Application 3 – Annotated Bibliography
tchyar
Assessingtheimpactofinformationtechnologyonfirmperformance.pdf
International Journal of Production Research, Vol. 45, No. 12, 15 June 2007, 2697–2734
Assessing the impact of information technology on firm performance
considering the role of intervening variables: organizational
infrastructures and business processes reengineering
A. ALBADVIy, A. KERAMATI*z and J. RAZMIz
yIndustrial Engineering Department, Faculty of Engineering,
Tarbiat-Modares University, Tehran, Iran
zIndustrial Engineering Department, Faculty of Engineering,
University of Tehran, Tehran, Iran
(Revision received April 2006)
The relationship between the use of information technology (IT) and firm performance has been widely researched over recent years. However, there has been no well-founded empirical research on the role of intervening variables on such a relationship. The current paper aims to present an instrument to be used in such research and to study the role of two intervening variables including organizational infrastructures and business processes reengineering in such a relationship. Data from 200 car part manufacturers were gathered in a field survey. The empirical work indicated that constructed measures demonstrate the key psychometric properties including reliability and validity. The findings also demonstrate moderating effects of organizational infrastructures and mediating role of business processes reengineering on the relationship between the use of information technology and firm performance.
Keywords: Information technology; Firm performance; Organizational infrastructures; Business process reengineering; Empirical study; Questionnaire
1. Introduction
There have now been many studies on the relevancy between the application of information technology (IT) and organizational efficiency or firm performance. The results have shown a significant and positive correlation between IT and firm performance (Alpar and Kim 1990, Harris and Katz 1991, Rai et al. 1997, Newman and Kozar 1994, Mukhopadhyay et al. 1995). Meanwhile the other researches have not been able to find such a relationship (Brynjolfsson and Hitt 1998, Davern and Kaffman 2000). This is called productivity paradox in the literature of IT and productivity. One suggested way to explain the paradox is to consider intervening variables such as total quality management, reengineering of processes and organizational infrastructures, on the relationship between IT and performance (Brynjolfsson 2003, Davern and Kauffman 2000). Here, we considered the intervening variables to understand the indirect relationship between IT and
*Corresponding author. Email: [email protected]
International Journal of Production Research
ISSN 0020–7543 print/ISSN 1366–588X online � 2007 Taylor & Francis http://www.tandf.co.uk/journals
DOI: 10.1080/00207540600767780
organizational performance. Not much previous research has been done on this aspect before; also little empirical research has been done on the impact of intervening variables on the relationship between IT and performance.
There are important challenges for firms in the IT era. Do business process reengineering (BPR) and organizational factors mediate the effect of IT adoption on a company’s performance? In this research we will investigate these important challenges. We will show the organizational infrastructures in which firms should invest in order to realize the IT capabilities. Also the effects of process changes on IT productivity will be examined in this research.
We have found organizational infrastructures and business process changes more significant than the other intervening variables that have been suggested in the related literature. This is attributed to the following.
1. According to Boyer et al. (1997), researchers have often diagnosed the productivity paradox as a failure to balance investments in IT with investments in the infrastructure to support it (Brynjolfsson 2000, Meredith 1987, Ettlie 1988, Zuboff 1988). Although IT provides powerful new capabilities for firms, these capabilities can only be fully realized when companies also invest in organizational infrastructures, such as providing quality leadership, empowering workers, decentralization, team working and process management provide one of the keys for unlocking the vast potential of IT.
2. BPR involves rethinking and redesigning the organizations to create more values. As Attaran (2003) mentioned, the rapid evolution of information technologies and its declining costs are creating opportunities for organiza- tions to change dramatically and improve the way they conduct business. IT provides strategic value to an organization by giving support to the business processes. It is used for cost reduction, product differentiation, quality improvement, integration with customers and suppliers, organiza- tional learning, and creating new business opportunities. IT is the most effective enabling technology for BPR (Attaran 2003).
3. We believe that a combination of organizational infrastructures and business process changes will provide an integrated organization perspective, involving everyone, everything and everybody associated with the company, including its customers and suppliers.
In section 2 a brief review of literature and theoretical framework of the relationship between IT and performance considering the role of intervening variables (organizational infrastructures and reengineering of processes) will be demonstrated. In section 3 the research methodology is explained. Moderating effects of organizational infrastructures and mediating effect of business process reengineering in relation with IT and performance will be empirically analysed in section 4. Limitations, conclusions and discussions will be mentioned in sections 5 and 6.
2. Literature review
With a careful scan of the published work at corporate level IT productivity, we find that researchers have developed two different approaches in assessing the correlation
2698 A. Albadvi et al.
between IT implementation and productivity. Broadly speaking, the first approach
focuses on the effects of IT investment on direct and intermediary and financial and
non-financial measures of productivity. This approach could positively prove either
a direct correlation or lack of such a relation. The second approach considers the IT
implementation but emphasizes the role of intervening investments that enhance and
complement the IT implementation. Our research on IT and firm performance is in
accordance with the second approach of IT productivity studies, which considered
the role of intervening variables. A summary of our review is shown in table 1. In the remainder of this section we
will discuss some of the important works that support the idea of the role of
intervening variables. Organizations can achieve more production from their IT investment if IT
investments are coordinated with organizational redesign and other managerial
decisions (Hunter and Lafkas 2003), business strategy and the nature of managerial
work (Pinsonneault and Rivard 1998, Pinsonneault and Kreamer 1997, Belleflamme
2001). Also investment on management skills, user training, application of standards
and the way people work and how their performance is measured and controlled
are critical to realizing more productivity from IT investment (Brynjolfsson 2003,
Davern and Kauffman 2000). Recent research focuses on the impact of IT on organizational structure, culture,
productivity, efficiency and quality. For example, Lau et al. (2001) have investigated
the effect of complexity, formalization, decentralization, span of control,
outsourcing and lateral communication as the factors of structure, and team
working and learning as organization culture. They find that IT investment has
significant impacts on organizational structure and culture. Decentralization and investment on human capital are considered by Brenham
et al. (2001) as IT complementary investments. They conclude that greater levels of
IT are associated with increased delegation authority, greater levels of skill and
education in the work force. Lucas et al. (1993) found that introduction of financial imaging system resulted
in improvements to customer service, control of certificates, higher-quality images,
improved search speed, and cost, time and staff reduction. In summary, the first approach of IT productivity studies is based on the belief
that IT investment leads to cost reduction and improves quality, variety, innovation,
etc. But paradoxical results and a huge variation across organizations (some have
spent vast sums on IT with little benefit, while others have spent similar amounts
with tremendous success) change the critical question facing IT managers
and researchers from ‘Does IT increase productivity?’ to ‘How can we invest in IT
to increase productivity?’ The results of this approach show that investment in
IT does not automatically increase productivity, but is part of a broader system of
organizational investment for changes that do increase productivity (Brynjolfsson
and Hitt 1998). Most importantly, the highest productivity of IT will be realized when IT
investment is integrated with complementary investments (Brynjolfsson and Hitt
1998); new strategies, new business processes, new working practices and new
organizations all appear to be important in realizing the maximum benefit of IT
(Brynjolfsson and Hitt 1998). These changes will require a time-consuming period of
Assessing the impact of information technology on firm performance 2699
T a b le
1 .
S el ec te d w o rk s o n IT
p ro d u ct iv it y .
R es ea rc h er (s )
M ea su re s
F in d in g s
S tu d ie s th a t fo u n d IT
d o es
n o t im
p ro ve
p ro d u ct iv it y
A lp a r a n d K im
(1 9 9 0 )
M u lt if a ct o r (l o a n s a n d d em
a n d d ep o si ts )
IT re su lt s in
d ec re a se
in co st s a n d in cr ea se
in ti m e
d ep o si ts .
H a rr is a n d K a tz
(1 9 9 1 )
O p er a ti n g ex p en se
a s a p er ce n ta g e o f
p re m iu m
in co m e
F ir m s th a t a re
p ro fi ta b le
h a v e h ig h er
g ro w th
o n IT
ex p en se
ra ti o s a n d lo w er
g ro w th
o n o p er a ti n g ex p en se
ra ti o s.
N ew
m a n a n d K o za r (1 9 9 4 )
P o si ti v e id en ti fi ca ti o n o f je w el le ry
S y st em
re su lt ed
in : B et te r a ss et
m a n a g em
en t a n d
fi n a n ci a l co n tr o l
A v a il a b il it y o f d ec is io n su p p o rt
fo r g em
o l-
o g is t th ro u g h o u t ev a lu a ti o n p ro ce ss
In cr ea se d p ro d u ct iv it y
R ed u ce d co st s a n d in cr ea se d re v en u e
B et te r q u a li ty
M er ch a n d is e
M u k h o p a d h y a y et
a l. (1 9 9 5 )
In v en to ry
tu rn o v er
E D I
re su lt ed
in co st
re d u ct io n s
($ 1 0 0
sa v in g s
p er
v eh ic le , a n n u a l sa v in g s o f $ 2 2 0 m il li o n )
O b so le te
in v en to ry
P re m iu m
fr ei g h t
A n n u a l p ro d u ct io n v o lu m e
P a rt s v a ri et y
N ew
p a rt s in tr o d u ct io n
R a i et
a l. (1 9 9 7 )
L a b o u r a n d re la te d ex p en se s
A ll m ea su re s o f 1 T in v es tm
en t a re
p o si ti v el y a ss o ci a te d
w it h fi rm
o u tp u t. IT
ca p it a l a n d cl ie n t/ se rv er
ex p en d i-
tu re s a re
p o si ti v el y a ss o ci a te d w it h re tu rn
o n a ss et s.
M o st
ex p en d it u re
ex ce p t so ft w a re
a n d te le co m
a re
a ss o ci a te d w it h in cr ea se d la b o r p ro d u ct iv it y .
T o ta l p ro p er ty , p la n t, a n d eq u ip m en t
T o ta l n u m b er
o f em
p lo y ee s co m p a n y se ct o r
sa le s
R et u rn
o n a ss et s re tu rn
o n eq u it y L a b o u r
p ro d u ct iv it y
A d m in is tr a ti v e p ro d u ct iv it y
IS st a ff , h a rd w a re , so ft w a re , a n d te le co m
ex p en d it u re s
a re
n eg a ti v el y re la te d w it h a d m in is tr a ti v e
p ro d u ct iv it y .
S tu d ie s th a t fo u n d IT
im p ro ve s p ro d u ct iv it y
M a h m o o d a n d M a n n (1 9 9 3 )
R et u rn
o n in v es tm
en t, re tu rn
o n sa le s,
g ro w th
in re v en u e,
sa le s b y to ta l a ss et s,
sa le s b y em
p lo y ee , m a rk et
v a lu e to
b o o k
v a lu e.
In d iv id u a l IT
in v es tm
en t v a ri a b le s w er e fo u n d to
b e
w ea k ly
re la te d to
o rg a n iz a ti o n a l st ra te g ie s a n d
ec o n o m ic
p er fo rm
a n ce .
2700 A. Albadvi et al.
L o v em
a n (1 9 9 4 )
P er fo rm
a n ce
ra ti o s (R
O I)
C o n tr ib u ti o n o f in v es tm
en t o n IT
w a s a b o u t 0 d u ri n g a
p er io d o f 5 y ea rs
st u d y
H it t a n d B ry n jo lf ss o n (1 9 9 6 )
P ro d u ct io n fu n ct io n
IT in cr ea se d p ro d u ct iv it y a n d co n su m er
v a lu e,
b u t d id
n o t re su lt in
su p er n o rm
a l b u si n es s p ro fi ta b il it y .
B u si n es s p ro fi ta b il it y
C o n su m er
su rp lu s
T h er e is n o in h er en t co n tr a d ic ti o n b et w ee n in cr ea se d
p ro d u ct iv it y , in cr ea se d co n su m er
v a lu e a n d
u n ch a n g ed
b u si n es s p ro fi ta b il it y .
T a m
(1 9 9 8 )
T o ta l sh a re h o ld er
re tu rn
IT in v es tm
en t is n o t co rr el a te d w it h sh a re h o ld er
re tu rn .
R et u rn
o n eq u it y , a ss et s, sa le s
L ev el
o f co m p u te ri za ti o n
is n o t v a lu ed
b y
th e st o ck
m a rk et
in d ev el o p ed
a n d n ew
ly d ev el o p ed
co u n tr ie s.
B o o k v a lu e o f a ss et s
M a rk et
v a lu e
T h er e is n o co n si st en t m ea su re m en t o f IT
in v es tm
en t.
A n d er so n et
a l. (2 0 0 3 )
1 . M a rk et
v a lu e
1 . IT
p ro d u ct iv it y p a ra d o x re m a in s in
th ei r d a ta
a n d it
p re se n ts
a n ew
IT p ro d u ct iv it y p a ra d o x .
2 . In ta n g ib le
a ss et s v a lu e (i n n o v a ti o n )
3 . E ff ec ts
o f in v es tm
en t in
co m p le m en ta ry
a ss et s su ch
a s g re a te r u se
o f te a m s,
b ro a d er
d ec is io n -m
a k in g a u th o ri ty , a n d
w o rk er
tr a in in g
2 . T w o p a ra ll el
ex p la n a ti o n s fo r th e p a ra d o x :
C o m p le m en ta ry
in v es tm
en t in
o rg a n iz a ti o n a l a ss et s
a cc o m p a n y in g im
p le m en ta ti o n o f E R P a n d re la te d
sy st em
s in cr ea se d in ta n g ib le
a ss et
v a lu e.
A n d th e
in te rw
ea v in g o f IT
li n k s th ro u g h o u t th e su p p ly
ch a in
cr ea te d v a lu e b y en a b li n g ea ch
m em
b er
o f th e su p p ly
ch a in
to id en ti fy
a n d re sp o n d to
d y n a m ic
cu st o m er
n ee d s.
S tu d ie s sh o w s th e ef fe ct s o f in te rv en in g va ri a b le s o n re la ti o n sh ip
b et w ee n IT
a n d p ro d u ct iv it y
L u ca s et
a l. (1 9 9 6 )
C h a n g es
in o rg a n iz a ti o n a l st ru ct u re , w o rk -
fl o w s a n d fu n ct io n s, in te rf a ce
o p er a ti o n s,
te ch n o lo g y
In tr o d u ct io n o f fi n a n ci a l im
a g in g sy st em
re su lt ed
in im
p ro v em
en ts
to cu st o m er
se rv ic e,
co n tr o l o f ce rt if i-
ca te s, h ig h er -q u a li ty
im a g es , im
p ro v ed
se a rc h sp ee d ,
co st
re d u ct io n , re se a rc h ti m e re d u ct io n , st a ff
re d u ct io n .
H en d er so n a n d L en tz
(1 9 9 5 – 9 6 )
O rg a n iz a ti o n a l le a rn in g
T h e b en ef it s a n ti ci p a te d fr o m
IT in v es tm
en ts
(e .g . in n o v a ti o n ) a re
m a rg in a l u n le ss
in te g ra te d ,
d y n a m ic p ro ce ss es
ex is t to
a ct iv el y m a n a g e a n d a d a p t
th es e in v es tm
en ts .
N ew
p ro d u ct s a n d se rv ic es
( co n ti n u ed
)
Assessing the impact of information technology on firm performance 2701
T a b le
1 .
C o n ti n u ed .
R es ea rc h er (s )
M ea su re s
F in d in g s
B ry n jo lf ss o n a n d H it t (1 9 9 8 )
P ro d u ct iv it y
In v es tm
en t in
co m p u te rs
d o es
n o t a u to m a ti ca ll y
in cr ea se
p ro d u ct iv it y , b u t is p a rt
o f a b ro a d er
sy st em
o f o rg a n iz a ti o n a l ch a n g es
th a t d o es
in cr ea se
p ro d u ct iv it y .
D ec en tr a li za ti o n
IT sp en d in g
B re sn a h a n et
a l. (2 0 0 0 )
D ec en tr a li za ti o n a n d in v es tm
en t o n h u m a n
ca p it a l
1 . G re a te r le v el s o f IT
a re
a ss o ci a te d w it h in cr ea se d
d el eg a ti o n o f a u th o ri ty , g re a te r le v el s o f sk il l a n d
ed u ca ti o n in
th e w o rk fo rc e,
a n d th e g re a te r em
p h a -
si ze s o n p re -e m p lo y ee
sc re en in g fo r ed u ca ti o n a n d
tr a in in g .
2 . T h es e w o rk
p ra ct ic es
a re
co rr el a te d w it h ea ch
o th er
D ev a ra j a n d K o h li (2 0 0 2 )
O rg a n iz a ti o n a l ch a n g e
IT in v es tm
en t co m b in ed
w it h b u si n es s p ro ce ss
re en g i-
n ee ri n g p o si ti v el y a n d si g n if ic a n tl y in fl u en ce s
p er fo rm
a n ce .
B ry n jo lf ss o n (2 0 0 3 )
H u m a n a n d o rg a n iz a ti o n a l ca p it a l
T h e g re a te st
IT b en ef it s a re
re a li ze d w h en
a n IT
in v es tm
en t is co u p le d w it h a sp ec if ic
se t o f
co m p le m en ta ry
b u si n es s in v es tm
en ts .
W o rk
p ra ct ic es
D ec is io n m a k in g p ro ce ss
S h er er
et a l. (2 0 0 3 )
In v es tm
en t in
ch a n g e m a n a g em
en t
P la n n ed
co m m u n ic a ti o n s a n d ch a n g e m a n a g em
en t
st ra te g ie s le d to
th e sm
o o th
im p le m en ta ti o n o f th e
u p g ra d e p ro ce ss
a n d co n tr ib u te d to
th e p a y o ff
fr o m
th e IT
in v es tm
en t.
2702 A. Albadvi et al.
reengineering and redesign of organization in order to best utilize their IT investment.
In this research we have considered the role of two important variables including organizational infrastructures and business process redesign in the relationship between IT and performance. These two variables cover many factors examined in previous research.
In the next section a theoretical framework has been developed to study the effects of IT on firm performance by considering the role of two intervening variables including organizational infrastructures and business process change.
2.1 Theoretical framework of assessing the impact of IT on performance
In figure 1, a theoretical framework of the role of organizational infrastructures and business process reengineering in relation with IT and organizational performance is presented. This framework is an interpretation and synthesis of two previous models. The first one, developed by Grover et al. (1998), studied the relationship between IT and performance through the mediation of BPR. The second model, presented by Boyer et al. (1997), studies the relationship between IT and performance in organizations considering the role of organizational infrastructures.
Studies of Boyer et al. (1997), Hitt and Brynjolfsson (2000) and Lau et al. (2001) show that in order to benefit from IT potentials and to improve organizational performance, proper organizational infrastructures are essential. Boyer et al. (1997) consider quality strategy, soft integration and worker empowerment as necessary infrastructures to unlock IT potentials. The results of several case studies by Hitt and
H1
H1
H1
H2
H2
H2
The influence of IT on business processes
• Order flow • Strategic processes • Product • Marketing and sales • Services • Accounting • Personnel • Technology
IT application • IT in communications • IT in planning • IT in operations • IT in quality control • IT as a support for decision making • IT in administrative or office work • IT in financialaffairs
Organisation infrastructures • Delegation of power (reducing hierarchy) • Decentralization • Training • Group work • Process management • Relationship with customers and suppliers
Interactions between technology and organisational
infrastructures
Performance upgrading • Customer results • People results • Operational results • Growth
Figure 1. Theoretical framework of the impact of IT on firm performance considering the role of intervening variables.
Assessing the impact of information technology on firm performance 2703
Brynjolfsson (2000) indicate that creation of necessary IT infrastructures is an indispensable element for gaining higher IT performance. They have organized these infrastructures into three general categories including inter-organizational transfor- mation, interactions with customers and interactions with suppliers. Lau et al. (2001) have investigated the effects of IT on working conditions including organizational structure and culture. They conclude that IT needs its own specific structure and culture. They succeeded in showing the effects of factors such as education, group work, control domain and decentralization in the workplace.
In this research we have selected and investigated the most noticeable structural elements. Based on the results of studies by Boyer et al. (1997), Hitt and Brynjolfsson (2000) and Lau et al. (2001) we consider the effects of organizational infrastructures as a moderator role. First research hypothesis, in relation to this association, is:
Hypothesis 1: The relationship between IT and firm performance will be moderated by the extent of practical diligence to organizational infrastructures.
Figure 1 also shows the role of business processes redesign in the relationship between IT and performance. The result of the studies on mediating and moderating effects of BPR on the relation between IT and performance by Grover et al. (1998) indicates that organizational reengineering has a mediating role in the relation between IT and performance. Gunasekaran and Nath (1997) and Attaran (2003) have also shown the mediating role of BPR. These studies show that in organizational process reengineering, IT is one of the fundamental factors that must be considered as the enabler.
Noticing IT potentials and its proper application is a critical factor for success in BPR programs (Hammer 1990). Executing successful BPR programs and proper IT application makes the organizations expect that substantial improvements be properly made, and these improvements in turn improve performance measures of the organization. BPR mediating effects in the relation between IT and performance are shown in figure 1.
This figure shows that IT investments can improve business processes and through which improve organizational performance. This relationship, stated in the form of the second research hypothesis, is:
Hypothesis 2: The relationship between IT and firm performance will be mediated by the extent of BPR associated with the IT.
Gunasekaran and Nath (1997, pp. 96–97) have shown the effect of IT on the reengineering of processes of order flow, strategic planning, product, marketing and sales, services, accounting, human resources and have indicated the key role of IT in their reengineering program. The same processes are considered in the framework of this research.
3. Methodology
3.1 Data collection and sampling
In a study of IT performance, Froza (1995) studied sample automotive industries and electronic industries in Italy. He asserts that the main reason behind choosing
2704 A. Albadvi et al.
the automotive industry is that it is one of the most competitive industries in which innovation and change play a crucial role. With Iranian automotive industry entering the international competitive arena (this is a strategy favoured by automakers, government and policy makers), competition, creativity and innovation in the Iranian automotive industry will achieve higher status. As Froza (1995) states, creativity and innovation require the application of modern technologies and reengineering program. We have investigated a sample of companies relating to the automotive industry in Iran including part manufacturers.
In Iran 560 companies are involved in car part and component manufacturing. Noticing that our sampling was purposive sampling, we have selected the top 200 suppliers companies respecting their yearly turnover. Because yearly turnover of these companies is significant as those firm’s can invest in IT and reengineering programs. 112 of these companies participated in the survey. Therefore, the response rate came to be 56%, a feasible rate for such research (Ang et al. 2001). The questionnaires were completed by people in organizational positions such as chief director, factory manager, quality control manager, computer and systems manager, production manager and management advisor or expert.
Noting a variety of respondents, it was essential to look into the probable influence that their views might have on research findings. In order to do that, using one-way ANOVA (analysis of variance), we analysed the differences in answers in relation to the respondent’s organizational position (table 2). Table 2 shows significant difference in responses by people in different positions (p50.05) in only 6 out of 89 measures. In other measures there is no significant difference between responses in different positions. As shown in table 6, t-test results indicate that advisors, compared with other positions, had more pessimistic views. Table 2 also shows that quality experts held more pessimistic views about improvement in technology and service processes.
3.2 Measurement instrument
Figure 1 depicts one independent variable ‘the extent to use IT’, two latent variables ‘organizational infrastructure and BPR’ and one independent variable ‘company’s performance’.
In this section we will operationally define every one of the research variables and then introduce their measuring instruments. It is important to note that reuse of instrument from previous studies ensures content validity of the current study. When necessary, we have defined some first time instruments that are validated at the end.
3.2.1 The extent of IT usage (ITU). A list of information technology use in companies based on literature by Boyer et al. (1997), Swamidass and Kotha (1998), Martinez-Lorente et al. (2004) is drawn out. Since variables are directly imme asurable, their measurement requires scale definition. Therefore, 35 measures have been defined to evaluate IT in organizations (Appendix 1). Then, they have been classified into four criteria in terms of their application objectives consisting of IT in communications, IT in decision-making support, IT in production and operation, and IT in administration (see table 3). Respondents were asked to indicate the application rate of each technology on a Likert scale from 1 (not used) to 7
Assessing the impact of information technology on firm performance 2705
T a b le
2 .
A N O V A
a n a ly si s o f th e d if fe re n ce
b et w ee n re sp o n d en t v ie w s in
d if fe re n t p o si ti o n s.
O rg a n iz a ti o n a l p o si ti o n o f th e re sp o n d en t
V a ri a n ce
a n a ly si s
Q u es ti o n co d e
A B
C D
E F
G H
F -v a lu e
S ig .
T -t es t
IT P O
1 .3
5 .3 0
4 .3 3
4 .7 6
5 .5 0
2 .3 3
8 .0 0
6 .5 0
5 .5 3
2 .2 2 9
0 .0 4 0
A 4 E , H 4 F
IT P O
2 .7
4 .0 5
2 .3 3
3 .0 0
4 .8 6
5 .3 3
1 .0 0
4 .5 0
2 .4 7
2 .7 2 0
0 .0 1 4
A 4 H , E 4 C , D 4
H , E 4 H
IT A D
1 .1
4 .5 9
6 .3 3
4 .1 2
6 .2 9
4 .3 3
1 .0 0
5 .5 0
4 .9 5
2 .3 2 5
0 .0 3 2
D 4 A , A 4
F , D 4 C , D 4 F , D 4 H , H 4 F
IT A D
1 .6
5 .0 3
5 .0 0
5 .3 5
3 .7 1
5 .3 3
1 .0 0
5 .0 0
5 .1 5
2 .1 5 6
0 .0 4 6
D 4 A , A 4
F , C 4 D , C 4 F , H 4 D , E 4 F , H 4 F
B P S E 1
5 .0 3
4 .0 0
4 .7 9
5 .6 7
5 .0 0
� 2 .0 0
5 .4 2
2 .3 5 4
0 .0 3 9
A 4 G , C 4 G , D 4 G , E 4
G , H 4
G B P T E 2
4 .9 3
2 .3 3
4 .7 1
4 .1 4
6 .3 3
3 .0 0
3 .0 0
4 .6 0
2 .2 3 0
0 .0 3 9
A 4 G , C 4 B , D 4
B , E 4 B , H 4 B , C 4 G , E 4
G , H 4
G
(A ) C h ie f d ir ec to r, (B ) fa ct o ry
m a n a g er , (C
) q u a li ty
co n tr o l m a n a g er , (D
) co m p u te r a n d sy st em
s m a n a g er , (E ) p ro d u ct io n m a n a g er , (F ) a d v is o r, (G
) q u a li ty
u n it ex p er t,
(H ) o th er .
* P 5
0 .0 5 .
2706 A. Albadvi et al.
T a b le
3 .
IT U
v a ri a b le .
M ea su re m en t cr it er ia
S o u rc e
D ef in it io n
IT in
co m m u n ic a ti o n s
G ro v er
et a l. (1 9 9 8 ), P in n es ea lt
(1 9 9 7 ), M a rt in ez -L o re n ze
(2 0 0 3 )
IT in
co m m u n ic a ti o n s re fe rs
to th o se
d ir ec tl y in v o lv ed
in tr a n sa ct io n o f in fo rm
a ti o n . T h is cr it er io n in cl u d es
th e
fo ll o w in g a p p li ca ti o n s: em
a il , fa x , ce ll p h o n e, In te rn et
a cc es s, lo ca l a cc es s n et w o rk s (L A N ) fo r te ch n ic a l
d a ta
w it h in
th e co m p a n y , L A N
fo r co m p a n ie s,
in te rn a l n et w o rk s o f th e co m p a n y , co m p a n y ’s w eb si te
fo r a d v er ti se m en t, in tr a n et , d a ta
in te ra ct io n w it h
su p p li er s a n d cu st o m er s.
IT in
d ec is io n m a k in g
S w a m id a ss
a n d K o th a (1 9 9 8 ),
B o y er
et a l. (1 9 9 7 )
T h is d ec is io n -m
a k in g su p p o rt
cr it er io n in d ic a te s th e
a p p li ca ti o n o f IT
in su p p o rt in g m a n a g em
en t o f
p ro ce ss es . S o , it in cl u d es
IT a p p li ca ti o n s su ch
a s
d ec is io n su p p o rt
sy st em
s (D
S S ), d a ta
a n a ly si s
te ch n iq u es
a n d p ro g n o st ic
so ft w a re .
IT in
m a n u fa ct u ri n g a n d o p er a ti o n
T u rb a n et
a l. (2 0 0 2 ), B o y er
et a l. (1 9 9 7 ), F ro za
(1 9 9 5 )
T h is cr it er io n w o rk s a s a n u m b re ll a to
d el in ea te
a ra n g e
o f co m p u te r- a ss is te d te ch n o lo g ie s fo r d ir ec t o r
in d ir ec t su p p o rt , co n tr o l, d et ec ti n g a n d m o n it o ri n g
o f m a n u fa ct u ri n g a ct iv it ie s.
IT in
a d m in is tr a ti v e o r o ff ic e w o rk
T u rb a n et
a l. (2 0 0 2 ), M a rt in ez -
L o re n ze
(2 0 0 3 )
T h is cr it er io n re fe rs
to th e u se
o f IT
to h el p a d m in is -
tr a ti v e o r o ff ic e w o rk
li k e o rg a n iz in g d o cu m en ts
o rg a n iz in g a n d st o ri n g d a ta
et c.
Assessing the impact of information technology on firm performance 2707
(very frequently used). In IT and performance literature, measuring IT in
organizations using subjective criteria is mainly carried out by researchers such as
Grover et al. (1998), Pinsonneault (1998) and Martinez-Lorenze (2003). In these
researches reliability and validity of such criteria are shown.
3.2.2 Performance measurement (PER). Researchers who have conducted the same studies as ours have reported that the number of people inclined to answer objective
questions about performance is usually 100% smaller than those who are motivated
to respond to subjective questions (Porter 1979, Vickery et al. 1993, Ward et al.
1994). Thus we have used Likert scale questions from subjective measures to evaluate
performance. To assess organizational performance we have defined measures in relation with
customer results, people results, operational results and growth using different
sources. We have used four different criteria for measuring performance (see table 4).
The first two questions concerning customer satisfaction and relationship are taken
from Froza (1995) and organizational elevation model from the European
Foundation for Quality Management (EFQM) (1999). The mean value for these two questions is termed ‘customer results’. The second criterion for measuring
performance consists of two questions that have been used to evaluate worker
satisfaction and performance. The mean value for these two is named ‘people
results’. These two questions are also taken from EFQM (1999). In the third
criterion, six questions for measuring improvement in flexibility, delivery, quality, cost, defective rates and cycle time have been taken from Froza (1995) and
Swamidass and Kotha (1998). The mean value for these questions is named
‘operational results’. The last criterion consists of two questions, which evaluate the
growth of the company in sales and return of investment (ROI). The respondents are
required to specify the condition of their company in comparison with four years
ago. The response is indicated through a seven-point Likert scale of 1 (significantly lower) to 7 (significantly higher).
Table 4. PER variable.
Measurement criteria Source Definition
Customer results Froza (1995), EFQM (1999)
Customer satisfaction of product quality and better customer rela- tionship are measured with this criterion.
People results EFQM (1999), Martinez-Lorenze (2003)
This criterion is used to measure worker satisfaction and performance.
Operational results Swamidass (1998), Froza 91995), Martinez- Lorenze (2003), Boyer et al. (1997)
It is used to measure improvement rate of flexibility, delivery, quality, cost, defectives, and time cycle.
Growth Martinez-Lorenze (2003), Boyer et al. (1997)
With this criterion, the growth rate in sales and return of investment (ROI) is evaluated.
2708 A. Albadvi et al.
3.2.3 Organizational infrastructure measures (OIS). This part of the questionnaire is also designed to measure the degree to which the company is involved in creating IT organizational infrastructures. The measures of this part are taken from works of Boyer (1997), Froza (1995), Lau et al. (2001), Ward et al. (1994), Pinsonnseault and Kramer (1997), Flynn et al. (1994), Brynjolfsson and Hitt (2000), EFQM (1999). The extent of involvement in creating seven organizational infrastructures including work empowerment, decentralization, training, team work, process management and customer relationship, changes in supplier relationship and leadership have been measured using 7-point Likert-type scale from ‘no involvement’ to ‘complete involvement. In table 5 a summary of measurement criteria for research variable, ‘organizational infrastructure’, is presented.
3.2.4 Business process reengineering measures (BPRM). The ranges of transforma- tions in eight business processes have been measured using 7-point Likert-type scale from ‘no change’ to ‘basic changes’. These business processes have been taken from Gunasekaran and Nath (1997, pp. 96–97). They have classified the most important processes in service and manufacturing companies. These include the following processes: order flow, strategic planning, product, marketing and sales, services, accounting, personnel and technology. In Appendix 1, assessment method of transformations of every one of the processes is given. In table 6 a brief account of measuring criteria of the mediator variable of this research (BPR) is presented.
In Appendix 1, the questionnaire used as data collection instrument in this study is presented. Measurement instrument in this questionnaire are developed based on the above definitions.
3.3 Pre-testing
To improve the validity and reliability of research data; pre-testing was conducted before sending questionnaires to respondents. In order to control elements such as understanding, number, order, sensitiveness, and required time of questions, initial personal interviews with eight experts (including academic and industrial experts) were held. First, we asked two experts for any modifications. After applying their views, the test was administered for the second time. When the last two experts did not have any significant points to add, we stopped the modification process.
3.4 Pilot-testing
After pre-testing, the questionnaire was sent to a group of 12 respondents in positions similar to those of final respondents. They were asked to answer the questions and suggest any modifying views concerning our questions. We then applied slight modifications and prepared the final draft.
3.5 Reliability and validity analysis
The reliability analysis of a questionnaire determines its ability to yield the same results on different occasions and validity refers to the measurement of what the questionnaire is supposed to measure (Cooper and Schindler 2003).
Assessing the impact of information technology on firm performance 2709
T a b le
5 .
‘O IS ’ v a ri a b le .
M ea su re m en t cr it er ia
S o u rc e
D ef in it io n
D el eg a ti o n o f p o w er
W a rd
et a l. (1 9 9 4 )
In h u m a n re so u rc e m a n a g em
en t d is cu ss io n s, d el eg a ti o n o f p o w er
is d ef in ed
a s g ra n ti n g w id es p re a d re sp o n si b il it ie s fo r ex ec u ti o n
a n d co n tr o l o f a ct iv it ie s re la ti n g to
w o rk er s’ li fe .
D ec en tr a li za ti o n
P in so n n ea u lt et
a l. (1 9 9 7 )
D ec en tr a li za ti o n re la te s to
re te n ti o n o r d el eg a ti o n o f d ec is io n
m a k in g o r o rd er -i ss u in g in
th e o rg a n iz a ti o n . It
cr ea te s m o re
fl ex ib il it y th ro u g h w h ic h o rg a n iz a ti o n a l d ep a rt m en ts
a n d u n it s
ca n b et te r in te ra ct
w it h in te rn a l a n d ex te rn a l p er ip h er y .
T ra in in g
L a u et
a l. (2 0 0 1 )
In o rd er
to en su re
th a t w o rk er s p o ss es s en o u g h th eo re ti ca l
k n o w le d g e a n d n ec es sa ry
in st ru m en ts
to ef fi ci en tl y ta k e th ei r
re sp o n si b il it ie s, th ey
sh o u ld
b e g iv en
es se n ti a l tr a in in g L eu
et a l. (2 0 0 1 ), L a u et
a l. (2 0 0 1 ) h a v e st re ss ed
th a t w o rk in g
cu lt u re
in co o p er a ti o n w it h te ch n o lo g y , in
w h ic h o p en
re la ti o n sh ip
w it h co -w
o rk er s, im
p ro v ed
co o p er a ti o n a n d
co n st a n t tr a in in g a re
o f g re a t im
p o rt a n ce .
T ea m
w o rk
P in o n n se a u lt et
a l. (1 9 9 7 )
W o rk
sh a ri n g in
w o rk
te a m s a n d th e ex is te n ce
o f m a tr ix
st ru ct u re
fo rm
a si g n if ic a n t a p p ro a ch
in th e o rg a n iz a ti o n ca n le a d to
im p ro v ed
p er fo rm
a n ce .
P ro ce ss
m a n a g em
en t a n d
cu st o m er
re la ti o n sh ip
F ly n n et
a l. (1 9 9 4 ),
B ry n jo lf ss o n a n d H it t
(2 0 0 0 ), E F Q M
(1 9 9 9 )
P ro ce ss
m a n a g em
en t fo cu se s o n d ir ec ti n g b u si n es s p ro ce ss es
b a se d o n cu rr en t a n d fu tu re
n ee d s o f cu st o m er s.
C h a n g es
in tr a n sa ct io n w it h su p p li er s
B ry n jo lf ss o n a n d H it t (2 0 0 0 )
T ec h n o lo g ie s su ch
a s el ec tr o n ic d a ta
in te ra ct io n (E D I) , a n d o th er
in tr a o rg a n iz a ti o n a l in fo rm
a ti o n sy st em
s h a v e si g n if ic a n tl y
re d u ce d co st , ti m e a n d o th er
p ro b le m s o f in te ra ct io n w it h
su p p li er s, O rd er in g , in v o ic e is su in g , a n d st o ck
co n tr o l a re
a m o n g fa ct o rs
th a t ch a n g e w it h in fo rm
a ti o n te ch n o lo g ie s
L ea d er sh ip
P in so n n ea u lt et
a l. (1 9 9 7 ),
F ly n n et
a l. (1 9 9 4 )
In o rd er
to su cc es sf u ll y ex ec u te
im p ro v em
en t p la n s, to p
m a n a g em
en t is su p p o se d to
ta k e le a d er sh ip
re sp o n si b il it ie s li k e
re la ti o n sh ip
w it h w o rk er s, en co u ra g em
en t a n d p ro m o ti o n .
T h er e is g re a t a m o u n t o f sy n er g y b et w ee n IT
a n d im
p ro v em
en t
p la n s su ch
a s T Q M
a n d B P R .
2710 A. Albadvi et al.
3.5.1 Reliability. In order to assess the reliability of instrument, we have calculated Cronbach’s alpha for criteria of research variables [IT application (ITU) including four criteria; the influence of IT in process reengineering (BPRM) including eight criteria; practical diligence in applying organizational infrastructures (OIS) including seven criteria; and finally improvement of performance (PER) including four criteria]. The strategic planning criterion (INSE) from OIS variable is the only criterion with an alpha of 60% that does not in fact possess acceptable reliability. Eliminating a measure, reliability index will increase to an acceptable level over 70% [see table 7(a)]. It is now time to assess the validity of instrument.
3.5.2 Validity analysis. Construct validity, content validity and predictive validity were analysed to ensure the validity of the instruments (Nunnally and Bernstein 1994).
Table 6. ‘BPRM’ variable.
Measurement criteria Source Definition
Order flow Gunase Karan, Nath (1997, pp. 96–97)
Order flow includes activities such as supply, product assembly, manufac- turing production, ordering, place and installation of the product. Notice that the role of IT in this process is defined in terms of basic activities, objectives or customer needs.
Strategic planning Strategic planning process is a blend of formulating strategy and planning of organizational structure. In this pro- cess we need not only external analy- sis but also analyses of the data with in the organization.
Product Product process includes planning activities, engineering and design.
Marketing and sales This process includes customer satisfac- tion, market survey anticipation and decision-making about product makeup.
Services This includes maintenance and repair of products, after sales services and quality control.
Accounting Accounting process includes product pricing, budgeting, and making deci- sions for purchase or manufacturing.
Personnel This process involves various units such as employment, selection, promotion systems, and performance upgrading.
Technology Technology process includes selection, installation, establishment and dispo- sal of the factory or its equipment. There are many uses for decision- making support systems and multi- media systems.
Assessing the impact of information technology on firm performance 2711
T a b le
7 (a ).
V a li d it y in d ex
a n d fa ct o r a n a ly si s o f v a ri a b le
B P R M .
V a ri a b le
M ea su re m en t
# o f
m ea su re s
# o f el im
in a te d
m ea su re s
N M ea n
S td .
d ev ia ti o n
A lp h a
E ig en v a lu e
% fr o m
to ta l
v a ri a n ce
T h e im
p a ct
o f
IT a p p li ca ti o n o n
b u si n es s p ro ce ss
re e n g in e e ri n g
(B P R M )
B u si n es s p ro ce ss
o f o rd er
fl o w : B P O F
5 0
9 7
5 .2 2
1 .0 5
0 .7 1 9 4
2 .5 4 9
5 0 .9 7 8
B u si n es s p ro ce ss
o f st ra te g y : B P S T
2 0
9 6
4 .8 6
1 .5 7
0 .8 2 4 6
1 .7 0 3
8 5 .1 5 2
B u si n es s p ro ce ss
o f p ro d u ct : B P P R
3 0
9 7
5 .5 7
1 .0 8
0 .7 0 8 2
1 .9 5 4
6 5 .1 3 5
B u si n es s p ro ce ss
o f m a rk et in g
a n d sa le s: B P M S
4 0
9 7
4 .9 2
1 .3 7
0 .8 7 7 3
2 .9 3 5
7 3 .3 8 4
B u si n es s p ro ce ss
o f se rv ic es : B P S E
3 0
9 7
5 .3 0
1 .1 9
0 .7 1 9 1
2 .0 0 1
6 6 .7 0 6
B u si n es s p ro ce ss
o f a cc o u n ti n g : B P A C
3 0
9 7
5 .2 5
1 .2 9
0 .8 1 2 6
2 .1 8 7
7 2 .9 0 1
B u si n es s p ro ce ss
o f p er so n n el : B P P E
4 0
9 7
4 .7 8
1 .2 5
0 .8 4 8 8
2 .7 8 4
8 9 .6 0 3
B u si n es s p ro ce ss
o f te ch n o lo g y : B P T E
2 0
9 7
4 .8 3
1 .5 7
0 .8 6 3 1
1 .7 6 0
8 7 .9 7 9
T o ta l B P R M
9 3
5 .0 9
1 .3 0
A n a lp h a o f b el o w
0 .7
a n d o v er
0 .6
fo r n ew
in st ru m en ts
is a cc ep ta b le
(N u n n ly
1 9 8 7 ).
A n a lp h a o f b el o w
0 .6
is n o t a cc ep ta b le .
2712 A. Albadvi et al.
Construct validity shows the extent to which measures of a criterion are
indicative of the direction and size of that criterion (Flynn et al. 1994). It also shows
that the measures do not interfere with measures of the other criteria (Flynn et al.
1994). Construct validity of measurement instrument is analysed through factor
analysis. In this study each measurement criterion is considered as a distinct
construct. The most common decision-making technique to obtain factors is to
consider factors with eigenvalue of over one as significant (Olson et al. 2005, Hair
et al. 1998). Factor analysis shows that ITPO, ITDS and ITAD possess more than one factor
with eigenvalue of over one. Eliminating ITDS3 solved the problem with ITDS.
Concerning ITPO and ITAD factor analysis indicates three and two factors for each
of these measures respectively [see tables 7(b) and 7(c)]. The type and definition of questions show that ITPO has three latent variables
including IT in planning, IT in operation and IT in quality control [see table 7(b)
below]. ITAD also has two latent variables including IT in administrative affairs and
IT in financial affairs [see table 7(c)]. To ensure instrument reliability we have calculated reliability indexes for all
final criteria again. Table 7(d) shows that all criteria of variable ITU except criteria of IT in
administrative and financial affairs have an alpha of over 0.7. An alpha of 0.6 was
Table 7(c). Factor loadings for ITPO.
ITPO criterion Factor 1 Factor 2 Factor 3
Measures of ITPO New code IT in planning IT in operations IT ion quality control
ITPO4 ITPO1.4 0.864394 0.100607 0.000795 ITPO5 ITPO1.5 0.768977 0.297352 �0.00291 ITPO11 ITPO1.11 0.744054 0.17913 0.171894 ITPO3 ITPO1.3 0.543544 0.178223 0.113729 ITPO8 ITPO2.8 0.319612 0.803941 0.083888 ITPO7 ITPO2.7 0.261655 0.799537 0.019016 ITPO9 ITPO2.9 0.090871 0.723657 �0.10322 ITPO13 ITPO3.13 0.057749 0.027447 0.935693 ITPO12 ITPO3.12 0.144478 �0.06436 0.923877
Table 7(b). Factor loadings for ITAD.
ITAD criterion Factor 1 Factor 2
Measures of ITAD New code IT in financial pecuniary affairs IT in administrative affair
ITAD10 ITAD2.10 0.841349 0.098666 ITAD8 ITAD2.8 0.782807 0.22032 ITAD9 ITAD2.9 0.728648 0.087321 ITAD7 ITAD1.7 0.066869 0.752603 ITAD6 ITAD1.6 0.040672 0.740113 ITAD2 ITAD1.2 0.114139 0.632419 ITAD1 ITAD1.1 0.389275 0.496301 ITAD5 ITAD1.5 0.188359 0.463711
Assessing the impact of information technology on firm performance 2713
T a b le
7 (d ).
V a li d it y in d ex
a n d fa ct o r a n a ly si s fo r IT
U v a ri a b le .
V a ri a b le
M ea su re m en t cr it er io n
# o f m ea su re s # o f el im
in a te d
m ea su re s
N M ea n
S td .
d ev ia ti o n
A lp h a
E ig en v a lu e %
fr o m
to ta l
v a ri a n ce
In fo rm
a ti o n
te ch n o lo g y
u se
(I T U )
IT in
co m m u n ic a ti o n s IT
C O
8 2
9 6
4 .3 7
1 .3 2
0 .7 6 7 3
2 .9 4 5
4 9 .0 8 6
IT in
p ro d u ct io n a n d
o p er a ti o n : IT
P O
IT in
p la n n in g
1 3
4 9 7
4 .4 3
1 .4 0
0 .7 5 2 1
2 .3 1 4
5 7 .8 5 3
IT in
o p er a ti o n
9 6
3 .9 2
1 .6 3
0 .7 1 0 6
1 .9 2 9
6 4 .3 0 6
IT in
q u a li ty
co n tr o l
9 7
5 .8 9
1 .4 8
0 .8 6 2 1
1 .7 6 0
8 8 .0 0 1
IT in
d ec is io n m a k in g a n d su p p o rt : IT
D S
4 1
9 7
3 .0 5
1 .5 1
0 .7 7 4 9
2 .1 0 2
7 0 .0 6 7
IT in
a d m in is tr a ti o n :
IT A D
IT in
a d m in is tr a ti o n
1 0
2 9 7
4 .5 2
1 .0 2
0 .6 3 6 4 *
2 .0 8 9
4 1 .7 7 5
IT in
p ec u n ia ry
a ff a ir s
9 7
5 .9 8
1 .0 4
0 .6 9 3 6 *
1 .9 6 1
6 5 .3 5 4
T o ta l IT
U 9 7
4 .5 9
0 .8 5
A n a lp h a o f b el o w
0 .7
a n d o v er
0 .6
fo r n ew
in st ru m en ts
is a cc ep ta b le
(N u n n ly
1 9 8 7 ).
A n a lp h a o f b el o w
0 .6
is n o t a cc ep ta b le .
2714 A. Albadvi et al.
obtained in criteria of IT in administrative and financial affairs. This is acceptable with regard to the fact that the criterion is new. This table also shows that some measures have been eliminated because they do not focus on one specific factor. The column for the percentage from total variance shows what percentage of total variance is covered by the relating factor. Except for IT in administrative affairs, all other criteria indicate a considerable percentage of the total variance. This produces a rather good construct validity for this variable.
A summary of calculations relating to reliability and validity indices of variable OIS is shown in table 7(e). Except for criterion INEM, other criteria have an alpha of over 0.7 and INEM also has an alpha of over 0.6. Therefore, all criteria possess an acceptable reliability index. Factor analysis also shows that all criteria lie on a factor with eigenvalue of over one. The only factor for each one of the criteria indicates a high percentage from the total variance (except for INEM). This table also shows that a measure from strategy criteria is eliminated owing to results from factor analysis.
In table 7(a) validity factor analysis results for BPRM variable are shown. These results indicate that all criteria of BPRM have an alpha of over 0.7, and all criteria only have a factor with an eigenvalue of over one. The column for the percentage from total variance also shows rather good construct validity for this variable.
The results of examining validity and reliability of variable PER are shown in table 7(f). As it is seen in this table, all criteria have an alpha of over 0.7 except for company’s growth rate (PEGR) that also has an alpha of near 0.7. One of the measures relating to PEOP is eliminated to place all instruments on one factor.
Content validity indicates meeting the specific range of contents that have been selected (Nunnally and Bernstein 1994). It also shows that measurement instruments have elements that cover all aspects of variables under measurement. Content validity cannot be numerically measured, but we can measure it subjectively and judgmentally. Basically, content validity depends on the appropriateness of the content and the method of rendering (Nunnally and Bernstein 1994). Since the selection of research variables is based on an intensive survey of literature and all the elements are supported by authentic research, the instrument has content validity. Furthermore, academic and industrial experts have examined the content of the questionnaire during the pre-testing.
Predictive validity is in fact the correlation between measurement instrument and an independent variable taken from relating criteria (Nunnally 1978). This validity is only possible through correlation between the predictor (independent variable) and criterion (dependent) variable (Nunnally and Bernstein 1994). In this study, the results of two-variable and multi-variable correlation between ITU as independent variables and PER as dependent variable have shown that there is significant correlation between intended criteria under measurement in this study.
3.6 Non-response bias test
Two time-dated groups were used to test for non-response bias test (Cooper 2003). First-group returns were received within one month after the survey was sent out (we had asked respondents to answer no later than one month, after they received the questionnaire). Subsequent responses, coded as second-group returns, were received after the reminder letters had been sent out to the managers to follow.
Assessing the impact of information technology on firm performance 2715
T a b le
7 (e ).
V a li d it y in d ex
a n d fa ct o r a n a ly si s o f v a ri a b le
O IS .
V a ri a b le
M ea su re m en t
N o . o f
m ea su re s
N o . o f el im
in a te d
m ea su re s
N M ea n
S td .
d ev ia ti o n
A lp h a
E ig en v a lu e
% fr o m
to ta l
v a ri a n ce
P ra ct ic a l d il ig en ce
fo r o rg a n iz a ti o n a l
in fr a st ru ct u re s (O
IS )
E m p o w er m en t: IN
E M
4 0
9 7
4 .9 8
0 .9 8
0 .6 3 4 5
1 .9 1 1
4 7 .7 7 3
D ec en tr a li za ti o n : IN
D E
5 0
9 6
4 .9 1
1 .0 2
0 .8 4 9 2
3 .1 6 7
6 3 .3 4 9
T ra in in g : IN
T R
3 0
9 7
5 .5 5
1 .0 1
0 .8 4 7 3
2 .3 0 0
7 6 .6 8 0
G ro u p w o rk : IN
G O
2 0
9 7
5 .5 1
1 .2 0
0 .7 5 1 8
1 .6 1 0
8 0 .4 8 0
P ro ce ss
m a n a g em
en t: IN
P C
7 0
9 7
6 .1 4
0 .7 9
0 .8 8 9 0
4 .2 5 6
6 0 .8 0 2
C h a n g e in
in te ra ct io n s w it h
su p p li er s: IN
S U
3 0
9 7
5 .9 3
0 .9 3
0 .7 9 4 5
2 .1 6 2
7 2 .0 6 7
L ea d er sh ip : IN
L E
4 1
9 7
6 .1 5
0 .8 2
0 .7 1 8 6
1 .9 4 4
6 4 .8 0 1
T o ta l O IS
9 3
5 .6 0
0 .9 7
A n a lp h a o f b el o w
0 .7
a n d o v er
0 .6
fo r n ew
in st ru m en ts
is a cc ep ta b le
(N u n n ly
1 9 8 7 ).
A n a lp h a o f b el o w
0 .6
is n o t a cc ep ta b le .
2716 A. Albadvi et al.
T a b le
7 (f ).
V a li d it y in d ex
a n d fa ct o r a n a ly si s o f v a ri a b le
P E R .
V a ri a b le
M ea su re m en t cr it er ia
N o . o f
m ea su re s
N o . o f el im
in a te d
m ea su re s
N M ea n
S td .
d ev ia ti o n
A lp h a
E ig en v a lu e
P er ce n ta g e fr o m
to ta l v a ri a n ce
P er fo rm
a n ce :
(P E R )
C u st o m er
re su lt s: P E C O
2 0
9 7
6 .1 4
0 .9 2
0 .7 4 1 7
1 .5 9 6
7 9 .7 8 4
E m p lo y ee
re su lt s: P E E M
2 0
9 7
5 .4 6
0 .9 3
0 .7 7 5 6
1 .6 3 8
8 1 .8 7 7
O rg a n iz a ti o n a l p er fo rm
a n ce
re su lt s: P E O P
6 1
9 7
5 .9 7
0 .8 1
0 .8 5 8 7
3 .2 0 3
6 4 .0 6 3
C o m p a n y ’s g ro w th
ra te : P E G R
2 0
9 7
5 .4 0
1 .0 8
0 .6 8 1 0 *
1 .5 5 8
7 7 .8 7 6
T o ta l P E R
9 7
5 .8 1
0 .7 6
T o ta l P E R * (P E G R
el im
in a te d )
9 7
5 .9 0
0 .7 8
* A n a lp h a o f b el o w
0 .7
a n d o v er
0 .6
fo r n ew
in st ru m en ts
is a cc ep ta b le
(N u n n ly
1 9 8 7 ).
A n a lp h a o f b el o w
0 .6
is n o t a cc ep ta b le .
Assessing the impact of information technology on firm performance 2717
To test the non-response bias, time-dated groups were compared with variables. No t-tests were statistically significant at the 0.05 level. These results show that findings can be generalized to the sample.
3.7 Method of analysis
The method of analysis is applied at three levels of study. First, data are examined and some descriptive statistics obtained in order to obtain an overview of the characteristics of the sample and to assess issues such as mean and standard deviation. This analysis examines the scales as independent entities to determine the extent of use of IT in sample companies, company’s performance, the extent of use of IT in BPR and the degree to which the company cares for creating IT organizational infrastructures. Second, bivariate correlations between variables are analysed with respect to the correlation between scales of IT use and company performance measures, and also two intervening variables. This aspect of the analysis forms a basis to examine the existence of association between the dependent, independent and intervening variables. The final stage of the analysis adopts a regression analysis. The variables are drawn together in the application of regression analysis to investigate the relationship between the extent of use of IT and company performance with considering the role of intervening variables. In particular, it examines the research hypothesises.
4. Empirical results
4.1 Univariate analysis
4.1.1 IT usage (ITU). This section highlights the extent of the use of IT in sample companies. Table 7(d) shows the total use of IT exceeded from moderate level (4.59). This table shows that the highest amount of IT usage is in the ‘IT in pecuniary affairs’ (5.98) closely followed by ‘IT in quality control’ (5.89). IT applications in pecuniary affairs are one of the eldest applications of IT (Turban 2002) and numerous software applications are developed and used in companies, inexpensively. Also, implementing a quality management system (such as ISO 9000, QS 9000) is one of the requirements of car part suppliers in Iran. These companies use IT applications for gathering and analysing quality data. Table 7(d) indicated that only ‘IT in decision support systems’ is used less than moderate level (3.05). Decision-support systems are more advanced and more expensive than the other type of IT applications in table 7(d).
4.1.2 Emphasize on organizational infrastructure (OIS). Table 7(e) indicates that companies under study pay considerable attention to organizational infrastructures. The total average of variable OIS is exceeded from the moderate level (5.60). Table 7(a) shows that all of the criteria of OIS variables are above 4.9 on a seven- point Likret scale. The ‘leadership’ has been emphasized at the highest level (6.14) followed closely by the ‘process management’ (6.14) and ‘Change in interactions with
2718 A. Albadvi et al.
suppliers’(5.93). Although the decentralization has the lowest mean of emphasis, the mean of this criterion is exceeded significantly from the moderate level (4.09).
4.1.3 The impact of IT application on business process reengineering
(BPRM). Table 7(a) indicates respondents’ perspectives of the influence of IT on their business process transformation. Table 7(e) shows that IT applications affect all of the business processes more than the moderate level (3.5). IT has the highest effect on ‘business process of product’ (5.57). The ‘business process of personnel’ has the lowest mean of IT effects (4.78). Table 7(e) summarize total effects of IT on all eight-business processes.
4.1.4 Company performance (PER). In this study we asked respondents to rate their plant’s position with respect to competitors on a seven-point Likert scale. Table 7(f) shows that most of the respondents recognized themselves as highly competitive. They recognized the most competitive improvement in ‘Customer results’ (6.14), in descending order, followed by ‘organizational performance results’(5.97), ‘employee results’(5.46) and ‘Company’s growth rate’ (5.40) (table 7(f)).
Consequently, the results of the univariate analysis indicate that four variables considerably exceeded moderate level in the sample companies of this study.
4.2 Bivariate correlation analysis
This section shows the results of testing the correlation between four research variables including amounts of use of IT (ITU), company performance (PER), practical diligence to organizational infrastructures (OIS) and the effects of IT on business processes reengineering (BPRM) (table 8(a)). Altogether, all of the bivariate correlations in tables 8(a), 8(b) and 8(c) are positive and statistically significant except the correlation between ‘growth rate (PEGR)’ and ‘IT in communication (ITCO)’ as well as ‘IT in production and operation (ITPO)’. Consequently, ‘growth rate (PEGR)’ scale has been deleted from the later analysis, because bivariate statistically significant correlation is essential for the special type of regression analysis in this paper. Tables 8(a)–8(c) show the values of the bivariate Pearson’s correlation coefficients (r) and respective statistical significant levels (p). Following these results, it appears logical to pursue regression analysis.
4.3 Findings about moderating effects of OIS
The procedure that is used to test the moderating effect of organizational infrastructures on relationship between IT usage and company performance is hierarchical regression analysis. Boyer et al. (1997), Cohen and Cohen (1975), Miller and Droge (1986), Stone and Hollenbeck (1989), Dean and Snell (1991), Baron and Kenny (1986) have suggested this procedure for this kind of research. This procedure facilitates an analysis of the effects of groups of variables in an incremental, controlled manner (Boyer et al. 1997). In order to test the moderating effect of each of the seven organizational infrastructure scales, seven regression equations are applied and analysed. This procedure is used to conduct seven separate
Assessing the impact of information technology on firm performance 2719
T a b le
8 (a ).
B iv a ri a te
co rr el a ti o n s b et w ee n IT
U sa g e a n d co m p a n y p er fo rm
a n ce .
C ri te ri o n
C u st o m er
re su lt s
(P E C U )
E m p lo y ee
re su lt s (P E E M )
P er fo rm
a n ce
(P E O P )
G ro w th
ra te
(P E G R )
T o ta l P E R *
(P E G R
el im
in a te d )
IT in
co m m u n ic a ti o n s:
IT C O
r 0 .3 0 2 y
0 .2 6 9 y
0 .3 1 8 y
0 .1 4 4
0 .3 3 5 y
p 0 .0 0 3
0 .0 0 8
0 .0 0 2
0 .1 6 2
0 .0 0 1
N 9 6
9 6
9 6
9 6
9 6
IT in
p ro d u ct io n
a n d o p er a ti o n : IT
P O
IT in
p la n n in g : IT
P O I
r 0 .4 2 4 y
0 .4 2 8 y
0 .4 4 9 y
0 .1 0 3
0 .4 8 2 y
p 0 .0 0 0
0 .0 0 0
0 .0 0 0
0 .3 1 4
0 .0 0 0
N 9 7
9 7
9 7
9 7
9 7
IT in
o p er a ti o n : IT
P O II
r 0 .2 0 2 *
0 .3 7 7 y
0 .3 4 5 y
0 .1 6 4
0 .3 5 4 y
p 0 .0 4 9
0 .0 0 0
0 .0 0 1
0 .1 1 1
0 .0 0 0
N 9 6
9 6
9 6
9 6
9 6
IT in
q u a li ty
co n tr o l: IT
P O II I
r 0 .2 6 3 y
0 .2 9 9 y
0 .2 7 2 y
0 .0 9 6
0 .2 9 3 y
p 0 .0 0 9
0 .0 0 3
0 .0 0 7
0 .3 5 2
0 .0 0 4
N 9 7
9 7
9 7
9 7
9 7
IT in
d ec is io n su p p o rt : IT
D S
r 0 .2 4 6 *
0 .3 3 6 y
0 .2 9 0 y
0 .1 0 4
0 .3 2 1 y
p 0 .0 1 5
0 .0 0 1
0 .0 0 4
0 .3 1 2
0 .0 0 1
N 9 7
9 7
9 7
9 7
9 7
IT in
a d m in is tr a ti o n :
IT A D
IT in
a d m in is tr a ti v e a ff a ir : IT
A D I
r 0 .4 2 8 y
0 .3 7 5 y
0 .4 6 0 y
0 .2 2 3 *
0 .4 7 6 y
p 0 .0 0 0
0 .0 0 0
0 .0 0 0
0 .0 2 8
0 .0 0 0
N 9 7
9 7
9 7
9 7
9 7
IT in
p ec u n ia ry
a ff a ir : IT
A D II
r 0 .3 5 1 y
0 .2 8 1 y
0 .4 2 7 y
0 .2 1 4 *
0 .4 1 6 y
p 0 .0 0 0
0 .0 0 5
0 .0 0 0
0 .0 3 5
0 .0 0 0
N 9 7
9 7
9 7
9 7
9 7
T o ta l IT
u sa g e:
IT U
r 0 .4 8 1 y
0 .5 3 5 y
0 .5 6 2 y
0 .2 2 8 *
0 .5 9 0 y
p 0 .0 0 0
0 .0 0 0
0 .0 0 0
0 .0 2 4
0 .0 0 0
N 9 7
9 7
9 7
9 7
9 7
* C o rr el a ti o n is si g n if ic a n t a t th e 0 .0 5 le v el
(2 -t a il ed ).
y C o rr el a ti o n is si g n if ic a n t a t th e 0 .0 1 le v el
(2 -t a il ed ).
2720 A. Albadvi et al.
hierarchical regressions: one for each of of the seven organizational infrastructure measurement scales (INEM, INDE, INTR, INGO, INPC, INSU, INLE). For each of the seven organizational infrastructure scales, this analysis is conducted in three steps:
1. In each equation, one of the organizational infrastructure scales is entered into the equation [for example INEM is entered in equation (1)].
2. Total mean of the ITU is entered into the equation. 3. Finally, the interaction between respective organizational infrastructure and
ITU are entered into the regression equation.
When these interaction terms account for a significant amount of incremental variance in the dependent variable, as measured by the t-tests for each interaction or by significance tests for the incremental F-statistic, then there is evidence to support research Hypothesis 1, that there is a moderating effect of infrastructure on the use of IT. Total mean of company performance scales (PER*) is considered as the dependent variable in each of the regression equation. Results of hierarchical regression are demonstrated in the following section.
Table 9 shows the results of a hierarchical regression with PER* as the dependent variable, the organizational infrastructure scales (for example INEM in first part of the table 9), ITU, and their interactions entered in the sequential manner described above. Results of hierarchical regression with, for example, INEM as the moderating variable will be discussed in the following paragraph. The discussion of the other moderating variables is the same as INEM.
Table 8(c). Bivariate correlations between PER, ITU and BPRM.
BPOF BPST BPPR BPMS BPSE BPAC BPPE BPTE
Total PER* (PEGR eliminated)
r 0.436 y
0.351 y
0.407 y
0.411 y
0.349 y
0.433 y
0.387 y
0.481 y
p 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 N 97 96 97 97 97 97 97 97
IT Usage: ITU r 0.354 y
0.269 y
0.406 y
0.325 y
0.333 y
0.326 y
0.327 y
0.324 y
p 0.000 0.008 0.000 0.001 0.001 0.001 0.001 0.001 N 97 96 97 97 97 97 97 97
*Correlation is significant at the 0.05 level (2-tailed). y Correlation is significant at the 0.01 level (2-tailed).
Table 8(b). Bivariate correlations between PER, ITU and OIS.
INEM INDE INTR INGO INPC INSU INLE
Total PER* (PEGR eliminated) r 0.491 y
0.410 y
0.314 y
0.221 y
0.518 y
0.395 y
0.592 y
p 0.000 0.000 0.002 0.030 0.000 0.000 0.000 N 97 96 97 97 97 97 97
IT Usage: ITU r 0.513 y
0.512 y
0.381 y
0.262 y
0.467 y
0.437 y
0.502 y
p 0.000 0.000 0.000 0.009 0.000 0.000 0.000 N 97 96 97 97 97 97 97
*Correlation is significant at the 0.05 level (2-tailed). y Correlation is significant at the 0.01 level (2-tailed).
Assessing the impact of information technology on firm performance 2721
The organizational infrastructure scale, which is entered into the model in the first step, accounts for a significant amount of variance (an R
2 of 0.241, P50.000).
The inclusion of ITU in the second step provides a significant improvement (an incremental R
2 of 0.154, P50.000), and also the interaction terms of step 3 result
in an incremental R 2 of 0.054, which is significant (P50.01). The overall effect of the
model is the explanation of 39.6% of the variance in PER*, which the associated F test indicates is significant at P50.000. Note that the interaction between ITU and INEM has a negative coefficient (�0.155). While at first glance this appears to provide evidence contradicting Hypothesis 1, an examination of table 8(b) shows that the negative coefficient is likely a result of multi-collinearity. Table 8(b) shows that the interaction between ITU and INEM has a significant, positive correlation
Table 9. Results of hierarchical regression analysis: testing moderating effects of OIS.
t-test F-test
Step Measurement scale B Statistics Sig. R 2
�R 2
Statistics Sig.
Empowerment: INEM 1 INEM 0.393 5.498 0.000 0.241 0.241 30.229 0.000 2 ITU 0.419 4.903 0.000 0.396 0.154 24.038 0.000 3 ITU*INEM �0.155 �3.026 0.003 0.450 0.054 9.155 0.003
Decentralization: INDE 1 INDE 0.315 4.354 0.000 0.168 0.168 18.953 0.000 2 ITU 0.463 5.239 0.000 0.357 0.190 27.452 0.000 3 ITU*INDE �0.147 �2.687 0.009 0.404 0.047 7.220 0.009
Overall 20.806 0.000
Training: INTR 1 INTR 0.242 3.218 0.002 0.098 0.098 10.358 0.002 2 ITU 0.504 6.147 0.000 0.357 0.259 37.782 0.000 3 ITU*INTR �0.157 �2.978 0.004 0.413 0.056 8.870 0.004
Overall 21.796 0.000
Group work: INGO 1 INGO 0.144 2.208 0.030 0.049 0.049 4.876 0.030 2 ITU 0.523 6.636 0.000 0.352 0.303 44.042 0.000 3 ITU*INGO �0.135 �2.747 0.007 0.401 0.049 7.545 0.007
Overall 20.744 0.000
Process management: INPC 1 INPC 0.510 5.897 0.000 0.268 0.268 34.778 0.000 2 ITU 0.407 5.021 0.000 0.423 0.155 25.209 0.000 3 ITU*INPC �0.164 �2.856 0.005 0.469 0.047 8.156 0.005
Overall 27.416 0.000
Change in interactions with suppliers: INSU 1 INSU 0.331 4.193 0.000 0.156 0.156 17.582 0.000 2 ITU 0.472 5.664 0.000 0.371 0.215 32.078 0.000 3 ITU*INSU �0.191 �3.629 0.000 0.449 0.078 13.168 0.000
Overall 25.251 0.000
Leadership: INLE 1 INLE 0.565 7.158 0.000 0.350 0.350 51.231 0.000 2 ITU 0.358 4.481 0.000 0.465 0.114 20.077 0.000 3 ITU*INLE �0.103 �1.821 0.072 0.483 0.018 3.317 0.072
Overall 28.975 0.000
2722 A. Albadvi et al.
with PER* when taken by itself. However, in the hierarchical regression of table 9 the inclusion of multiple variables in the model causes some of the variables to take on negative correlations, a common occurrence in regression analysis (Cooper 2003).
In short, as implied in table 9, moderating effects are observed for all of the organizational infrastructure scales (as indicated by the significance level of the interaction effect with p50.05, except for INLEA which is significant at p51).
The regression model shown in table 9 has two major implications. First, the overall result indicates that organizational infrastructure and the interactions between information technology usage and organizational infrastructure have positive associations with company performance. This outcome is important because it provides support for the proposition that practical diligence to the organizational infrastructure and the IT usage in a plant is positively associated with performance. Second, the significant incremental improvement in the model upon the addition of the interactions between ITU and OIS supports the premise that organizational infrastructures have a positive moderating effect on the relationship between ITU and performance. The results therefore support Hypothesis 1.
4.4 Findings about mediating effects of BPRM
Judd and Kenny (1981) noted that a series of regression models provides the best test of a mediating effect. To establish mediation, the following conditions must hold:
1. The independent variable must affect the mediator [equation (1)]. 2. The independent variable must affect the dependent variable [equation (2)]. 3. The mediator must affect the dependent variable equation (3). 4. If these conditions hold, then the effect of the independent variable on the
dependent variable must be less in equation (3) than in equation (2).
Table 10 contains the results of the regression equations estimated for a mediating effects model. As shown in the first row of table 10, the regression equations PER¼ f(ITU) suggests that higher IT usage is associated with higher levels of company performance improvement. Regression equations No. 1 in table 9 suggests that for total average of ITU company performance improvement are strongly associated with business process change. Table 10 shows that in descending order, the strongest associations are observed for business process of order flow (BPOF) (b¼0.324, p50.000), business process of product (BPPR) (b¼0.296, p50.000), business process of personnel (BPPE) (b¼0.242, p50.000), business process of technology (BPTE) (b¼0.239, p50.000), business process of marketing and sales (BPMS) and business process of accounting (BPAC) (b¼0.236, p50.000), business process of services (BPSE) (b¼0.230, p50.000) and business process of strategy (BPST) (b¼0.175, p50.000). The regression results seem to suggest that, to varying degrees, ITU is a positive contributor to performance. The results also suggest that process redesign with respect to ITU is directly associated with company performance improvement, a first indication of mediating effects between ITU and company performance improvement.
Where IT usage significantly affects process change [rows No. 2 in table 10: BPxx¼ f(ITU)), assessment of mediation can be made through comparison of the
Assessing the impact of information technology on firm performance 2723
regression coefficients of PER*¼ f(ITU), rows No. 1 (PER1¼f(BPxx)), and rows No. 3 (Per¼ f(ITU, BPxx).
In the case of BPOF, the beta-coefficient of equation PER*¼f(ITU) suggests that Performance is a function IT Usage (b¼0.0.540, p50.000). The coefficient of
Table 10. Results of regression analysis: testing mediating effects of BPRM.
t-test F-test
Measurement scale B Statistics Sig. R 2
Adj. R 2
SE Statistics Sig.
No. PER1¼f(ITU) 0.540 7.114 0.000 0.348 0.341 0.6358 50.607 0.000
Business process of order flow: BPOF 1 PER1¼f(BPOF) 0.324 4.726 0.000 0.190 0.182 0.70829 22.335 0.000 2 BPOF¼f(ITU) 0.437 3.691 0.000 0.125 0.116 0.99122 13.623 0.000 3 PER1¼f(ITU, BPOF) 0.456 5.856 0.000 0.407 0.394 0.60951 32.224 0.000
0.193 3.062 0.003
Business process of strategy: BPST 1 PER1¼f(BPST) 0.175 3.632 0.000 0.123 0.114 0.73810 13.190 0.000 2 BPST¼ f(ITU) 0.495 2.713 0.008 0.073 0.063 1.5173 7.359 0.008 3 PER1¼f(ITU, BPST) 0.486 6.256 0.000 0.383 0.370 0.62252 28.842 0.000
0.104 2.461 0.016
Business process of product: BPPR 1 PER1¼f(BPPR) 0.296 4.345 0.000 0.166 0.157 0.71895 18.879 0.000 2 BPPR¼f(ITU) 0.511 4.333 0.000 0.165 0.156 0.98885 18.775 0.000 3 PER1¼f(ITU, BPPR) 0.465 5.721 0.000 0.381 0.368 0.62248 28.957 0.000
0.146 2.262 0.026
Business process of marketing and sales: BPMS 1 PER1¼ f(BPMS) 0.236 4.395 0.000 0.169 0.160 0.71758 19.314 0.000 2 BPMS¼f(ITU) 0.520 3.353 0.001 0.106 0.096 1.2985 11.241 0.001 3 PER1¼ f(ITU, BPMS) 0.467 6.040 0.000 0.401 0.389 0.61228 31.507 0.000
0.141 2.906 0.005
Business process of services: BPSE 1 PER1¼f(BPSE) 0.230 3.625 0.000 0.121 0.112 0.73779 13.138 0.000 2 BPSE¼ f(ITU) 0.462 3.444 0.001 0.111 0.102 1.1243 11.864 0.001 3 PER1¼f(ITU, BPSE) 0.488 6.151 0.000 0.374 0.360 0.62631 28.031 0.000
0.113 1.976 0.051
Business process of accounting: BPAC 1 PER1¼f(BPAC) 0.263 4.687 0.000 0.188 0.179 0.70940 21.966 0.000 2 BPAC¼f(ITU) 0.492 3.361 0.001 0.106 0.097 1.2252 11.294 0.001 3 PER1¼f(ITU, BPAC) 0.459 5.999 0.000 0.413 0.400 0.60647 33.020 0.000
0.164 0.228 0.002
Business process of personnel: BPPE 1 PER1¼f(BPPE) 0.242 4.096 0.000 0.150 0.141 0.72569 16.775 0.000 2 BPPE¼f(ITU) 0.480 3.369 0.001 0.107 0.097 1.1932 11.353 0.001 3 PER1¼f(ITU, BPPE) 0.475 6.081 0.000 0.390 0.377 0.61803 30.053 0.000
0.136 2.558 0.012
Business process of technology: BPTE 1 PER1¼f(BPTE) 0.239 5.352 0.000 0.232 0.224 0.68998 28.645 0.000 2 BPTE¼f(ITU) 0.596 3.337 0.001 0.105 0.096 1.4972 11.137 0.001 3 PER1¼f(ITU, BPTE) 0.444 5.948 0.000 0.442 0.430 0.59125 37.191 0.000
0.161 3.982 0.000
2724 A. Albadvi et al.
row 2 suggests that changes in BPOF is a function of IT Usage (b¼0.437, p50.000) and the coefficients of row 3 suggest that performance improvement is a function
of IT Usage (b¼0.456, p50.000) and changes in BPOF (b¼0.193, p50.003). Since the coefficient associated with IT Usage is less in row 3 than in
equation PER*¼ f(ITU), and rows 1 and 2 are both significant, a mediating effect
is implied. This phenomenon is also observed for BPOF, BPST, BPPR, BPMS, BPSE,
BPAC, BPPE, BPTE. In summary, the results suggest that business process change is
a necessary and sufficient condition for improvements in Performance. The results
therefore support Hypothesis 2.
5. Limitations
The most important limitation of this study lies in the study’s sample size. The
study’s sample size is 112 plants (out of 200 plants). This size is considered small for
our statistical analysis. On the other hand, this size is generally used at individual
respondent level of analysis, where measures’ instability is fairly high (Froza 1995,
Hofstede et al. 1990). In the present study, each measure used, has high internal
consistency, in other words, the answers are highly correlated, and this consistency
increases the stability of measure (see table 7). Hofstede et al. (1990) state that a
lower sample size is acceptable when this kind of stable data with high internal
consistency is used. The second potential limitation lies in the process of making the research variable
of PER operational. We used four separate subjective measures to assess the company
performance. Researchers, conducting similar studies, have reported that the number
of people willing to answer objective questions on the company performance is more
than those who want to answer the subjective questions (Boyer et al. 1997, Forza 1995,
Dewhurst 2003 and Ang et al. 2001). This is most likely that the result of being
reluctant to divulge the companies’ confidential performance information somehow
undermine the findings, so we used objective, Likert scale questions to assess
performance. The third limitation of this research is about the stability of performance
measures. We have described four criteria to measure performance: ‘customer
satisfaction and relationship’ were grouped together under a new variable
‘customer results’ based on the mean value; a similar process was done to other
indicators in the questionnaire and related to ‘worker satisfaction and
performance’, labelled ‘people results’ and other six other questions labelled
‘operational results’. Although factor analysis shows that the above measures
cannot be grouped together, according to the previous studies (Froza (1995),
EFQM (1990) and Swamidass and Kotha (1998)), we grouped questions
together based on the mean value and created four above-mentioned criteria
to measure performance. The validity and reliability of the measures are
presented in table 7(f). Only company’s growth rate (PEGR) cannot show
acceptable Alpha (reliability index), consequently, PEGR is eliminated from our
analysis.
Assessing the impact of information technology on firm performance 2725
6. Conclusions and discussions
6.1 Measurement instrument
In this study, measurement instruments of the impact of IT on the performance of manufacturing companies regarding the role of intervening variables including organizational infrastructures and business processes reengineering have been developed and their reliability and validity, based on a survey in 200 companies of car part manufacturers in Iran, have been assessed. In order to achieve this, four variables have been examined: the application of IT as independent variable, firm performance as dependent variable, the impact of IT on transformation as mediator and finally organizational infrastructures as moderator variable. We have defined and mentioned all measurement criteria and their applications in the literature. Their validity and reliability have been tested and modified accordingly. Ultimately, we have introduced valid and reliable criteria (seven for ITU variable, three for firm performance, eight for the impact of IT on reengineering, and eight for organizational infrastructures). Some criteria were initially defined to be used in measuring the application of IT in companies. The defined criteria are: IT in communications, IT in production and operation, IT in administration and office work, and IT in decision-making.
Although the criteria used in other studies have been proven valid and reliable, using confirmatory factor analysis (CFA) with regard to latent structure among these criteria, we found new dimensions in the application of IT in companies under study. The new criteria resulting from this study are: IT in communications, IT in planning, IT in operation, IT in quality control, IT in decision-making, IT in financial affairs and IT in administration and office work.
Another important point about measurement instrument in this study is that measures for measuring the impact of IT on business processes reengineering have been created. The impact of IT on business processes and reengineering of processes has been investigated in many studies, but valid measures for quantitative measurement of this impact have not been reported. Only one study (Grover et al. (1998)) examined the impact of IT on transformation in business processes adopting quantifiable methods. The difference between their criteria and the ones defined in this study is that in their study the impact of ten ITs including email, electronic data interchange, the internet, client/server, RDBMS, LAN (local area network). Imaging technology has been matured, but in our study we have measured the impact of IT on processes of order flow, strategy product, marketing and sales, services, accounting, personnel and technology. The variables used in this study are the result of qualitative research and case studies, but have never been quantitatively used in a survey. The growth of qualitative research concerning the impact of IT and reengineering of processes has led to the conception of these criteria and paved the way for the employment of such criteria in quantitative research. Validity and reliability of these criteria are proved in this study.
6.2 OIS moderating effect
Results of this study prove the moderating effect of organizational infrastructures in the relationship between IT and firm performance. In fact, this study shows that
2726 A. Albadvi et al.
practical diligence for organizational infrastructures including work empowerment,
decentralization, training, teamwork, process management and customer relation-
ship, changes in supplier relationship and leadership, strengthen the relationship
between IT and firm performance. These results are consistent with the study of
Boyer et al. (1997): the only difference is that they did not consider the role of process
management and customer relationship, changes in supplier relationship in their
study. First, we considered Empowerment as an organizational infrastructure.
Management information systems (MIS) and email simplify communication and
interchange of reports between different organizational levels. Utilization of IT
enables top management to have direct control over different executive organiza-
tional levels and have access on the summarized and graphical reports of their
subordinates. Therefore, organizations can decrease the middle management and
bureaucracy; in return, management should give more authority and power to the
employees in production and operations planning and control. These results
regarding empowerment are consistent with the study of Pinsonneault and Rivard
(1998), which evaluate the effects of IT on managerial nature. Decentralization is the second organizational infrastructure in this study.
Decreasing the middle management levels require the increase in the authority of
reminder of the middle management levels; it means organizations should try to give
decision power in cases of human resource, financial and operations management to
the reminder levels of middle management. Results of decentralization criterion are
in consistent with the study of Boyer et al. (1997). Continuous training of employees improves the utilization of IT and means that
an improvement is expected in their productivity. We considered teamwork as
the next organizational infrastructure in our study. Nowadays technologies such as
group-wares, the internet, intranet, email, and EDI facilitates and improves the
teamwork in organizations. On the other hand, advantages such as synergy and
knowledge sharing in teamwork encourage the teamwork in organizations. This
study shows that group projects and matrix organizational structure are necessary to
realize IT potential. Results of training and teamwork are in consistent with the
study of Lau et al. (2001). Process management is another IT organizational infrastructure. Process
management can be implemented through quality management systems in
accordance with ISO 9000: 2000 or another TQM program. In this approach
business processes are defined according to customer needs. Evaluation criteria are
defined and measured according to processes. IT systems such as process flow
management facilitate process management approach. These systems could be used
to collect data for evaluating the performance and analysis and present the results
of evaluation. Brynjolfsson and Hitt (2000) considered the change in interactions between firm
and customers and also suppliers as one of the requirements in improving the
organizational IT productivity. We considered above-mentioned changes as
organizational infrastructures and proved the moderating effects of those changes
in relationship between IT and firm performance. IT systems such as EFT (electronic
found interchange) and EDI (electronic data interchange) facilitate the processes
of ordering, billing, receipt, and money exchange. Also, the inter-organizational,
Assessing the impact of information technology on firm performance 2727
customer relationship management (CRM), and supply chain management (SCM) systems are more applicable in this category.
Leadership is considered as the last organizational infrastructures to realize the IT potentials in our study. The results of this research show that top management commitment in continual improvement of processes, training and motivating all employees in participating in enhancement the quality leads to more IT potential
utilization. These results are in consistent with work of Boyer et al. (1997).
6.3 BPRM mediating effect
One of the most important outcomes of this study is to show the mediating effect of BPR in the relationship between IT and firm performance. The outcome shows that transformation in the processes of order flow, strategic planning, product, marketing and sales, services, accounting, personally and technology is the necessary precondition for improving the firm performance made by IT usage. The result of our study is consistent with the outcomes of the research study of Grover et al.
(1998), which showed that the mediating effect of BPR is stronger than the moderating effect of this variable. And also results of Hammer and Champy’s study (1993), which indicated that IT is an important BPR enabler, support our outcome. As Gunasekaran and Nath (1997) mentioned, BPR and IT form an integral system in improving the performance of manufacturing companies drastically. Basically, IT can save time and improve accuracy in exchanging information about company goals and strategies. It removes much of the human error inherent complex and repetitive tasks. IT saves money because it reduces errors, and the time it takes to accomplish tasks. IT provides a competitive advantage by helping a company’s position and
capitalizes on trends so that it should be the first to market a new product. Therefore, it is highly recommended to: (a) use the IT potentials in transforming the business processes, and (b) develop the business processes in alignment with IT potential for reengineering processes.
7. Future research directions
The strong role of intervening variables such as BPR and OIS to realize IT potential is outlined in this study. We have considered the role of only two of the above- mentioned important intervening variables in relationship between IT usage and company performance: it seems that researchers can study the role of other variables
such as management style and total quality management on such a relation. In addition, the research instrument developed here is useful for further IT and performance studies.
The second future research direction lies in method of analysis. We used regressing analysis, which is not based on the examination of simultaneous equations; rather it takes into account separate equations. However, recent development in the IS field shows a trend in the use of a second-generation simultaneous equation models (SEMs). We suggest using this approach to further knowledge about our model.
2728 A. Albadvi et al.
Appendix 1. Questionnaire
Please indicate the extent to which IT has been used by your company by marking
the alternative that best describes your idea, ranging from 1 to 7: (1¼not at all,
4¼ to some extent, 7¼strongly)
Code Measures Later code changed to
ITU IT Use ITCOM Communication IT
ITCOM1 e-mail ITCOM2 Fax Later deleted ITCOM3 Mobile Later deleted ITCOM4 Internet ITCOM5 LAN: Local Area Network ITCOM6 Web site for advertisement ITCOM7 Intranet ITCOM8 EDI: Electronic Data
Interchange for interactions with suppliers
ITPOM Production and operation IT
ITPO1 Barcode Later deleted ITPO2 Automatic warehousing Later deleted ITPO3 Software for project
management ITPO1.3 (Factor1: IT in planning)
ITPO4 CAPP: Computer Aided Production Planning
ITPO1.4 (Factor1: IT in planning)
ITPO5 MRP: Manufacturing Requirement Planning
ITPO1.5 (Factor1: IT in planning)
ITPO6 CAD: Computer Aided Design Later deleted ITPO7 CAM: Computer Aided
Manufacturing ITPO2.7 (Factor2: IT in operation)
ITPO8 CAE: Computer Aided Engineering
ITPO2.8 (Factor2: IT in operation)
ITPO9 CNC: Computer Numerical Control
ITPO2.9 (Factor2: IT in operation)
ITPO10 Robotics Later deleted ITPO11 Computer aided production
planning ITPO1.11 (Factor1: IT in planning)
ITPO12 Final product quality control ITPO3.12 (Factor3: IT in quality control)
ITPO13 Process quality control ITPO3.13 (Factor3: IT in quality control)
ITDS Decision support IT
ITDS1 Data analysis ITDS2 Graphical data presentation
tools Later deleted
ITDS3 DSS: Decision Support Systems
ITDS4 SIS: Strategic Information Systems
(continued)
Assessing the impact of information technology on firm performance 2729
Please indicate the extent to which information technology (IT) has been changed the
following business processes in your company Likert scale ranging from 1¼no
effect, to 4¼moderate effects, to 7¼extreme effects)
Code Measures
BPRM Business process changes
BPOF Order flow BPOF1 Raw material BPOF2 Product assembly BPOF3 Obtaining orders BPOF4 Delivery of the product BPOF5 Installation of the product BPST Strategic process BPST1 Formulation of the strategy BPST2 Organizational and behavioural issues BPPR Product BPPR1 Design of product BPPR2 Engineering BPPR3 Process planning BPMS Marketing/sale
BPMS1 Customer satisfaction BPMS2 Market research BPMS3 Forecasting BPMS4 Product-mix decisions BPSE Services
BPSE1 Maintenance of the product BPSE2 Quality assurance BPSE3 After-sale service BPAC Accounting
BPAC1 Product costing BPAC2 Make-or-by decisions BPAC3 Budgeting BPAC4 Recruitment BPAC5 Training BPAC6 Motivation BPAC7 Performance appraisal BPTE Technology
BPTE1 Selection of plant and equipment BPTE2 Installation of plant and equipment
Continued.
Code Measures Later code changed to
ITAD Administrative IT
ITAD1 Databases ITAD1.1 (Factor1: IT in administration) ITAD2 Spread sheets ITAD1.2 (Factor1: IT in administration) ITAD3 Word possessors Later deleted ITAD4 Workflow management system Later deleted ITAD5 Internet recruitment ITAD1.5 (Factor1: IT in administration) ITAD6 Training system ITAD1.6 (Factor1: IT in administration) ITAD7 Performance analysis system ITAD1.7 (Factor1: IT in administration) ITAD8 Payroll system ITAD2.8 (Factor2: IT in financial affair) ITAD9 Invoice systems ITAD2.9 (Factor2: IT in financial affair) ITAD10 Financial system ITAD2.10 (Factor2: IT in financial affair)
2730 A. Albadvi et al.
Indicate the degree of emphasis that your manufacturing plant places on the
following activities. (Likert scale ranging from 1¼no emphasis, to 4¼moderate
emphasis, to 7¼extreme emphasis).
Please indicate your level of agreement or disagreement with the following
statements. (Likert scale ranging from 1¼strongly disagree, to 4¼neither agree
nor disagree, to 7¼strongly agree).
Code Measures
OIS Organizational infrastructures INEM Empowerment
INEM1 Giving authority of scheduling to the workers INEM2 Giving authority of inspection and quality control to the workers INEM3 Changes in managers responsibilities INEM4 Giving workers a broader range of tasks INDE Decentralization
INDE1 Giving authority of recruitment to middle managers INDE2 Giving authority of workers assignment to middle managers INDE3 Giving authority of workers control to middle managers INDE4 Giving authority of financial resources assignment to middle managers INDE5 Giving authority of physical assets assignment to middle managers INTR Training
INTR1 Improving supervisors training INTR2 Improving workers training INTR3 Improving direct workers motivation INTE Teamwork
INTE1 Permanent project teams (with people from different functional areas) INTE2 Matrix organization (people working on a project report functionally
within their department but report to a project manager for project work)
INPC Process management and customer relationship
INPC1 Process management INPC2 Statistical process control INPC3 Assessment of processes INPC4 Continues improvement of processes INPC5 Customer needs assessment INPC6 Customer satisfaction measurement INPC7 Customer relationship management INSU Changes in transaction with suppliers INSU1 Supplier relationship management INSU2 Improvement of financial exchange with suppliers INSU3 Involvement in supplier quality assurance
INLE Leadership
INLE1 All major department heads within our plant accept responsibility for quality
INLE2 Plant management provides personal leadership for quality improvement
Later deleted
INLE3 The top priority in evaluating plant management is quality performance
INLE4 Our top management strongly encourages employee involvement in the production process
Assessing the impact of information technology on firm performance 2731
For your major product line, indicate your position with respect to your competitors
on the following dimensions for the last 2 years. (Likert scale ranging from
1¼significantly lower, to 4¼equal, to 7¼significantly higher).
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