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This is the author’s version of a work that was submitted/accepted for pub- lication in the following source: Prasad, Acklesh & Heales, Jon (2010) On IT and business value in de- veloping countries : A complementarities-based approach. International Journal of Accounting Information Systems, 11(4), pp. 314-335. This file was downloaded from: Notice: Changes introduced as a result of publishing processes such as copy-editing and formatting may not be reflected in this document. For a definitive version of this work, please refer to the published source: http://dx.doi.org/10.1016/j.accinf.2010.09.001
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This is the author’s version of a work that was submitted/accepted for pub-lication in the following source:
Prasad, Acklesh & Heales, Jon (2010) On IT and business value in de-veloping countries : A complementarities-based approach. InternationalJournal of Accounting Information Systems, 11(4), pp. 314-335.
This file was downloaded from: http://eprints.qut.edu.au/48570/
Notice: Changes introduced as a result of publishing processes such ascopy-editing and formatting may not be reflected in this document. For adefinitive version of this work, please refer to the published source:
http://dx.doi.org/10.1016/j.accinf.2010.09.001
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ON IT AND BUSINESS VALUE IN DEVELOPING COUNTRIES: A
COMPLEMENTARITIES-BASED APPROACH
Acklesh Prasad
School of Accounting and Finance
The University of the South Pacific
Suva, Fiji
Email: [email protected]
Phone: +679 3232088
Fax: +679 32321506
Jon Heales
UQ Business School
The University of Queensland
Brisbane, Queensland 4072, Australia
Email: [email protected]
Phone: +617 33468039
Fax: +617 33656988
ABSTRACT
Developing economies accommodate more than three quarters of the world's population. This means
understanding their growth and well-being is of critical importance. Information Technology (IT) is one
resource that has had a profound effect in shaping the global economy. IT is also an important resource for
driving growth and development in developing economies. Investments in developing economies,
however, have focused on the exploitation of labor and natural resources. Unlike in developed economies,
focus on IT investment to improve efficiency and effectiveness of business process in developing
economies has been sparse, and mechanisms for deriving better IT-related business value is not well
understood. This study develops a complementarities-based business value model for developing
economies, and tests the relationship between IT investments, IT-related complementarities, and business
process performance. It also considers the relationship between business processes performance and firm-
level performance. The results suggest that a coordinated investment in IT and IT-related
complementarities related favorably to business process performance. Improvements in process-level
performance lead to improvements in firm-level performance. The results also suggest that the IT-related
complementarities are not only a source of business value on their own, but also enhance the IT resources’
ability to contribute to business process performance. This study demonstrates that a coordinated
investment approach is required in developing economies. With this approach, their IT resources and IT-
related complementaries would help them significantly in improving their business processes, and
eventually their firm level performances.
Keywords: IT Investments, IT-Related Complementaries, Process-Level Performance, Firm-Level
Performance, Business Value, Developing Countries
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1. INTRODUCTION
Today, eighty four percent of the world’s population resides in developing countries (The World
Bank, 2006). The prevailing forces of globalization means the world is becoming increasingly
interconnected in all aspects of society (Crenshaw and Robison, 2006). In this current global
environment, despite ones views on trends towards globalization, the concerns of the wider
community, including the developing countries, need consideration in all domains of work.
Information Technology (IT) has made a profound contribution to this growing trend of
globalization. Global investment into IT is in trillions of U.S. dollars (McKinsey Global Institute,
2003; Pohjola, 2001). The developing countries are progressively receiving a bigger portion of
the IT investment dollars (Shih et al., 2007). In the past few decades, IT has transformed the
world (The World Bank, 2006). Initially, the benefits of applying IT for promoting economic
growth and social well-being were not widely understood, with questions raised on IT’s
relevance to developing countries. The important question today is how IT can benefit the social
and the economic development (Walsham et al., 2007).
The developing countries secure IT investments from donor agencies, local private firms,
multinational corporations, and local governments. These contributors play an important role in
IT-related economic growth and development in developing countries (Puri, 2007). The most
critical of these is a vibrant private sector investment, one where firms invest, create jobs,
promote growth, and expand opportunities for people (The World Bank, 2006). Private sector
investments in IT in developing countries have led to significant economic and social
improvements. However, the gap in access to IT resources remains large across and within the
developing countries (Walsham et al., 2007). This disparity is increasingly becoming evident as
fast growth in large emerging markets like Brazil, China, and India mask slower development
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elsewhere (Kraemer and Dedrick, 1994; Shih et al., 2008). Continued private sector investments,
especially in smaller developing countries, is essential for their continued social and economic
development (United Nations Development Program (UNDP), 2001). Improperly planned
development and privatization policies of the local governments constrain this effort. The result
is investors in developing countries demanding higher returns, better productivity, and a
sustainable diversified investment exposure from their IT investments.
Information Systems (IS) researchers contribution in prompting investor confidence in
developing countries, and in promoting IT investments, has been relatively sparse. Researchers in
developed countries (e.g., Dehning and Richardson, 2002; Saunders, 2007; Sircar et al., 2000;
Vessey et al., 2002; Walsham et al., 2007) have recognised this disparity. The result of this
recognition led to research in developing countries focusing on the development of information
systems (Braa et al., 2004; Braa et al., 2007), enhancing the IT knowledge base (Puri, 2007),
information systems interaction with traditional systems (Miscione, 2007), and cultural aspects of
socio-technical change (Avgerou and McGrath, 2007). Evaluation of the extant literature suggests
that the important issue of understanding how to source business value from IT investments at an
organizational level has not received any resolute attention. This understanding is vital for
promoting investor confidence in the stakeholders in the developing countries. IT business value
is organisational performance impacts of IT at both the process and the firm levels.
The IT business value studies in the developed countries have looked extensively into the
phenomenon of diffusion of IT resources to understand how to derive IT-related business value.
These studies advocate the notion of competitive strategy (Porter, 1985), synergizing IT-related
resources (Milgrom et al., 1995), and IT-related capabilities (Barney, 1991) as a source of IT-
related value in firms. With the central premise of the existence of a competitive and efficient
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market, the concept of obtaining and sustaining competitive advantage through IT has featured
prominently in these studies.
In developing countries, however, while economic sectors are gradually being liberalized, the
markets are still monopolistic, oligopolistic, or marginally competitive (The World Bank, 2006).
The focus in this environment is to enhance the productivity-related operational efficiencies and
effectiveness (Pimchangthong et al., 2003). The overarching motive of foreign private investors
for a diversified IT investment strategy is one of competitive advantage. However, at the local
level, the IT investments’ objective is to improve process level efficiency and effectiveness. This
disparate focus makes it challenging to use the studies conducted in developed countries to make
inferences on how IT resources may contribute to better business value in developing countries
(Chau et al., 2007; Mahmood and Mann, 2000). These studies, however, provide a rich source of
knowledge for the development of a model of IT business value for developing countries.
This study suggests an environment within which IT investments can contribute to business value
in developing countries. It presents a complementary model of IT business value for developing
countries. This complementary model provides researchers and decision makers with insights on
ways IT investments can contribute to business value at both process and firm levels. The ability
to provide economical human resources has made the developing markets an attractive source of
private sector investments (Hoskisson et al., 2000; Tybout, 2000). This situation renders a strong
association between the business processes and human resources (Napier and Vu, 1998; Watson
et al., 1997). Introduction of IT, albeit existing and mature (Mastromarco, 2008), would present a
challenging work environment, and would place immense pressure on the users and managers of
this technology.
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Consideration of human resources and other related factors is essential to maximize the benefits
of IT resources in this environment (Shih et al., 2008). This includes recruitment, training and
retaining IT staff, and a proactive end user training program. The strong bind between the human
resources and business processes means that greater benefits from IT resources require
complementary investment into IT-related human resources initiatives. The result is a
coordinated IT investment strategy that builds an IT infrastructure that is flexible and agile to
accommodate future IT-related value-creating initiatives. Firms that adopt this coordinated IT
deployment approach will benefit through efficiency and effectiveness in their business
processes. These efforts will mean that IT investments will consume a substantial amount of
financial resources. Deriving financial benefits from these investments is essential to ensuring
continued private sector investment. Firms that adopt a coordinated IT investment strategy will
improve their business processes, and this improvement in business processes will contribute to
overall firm-level performance.
Results from archival and field survey data suggest that the level of IT investment and the related
complementarities associate favorably with various measures of process-level performance. The
complementarities contribute to process-level performance on their own, and enhance the IT
resources’ ability to contribute to process-level performance. The process-level performances
also relate positively to firm-level performance. The results provide strong support for a model of
complementary IT-related investment as a source of IT-related business value in developing
countries. The rest of the paper progresses as follows. The next section presents the theoretical
framework of this study. The following section presents a complementarity model of IT
investments in developing countries. This follows discussion of the research design and
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presentation of the results of this study. The final sections discuss the results, contributions and
implications, limitations, and provide directions for future research.
2. THEORETICAL FRAMEWORK
Introduction of IT in organizations inevitably brings changes in structures and processes (Leavitt
and Whisler, 1958; Markus and Robey, 1988). Organizational behavior is a natural domain for
fit-based theories on managing the technological and the organizational changes. Organizational
behavior research has relied heavily on the contingency and socio-technical theories for their
theoretical lens on change-related propositions. Contingency theory postulates that the
organizational design is contingent upon the organization’s internal and external context
(Ginsberg and Venkatraman, 1985). Contingencies could be based on selections, interactions, and
systems approaches (Van de Ven and Drazin, 1985). The socio-technical theory suggests a
stronger role of technology in organizational design. This theory suggests that organizational
outcomes depend upon both social and technological factors (Barua et al., 1996).
These fit-based theories provide a sound conceptual basis for understanding organizational and
technological changes, but their theoretical justification for the fit between variables is weak
(Barua et al., 1996). The fit theories do not suggest ways to model the relationship between
contextual variables and firm performance. This is a crucial understanding of the effects of socio-
technological changes in organizations, and is an aspect of the fit theories that is often criticized
(e.g., Weill and Olson, 1989). Evaluation of IT-driven initiatives against measures of
improvements of such initiatives is important for continued IT-driven investments in developing
countries. This outcome will ensure that such nature of investment remain an important
component in the investor’s wider goal of achieving competitive benefit. The complementarity
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theory accords operational insights into the nature of changes required, and ways to map the
benefits of these changes to business value.
The complementarity theory (Edgeworth, 1881), is an old but powerful concept with the basic
premise of the establishment of an activity pattern (Milgrom and Roberts, 1990). The factors
within this activity pattern must be complementary; advocating increasing one factor will
increase the benefits when other complements move in the same direction. Complementary
factors need to change in a coordinated fashion, in the right direction, and in the right magnitude
for maximum organizational payoff. This suggestion articulates a concerted change in a large set
of variables. The complementarity theory advocates a change of a particular magnitude and
direction. This notion extends the conceptualizations of the fit theories by allowing mapping of
the complementary changes to the related output measures. The complementarity theory also
internalizes the fit factors requiring a coordinated change, thus suggesting the concept of input-
level multidimensionality in realizing IT-related business value.
This complementarity perspective has proposed a business value complementarity model for
reengineering (Barua et al., 1996), by embracing Topkis (1978) theory of supermodularity. The
findings indicate that when a complementary reengineering variable is unchanged, the
organization would not be able to obtain full benefits of reengineering. With manufacturing
functions, complementarity perspective suggests that firms’ integrated IS capability as well as
complementary effects of IS capability with these factors are significant predictors of
manufacturing performance (Bharadwaj et al., 2007). The complementarity theory affirms that
IT inputs are a component in the organizational design. This affirmation articulates that the
success of IT is contingent upon complementary investments and considerations in appropriate
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resources, processes, incentives, policies, and control systems (Barua et al., 1995; Barua and
Mukhopadhyay, 2000; Lee et al., 2000).
Successful IT deployment will require a complementary presence of related resources to source
business value in developing countries. Improving existing processes will not succeed with
isolated investments in IT. Benefits from IT investments differ across firms because companies
have other resources and characteristics that are complementary with the nature of technology.
Maximum payoff from IT is possible when other complementary factors such as decision
authority, training and development, and investment policies change in a coordinated fashion in
the right direction. This is this study’s complementary theoretical prescription to the notion of a
systematic approach to IT-related business process improvement. National productivity gain
studies show that developing countries do not experience desired gains associated with IT
investments (e.g., Dewan and Kraemer, 2000; Pohjola, 2001; Tam, 1998). This outcome is
because of insufficient investment in complementary assets to permit developing countries to
enjoy IT-related productivity benefits (Dewan and Kraemer, 2000; Shih et al., 2008).
Investment in IT and related complementarities first help attain specific business objectives at the
process level (Alter, 2003). This means that assessment of the business value of IT investments
should reflect a direct path from IT and IT-related investment to specific metrics that reflect the
business objectives being sought (Dehning et al., 2007). Mapping IT investments directly to firm-
level performance creates noise from not considering the direct path (Dehning and Richardson,
2002). IT and complementary factors also affect overall firm-level performance, albeit indirectly
(Dehning and Richardson, 2002). The measures of IT-related value at the process level capture
the direct effect of IT investments and related complementarities. Relating the process-level
performance to firm-level performance captures the indirect effect of IT and IT-related
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investments. Consistent with the above conceptions, the following section describes a
complementary business value model for IT investments in developing countries.
3. HYPOTHESES
3.1 The Level of IT Investment
IT, broadly defined, is a collection of computing systems used by organizations, incorporating
hardware, software, and networks. IT-enabled information systems have become a major
facilitator of business activities in the world today. IT acts as a catalyst for fundamental changes
in the strategic, structural, and operations management of organizations (Wreden, 1997).
Expanding power and declining costs enable new and more extensive applications of IT, making
it possible for organizations to improve their efficiency and effectiveness (Turban and Volonino,
2010).
IT productivity assessment gained a lot of attention over the past few decades. Lack of evidence
of a positive relationship between IT investment and measures of performance, including
productivity, in the early research is rife in literature (e.g., Barua et al., 1995; Dehning and
Richardson, 2002). Studies using the production function theoretical lens failed to demonstrate a
positive association between IT expenditure and productivity in developed markets. Rather, these
studies showed that the costs exceeded the benefits (e.g., Cron and Sobol, 1983; Loveman, 1994;
Roach, 1987; Strassmann, 1985). Data and measurement issues (Brynjolfsson, 1993), sample
size, level of analysis, and choice of measurement variables (Wade and Hulland, 2004) were
identified as potential factors that attributed to this outcome.
New datasets and alternative theoretical lenses led to research finding some positive relationships
between IT spending and market measures (e.g., Hitt and Brynjolfsson, 1996; Krishnan and
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Sriram, 2000; Oh and Kim, 2001) and between IT spending and accounting measures (e.g., Barua
et al., 1995; Mitra, 2005; Sircar et al., 2000). A cursory evaluation of practice-related literature
now lends ample support to the conventional view of IT as an enabler of growth, with the
concurrence that IT resources can have a direct effect on firm effectiveness and efficiency (e.g.,
Hayes, 2001).
Understanding how IT contributes to business value remained inconclusive. Concurring that an
organization is a bundle of resources (Mata et al., 1995), a resource-centric approach gained
prominence to understanding how and where IT may contribute to business value. The result, the
strategic necessity hypothesis (Powell and Dent-Micallef, 1997), suggests that investment in IT is
important for internal and external coordination to achieve efficiency and effectiveness.
Notwithstanding above, per se, firms cannot expect IT resources to contribute to business value
because they are readily available. Rather, it is the unique IT-related capabilities that the firms
possess, and how these capabilities leverage the IT resources that determines the extent of IT’s
business value (Powell and Dent-Micallef, 1997). The resource-based view of the firm theoretical
lens (RBV) (Barney, 1991) has been used to successfully demonstrate the above notion (e.g.,
Jeffers et al., 2008; Ray et al., 2005; Wade and Hulland, 2004).
The economic environment in the developing markets, however, is different from that of the
developed market (Walsham, 2001). With one or few players in economic sectors, IT investments
decisions depict acquiring IT more as a want rather than a need. In resource-based logic, this
suggests that the result of investment in IT is acquiring an organisational resource that possesses
capability-like features. This is because a firm with IT resources can do things in way that firms
without the resources cannot. This feature makes the level of raw dollar spending on IT by a firm
an important indicator of the level of their performance-differentiating IT resources. These IT
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resources will provide the firm access to the fundamental and necessary tools to achieve
efficiency and effectiveness for their core business processes. These, per se, will be the generic
gains that IT as a resource can provide without any substantial level of resource manipulation.
This means that in developing markets, a firm’s failure to invest in IT resources puts them at a
disadvantage. The impacts of IT on productivity and growth became widely recognized after
decades of cumulative investment (Jorgenson, 2001). Growth in developing markets will also
come from technological accumulation through an evolutionary process of imitation and
innovation (Bell and Pavitt, 1993). A higher level of investment will mean a better bundle of IT
resources for the firms. This IT resource will have immediate effect on firms’ business processes.
This is possible because investments will be made in IT that is mature and well-tested in
competitive markets (Shih et al., 2008). As with developed countries, investment in IT in
developing countries is a strategic necessity, but in developing countries, per se, it can also be a
source of their business value. Even in developed countries, despite concurrence on strategic
necessity hypothesis, there is recent evidence that demonstrates that well- targeted, timed, and
managed IT investments can provide business value (e.g., Dehning et al., 2007). Consistent with
the above arguments this study hypothesizes that:
H1: The level of IT Investment will be positively associated with business process performance in
developing countries.
3.2 IT-Related Human Resource Training
Organizational culture is an overarching factor that offers powerful forms of competitive
advantage (Huselid, 1995). Organisation cultures are difficult to articulate and require
simultaneous manipulation of complex relationships and technologies (Fiol, 1991; Fiol and
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Lyles, 1985; Reed and DeFillippi, 1990). The human resource factors form an integral part of the
unique cultural formations in organizations, and explain greater proportion of performance
variance than strategy and economic factors (Hansen and Wernerfelt, 1989). Continued
investment interest in developing countries stems from their ability to provide an affordable
labour market (Hoskisson et al., 2000; Tybout, 2000). Human resource performance has
implications for organizational performance outcomes (Huselid, 1995). Human resources,
however, are frequently underutilized because employees often perform below their maximum
potential (Bailey, 1993). Organizational efforts that elicit discretionary effort from employees are
likely to provide returns in excess of any relevant costs (Bailey, 1993). This effort is especially
pertinent during a period of technology adoption, as it presents the employees with a varied
working environment. End-user training is a critical intervention to support successful use of
new IT resources (Bostrom and Olfman, 1993; Bostrom et al., 1990; Compeau and Higgins,
1995; Compeau et al., 1999). For this reason, introduction of IT in organizations must typically
accompany substantial investments and consideration of complementary business resources
(Olfman and Pitsatorn, 2000; Powell and Dent-Micallef, 1997).
IT training is an indispensible complement to investment in IT resources (Benjamin et al., 1984;
Kanter, 1984; Powell and Dent-Micallef, 1997). Sustainable value of IT training emerges from
merging firm-specific IT with firm-specific training to produce distinctive organizational
capabilities (Barney, 1991). This outcome is possible through a set of formal and on-the-job
training initiatives. Theories of individual learning informs the effectiveness of various training
methods to impart technical knowledge to end users (e.g., Olfman and Pitsatorn, 2000;
Santhanam and Sein, 1994; Yi and Davis, 2003). This interaction between experts and novices
engages end users in cognitive activities, through which they acquire imparted knowledge
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(Gallivan et al., 2005). End users also acquire knowledge from other sources, including situated
learning, learning-by-doing, and learning-by-using (Attewell, 1992; Sharma and Yetton, 2007).
Formal training, however, is an important source of knowledge for them, and an important
mediator contributing to successful use of new IT resources (Powell and Dent-Micallef, 1997).
End users need to acquire new knowledge to effectively use the newly-introduced IT (Attewell,
1992; Nelson and Cheney, 1987). This includes training domains of application knowledge,
business context knowledge, and collaborate task knowledge (Kang and Santhanam, 2004).
Training in each of these domains minimizes any knowledge barriers to successful use of new
technologies (Attewell, 1992). Training also influences new technology adoption benefits
through its effects on the beliefs of end users, their attitudes, and their perceptions of usefulness
and ease of use (Agarwal and Prasad, 1999).
Successful training effort on implementation and use of new technologies enhances individual
cognitions of application knowledge and business context knowledge, and the inter-individual
cognitions of transactive memory and collaborative task knowledge (DeLone, 1988; Fuerst and
Cheney, 1982; Yetton et al., 1999). Human resource complementarities like end-user training
create embedded advantages that explain significant performance variance amongst firms (Powell
and Dent-Micallef, 1997). In developing markets, appropriate end-user training will ensure a
coordinated and comprehensive approach to the introduction of new technology. Investment in
mature technology means that the potential of the newly introduced technology is established. In
this environment, training will ensure that the end-users are able to capitalize on the opportunities
that the new but established technology offers. This fusion will be a source of process-level
business value. Consistent with these arguments this study hypothesizes that:
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H2: The level of end-user training will be positively associated with business process performance in
developing countries.
3.3 IT Human Capital
New IT business environments’ success is contingent upon the its ability to be adaptive,
responsive, and aligned to business needs (Ross et al., 1996). The greatest impediments to
success in a technology-oriented environment are often related to people rather than information,
technology, and systems (Roepke et al., 2000). Firm’s IT human capital constitutes a critical
capability that needs appropriate management and nurturing for successful business partnerships
(Mata et al., 1995; Ross et al., 1996). The IT human capital of a firm in any IT-related
environment may well represent its most important resource. This resource will not only enable
organizational change, but also act as the mechanism through which to achieve greater
organizational effectiveness (Roepke et al., 2000).
Introduction of IT in any market will result in some level of transformation in the organization.
The changed environment will inevitably have wide-ranging implications for the skills,
behaviors, and orientations of IT and other staff. In this environment, the need for IT
professionals will intensify, requiring them to assume entrepreneurial roles, and provide
directions for possible IT-related change. The presence of IT professionals signifies a proactive
approach to creating opportunities by deploying IT to serve the business needs. The presence of
an effective IT workforce helps businesses foster strong partnership skills, a culture of
willingness to change, and an environment where the IT staff and the end users act without overt
and persistent guidance (Bartol and Martin, 1982; Bresnahan et al., 2002).
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Human IT capital comprises of technical IT skills or managerial IT skills, and both skills are
useful in utilizing newly adopted technology (Mata et al., 1995). Technical skills refer to know-
how needed to build IT applications using the available technology, and assist the end users in
operating these applications to make products and provide services (Green, 1989; Mata et al.,
1995). Technical skills include knowledge of programming languages, understanding operating
systems, and understanding of communication protocols and products, all of which enable firms
to effectively manage technical skills associated with investing in IT (Mata et al., 1995).
Managerial IT skills nourish an organization’s ability to conceive of, develop, and exploit IT
applications to support and enhance other business functions (Capon and Glazer, 1987). IT
management human capital ensures a better understanding of IT needs, improves IT and IT user
relationship, coordinates IT activities to support business processes, and anticipates future IT
needs.
The presence of IT personnel, and their ability to share organizational knowledge with other
management enhances the relative process performances (Ray et al., 2005). The presence and
collaboration of IS managers improves operational and service performance of the IS groups
(Nelson and Cooprider, 1996). IT management’s presence and contribution is also an important
IT-related flexible capability, which can improve third party logistics processes (Jeffers et al.,
2008). In developing markets, the presence of human IT capital will provide the important fusion
between the introduced technology and the business processes. The result will be a set of refined
business processes with improved level of efficiency and effectiveness. This makes the human IT
capital an important complementary to investments in IT. Consistent with the above arguments,
this study hypothesizes that:
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H3: The level of Human IT Capital will be positively associated with business process performance in
developing countries.
3.4 A Flexible IT Infrastructure
IT infrastructure can have an indirect effect on firm’s growth (Mitra, 2005). A flexible IT
infrastructure can also have a direct influence on a firm’s growth, where the magnitude of
increase in revenue is higher than that of the cost of operations (Duncan, 1995; Mitra, 2005;
Sambamurthy et al., 2003). Firms incur higher control and coordination costs as they grow in size
and complexity, and their operations become more complicated. A flexible and superior IT
infrastructure supports efficient growth by facilitating a rapid development and implementation
of IT applications (Ray et al., 2005). This environment enables organizations to respond swiftly
to benefit from emerging opportunities (Ray et al., 2005). A flexible IT infrastructure also helps
firms to control their complexity-related costs as they expand their operations (Mitra, 2005). IT
infrastructure as a key part of firms’ strategy to build cost effective systems, and a flexible IT
infrastructure, in being responsive towards emerging opportunities, in is an important enabling
tool.
A flexible IT infrastructure is a shared tangible IT resources (Earl, 1989; Weill et al., 2002). It
acquires an important ability to provide a foundation to develop present and future business
applications (Earl, 1989; Neiderman et al., 1991). The flexibility of an IT infrastructure is a
firm’s core competence relative to IT (Barua et al., 1997). A Flexible IT infrastructure is an
important contributor in a technology-oriented environment (Armstrong and Sambamurthy, 1999;
Duncan, 1995; Ray et al., 2005; Sambamurthy et al., 2003; Weill, 1993). The flexibility of the IT
infrastructure relates to the improvement in process-level performance (Ray et al., 2005).
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A firm’s flexible IT infrastructure is inductive of a careful plan of IT investment. This is because
the flexibility in an infrastructure develops progressively. Compared to ad hoc investments in IT,
the flexible IT infrastructure developed from a careful IT investment plan will determine the
extent to which the firms will be able to seize emerging opportunities. The result of this will be
refined and aligned IS applications, which will enhance the efficiency and effectiveness of the
process-level performance. Firms in developing markets that adopt a plan of IT investment will
have a flexible IT infrastructure that will explain differences in the process-level performance
across firms. Consistent with these arguments this study hypothesizes that:
H4: The level of flexible information technology infrastructure will be positively associated with business
process performance in developing countries.
3.5 The Enhancing Role of IT-Related Complementarities
Information technology can affect improvement in business processes in developing countries in
two ways. First, if firms acquire the necessary IT resources, the application of this technology can
lead to relative gains in business process performance. IT is a differential resource in
uncompetitive markets, and its presence will provide value to a firm by increasing its internal and
external coordinating efficiencies. Firms that do not adopt these technologies will have higher
cost structures and will be at a performance disadvantage. In developing countries, as long as the
disparity in IT investments exists, IT will provide sustained advantage for a relative period.
Second, firms that possess related complementarities to the IT resources will successfully
leverage the potential of their IT resources. IT is a skill-based technology, and its value is closely
linked to the user skill levels available to the firm (Bresnahan et al., 2002; Shih et al., 2007). The
acceptance of IT depends upon the IT itself, and the level of skills of employees that use the IT
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(Igbaria et al., 1995; Nelson, 1990). End-user training affects individual’s skills and competence,
which influence their beliefs and usage of IT (Igbaria et al., 1996). This outcome increases user’s
confidence and their ability to master and use IT in their work (Gist et al., 1988; Igbaria et al.,
1995). End-user training improves system usage, and lack of training is a major reason for lack of
IS success (DeLone, 1988; Fuerst and Cheney, 1982; Igbaria et al., 1994; Igbaria et al., 1996).
Coordinated and complementary IT-related end-user training will not only be a source of
productivity growth on its own, but will also improve the productivity output from the IT
investment.
Introduction of IT inevitably creates a new business environment. Appropriate consideration in
acquiring or enhancing firm’s IT-related human capital in this new environment is essential. IT
professionals ensure effective and opportune use of IT to derive the anticipated benefits from the
new investment. Human capital is most valuable when it is firm specific and resides in the
environment where it was optimally developed (Hatch and Dyer, 2004; Hitt et al., 2001). Firms
that build strong competencies (i.e. IT human capital) are able to take advantage of strategic
opportunities, and this will help firms create value (Lei et al., 1996). Human IT capital is a vital
resource for implementing operational and strategic business initiatives (Lee and Miller, 1999).
Human capital interacts with various firm resources, and this interaction has a positive effect on
firm performance (Hitt et al., 2002). Various human capital nourishing mechanisms improve a
firm’s ability to contribute to sustainable competitive advantage (Hatch and Dyer, 2004). Firms
IT human capital will not only be a source of productivity growth on its own, but will also
improve the productivity output from the IT investment.
A flexible IT infrastructure indicates a coordinated and progressive IT investment strategy.
Progressive IT investment recognizes emerging IT-related opportunities, and recognizes the
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synergy between the business opportunities and the potential of IT to leverage those
opportunities. Firm’s IT resources in this environment will contribute more to business process
improvements. Changed business practices and strategies will recognise further opportunities,
and a flexible IT infrastructure will allow IS personnel to respond quickly and cost-effectively to
users demands. In developing countries too, firms IS with a coordinated change in related
complementarities is perceived to be eminently imitable (Duncan, 1995). A set of resources that
promote innovation and continuous improvement of IS’s is a firm’s additional source of business
value (Duncan, 1995). In developing countries, firm’s forethought of IT investment opportunities
emerging from its agile IT infrastructure will benefit its business processes, and this ensures
better leveraging of IT resources. Consistent with these arguments this study hypothesizes that:
H5a: The level of IT investment, in the presence of end-user training, will be positively associated with
business process performance in developing countries.
H5b: The level of IT investment, in the presence of human IT capital, will be positively associated with
business process performance in developing countries.
H5c: The level of IT investment, in the presence of a flexible IT infrastructure, will be positively
associated with business process performance in developing countries.
3.6 Business Value Measurement Levels
While determining a path of IT’s business value generation is a contentious issue, business
processes are appropriate initial unit of measurement of IT-related business value (Alter, 2003;
Davenport, 1990). Businesses acquired IT resources relate to improvements in the process-level
performance (Barua et al., 1995; Dehning et al., 2007; Melville et al., 2004; Ray et al., 2005;
Tallon, 2007). In developing countries too, IT resources and suggested complementarities will
first improve the efficiency and effectiveness of the business processes. Specific attributes like
- 20 -
customer service improvement can measure the business process performance (Jeffers et al.,
2008; Ray et al., 2005). However, such attributes are appropriate for service processes where
customer experience is the critical competitive performance criterion. Common efficiency and
effectiveness measures are more appropriate when considering firms across industries and
suggesting a generic business value model (Ray et al., 2005). This study uses five generally
accepted measures to evaluate the impact of IT investments and related complementarities at the
business process level. These measures relate to process level cost effectiveness and revenue-
generating efficiencies, and can be used to evaluate IT investments and related complementarities
association with process level performance (Dehning et al., 2007; Mitra and Chaya, 1996).
Acquiring IT and IT-related resources and implementing changes in organizations consume
substantial financial resources. This means that businesses are concerned about the monetary
return on their investments at the firm level. An organization’s firm-level performance is
contingent upon the effectiveness of the business processes in supporting the businesses’ goals
(Barua et al., 1995; DeLone and McLean, 2003; Ray et al., 2004; Ray et al., 2005). IT and non-IT
inputs relate to process-level performance, and process level performance carries through to
overall firm-level performance (Barua et al., 1995). IT-enabled systems also relate to improved
process-level performance, and the process level performance translates into firm-level
performance (Dehning et al., 2007).
Investments in IT and related complementarities in developing countries will also follow a
similar path of business value generation. Mapping productivity-related process improvements to
firm-level performance establishes a clear and tangible path of benefits of IT and IT-related
investments. Return on Assets (ROA), Return on Sales (ROS), and Return on Equity (ROE) are
conventional measures of firm-level performance (Barua et al., 1995; Dehning et al., 2007; Hitt
- 21 -
and Brynjolfsson, 1996; Rai et al., 1997; Tam, 1998). Net income is a key component in the
constitution of these firm-level performance measures. The level of net income is contingent
upon the level of improvement in the process level cost effectiveness and efficiency in revenue-
generation. The magnitude of change in net income in relation to the assets, equity, and sales
firms will determine the firm-level performance. Organizations that complement their IT well,
and use the IT resources efficiently, will generate greater benefits at the business process level,
and these benefits will contribute to overall business value (Barua et al., 1995; Davamanirajan et
al., 2006; Melville et al., 2004). These arguments lead to the following hypothesis:
H6: Business processes performance will be positively associated with firm-level performance in firms in
developing countries.
Figure 1 proposes a model for IT business value in developing countries as follows:
[INSERT FIGURE 1 HERE]
4. RESEARCH METHOD
A survey research methodology collects unpublished data to test the proposed model. A survey
research approach makes it possible to cover a wide geographical area, and allows contacting the
potential respondents with minimal increased marginal cost. The sampling frame constituted
publicly listed, statutory, and private companies. Two survey instruments were used to obtain
data for the constructs in the model. The published annual reports provided the financial data for
the publicly listed and the statutory companies. In these companies, the administered research
instrument gathered quantitative data on measures not published in their annual reports.
Perceptual items measured firms’ flexible IT infrastructure. The survey instrument gathered data
- 22 -
for all measures from the private companies. A Pre-test with faculty colleagues and a pilot test
with a small sample of companies from the sampling frame validated the research instrument to
ensure quality of self-reported data.
Single measures, such as IT expense to proportion of sales and operating expense (Mitra and
Chaya, 1996; Weill, 1992), and multiple measures (Mahmood and Mann, 1993) can represent
firms total IT investments. While each measure has its advantages and disadvantages (Mitra and
Chaya, 1996), the standard benchmark of IT spending per employee (Ray et al., 2005) measures
firms’ level of IT investment in this study. IT-staff training budget per employee measures the
level of IT staff training, and IT human resource expenditure (including IT staff salary and other
recruitment expenses) per employee measures the level of human IT capital. Flexible IT
infrastructure measures, adopted from Duncan (1995), focuses on the level of IT platform
standardization.
A business process is a set of linked activities that create value by transforming an input into a
more valuable output. Both inputs and outputs can be artifacts and/or information, and human
actors, machines, or both can perform the transformation. Five generic items measure the
efficiency and effectiveness of the business processes. Sales revenue per employee and sales as a
percentage of total assets measures the effectiveness of using IT and related resources to earn
revenue. These are typical measures of a firm’s sales and marketing productivity at the process
level (Sircar et al., 2000; Strassmann, 1997). Operating expenses as a percentage to sales, the
most general and encompassing measure of a firm’s operational cost (Mitra and Chaya, 1996),
represents firm’s total cost of operations. This measure excludes depreciation, interest expenses,
extraordinary items, and taxes to isolate costs resulting from non-recurring situations, and
varying accounting and financing methods. Selling and general expenses, including cost of goods
- 23 -
sold and administrative costs as a percentage of sales, represents firm’s selling and overhead
related costs (Mitra and Chaya, 1996; Rai et al., 1997). Labor cost as a percentage of sales
measures firm’s average labor cost per unit of sales.
Return on assets (ROA), return on equity (ROE), return on sales (ROS), market share, market
capitalisation, return on shareholders’ funds, market value, and total asset turnover are traditional
measures of firm-level performance (Barua et al., 1995; Hitt and Brynjolfsson, 1996; Rai et al.,
1997; Tam, 1998). With the sampling frame containing a mix of public, private, and government
agencies, ROA, ROE, and ROS measure firm-level performance.
Firm size (total assets), number of years of IT investment, and the presence of separate IT
departments are the control variables. These variables are included to discount for rival
hypotheses that may drive process-level and organizational-level performance. The length of time
a business engages itself in its processes, thus maturing its capability, can relate to their process
performance. The number of years of that firm’s investment in IT can relate to improvement in
their process level performance. A firm's IT maturity relates to the role it gives to IT investment
in sourcing business value (Benbasat et al., 1980; Karimi et al., 1996; Karimi and Somers, 2001;
Mahmood and Becker, 1986). Better management of IT can also relate to process level
performance. IT management is a key determinant of successful IT use in organizations (Boynton
et al., 1994; DeSanctis and Jackson, 1994; Sambamurthy et al., 2003). Firm size is the most
frequently examined structural characteristic (e.g. DeLone, 1981; Harris and Katz, 1991),
because it is presumed that managers are aware of the economic and strategic incentives that
favor the adoption and use of IT by large firms (Gremillion, 1984).
- 24 -
5 DATA COLLECTION AND DIAGNOSTICS
The study suggests a model of successful use and evaluation of IT for growth and development in
developing countries. The market operations, investment sources, and cultural differences in
developed countries mean that the related studies conducted in developed countries render little
value to understanding successful IT utilization in smaller developing countries. This study’s
sampling frame contains firms from a geographical sphere representing the smaller developing
countries with local and multinational private IT-related investments. These countries have the
potential to produce output effectively and efficiently with investment in IT and related
resources. While many countries fit this definition, access and proximity led us to choosing Fiji
as the country for the source of data.
Fiji has a good mix of publicly listed companies, public enterprises (firms partly owned by the
Government), private, and partnership forms of business organization. It is the most
industrialized developing country, and a lower-to-middle income economy within the South
Pacific (Asian Development Bank, 2006). Fiji has a diversified open economy with the service
sector contributing 67% to the GDP. There is strong foreign private investment in banking,
insurance, tourism, construction, and manufacturing sectors. The local businesses represent well
in manufacturing, retail, tourism, and agricultural sectors. All these sectors have processes that
can benefit from IT. Selecting Fiji means that the sampling frame is represented well by firms
investing in IT in smaller countries that do not receive due attention by researchers compared to
the more industrialized developing countries.
Information from the central business registry, sector associations (e.g., Manufacturing
Association, the Hotel Association, the Association of Banks, the local Stock Exchange), and the
local Public Enterprises Ministry helped in developing the study’s sampling frame. Careful
- 25 -
evaluation of the registration details led to selection of 130 firms in the final sampling frame.
This sampling frame represented all publicly listed companies and public enterprises, and
medium to large private companies and partnerships. The firms received a survey package
containing the cover letter, the research instrument, and a self-addressed prepaid envelope.
Dillman’s (2007) methodology was closely followed in developing and administrating the
instrument. The first mail and telephone follow-up took place three weeks later. The mail follow-
up contained a follow-up letter and a copy of the instrument. The second mail and telephone
follow-up was after another three weeks. This time, the mail follow-up contained a follow-up
letter, but not a copy of the instrument. The research instrument could collect data for six years. It
was assumed that the respondents perception of the flexibility of their IT infrastructure to be
statistically indifferent in the six years. Progressively, 51 firms responded to the survey with most
providing information for more than one year, providing 192 valid datasets. All data were
converted to a base year using the trimmed inflation rate to control for the effect of inflation on
reported values (Reserve Bank of Fiji, 2006). The trimmed inflation rate excludes temporary
price changes, as the effects of these price changes are short-lived.
Table 1 presents the variables and their descriptive statistics. Level of IT investments, end user
training, and IT human capital varies across firms. Firms also have varying returns on their
assets, equity, and sales, costs in relation to sales, and revenue in relation to employees. Table 2
presents the bivariate correlations between the dependent variables, independent variables, and
the control variables. The correlation matrix shows that firms with higher IT investments have
better sales revenue per employee, and mature IT investors have a more flexible IT infrastructure.
The first and the last twenty responses were used to test the non-response bias for the perceptive
measures of flexible IT infrastructure. T-test of the two independent, but equal, samples showed
- 26 -
no significant differences on any of the five items. Pre-analysis examination of the data for
normality (skewness and kurtosis) revealed that firm-level performance measures were slightly
non-normal. Model testing included their log-transformed values. Post analysis, the residuals
tested for normality, and the p-values of the Kolmogorov-Smirnov test did not indicate a
violation of the normality assumption. The White’s test checked for heteroscedasticity and did
not identify any issue of non-random variance. The Durbin-Watson statistic did not indicate any
problem of serial correlation in the estimation. The variance inflation factors (VIF) were below
the threshold value of 10, suggesting multicollinearity was not an issue. The interaction terms,
however, showed higher end of the acceptable VIF.
[INSERT TABLE 1 ABOUT HERE]
[INSERT TABLE 2 ABOUT HERE]
6 RESULTS
6.1 The Relationship between IT Investment and Related Complementarities and Measures of
Process Performance
Table 3 provides the regression results of the relationship between IT investment and related
complementarities, and five measures of business process performance modeled as follows:
SIZEITDPYINVFLEXITHCTRNGITINY 76543210
Where
Y = Five measures of process level performance (SREM, OESA, LCSA, SGEX, and SATA)
ITIN = Annual IT investment
TRNG = Annual Spending on End User Training
ITHC = Annual Spending on IT Human Capital
FLEX = Flexible IT Infrastructure
YINV = Number of Years of IT Investment
SIZE = Firm Size measured by total assets
IT investment has a significant and favorable association with sales revenue per employee (β =
0.851***). End user training is favorably and significantly associated with labor cost as
- 27 -
parentage of sales (β = 0.906***) and selling and general expense as percentage of sales (β = -
0.898***). Human IT Capital has a significant and favorable association with four measures of
process-level performance. The magnitude of change in these performance measures caused by a
unit of change in HITC ranges from 0.199** to 0.527***. Flexible IT infrastructure shares a
favorable and significant relationship with two measures of process level performance (β (LCSA
= -0.119**, and β (SATA) = 0.217**). The control variables of size (TA) and the presence of
separate IT department (ITDP) significantly associate with four of the five process level
measures. The overall level of explained variance in process-level performance by the IT
investments and related complementarities ranges from 11.8% in SATA to 85.7% in LCSA.
Overall, the results support Hypotheses 1, 2, 3 and 4.
[INSERT TABLE 3 ABOUT HERE]
6.2 Interaction Effects of IT Infrastructure Investments and Related Complementarities
Table 4 provides the result of the contingency relationships suggested in hypotheses 5a, 5b, and
5c modeled as follows:
SIZEITDPYINITINxFLEX
ITINxITHCITINxTRNGFLEXITHCTRNGITINY
10987
6543210
Where
Y = Five measures of process level performance (SREM, OESA, LCSA, SGEX, and SATA)
ITIN = Annual IT investment
TRNG = Annual Spending on End User Training
ITHC = Annual Spending on IT Human Capital
FLEX = Flexible IT Infrastructure
YINV = Number of Years of IT Investment
SIZE = Firm Size measured by total assets
This study adopts a moderated regression analysis (Aguinis, 2004; Aiken and West, 1991), where
the interaction terms are a product of centering (subtracting the mean value from each
observation) and then multiplying the moderator variable with the main variable (IT investment).
- 28 -
Centering reduces the multicollinearity between interaction terms and the component multipliers.
As the interaction variables share the same multiplier, a separate regression evaluates each
interaction effect to reduce any further instances of multicollinearity.
Hypotheses 5a, 5b, and 5c predicted that the interaction terms of the three complementarities
(end-user training, human IT capital and flexible IT infrastructure) and IT investment will explain
variance in process-level performance. The coefficient for the interaction term IT Investment x
End-User Training is significant with SATA (β = 0.254**). The coefficient for the interaction
term IT Infrastructure x Human IT Capital is significant with business process measures of LCSA
(β = -0.323***), SGEX (β = -0.311***), and SATA (β = 0.471***). Similarly, the coefficient for
the interaction term IT Infrastructure x Flexible IT Infrastructure is significant with business
process measures of SREM (β = 0.219**). The inclusion of the contingency relationships
explained a greater proportion of variance in measures of business process performance
compared to the direct relationships. The interaction terms increased the variance explained in
SREM by 14%, in OSEA by 0.4%, in LCSA by .01%, in SGEX by 3.7%, and in SATA by 3.3%.
The results suggest that the interaction between the level of investment in IT (IT resources) and
IT-related complementaries favorably associate with some measures of processes-level
performance. There is a greater influence of HITC on IT investments than TRNG and FLEX.
Overall, the data moderately supported hypotheses 5a, 5b, and 5c.
[INSERT TABLE 4 ABOUT HERE]
6.3 The Relationship between Business Process Performance and Firm-Level Performance
Table 5 provides the result of test of the relationship between the measures of process-level
performance and firm-level performance modeled as follows:
- 29 -
SATASGEXLCSAOSEASREMY 543210
Where
Y = Three measures of firm-level performance (ROA, ROS, and ROE)
SREM = Sales Revenue per Employee
OSEA = Operating Exp as a Percentage to Sales
LCSA = Labor cost as a percentage of Sales
SGEX = Selling and General Expense as a Percentage of Sales
SATA = Sales to Total Assets Ratio
The process performance measure of percentage of sales revenue per employee favorably and
significantly associates with the firm-level performance measure of return on sales (β = 0.150**).
All three expense-related measures of process-level performance (OSEA, LCSA, and SGEX)
favorably and significantly associate with all three measures of firm-level performance (the β
ranging from β = 0.568*** to β = 0.213***). The sales to total assets ratio also favorably and
significantly associates with all three measures of firm-level performance β (ROA) = 0.293***, β
(ROS) = 0.283***, and β (ROE) = 0.138**. The data supports hypothesis 61.
[INSERT TABLE 5 ABOUT HERE]
Test of mediation of process-level performance can also inform about the direct and indirect
effect of IT and related complementarities on performance. A method suggested by Baron and
Kenny (1986) tests this mediation effect. The first consideration is the direct relationship with IT
investments and complementarities as the predictor variable and firm-level performance as the
criterion variable. Whether the predictor variable (IT investments and complementarities)
1 We also evaluated the incremental effect of time (year of investment) on the measures of process-level
performance and firm level performance. The base year was the constant and dummy variables for each of the
following years allowed the intercept to vary by year. The result indicated that time is positively related to (from one
year to another) process-level and firm-level performance. We conducted a test to determine whether the process and
firm-level performance differed across industry types. The data was divided into eight industry types (Agriculture,
Finance, Manufacturing, Media, Retail, Telecommunications, Tourism, and Transportation), with Agriculture as the
base industry. This analysis revealed that impact of IT and complementarities on process-level and firm level
performances differ across industries when compared to the Agricultural industry.
- 30 -
correlates with the mediating variable (business processes) is considered next. This step tested
hypotheses 1 to 4 in section 6.1. The final step is evaluating whether the mediating variable
(process-level performance) affects the criterion variable (firm-level performance) by using firm-
level performance as the criterion variable and IT investments and complementarities and
process-level performance measures as predictors. This process establishes the magnitude of the
mediation effect of process-level performance and the relationship between the initial predictor
and criterion variables.
Section 6.1 reports a significant and favorable relationship between the level of IT investment
and IT-related complementarities and measures of process-level performance. The
unstandardised regression coefficients of IT investment and complementarities also supported
this outcome. Changes in the unstandardized regression coefficients of IT investment and
complementarities when regressed together with process-level performance measures also
suggested that measures of process-level performance mediated the relationship between IT
investments and complementarities and firm-level performance. The magnitude of change in the
unstandardized regression coefficients of IT investment and complementarities determines the
significance of the mediation. This is determined by the dividing the product of the
unstandardized regression coefficients of process-level performance measures and IT Investments
and complementarities by a standard error term (Baron and Kenny, 1986). The highlighted
portion of the equation represents the standard error term:
z-value = a*b/SQRT(b2*sa
2 + a
2*sb
2 + sa
2*sb
2)
Where
a and b are unstandardized regression coefficients’ and
sa and sb are their standard errors.
- 31 -
The product (z-score) was greater than 1.96, suggesting the mediating effect was significant at
p<0.05. These results indicate that business process performance mediates the relationship
between level of IT investment and complementarities, and measures of firm-level performance,
and that this mediated effect is statistically significant.
The above analysis, however, does not inform whether IT-related firm-level performance
materialize from improvement in efficiency or increased profitability. Table 6 informs that IT
investments and related complementarities relate to firm-level performance. Table 5 informs that
process improvements relate to overall financial performance. DuPont analysis makes possible a
simultaneous analysis of efficiency and profitability, and they show how they interact to
determine overall financial performance (Dehning and Stratopoulus, 2002). The ROA is a
product of Net Profit Margin (NPM) and Total Asset Turnover (TAT) in a DuPont analysis,
shown as the following formula.
(Net profit/Total asset) = (Net profit/Net sales) x (Net sales/Total assets)
(ROA) (NPM) (TAT)
An extension of the basic DuPont analysis can explore the determinants of ROE, shown as the
following formula.
Return on Equity= Asset Turnover x Net Profit Margin x Leverage
(Net profit/Equity) = (Net profit/Sales) x (Sales/Total assets) x (Total assets/Equity)
(ROE) (NPM) (TAT) 1/(1-DR)
Where DR is the debt ratio= debt (D)/assets (A)
- 32 -
Breaking ROE into these three parts allows evaluation of how well one can manage the
company’s assets, expenses, and debt. Improved operating performance in terms of ROA and
ROE can eventuate from increased capital asset turnover, increased operating profit margins, and
changed financial leverage. Specific decisions on cost control, efficiency productivity, marketing
choices affect each of these primary drivers.
Sales revenue per employee and sales as a percentage to sales measure efficiency. This efficiency
will show up in Asset Turnover (TAT). Operating costs as percentage of sales (OSEA, LCSA,
and SGEX) measure profitability, and will show in net profit margin (NPM). Table 3 shows that
investments in IT significantly associate with efficiency contributors of SREM and SATA.
Investments in IT-related complementarities associate with profitability contributors of OSEA,
LCSA, and SGEX. Table 5 shows that profitability process-level measures related strongly to
ROA than efficiency process-level measures. This analysis suggests that IT investments
contribution to overall financial performance measure of ROA is through moderate efficiency
improvements. IT-related complementarities improve profitability, and improved profitability
contributes more towards overall financial performance measure of ROA. In DuPont analysis
terms, the net profit margin contributes more towards ROA than total asset turnover. Analysis of
composition of ROE with profitability and efficiency measures suggest that the net profit margin
(profitability) contributes more towards ROE than total asset turnover (efficiency). The impact of
the financial leverage was negligent. The outcome of this analysis suggests a complementary IT
investment approach can provide better overall financial performance in firms in developing
countries.
- 33 -
7. DISCUSSION
A majority of the world’s population resides in developing countries, making it important to
understand how to improve and sustain their overall well-being. IT has played a central role in
the development of a global economy, but understanding the contribution of IT in smaller
developing countries has not received due attention. Sustainable private sector investment in IT
in developing countries is critical for their growth and development. Understanding how to
maximize IT investments contribution to business value is an important venture to ensure
sustained investment in IT resources.
This study’s complementarity IT business value model suggests that investment in IT and related
complementarities relates to improving firms process-level performance. Firms that improve their
process-level performance through the complementary investment strategy also improve their
firm-level performance. This outcome demonstrates the importance of appropriate investment in
IT and related resources (e.g., human resources). IT is a commodity (Clemons and Row, 1991;
Powell and Dent-Micallef, 1997), and for developing countries, IT resources are new
commodities. In competitive markets, IT resources are a common commodity, and, per se, do not
explain performance differences across firms. The value-generating potential of IT in these
economies is contingent upon how the organizations’ unique capabilities leverage the IT
resources.
IT investments in developing countries can provide sustainable IT-based advantages because
investment in IT depicts acquiring a want rather than a competitive need. This study’s outcome
confirms this position. Firm’s level of investment into IT favorably associates with their
effectiveness in revenue generation and efficiency in conducting their business. This finding is
also consistent with prior studies in developed countries that assert that a well-directed and
- 34 -
planned IT investment can provide business value (Barua and Mukhopadhyay, 2000; Dehning et
al., 2007).
Better IT-related value emerges from complementary consideration of related resources.
Investment in IT provides new resources to firms. Appropriate complementary consideration in
the firms key interacting resource, human resources is important to secure IT-related business
value (Powell and Dent-Micallef, 1997). The human resources considerations in the form of end-
user training and human IT capital ensures that firms possess adequate knowledge to efficiently
and effectively use their IT resources to improve their performance. End-user training improves
operational efficiencies through improved revenue generation, and effectiveness through lower
operational, labor, and selling costs. Complementary investments in human IT capital better their
revenue-generating potential, and improve effectiveness through lower costs. A coordinated IT
investment strategy results in a flexible IT infrastructure, which also relates to improved process-
level performance. This outcome is evident with lower labor costs, and improved revenue-
generating potential of their assets.
The related complementarities also enhance the IT resources ability to contribute to business
value. This contribution is in the form of lower operational and labor costs in relation to sales and
improvement in revenue per employee. Understanding and indentifying the interaction effects of
various organizational resources is challenging (Jeffers et al., 2008). However, this study’s
outcome indicates that the interaction between IT resources and the three related
complementarities improve some of the business processes, as they explain some additional
variance in the measures of process-level performance.
- 35 -
Process-level efficiency and effectiveness impacts firm’s net position (net income). This outcome
is possible through increased revenue and/or reduced costs in relation to revenue and other
resources. The result is efficient use of firm’s assets to earn revenue, reflected in firm-level
measures of performance. This study’s findings support this notion as it shows a positive
association between process-level and firm-level performance. A complementary IT investment
strategy in developing countries has implications for process-level performance (directly), and
firm-level performance (indirectly). The test of the mediation-effect of process-level performance
also supports that IT resources and related complementarities have a direct and indirect impact
and business value.
The study’s outcome promotes confidence in IT investors in developing countries. It presents
investors the justification that their IT investment on its own can contribute to business value.
Investment in related-complementarities can provide additional business value on their own, and
improve leverage of the IT resources. Investors can improve the process-level performance
directly and the firm-level performance from this effort.
Additional analysis reveals that the relationship between IT resources and complementarities,
process-level performance, and firm-level performance improves over time. This outcome
indicates that a coordinated and progressive IT investment approach will provide incremental
benefits to firms. The result of this effort will be an agile IT infrastructure that is able to foresee
emerging IT-related value-enhancing opportunities. The relationship between IT investments and
complementarities, process-level, and firm-level performance also differs across industries. This
outcome is consistent with the notion that fit between technology and processes differ across
industries, leading to a number of industry specific studies (e.g., Dehning et al., 2007; Ray et al.,
2005).
- 36 -
8. CONTRIBUTIONS AND IMPLICATIONS
There are several important implications for researchers and practitioners in this study. This study
presents a complementary IT business value model for developing countries. This effort was
necessary because the capabilities-based IT business value models of the developed countries do
not fit well with the IT investment environment of the developing economies. This model is
conceptualised based on research in developed economies (e.g., Barua et al., 1995; Dehning and
Richardson, 2002), but localized to demonstrate that a complementary IT investment approach
results in firms achieving process-level benefits and overall business value in developing
economies. This important effort provides researchers with opportunities to understand the
environment in which businesses in developing countries can source IT-related business value.
This study’s model focuses on the human resource-related complementarities, but presents
opportunities to consider other resources that could be ideal complementarities to IT resources in
developing countries.
This study finds favorable relationships between IT investments and related complementarities
and measures of business value at an aggregate level. Some process-level measures did not
favorably relate to IT resources and related complementarities at this level. Additional analysis
suggested that the contribution of IT differs across industries. These outcomes suggest that a
deeper understanding of the contribution of IT to business value is possible through industry
specific studies. Considering specific industries will develop further knowledge on the specific
process-level improvements in industries, and their relationship to various firm-level performance
measures. The interaction effects of IT resources and related complementarities on process-level
performance found unconvincing results. Future research, by considering specific industries, can
- 37 -
broaden understanding on the nature of interaction between resources within industries that is an
additional source of business value for them.
This study presents opportunity for researchers to evaluate IT investment performance impacts in
smaller firms in developed countries. Much of IT business value research in developed countries
focuses on the large firms. Smaller firms contribute significantly towards the prosperity of
developed countries. These smaller firms may exhibit characteristics of the firms in developing
countries. This means that the proposed model would be appropriate in understanding how they
could improve on their IT-related business value. This effort will make an important contribution
to understanding IT-related business value generation in small firms in the developed countries.
For practice, this study suggests that investment in IT does contribute to business value in
developing countries. This achievement, however, requires a coordinated IT investment strategy
that embraces the IT deployment environment. Manageable level of investment in IT will suffice
with appropriate consideration in related complementary resources. End-user training and
acquiring human IT capital are important complementary resources to consider with new
investment in IT. Process-level and firm-level performance is possible with this coordinated IT
investment strategy.
9. LIMITATIONS
A number of limitations need consideration when interpreting the findings discussed above. This
study’s sampling frame included all firms that invested in IT in Fiji, an excellent candidate for a
developing economy. Fifty-one firms responded, giving a response rate of 39.2%. The research
instrument could collect data for six years, thus the model test conducted with one hundred and
ninety two data sets. Though the diagnostic checks did not reveal any issues with data quality,
- 38 -
readers may exercise of some caution when generalizing the findings. Organizational and societal
cultural differences exist across countries, even if they are in close proximity. The study’s dataset
represents well the smaller developing economies, and smaller firms in more industrialized
developing countries. Multi-country studies can provide insights on the role of culture in sourcing
IT-related business value. The limited dataset allowed the conduct of this study at an aggregate
level. This restricted the study to use the generic measures of process and firm level
performances. Possible differences may exit across industries making specific process level
measures relevant in some industries. Future research can capitalize on this opportunity with a
larger dataset. This study uses actual financial data from public and private companies. Financial
data may differ with the choice of accounting methods, especially data relating to firm-level
measures. While collecting data from one country minimizes this limitation, controlling for
differences in accounting methods between companies can eliminate any biases owing to firms
accounting choices.
10. CONCLUSIONS
IT resources play an important role in shaping economies globally. However, the mechanism for
deriving benefits from IT in developing countries is less clear. This study presents a model of IT
business value for developing countries that incorporates the effect of IT and complementary
investments on business processes and firm-level performances. This model tested its predictions
with actual financial data. IT investments can contribute to business value in developing
countries. The relatively tranquil economic conditions provide an ideal opportunity for firms to
utilize IT resources to increase their internal and external coordinating efficiencies and lower
their cost structure. Absence of strong competition allows firms to sustain the benefit and enjoy
improvements in their businesses processes and overall performance.
- 39 -
However, IT remains a commodity. Securing benefits from IT is contingent upon its successful
utilization (Clemons and Row, 1991; Mata et al., 1995; Powell and Dent-Micallef, 1997). Human
resource factors influence the use of this commodity (Clemons and Row, 1991; Powell, 1995;
Powell and Dent-Micallef, 1997), and merging IT with human dimensions ensures better IT-
related advantage. This is also true in developing countries, and this study suggests that
complementary investment in end user training and investment into human IT capital betters IT-
related business value. A coordinated IT investment approach also builds a flexible and agile IT
infrastructure, allowing firms to model their information systems to take advantage of the
opportunities provided by IT. This study encourages scholars to provide further directions and
motivations for continued IT investments in developing countries. This important initiative will
ensure developing countries’ continued growth and sustainability in a truly globalized
environment.
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IT Investments
IT Human Capital
End-User
Training
Process-Level
Performance
Flexible IT
Infrastructure
Firm-Level
Performance H1
H3
H4
H6
H5b
H5
c H
5a
Controls
H2
Figure 1. Complementarities-Based Business Value Model
- 48 -
Table 1
Variable Definition and Descriptive Statistics (N = 192)
Variable Description Sample
Minimum
Sample
Maximum
Sample
Mean
Sample
Standard
Deviation
ITIN (M$) Annual IT investment 0.025 62 0.8 2.3
TRNG (M$) Annual Spending on End User Training 0.002 1.2 .16 .22
HITC (M$) Annual Spending on IT Human Capital 0.003 4.7 0.35 1.07
FLEX Flexible IT Infrastructure 2 7 4.597 1.338
YINV Number of Years of IT Investment 1 54 26 26
TA ($M) Total Assets (Proxy for Firm Size) 0.5 2484 234 473
SREM($M) Sales Revenue per Employee 0.015 8 0.36 1.02
OESA Operating Exp as a Percentage to Sales 0.024 0.856 0.654 0.119
LCSA Labour Cost as Percentage to Sales 0.012 0.608 0.129 0.119
SGEX Selling and Gen. Exp. as a % to Sales 0.009 0.40 0.088 0.103
SATA Sales to Total Assets Ratio 0.029 8.877 0.796 1.091
ROA Return on Assets -0.11 0.45 0.07 0.10
ROE Return on Equity -0.58 0.72 0.17 0.18
ROS Return on Sales -0.19 0.96 0.16 0.207
Table 2
Correlation Coefficients
ITIN TRNG HITC FLEX YINV IDIP TA SREM OSEA LCSA SGEX SATA ROA ROE
TRNG 0.35
***
HITC 0.34
***
0.59
***
FLEX 0.38 ***
0.26 ***
0.32 ***
YINV -0.02
0.30
***
0.35*
**
0.79
***
ITDP 0.15 **
0.23 ***
0.35***
0.37 ***
0.35 ***
TA -0.00
-0.03
0.13
0.29
***
0.26
***
0.30
***
SREM 0.84
****
0.10
**
0.14
**
0.01
-0.05
0.12
0.20
***
OESA 0.08
-0.15
*
-0.12
0.05
-0.03
-0.12
-0.48
*** -0.08
LCSA -0.04
-0.91
***
-0.62
***
-0.18
-0.14
-0.13
-0.09
-0.07
0.14
SGEX -0.04
-0.90 ***
-0.60 ***
-0.16 **
0.13
0.12
-0.09
-0.06
0.12
0.59 ***
SATA 0.08
0.07
0.15
*
0.21
***
-0.12
-0.17
**
-0.29
***
-0.02
0.01
-0.04
-0.01
ROA 0.07
-0.22 ***
-0.29 ***
0.34 ***
0.24 ***
0.04
0.06
0.01
-0.52 ***
-0.19 ***
-0.15 **
0.36 ***
ROE 0.10
**
-0.22
***
-0.14
0.05
0.02
0.14
0.10
-0.07
-0.59
***
-0.24
***
-0.22
***
0.16
**
0.66
***
ROS 0.35
**
-0.21
***
-0.18
0.03
0.05
0.28
***
0.69
***
0.23
**
-0.65
***
-0.22
***
-0.20
***
0.27
***
0.48
***
0.55
***
* p< 0.05, ** p<0.01, and ***p<0.001
- 49 -
Table 3
Direct Effects Model
Independent Variables Hypothesis Model 1(+)
DV=SREM
Model 2(-)
DV=OESA
Model 3(-)
DV=LCSA
Model 4(-)
DV=SGEX
Model 5(+)
DV=SATA
IT Investments H1 0.851*** 0.064 -0.038 -0.020 0.059
End-User Training H2 0.078 -0.039 -0.906*** -0.898*** 0.045
Human IT Capital H3 0.254*** -0.199* -0.203** -0.527*** 0.127
Flexible IT Infrastructure H4 0.022 0.060 -0.119** -0.087 0.217**
Controls
Years of IT Investment -0.008 -0.055 -0.190 0.171 -0.149
Separate IT Department -0.003 -0.009 -0.024* -0.030* -0.026
Size 0.249*** -0.524*** -0.008 -0.007 -0.235
R2 0.798*** 0.301*** 0.857*** 0.854*** 0.118***
Max VIF 2.966 1.697 1.569 1.986 2.785
*p<0.05, **p<0.01, and ***p<0.001 (All tests are two-tailed)
Note: The (+) and (-) signs beside the model labels indicate the sign of the beta values that would depict a
favourable relationship between the independent and dependent variables. This means a favourable relationship
is a positive association between SREM and SATA and the independent variables and a negative relationship
between OSEA, LCSA, and SGEX and the independent variables.
Table 4
Interaction Effects of IT Infrastructure Investments and related Complementarities
Variable Hypothesis Model 1(+)
DV=SREV
Model 2(-)
DV=OSEA
Model 3(-)
DV=LCSA
Model 4(-)
DV=SGEX
Model 5(+)
DV=SATA
IT Investments x End-
User Training H5a 0.021 -0.003 -0.011 -0.010 0.254**
IT Investments x Human
IT Capital H5b 0.016 -0.022 -0.323*** -0.311*** 0.471***
IT Investments x
Flexible IT
Infrastructure
H5c 0.219** -0.030 -0.015 0.019 0.098*
Controls
Years of IT Investment -0.008 -0.055 -0.190 0.171 -0.149
Separate IT Department -0.003 -0.009 -0.024** -0.030** -0.026
Size 0.249*** -0.524*** -0.008 -0.007 -0.235
R2 0.938*** 0.305*** 0.858*** 0.891*** 0.150***
Adjusted R2 0.935 0.263 0.852 0.889 0.098
Max VIF 6.328 6.128 6.358 6.285 7.325
*p<0.05, **p<0.01, and ***p<0.001 (All tests are two-tailed)
- 50 -
Table 5
Relationship between Process-Level Performance and Firm-Level Performance
Variable Hypothesis Model 1
DV=ROA
Model 2
DV=ROS
Model 3
DV=ROE
Sales Revenue Per Employee H6(+) 0.050 0.150** 0.030
Operating Expenses as a Percentage of Sales H6(-) -0.468*** -0.568*** -0.566***
Selling Expenses as a Percentage of Sales H6(-) -0.298*** -0.216*** -0.214***
Labor Expenses as a Percentage of Sales H6(-) -0.214** -0.213*** -0.218***
Sales to Total Assets Ratio H6(+) 0.293*** 0.283*** 0.138**
Controls
Years of IT Investment 0.189** 0.04 0.06
Separate IT Department 0.02 0.14 0.10
Size 0.05 0.213** 0.583***
R2 0.461*** 0.583*** 0.489***
Adjusted R2 0.446 0.561 0.463
*p<0.05, **p<0.01, and ***p<0.001 (All tests are two-tailed)
Table 6 Relationship between IT Investments, IT-Related Complementarities, and Firm-Level Performance
Variable MODEL 1
DV=ROA
MODEL 2
DV=ROE
MODEL 1
DV=ROS
IT Investments 0.080** 0.110** 0.070**
End-User Training 0.220*** -0.230*** -0.210***
Human IT Capital -0.340*** -0.030 -0.380***
Flexible IT Infrastructure 0.430*** 0.190** 0.020
Controls
Years of IT Investment 0.010 0.010 0.030
Separate IT Department 0.270*** 0.230*** 0.240***
Size 0.010 0.040 0.720***
R2 Model 1 0.221*** 0.114*** 0.609***
Adjusted R2 0.201 0.103 0.588
*p<0.05, **p<0.01, and ***p<0.001
