of the Relationships between Organizational Factors,

Business Process Improvement, and ERP Success”, Benchmarking: An International Journal, vol. 14,

no. 3, (2007), pp. 387-406.

[12] Nicolaou A. I. and Bhattacharya S., “Organizational performance effects of ERP systems usage: The

impact of post-implementation changes”, International Journal of Accounting Information Systems, vol.

7, (2006), pp. 18-35.

[13] Poston R. and Grabski S., “Financial Impact of Enterprise Resource Planning Implementations”,

International Journal of Accounting Information Systems, vol. 2, no. 4, (2001), pp. 271-94.

[14] Shang S. and Seddon P. B., “Assessing and Managing the Benefits of Enterprise Systems: The Business

Manager’s Perspective”, Information Systems Journal, vol. 12, (2002), pp. 271-99.

[15] Wier B., Hunton J. and HassabElnaby H. R., “Enterprise Resource Planning Systems and Non-Financial

Performance Incentives: The Joint Impact on Corporate Performance”, International Journal of

Accounting Information Systems, vol. 8 no. 3, (2007), pp. 165-90.

[16] Bollen K. A., “Structural Equations with Latent Variables”, John Wiley & Sons Inc., New York, (1989).

[17] General Statistics Office of Vietnam, “Statistical Yearbook, 2015”, Statistical Publishing House, Hanoi,

(2015).

[18] Hair J. F., Black W., Babin B., Anderson R. E. and Tatham R. L., “Multivariate Data Analysis”, 5th ed.,

Prentice Hall, New Jersey, (2005).

[19] Kenny David A., “Meta-analysis: Easy to Answer", University Press, University of Connecticut, (2003).

[20] Vietnam Ministry of Industry and Trade, “Vietnam E-commerce Report 2014, Vietnam E-commerce

and Information Technology Agency, Hanoi, (2014).

Authors

Minh Duc Le, She received the B.A. from Posts and

Telecommunications Institute of Technology in 2005 and the MBA

from Danang University of Economics, Vietnam in 2010. She

currently studies for a Ph.D degree in Graduate School of Soongsil

University, Korea. Prior to that, she worked as a lecturer at E-

commerce Department of Vietnam-Korea Friendship Information

Technology College. Her research interests include Business

Consulting, ERP, Behavioral issues in E-commerce.


Vol. 10, No. 9 (2016)


Kyeong Seok Han, He is a Professor at the School of Business

Administration, Soongsil University, Korea. He received his Ph.D.

degree in MIS from Purdue University, United States in 1989, and

prior to that, he earned B.A. in 1979 and MBA in 1983 from Seoul

National University. He formerly was a Professor of University of

Houston. His major research interests include Digital Economy,

Business Consulting, ERP, e-CRM, Big Data, Agent-based

Simulation.


Vol. 10, No. 9 (2016)


Understanding the Impact of ERP System Implementation on Firm … · 2017. 10. 28. ·...

Documents

Transcript of Understanding the Impact of ERP System Implementation on Firm … · 2017. 10. 28. ·...