Legatura Intre It, So Si Os [612787]

Business Process Management Journal
Aligning IT , strategic orientation and organizational structure
Prodromos D. Chatzoglou, Anastasios D. Diamantidis, Eftichia Vraimaki, Stergios K. Vranakis, Dimitrios A.
Kourtidis,
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Prodromos D. Chatzoglou, Anastasios D. Diamantidis, Eftichia Vraimaki, Stergios K. Vranakis, Dimitrios
A. Kourtidis, (2011) "Aligning IT, strategic orientation and organizational structure", Business Process
Management Journal, Vol. 17 Issue: 4, pp.663-687, doi: 10.1108/14637151111149474
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Aligning IT, strategic orientation
and organizational structure
Prodromos D. Chatzoglou, Anastasios D. Diamantidis,
Eftichia Vraimaki and Stergios K. Vranakis
Department of Production and Management Engineering,
Democritus University of Thrace, Xanthi, Greece, and
Dimitrios A. Kourtidis
Business School, Glasgow Caledonian University, Glasgow, UK
Abstract
Purpose – The purpose of the paper is to examine and analyze the alignment between (information
technology) IT, strategic orientation (SO) and organizational structure (OS) and their impact on firm
performance (FP).
Design/methodology/approach – A theoretical framework is proposed regarding the constructs of
IT, SO and OS. A model incorporating these three constructs is examined and their impact on FP is
assessed using structural equation modeling (SEM). The sample data from 295 firms were obtainedthrough structured questionnaires.
Findings – The results of the SEM support the hypothesis that the alignment between IT, SO and OS
significantly affects FP.
Research limitations/implications – Non-financial and intangible performance measurements
are not included and the sample is not homogeneous.
Practical implications – This study suggests that managers should choose the appropriate level
and type of IT, depending on a firm’s structure and SO, in order to benefit from the advantages of IT
usage and achieve higher performance levels.
Originality/value – This study presents an overview of the impact of SO, OS and IT on FP, and that
shows that there is scope for further research into the inter-organizational relationships that exist
between them.
Keywords Strategic orientation, Organizational structures, Information technology, Firm performance,
Structural equation modeling
Paper type Research paper
1. Introduction
The growth and diversity of international business has raised new competitivechallenges and requirements, forcing firms to re-examine their internal environment inorder to improve their performance and achieve a sustainable competitive advantage(Wright et al., 1995). Thus, many firms have spent a vast amount of resources in order
to improve their competitiveness by looking at their internal processes (Day and
Lichtenstein, 2006; Stewart, 2007).
During the 1980s, it was believed that the basic source of a firm’s competitive
advantage relied on industry structure (Porter, 1985). In the 1990s, researchers (Barney,
1991; Kay, 1995; Powell and Dent-Micallef, 1997) focused their studies on firm’s internalfactors, introducing the “resource-based” view of the firm. Recent research findingssuggest that firms may improve the value of their established competitive advantagethrough their strategic orientation (SO) (Morgan and Strong, 2003), informationThe current issue and full text archive of this journal is available at
www.emeraldinsight.com/1463-7154.htm
IT, orientation
and structure
663
Business Process Management
Journal
Vol. 17 No. 4, 2011
pp. 663-687
qEmerald Group Publishing Limited
1463-7154
DOI 10.1108/14637151111149474
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technology (IT) (Griffiths and Finlay, 2004; Stewart, 2007) and business structure
(Bergeron et al. , 2004). Actually, the relationship between SO, IT, organizational
structure (OS) and firm performance (FP) has been the focal point for a number of
researchers (Raymond et al. , 1995; Croteau et al. , 2001; Bergeron et al., 2004).
In response to anticipated changes in their environment, firms are deploying IT at
an increasing rate. Thus, IT investment has been an important issue for seniorexecutives, as it is one of the major budget items in most businesses. However, there is
more than one way to invest in IT, this is why several theoretical IS models focus onthe impact of alignment upon performance (Bergeron et al. , 2004). IT could influence
business performance in a way that it would be in “alignment” or “fit” with thestrategic, structural, and environmental dynamics specific to each organization.Interestingly, a fundamental question underlying these transformations has been
raised: how can an organization:
.translate its IT investments into increased business performance;
.improve its productivity; and
.increase the market share it holds, and profitability or other indicators oforganizational effectiveness?
Management literature has shown contradictory results on the impact of IT
investments on business performance (Sircar et al., 2000), meaning that IT investments
can improve business performance under many market conditions.
SO is one of the aspects of corporate culture of a firm (Deshpande et al. , 1993; Hurley
and Hult, 1998; Narver and Slater, 1990). Corporate or organizational culture representsintangible resources for firms (Barney, 1991; Grant, 1991). Managers place different
emphases on strategic behaviors and select specific SOs depending on what they wish
to accomplish (Olson et al., 2005). For example, many firms with a strong customer
orientation emphasize the creation and maintenance of customer value. Other firms,
more competitor oriented, encourage in-depth assessment of targeted competitors,
while, on the other hand, and cost-oriented firms pursue efficiency throughout theirvalue chain (Day, 1990; Porter, 1985). These different types of SOs are not mutually
exclusive; firms may engage in multiple sets of behaviors (Gatignon and Xuereb, 1997).
The purpose of this paper is to analyze the contemporary impact of SO, OS and IT
on FP and to assess the organizational fit, incorporating all these constructs into a
model that is tested using the structural equation modeling (SEM) approach. Literature
suggests that the majority of the studies on alignment have focused on two
dimensions, as for example between business and IT strategies or between the formerand IT structures (Sabherwal et al. , 2001). Moreover, Bergeron et al. (2004, p. 1016)
point out that alignment research has been undertaken using samples from “[ …] large,
technologically sophisticated organizations”; hence, results not only cannot begeneralized to other organizations, but also do not assists researchers to develop and
test “[ …] a valid operational model of strategic alignment”. Based on the research
model proposed by Bergeron et al. (2004), the effect of each of SO, OS and IT constructs
on performance versus their effect, when considered as a cohesive, aligned group ofconstructs is examined. In this respect, the current constitutes a replication research,
which not only re-tests the alignment hypothesis but it does so in a very differentnon-North American setting, using a sample that comprises all kinds of firms, fromvery small to very large, operating in Southeastern Europe.BPMJ
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2. Literature review
2.1 Strategic orientation
The concept of strategy has been associated with FP, as it is a focal issue that highlydetermines the decision-making processes within organizations (Morgan and Strong,
2003). This is why, explaining as well as predicting FP is a central objective in the
strategic management research (Ketchen et al., 1996). Furthermore, contemporary
strategic management research aims at identifying the sources and determinants of
observed differences in profitability among organizations (Spanos et al., 2004). As
Escriba-Esteve et al. (2008), claim that the positive influence of the firm’s SO may be
moderated by the environment conditions, the experience of top management team,and the corporate and competitive strategies developed by the firm.
Traditionally, the concept of strategy has been viewed in two dimensions, namely
process and content. The strategy process refers to the activities that guide an
organization towards choosing a competitive strategy (Ketchen et al. , 1996). Strategy
content, on the other hand, is related to a firm’s competitive forces present in the
environment, such as actual and potential competitors, buyers and suppliers, as well as
product/service substitutes (Porter, 1980). The strategy chosen enables the
organization to predict, respond to, or dictate the existing environmental forces,
making strategic content a key determinant of performance (Ketchen et al. , 1996).
However, other researchers (Huff and Reger, 1987) argue that this distinction
between process and content is, to a large extent, artificial. Therefore, an integratedapproach to strategy, accounting for process and content, as well as their interactions,
is needed, as research suggests that process and content factors have a major impact
on performance along with their interactions (Ketchen et al., 1996).
Strategy content is merely preoccupied with how an organization uses strategy to
adapt or to change some characteristics of its environment in order to achieve a moreadvantageous alignment with them (Manu and Sriram, 1996). It focuses upon the
outcome of strategic decisions, while its identifiable form in organizations has beenalso described as strategic fit, strategic predisposition, strategic thrust, strategic choice
and, more frequently, is referred to as SO (Morgan and Strong, 1998, 2003).
Relevant literature has followed three main approaches regarding SO measurement:
the narrative approach, the classificatory approach and the comparative approach(Venkatraman, 1989; Morgan and Strong, 1998, 2003). As Venkatraman (1989)
describes, the narrative approach mirrors the case-based tradition of business policy,
based on the notion that the complex features of business strategy should only be
illustrated in their holistic and contextual form. It is based on the belief that thedistinctiveness of the concept of strategy is grounded upon its uniqueness to a specific
situation, adopting a rather philosophical method for examining an organization’s SO
(Venkatraman, 1989).
The classificatory approach, according to Venkatraman (1989), moves away from
the idiosyncratic, narrative description of strategy, developing conceptual or empiricalclassifications of strategy. This approach attempts to classify SO based on either ex
ante theoretical reasoning (“typologies” – Porter, 1980) or ex post empirically obtained
categorizations (Morgan and Strong, 2003). Empirical categorizations are also knownas “taxonomies” and reflect empirical existence of internally reliable patterns. This
approach is believed to accurately capture the breadth and integrative character of
business strategy based on its internal consistency; it is however difficult to grasp theIT, orientation
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intra-group differences regarding the core strategic dimensions (Venkatraman, 1989;
Speed, 1993).
Finally, the comparative approach used here intends to identify and measure the key
traits/dimensions of the strategy construct (Venkatraman, 1989). According to Lukaset al. (2001), strategy is best specified as a multifaceted construct consisting of different
orientations. This way, business strategy is viewed in terms of the relative emphasisplaced by the organization, along each underlying dimension or subset of dimensions ofthe SO, rather than across various strategic classifications (Venkatraman, 1989; Morgan
and Strong, 1998, 2003; Lukas et al. , 2001). Venkatraman (1989) aiming to arrive at a set
of operational indicators for the dimensions of the “SO of business enterprises”
construct, proposed a six-dimensional model of SO: aggressiveness, analysis,defensiveness, futurity, proactiveness and riskiness. These operational indicators
have been commonly used in strategy research (Morgan and Strong, 1998, 2003; Lukas
et al., 2001) and serve as useful measures for relevant research in an attempt to captureand test theoretical relationships (Venkatraman, 1989).
2.1.1 Aggressiveness . Aggressiveness is a component of SO, which describes a
continuum ranging from offensiveness to defensiveness in a firm’s behaviour (Covinand Covin, 1990). This refers to the allocation of business resources and business’s
improved position, in terms of market share, at a rate relatively faster than competitors
(Clark and Montgomery, 1996). In order to differentiate from competitors, businessesoften choose to invest in product innovation (Morgan and Strong, 2003), in order togain a niche market position. When a firm outperforms its rivals, strong offensive
posture and aggressive responses to the actions of competitors are critical to market
performance (Fombrun and Ginsberg, 1990; Lumpkin and Dess, 2001). The assumptiongenerated by the above is that when a firm orients itself aggressively, performance
can be positively affected, as originally tested by Levitt in the 1960s (Morgan and
Strong, 2003).
2.1.2 Analysis . The analysis dimension reflects a firm’s capability to secure an
advantage in a competitive market (Morgan and Strong, 2003). According toVenkatraman (1989), SO is related to the overall problem-solving position assumed.Being an important characteristic of the decision-making processes in a firm, analysisseeks the best possible solution for this firm’s problems (Miller and Friesen, 1984).
Analysis also incorporates the level of internal consistency achieved in the overall
resource allocation (Grant and King, 1982), as well as the use of suitable managementsystems, including reward, information and control systems (Venkatraman, 1989).
From a market perspective, analysis includes predicting changes in customer base,
competitive structure, market partners, industry and environmental factors (Ganesan,1994). Chan et al. (1998) reported that analysis could be defined as the reliance on
detailed, numerically-oriented studies, prior to action.
2.1.3 Defensiveness. Defensiveness is the organization’s ability to maintain
prominence within its domain (Morgan and Strong, 2003), a concept that was firstintroduced by Chaganti and Sambharya (1987). This orientation aims at helping a firm
to form tight marketplace alliances with its customers, suppliers and distributors
(external defensiveness). The same tightness is also applied internally (internaldefensiveness) (Chan et al., 1998). McKee et al. (1989) and Day (1994) proposed a
positive relationship between business performance and defensiveness. The sameconclusion was also reached by Venkatraman (1989) and Morgan and Strong (2003).BPMJ
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2.1.4 Futurity . The futurity dimension refers to the adoption of a forward-looking,
long-term focus (Chan et al., 1998), reflecting one of the basic notions of strategic
management support, that is, how well prepared for and positioned in future
environmental situations an organization can be (Morgan and Strong, 1998).
Futurity can also be indicative of temporal considerations reflected in key strategic
decisions, in terms of the relative emphasis on effectiveness (longer term) considerationsversus efficiency (shorter term) considerations (Venkatraman, 1989). As far as therelationship between futurity and performance is concerned, it has been found that
commercial payoffs tend to be noticeable in firms pursuing a long-term strategy,
in comparison with short-term and transitory firms, regardless of the measures used toassess business performance (Doyle and Hooley, 1992, cited in Morgan and Strong, 2003).
2.1.5 Proactiveness . Proactiveness of SO allows an opportunity-seeking and
forward-looking perspective and reflects a firm’s tendency to participate in emergingindustries and continuously pursue market opportunities (Miles and Snow, 1978;Venkatraman, 1989). It is also considered as a core characteristic of innovative behavior(Manu and Sriram, 1996). The introduction of new technologies, ahead of the competition,allows the realization of pioneer advantages (Dess et al. , 1997). From the other side,
eliminating technologies ensures an adequate technology focus (Venkatraman, 1989). Thisdimension is indicative of a firm’s aspiration to continuously introduce new brands and
products (Lukas et al., 2001) and being one step ahead of its competitors (Chan et al., 1998).
The proactiveness dimension also entails removing resources from operations and
products in mature stages of the life cycle and investing in the introduction of new
products and processes (Wiklund and Shepherd, 2005). Considering these findings,successful management of innovation requires a proactive posture towards the marketand technology (Talke, 2007). Okpara’s (2009) results indicated that firms that adoptedproactive orientation achieved higher performance, profitability, and growth comparedwith those that adopted a conservative orientation.
2.1.6 Riskiness . A firm’s level of riskiness refers to how decisions are made and
action is taken with respect to the certain knowledge of probable outcomes (Talke,2007). This commits significant resources to uncertain projects (Dess and Lumpkin,
2005). The riskiness trait pertains mainly to resource allocation decisions, the choice of
products and markets (Venkatraman, 1989) and, in general, the gains or losses abusiness decision and consequent actions can generate (Clark and Montgomery, 1996).Risk taking has also been traditionally treated as an individual trait, usually referringto the business behavior of higher level administration (CEO’s) (Venkatraman, 1989).
Several studies show that an active risk management is of central relevance for FP
under uncertain market and technology conditions (Raz et al., 2002; Dvir et al. , 2003;
Salomo et al., 2004). Where these traits of riskiness can be found in a firm’s SO, as
Morgan and Strong (2003) indicate, performance is enhanced.
2.2 Organizational structure
The OS of an enterprise refers to an internal model of links and relationships betweenand within its factors, at all levels of the organization, in precisely defined quantities(Zehanovic and Zugaj, 1997).
Campbell et al. (1974) implied a useful distinction between structural and
structuring characteristics of organizations. For example, the physical characteristics,such as size, span of control, and flat/tall hierarchy, are the structural qualities ofIT, orientation
and structure
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an organization. In contrast, structuring includes policies and activities occurring
within the organization members, such as formalization, centralization, specialization,professionalization and vertical differentiation, that have received a great deal ofattention (because of their impact on organizational performance) (Stank et al., 1994).
Formalization refers to the degree to which decisions and working relationships are
governed by formal rules and standard policies and procedures (Tsai, 2002; Iyer et al.,
2004). Centralization, on the other hand, refers to the focus of decision-making
authority and control within an organizational entity (Tsai, 2002). Maximum
centralization implies decisions taken at the highest level possible (Andersen, 2002).
Specialization includes the department of tasks and activities across positions withinthe organizational entity (Tsai, 2002). Professionalization refers to the percentage ofprofessional staff members with certain educational backgrounds and noteworthyexperience (Miller et al., 1991). Vertical differentiation, finally, refers to the number of
levels in the firm’s hierarchy below the chief executive level (Damanpour, 1991).
OS is generally believed to be associated with FP (Meijaard et al., 2005). Spanos et al.
(2004) indicated a significant influence of business structure on firm profitability, whileTang et al. (2006) found that indeed the characteristics of OS affect organizational
performance. Furthermore, Tsai (2002) claims that three of the structuring components,formalization, centralization and specialization, are commonly considered to be
important influences on organizational performance.
Similarly, Meirovich et al. (2007) found that formalization improves organizational
performance, which is also supported by Kim (2007), as well as Wang (2003), who claims
that when a firm characterized by high formalization can, in fact, perform better than itscompetitors. Formalization enables the creation of organizational memory of bestpractices, which, in turn, makes knowledge use more efficient and may has a positiveimpact on performance, especially when it serves to collect valuable information andconveys priorities and values (John and Martin, 1984). On the other hand, Lin et al. (2008)
found that OS (formalization and decentralization) does not play a moderating role in therelationship between innovativeness and business performance; whereas the extent offormalization of an OS negatively correlates with business performance.
A number of studies (Reiman, 1975; Wang, 2003; Robson, 2004; Kim, 2007) implied
that specialization improves organizational performance. Further, Martı ´nezet al. (2007)
suggest that when firms improve their level of professionalization, they may takeadvantage of their strengths and achieve better performance. Thus, there is a positivelinkage between firm’s professionalization and performance. Finally, Ensley et al. (2006)
stated that there might be a positive relationship between vertical differentiation and FP.
2.3 Information technology
During the past 15 years, a number of researchers (Boudreau et al., 1998; Griffiths and
Finlay, 2004; Stewart, 2007) focused on the impact of IT investment on organizations’competitiveness, producing condlicting results. For example, Loveman (1994) concludedthat IT investments have practically no impact on productivity. In contrast, otherresearchers have reported that investments in IT have a positive impact onorganizations’ performance (Barua et al. , 1995; Hitt and Brynjolfsson, 1996).
The common purpose of investing on IT is to improve organizations’ competitive
advantages and, thus, its performance (Mahmood and Mann, 1993; Ragowsky et al.,1 9 9 6 ) .
According to Bergeron et al. (2004), there must be an “operationalized alignment” betweenBPMJ
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business strategy, business structure, IT strategy and IT structure. In other words, IT has
to “fit” an organization’s strategy, structure and environment. Focusing on the terms IT
strategy and IT structure, they concluded that:
(1) IT strategy consists of:
.IT environmental scanning; and
.strategic use of IT, while
(2) IT structure consists of:
.IT planning and control; and
.IT acquisition and implementation.
IT environmental scanning expresses an organization’s ability to identify and
understand the technological changes in its industry. Heo and Han (2003) approach
firms’ IT environment by using two measures:
(1) the identification of the characteristics and the number of alternative IT
structures; and
(2) the description and testing of the relationships between IT structure and
performance.
Their research results suggest that there is a positive relationship between IT
environmental scanning and FP.
The term “strategic use of IT” refers to the way firms use IT, in order to achieve and
create a significant competitive advantage in their industry (Bergeron et al., 2004) and,
as a consequence, improves product quality and performance (Blili and Raymond,
1993). Further, Duh et al. (2006) found that IT planning and control is positively related
to and directly impacts performance. Finally, Li and Ye (1999) examined the impact of
the environmental dynamism on the relationship between IT investment and FP to find
a strong positive effect. They also reported that IT implementation improves a firm’s
overall performance.
2.4 Firm performance
Performance measurement systems play an important role in developing strategic
plans and evaluating the achievement of organizational objectives. An effective
performance measurement system should cover all aspects of performance that are
relevant to the existence of an organization and the means by which it achieves successand viability (Kaplan and Norton, 1996; Hillman and Keim, 2001).
Generally, performance indicators combine financial, strategic and operating business
measures to estimate how well a company meets its targets. Business performance enablesthe management to evaluate the position of the organization, translating the needs for
performance improvement. Business performance management research has defined
performance from a variety of perspectives (Venkatraman and Ramanujam, 1986). In thisstudy, business performance was measured by using four financial items: ROA, sales
growth, profitability (Brown and Blackmon, 2005) and liquidity. Financial measures were
selected due to the fact that non-financial measures have some limitations. For example,some non-financial performance measures may be difficult to measure accurately,
efficiently, or in a timely fashion.IT, orientation
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Strategic management researchers have proposed a perceptual (primary) approach to
measure business performance (Dess and Robinson, 1984; Miller, 1987; Venkatraman
and Ramanujam, 1986). Venkatraman and Ramanjuam (1985) found positive andstatistically significant association between perceptual (primary) and secondary data on
performance indexes were observed. In this approach, respondents are asked to indicate
on a seven-point Likert scales how his or her firm performed relative to the competition.
Such an approach is most appropriate in a small business context where financial data
are often unavailable or unreliable (Sapienza et al., 1988).
2.5 Organizational (co-) alignment
Coalignment (also termed consistency, contingency, or fit) [… ] between strategy and its
context – whether it is the external environment [… ] or organizational characteristics, such
as structure [ …] administrative systems [… ] and managerial characteristics – [… ] has
significant positive implications for performance (Venkatraman and Prescott, 1990, p. 1).
Business-IT alignment, on the other hand, is important to organizations primarilybecause it assists the “ [ …] development and implementation of cohesive organization
and IT strategies that enable firms to focus on the application of IT to improve thebusiness” (Papp, 1999, p. 367).
Many studies (Tallon and Kraemer, 1999; Croteau et al., 2001; Pollalis, 2003; Byrd et al.,
2006; Rivard et al., 2006) investigate the alignment of IT, SO and OS and reported that this
alignment may have positive effects on FP. For example, Lee et al. (2008) suggested that
alignment between business and IS groups increased IS effectiveness and businessperformance, while business-IT alignment, resulting from socio-technical arrangements infirms’ infrastructure has been found to positively affect performance. Jean et al. (2008)
claimed that IT capabilities contribute directly to improved organizational process such ascoordination, transaction specific investment, absorptive capacity and monitoring; these,
in turn, contribute to strategic and operational performance outcomes.
According to Sabherwal et al. (2001), this alignment can be decomposed to:
.“cross-dimensional” alignment (IT and SO fit);
.“structural” alignment (IT and OS fit); and
.“business” alignment (SO and OS fit).
Further, Venkatraman and Prescott (1990) pointed out that a holistic examination
(contingency theory) of the interrelations of these constructs (organizational
alignment), has greater exploratory power because of the nature and complexity of
the interrelations of the examined constructs. This study adopts this view andexamines the combined impact of IT and organizational alignment on FP (Figure 1).
Subsequently, the following hypothesis is proposed:
H1. SO, IT and OS will have a stronger impact on performance when aligned than
that each of them has when considered independently.
3. Research methodologyA structured questionnaire was designed and used for the collection of the data.All constructs were measured using multiple items and all items (totaling 53)
were measured using a seven-point Likert-type scale ranging from one (very low)BPMJ
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to seven (very high). The questionnaire is divided into five sections. The first section
refers to the general characteristics of the firm (industry, size, sales, market share andnumber of employees). The second section contains questions concerning firm’s SO. The
next section measures firm’s business structure, while section four deals with IT-related
issues. Finally, the last section is about firm’s business performance (ROA, sales growth,
profitability and liquidity). Table I presents all constructs, their factors and the number
of items used to measure each construct along with the related literature.
Content validity was established adopting a questionnaire pre-testing process
(Zikmund, 2003). Pre-test participants (ten managers or CEOs and expert reviewers) were
asked to comment on any difficulty or lack of clarity in the scale items and instructions.Figure 1.
The proposed research
modelStrategic
orientation
Organizational
structure
Information
technologyOrganizational
alignmentBusiness performance
Constructs Factors Items References
SO Aggressiveness 4 Venkatraman (1989), Morgan and Strong (2003),
Talke (2007)
Analysis 6 Venkatraman (1989), Morgan and Strong (2003),
Talke (2007)
Defensiveness 4 Venkatraman (1989) and Morgan and Strong (2003)
Futurity 4 Venkatraman (1989) and Morgan and Strong (2003)
Proactiveness 4 Venkatraman (1989), Morgan and Strong (2003),
Talke (2007)
Riskiness 4 Venkatraman (1989), Morgan and Strong (2003),
Talke (2007)
OS Formalization 1 Bergeron et al. (2004)
Professionalization 1 Bergeron et al. (2004)
Centralization 1 Bergeron et al. (2004)
Vertical differentiation 1 Bergeron et al. (2004)
Specialization 1 Bergeron et al. (2004)
IT IT environmental scanning 3 Bergeron et al. (2004)
IT strategic use 6 Bergeron et al. (2004)
IT planning control 5 Bergeron et al. (2004)
IT acquisition and
implementation4 Bergeron et al. (2004)
FP ROA 1 Young and O’Byrne (2001)
Sales growth 1 Bergeron et al. (2004)
Profitability 1 Bergeron et al. (2004)
Liquidity 1 Young and O’Byrne (2001)Table I.
Questionnaire constructs,
factors and itemsIT, orientation
and structure
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Some modifications were made (wording) in order to ensure that the original text was
clearly interpreted in the target language, i.e. Greek. Then, the translated questionnairewas validated using the “back-translation” method, which is, translating back into theoriginal language to ensure correspondence with the original version (Zikmund, 2003).Wording of questions was again slightly modified before the final format was established,based on remarks and suggestions offered by the pre-testing participants.
Initially, a phone contact was established with people from the targeted firms to
investigate their willingness to participate in the study. Totally, 500 firms, mainlylocated in Northern Greece, were contacted and 318 accepted to participate in thisresearch. Respondents were identified after the nature of the study and informationrequired had been explained to the manager of each firm. From them, 295 firms(92.7 percent) finally participated and successfully completed the research instrument.Questionnaire were distributed and returned between September and December 2008.Table II presents the profile of the research participants.
The theoretical model developed to test the alignment hypothesis was analyzed
using multivariate statistical analysis, via SEM, using AMOS 7. Goldberger (1972,p. 979) describes that structural equation models as:
[…] stochastic models in which each equation represents a causal link, rather than a mere
empirical association. The models arise in nonexperimental situations and are characterized
by simultaneity and/or errors in the variables.
Such techniques can be used to conduct tests of complex theory on empirical data
(Brannick, 1995, p. 201). The data were analyzed following a two-step approach(Anderson and Gerbing, 1998); in the first step, confirmatory factor analysis (CFA) isperformed to assess the adequacy of the measurement model, while in the second stepthe structural model is tested using SEM. The level of analysis is set at the firm.
Bagozzi and Yi (1989, p. 282) argue that SEM has the following advantages over
other (traditional) statistical analysis methodologies:
First, the new procedures are more general and do not involve the restrictive assumption of
homogeneity in variances and covariances of the dependent variables across groups [ …]
Second, the new procedures provide a natural way to correct for measurement error in themeasures of variables and thus reduce the chances of making type II errors [ …] Third,
structural equation models allow for a more complete modeling of theoretical relations,
whereas traditional analyses are limited to associations among measures. Fourth, covariates
in step-down and MANCOVA analyses can be treated as latent variables with the new
procedures, thereby permitting a correction for attenuation and increasing the chances that
valid experimental effects will be detected. The traditional procedures cannot take into
account measurement error in covariates. Finally, structural equation models constitute
flexible, convenient procedures. They not only perform tests of experimental effects and
homogeneity, but are special cases of very general programs and easily implemented.
4. Data analysis and results
4.1 The measurement modelsIn order to assess the construct validity (convergent and discriminant validity) a CFAwas performed (Muttar, 1985). According to Hair et al. (1995), Kaiser-Meyer-Oklin
(KMO) measure of sampling adequacy and Barlett’s test of sphericity are the measuresthat are recommended for measuring construct validity. Straub et al. (2004) pointed outBPMJ
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Statistics
Mean SD % %
Position CEO 35.6 Department manager 36.1
Branch manager 6 Line manager 22.3
Education High school 19 University 65.1
Postgraduate 15.9
Experience (years) 16 9.093
Establishment date 1977 30.41
Total number of employees ,50 61.3 251-1,000 7.8
51-250 26.3 .1,000 4.6
Administrative employees 96 659.52
Production employees 150 762.25
Sector Manufacturing 37.9 Tourism 2.2
Commerce 28.4 Banking 8.6
Construction 10.8 Services 11.6
Sales e11 m ,e1 m 32.4 e10-50 m 16.9
e1-10 m 44.4 .e50 m 6.3
Sales increase (%) 19.4% 32.24 210 to 0% 4.23 10-30% 36.3
0-10% 47.7 .30% 11.4
Market share (local) 40.8% 29.66 0-10% 17.7 31-50% 17.2
11-30% 34.2 51-100% 30.9
Market share (national) 25.8% 27.49 210 to 10% 41.7 31-50% 11
11-30% 30 50-100% 17.3
Market growth (%) 12.5% 16.57 215 to 0% 7.1 10-30% 27.5
0-10% 56.6 .30% 8.8
Growth of industry (%) 15% 29.20 215 to 0% 5.7 10-30% 25.9
0-10% 60.8 .30% 7.6
Competitive position 2.36 1.02 Leader 24.5 Small player 11.9
Big player 29.4 Follower 1.4
Competitive 32.9
Table II.
Descriptive statisticsIT, orientation
and structure
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that Cronbach’s areliability test can be used to assess internal consistency of
measurements. The total variance explained (TVE) score is also used to measure how
data is distributed within a range and how much the responses differ.
Table III presents the results of the factor and reliability analyses. Focusing on
these results, KMO is above the minimum accepted level of 0.5 (Hair et al., 1995), while
Cronbach’s ais also at acceptable levels (threshold 0.6, Malhotra, 1999) for all
constructs. Similarly, TVE score for all factors is satisfactory (above 0.5). Finally,factor loadings for all the items are acceptable and vary from 0.658 (proactiveness,third item) to 0.922 (IT planning and control, second item). It is important that only twoout of the 53 items were discarded.
4.1.1 Strategic orientation . CFA was used to examine whether SO consists of all six
factors included in the analysis. The results showed (Table IV) that two factors(aggressiveness and riskiness) should be excluded from the analysis (because ofrelatively low estimates or factor loadings). The overall model fit was evaluated usingfour fit measures: x
2/d.f., goodness-of-fit index (GFI), comparative fit index (CFI) and
root mean square error of approximation (RMSEA) (Smith and McMillan, 2001).The level of all the above indexes was within acceptable range indicating good fit of
the measurement model.
4.1.2 Organizational structure . The same analysis for OS (measured using only five
items), indicated (Table IV) that:
.“professionalization” should be excluded from the “OS” construct (item loadingequals to 0.04); and
.there is a negative relationship between “administrative efficiency” and “OS”.
This negative relationship between “administrative efficiency” and “OS” could be
attributed to the culture of the Greek firms and the size of the firms included in theresearch sample. More specifically, most Greek firms are small to medium-sized family
business, where decision making is a privilege of the family members and especially its
leader. There are, therefore, very few hierarchical levels and a very loose “informal”OS. On the other hand, large firms usually establish formal OS with well-defined rolesfor each hierarchical level, which is also responsible for specific actions
(decentralization – span of control). Although factor loadings are relatively low, thelevels of all four fit measures are acceptable, indicating that the suggested model is
appropriate for measuring OS.
4.1.3 Information technology . An intriguing relationship has been found when CFA
was conducted to assess the validity of IT research factors (Table IV). The model fit
indicators are acceptable and the results presented an internal relationship between“IT environmental scanning” and “IT strategy”, implying that managers often scantheir business internal environment, and only after that, do they plan and apply their
IT strategy, in order to effectively reach their managerial goals. All factors initially
examined are included in the final model for IT and all model fit indicators are withinacceptable levels.
4.1.4 Firm performance . Table IV presents the results of the CFA conducted for FP.
It can be noticed that “profitability” has the strongest loading (0.92) and ROA theweakest (0.69). It must also be noted here that “liquidity” has been removed from the
CFA model because of its high relationship with “sales growth”, to improve construct
uni-dimensionality. Finally, all CFA model fit indicators are within acceptable levels.BPMJ
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Construct Factors Statistics Items Loadings
SO Aggressiveness KMO ¼0.729 We often sacrifice profitability to gain market share 0.838
Bartlett’s sig. ¼0.00 Cutting prices to increase market share 0.878
TVE¼65.245 Setting prices below competition 0.742
Cronbach’sa¼0.818 Seeking market share position at the expense of cash flow and
profitability0.765
Analysis KMO ¼0.862 Emphasize effective coordination among different functional areas 0.748
Bartlett’s sig. ¼0.00 Information systems provide support for decision making 0.769
TVE¼61.983 When confronted with a major decision. we usually try to develop
thorough analyses0.775
Cronbach’sa¼0.875 Use of planning techniques 0.813
Use of the outputs of management information and control systems 0.835
Manpower planning and performance appraisal of senior managers 0.781
Defensiveness KMO ¼0.648 Use of cost control systems for monitoring performance 0.798
Bartlett’s sig. ¼0.00 Use of production management techniques 0.890
TVE¼68.797 Emphasis on product quality through the use of quality circles 0.796
Cronbach’sa¼0.772
Futurity KMO¼0.784 We emphasize basic research to provide us with future competitiveedge0.731
Bartlett’s sig. ¼0.00 Forecasting key indicators of operations 0.803
TVE¼63.339 Formal tracking of significant general trends 0.732
Cronbach’sa¼0.803 “What-if “ analysis of critical issues 0.747
Proactiveness KMO ¼0.612 Constantly seeking new opportunities related to the present operations 0.788
Bartlett’s sig. ¼0.00 Usually the first ones to introduce new brands or products in the
market0.768
TVE¼54.784 Operations in larger stages of life cycle are strategically eliminated 0.658
Cronbach’sa¼0.575
Riskiness KMO¼0.701 We seem to adopt a rather conservative view when making majordecisions0.69
Bartlett’s sig. ¼0.00 New projects are approved on a “stage-by-stage” basis rather than
with “blanket” approval0.794
TVE¼57.364 A tendency to support projects where the expected returns are certain 0.751
Cronbach’sa¼0.743 Operations have generally followed the “tried and true” paths 0.790
(continued )
Table III.
Construct validityIT, orientation
and structure
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Construct Factors Statistics Items Loadings
IT IT environmental
scanningKMO¼0.734 Instituting a technology watch in order to change rapidly your ITwhen necessary0.873
Bartlett’s sig. ¼0.00 Knowing the information technology used by your competition 0.910
TVE¼80.816 Ensuring that your choice of information technology follows the eution
of your environment0.913
Cronbach’sa¼0.879
IT strategy KMO¼0.867 Use of IT to reduce your production costs 0.806
Bartlett’s sig. ¼0.00 Use of IT to make substantial savings 0.861
TVE¼69.375 Use of IT to improve your firm’s productivity 0.881
Cronbach’sa¼0.910 Use of IT to increase your firm’s profitability 0.873
Use of IT to improve the quality of products 0.813
Use of IT to improve the quality of services 0.757
IT planning andcontrolKMO¼0.877 Having the required human and organisational resources to managethe information systems0.859
Bartlett’s sig. ¼0.00 Having the ability to effectively identify the needs in information
technology0.922
TVE¼73.399 Having the ability to effectively fill the needs in information
technology0.873
Cronbach’sa¼0.906 Strategic planning of information systems in relation to the
organisation’s business objectives0.760
Mastering the technology presently in use in your organisation 0.862
IT acquisition andimplementationKMO¼0.831 Use of specific selection criteria for the acquisition of new informationsystems0.876
Bartlett’s sig. ¼0.00 Choosing information technology related to the SO of your firm 0.900
TVE¼64.482 Knowing the results of a financial feasibility study before the
acquisition of IT0.910
Cronbach’sa¼0.844 Evaluating the employee’s aptitude to use the chosen IT 0.854
FP KMO¼0.778 ROA 0.828
Bartlett’s sig. ¼0.00 Sales growth 0.831
TVE¼68.689 Profitability 0.901
Cronbach’sa¼0.844 Liquidity 0.749
Table III.BPMJ
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4.2 Testing the alignment hypothesis: the structural models
To test the alignment hypothesis, data were analyzed in three steps. Initially, the
individual effects of the exogenous constructs, namely IT, SO and OS, on performance
were examined (Figure 2). The results of the analysis indicated that, while ITand SO have a statistically significant effect on performance (0.39, p,0.001 and
0.12, p,0.05, respectively), the direct effect of OS on performance was insignificant.
These finding is in line with the study of Byrd et al. (2006), who also found that IT and
SO are positively related with FP. With respect to structure, a study by Pelham andWilson (1996) also indicated a weal effect of structure on performance in small firms.
Finally, fit indices indicated that the model, as it stands, has poor fit to the data (none of
the indices is above the suggested cut-off values), while R
2for performance is 0.17.
At a second stage, the exogenous constructs of the model were allowed to freely
covary (Figure 3). The analysis indicated that in this model has good fit to the data,while the explained variance in performance increased by 5 percent ( R2¼0.22). The
effect of OS on performance remains insignificant, but analysis showed relativelystrong and statistically significant covariances among the exogenous constructs.
The latter was a first indication of a strong association among IT, SO and OS. Such
associations have also been reported by Henderson and Venkatraman (1999), Croteauand Bergeron (2001), Croteau et al. (2001) and Chan and Horner (2007).
Finally, the three constructs were regarded as facets of a single construct,
i.e. organizational performance. The examination of the third structural model hasproduced some interesting results (Figure 4). First, IT remains the factor with thestrongest loading (0.85) within the organizational alignment construct, as was also
indicated by the previous analyses. Second, the loading of SO has been significantly
strengthened (0.67), while OS has a relatively weak loading, but its effect also has beenHyper-construct Constructs Factor loading CMIN/df GFI CFI RMSEA
SO Aggressiveness – 1.951 0.978 0.982 0.057
Analysis 0.80*
Defensiveness 0.72*
Futurity 0.87*
Proactiveness 0.75*
Riskiness –
Organizational Formalization 0.54* 1.244 0.999 0.996 0.009
structure Professionalization –
Centralization 20.40*
Vertical differentiation 0.69*
Specialization 0.57*
Information Environmental scanning 0.73* 6.071 0.990 0.993 0.131
technology Strategy 0.71*
Planning and control 0.90*
Acquisition and implementation 0.93*
FP (financial) ROA 0.69* 6.252 0.981 0.978 0.134
Sales growth 0.77*
Profitability 0.92*
Liquidity –
Note: Significant at:*p,0.001Table IV.
Second-order CFA for the
SO, OS, IT and business
performance
hyper-constructsIT, orientation
and structure
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strengthened and has now become statistically significant (0.36). Further, there is a
noteworthy relation between organizational alignment and performance ( r¼0.53),
implying that organizational alignment may indeed positively affect FP, as other
researchers also found (Pollalis, 2003; Rivard et al., 2006). The third model can explain
a larger amount of variance in performance ( R2¼0.28), compared to the preceding
models tested.Figure 2.
Structural model 1Performance
(R2 = 0.17)ROA
Sales growth
Profitability0.71***
0.80***
0.85***IT
Strategy
Structure0.39***
0.12*
0.04
Model fit
CFI RMSEA GFI
0.850 0.736 0.237CMIN/DF
17.485
*** p < 0.001, * p < 0.05
Figure 3.Structural model 2Performance
(R2 = 0.22)ROA
Sales growth
Profitability0.72***
0.81***
0.86***IT
Strategy
Structure0.39***
0.12*
0.04
Model fit
CFI RMSEA GFI
0.989 0.993 0.046CMIN/DF
1.621
*** p < 0.001, * p < 0.050.57***
0.26***0.30***BPMJ
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5. Conclusions and research limitations
5.1 Conclusions
This study has examined the relationships of SO, OS and IT with FP. The results of the
analysis support the research hypothesis that IT, organizational strategy and OS have
a stronger impact on performance when they are aligned, than when each of these is
considered independently. Moreover, since the sample utilized comprises firms of all
sizes (although the majority is very small), it can be argued that the impact of the
organizational alignment on FP is significant, regardless the size of the firm and
business industry that it belongs to, empirically supporting the suggestions of otherresearchers (Tallon and Kraemer, 1999; Bergeron et al. , 2001; Pollalis, 2003; Rivard et al.,
2006). Finally, results confirm the findings of the study conducted by Bergeron et al.
(2004) in a North American context.
5.2 Managerial implications
From a managerial perspective, although SO, OS and IT affect business performance
separately, their impact is significantly higher when they are aligned. More
specifically, this study suggests that IT appears to be a key element in improving the
coordination between organizational strategy and structure, as Tallon (2008) also
points out. Thus, managers have to choose the appropriate IT infrastructure (related to
their organizational strategy and structure) in order to facilitate the alignment of
organizational strategy and structure. Further, managers have to make sure that IT is
utilized in such a way to empower SO and OS. Also, managers have to draw firm’s
strategy in relation with firm’s IT system and OS.
5.3 Research limitations/suggestions for further research
The first potential limitation of this research has to do with the sample size, which is
considered as relatively small (295), although it is generally accepted that it is the right
one for this kind of survey (Bergeron et al., 2004). The second limitation is about the
one-dimensional nature of performance measures (financial). Non-financial andintangible performance measurements should be included, so that a holistic view of a
FP is examined (Copeland et al. , 1996; Dixon and Hedley, 1997; Young and O’Byrne,
2001; Herrmann, 2005). Another, possible limitation is the fact that the research sampleis derived from firms belonging to various industries.Figure 4.
Structural model 3Performance
(R2 = 0.28)AlignmentROA
Sales growth
Profitability0.72***
0.81***
0.86***0.53***IT
Strategy
Structure0.85***
0.67***
0.36***
Model fit
CFI RMSEA GFI
0.966 0.988 0.030CMIN/DF
1.272
***p < 0.001IT, orientation
and structure
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Finally, future studies could be designed to examine firms’ inter-organizational
relationships of SO, OS, IT and performance, using more advanced information
intensity measurements and modeling techniques.
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About the authors
Prodromos D. Chatzoglou is a Professor of MIS in the Department of Production andManagement Engineering, Democritus University of Thrace, Xanthi, Greece. He holds a Bachelorof Arts (BA) (Economics), Graduate Industrial School, Thessaloniki, Greece, a Master of Science(MSc) (Management Sciences), and a PhD (Information Engineering), both from UMIST,
Manchester, UK. His research interests include information systems management, knowledge
management, E-business and strategic management. His work has been published in Decision
Sciences ,International Journal of Medical Informatics ,Information Systems Journal ,European
Journal of Information Systems , among others. Prodromos D. Chatzoglou is the corresponding
author and can be contacted at: pchatzog@pme.duth.gr
Anastasios D. Diamantidis holds a PhD from the Department of Production and Management
Engineering, Democritus University of Thrace, Xanthi, Greece. He also received a BA inEconomics from the University of Macedonia, Thessaloniki, Greece, and an MSc in Finance andFinancial Information Systems from the University of Greenwich, London, UK. He has presentedsome of his research work in scientific conferences. He is also involved in a couple of EU funded
research projects. His research interests include information technology management, human
resources management, and knowledge management.
Eftichia Vraimaki holds a PhD from the Department of Production and Management
Engineering, Democritus University of Thrace, Xanthi, Greece. She also received a BA inLibrarianship and Information Science from the Technological Educational Institute of Athens,
Greece, and an MSc in Finance and Financial Information Systems from the University of
Greenwich, London, UK. She has presented some of her research work in scientific conferences.Eftichia Vraimaki is also involved in a couple of EU funded research projects. Her researchinterests include knowledge management, human resources management, psychology andlibrary information systems.BPMJ
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Stergios K. Vranakis is a PhD candidate in the Department of Production and Management
Engineering, Democritus University of Thrace, Xanthi. Greece. He holds a Diploma in
Mechanical and Aerospace Engineering from the Technical School of the University of Patras,Patras, Greece. His research interests include industrial management, operation and production
management, management information systems, and strategic management.
Dimitrios A. Kourtidis is a PhD student in Glasgow Caledonian University. He gained a BA in
Accounting (TEI of Serres, Greece) in 2004, and he completed an MSc in Finance and Financial
Information Systems in the University of Greenwich in 2006. He is currently a part-time
Lecturer in the Accounting Department of Technological Educational Institute of Kavala,
Greece. His research interests include behavioural finance and financial management.IT, orientation
and structure
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