Information management (IM) strategy: the construct and its measurement

Journal of Strategic Information Systems 10 (2001) 265±289 www.elsevier.com/locate/jsis

Information management (IM) strategy: the construct and its measurement Bhanu Ragu-Nathan a, T.S. Ragu-Nathan a,*, Qiang Tu b, Zhengzhong Shi c a

b

College of Business Administration, The University of Toledo, Toledo, OH 43606, USA School of Business, Rochester Institute Technology, The University of Toledo, Toledo, OH 43606, USA c College of Business Administration, North Dakota State University, The University of Toledo, Toledo, OH 43606, USA Revised 1 July 2000; accepted 23 August 2001

Abstract The information systems (IS) literature has consistently emphasized the need for a proper alignment of IS goals and strategies with organizational goals and strategies. A number of theoretical frameworks have been proposed to develop the linkages between IS and organizational strategies. However, while there has been much theorizing in the area, validated instruments for empirical testing of these theories have been scarce. This research reports on the development and validation of a set of operational measures for Information Management Strategy which is one of the components of the three-level framework for information system strategy proposed in the literature. The operational measures were subjected to rigorous tests of measurement properties. This initial set of operational measures are expected to serve as a useful tool in future empirical research on IS and organizational strategy linkages. q 2001 Elsevier Science B.V. All rights reserved. Keywords: Information systems; Information management; Theoretical framework

1. Introduction A dominant theme for information systems (IS) research in recent times has been the role of IS in advancing organizational strategy and organizational goals. A stream of studies focusing on the exploitation of IS for strategic advantage and emphasizing frameworks for analysis, has appeared in the literature. This research stream has provided the conceptual foundation for the study of several strategic IS issues, and is exempli®ed by * Corresponding author. 0963-8687/01/$ - see front matter q 2001 Elsevier Science B.V. All rights reserved. PII: S 0963-868 7(01)00053-1

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writings on topics such as IS strategic planning (Segars and Grover, 1999), alignment of IS planning and strategies with business planning and strategies (King, 1978; Teo and King, 1997; King and Teo, 1997; Chan, et al., 1997), integrated IS strategic frameworks (Wiseman, 1988; Earl, 1989; Henderson and Venkatraman, 1993; Venkatraman, 1997), competitive advantages from IS (Parsons, 1983; Sethi and King, 1994; Venkatraman, 1994; Segars and Grover, 1998), IS success sustainability factors (Kettinger et al., 1994), and buyer/seller strategies in the emerging e-commerce business world (Grover and Ramanlal, 1999). However, while there has been much theorizing in the area, comprehensive and validated instruments of strategy that would allow empirical testing of these theories have been very scarce in the literature. Some notable exceptions to this are Sethi and King (1994) and Chan et al. (1997). The purpose of the research reported here is to address a gap in the literature with respect to both the availability of operational measures of strategy, and the less comprehensive view of strategy that has been adopted in prior studies. The current study develops and validates a set of operational measures for strategy as it relates to the management of the information systems function (Earl, 1989), paying close attention to the expressed concern that instrument validation has been inadequately addressed in IS research (Straub, 1989) and to the call for greater rigor in IS measurement research (Sethi and King, 1991). It is hoped that the measures developed here can play a useful role in future empirical research on IS and organizational strategy linkages. This paper is organized as three sections. This section provides a frame of reference for this research by discussing the theoretical relevance of this research within the context of the existing literature, and articulating the conceptualization of strategy used here, within the framework of a broader de®nition of strategy as it relates to information systems. Section 2 elaborates on the multidimensional nature of the information management strategy construct. Section 3 describes the research methodology including model estimation, discussion of results, and directions for future research. 1.1. Theoretical relevance of this research In the 1980s, IT was typically viewed and managed as a cost center. All the ®nancial, performance management, budgeting, project management, personnel performance review, and charge out or cost accounting systems that were developed in that era were used primarily to ensure that IT activities were ef®cient. In this context, steering committees, extensive planning, and formal policies were instituted to bring rationality to the IT infrastructure and data archive. In today's context, IT is viewed as a strategically valuable organizational asset. This presents new challenges and new roles for information systems managers. In this environment, sophisticated controls are notably absent, innovation is nurtured, failures are tolerated, more resources are committed, and exploration of new avenues to achieve competitive advantage is encouraged. This IT environment has channelized IS management's attention to focus heavily on the strategic use of information systems (Cash et al., 1992; Sethi and King, 1994; Kettinger et al., 1994; Chan et al., 1997; Grover and Ramanlal, 1999): the dramatic growth of IS applications both in size and complexity, and the shift in focus from an operational to a strategic orientation, have

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made it a critical necessity for IS management to develop strategies to assimilate IS resources into a ®rm's operations. It has been well recognized that the implementation of corporate strategy requires functional strategies that are well integrated and coordinated. The need for such integration and coordination has been widely discussed at a theoretical level, both in the general strategic management literature and, in the particular context of the IS function, in the IS management literature. There has been a consistent emphasis in the IS management literature on the need for a proper ®t between organizational and IS goals and strategies. A survey by Lederer and Mendelow (1988) found that IS executives are increasingly concerned about co-ordination between organizational and IS directions. Henderson and Sifonis (1988) pointed out that effective strategies provide internal consistency between IT goals and ®rm goals. Frenzel (1992, p. 76) extended this line of thinking by proposing that the alignment of IT goals and strategies with the ®rm's goals and strategies should be regarded as a critical success factor for the IT organization. Similar views on the importance of developing strategies for assimilating information systems resources into a ®rm's operations were expressed by researchers such as Cash et al. (1992). Wiseman (1988) forcefully articulated these views when he proposed that the implementation of competitive strategies, supported or shaped by any but the most primitive information systems, should require close coordination between the business and technology groups. He further stated that, to avoid misallocation of resources, mistakes in setting priorities, and delays in systems delivery that may jeopardize its competitive position, the business unit should synchronize its strategy with the information management group's information systems plan. It has been pointed out that lack of synchronization or misalignment can result in ªIT effects on the value chain that are inconsistent with ®rm strategyº and ªmisaligned IT undermines strategy and decreases organizational performanceº (Floyd and Woolbridge, 1990); in some cases such misalignment has, in fact, made IT a competitive burden (Warner 1987). There is, thus, strong support in the IS literature for the need to align organizational strategy with IS strategy in order to assimilate IS resources to advance organizational goals. At the same time, as is evident from the studies quoted above, such need has been emphasized primarily through theoretical discussions of the bene®ts of alignment, with very little empirical support for such conceptualizations. Research by Chan et al. (1997) represents the ®rst major effort at empirically investigating the nature of the alignment between organizational and information systems strategy. Their study is an important ®rst step in cumulative theory building. Their development of the STROEPIS instrument to measure information systems applications strategy (to parallel the STROBE instrument developed by Venkatraman (1989) for measuring organizational strategy) has been the ®rst research attempt to systematically validate the nature of the alignment. While the Chan et al. effort has been a signi®cant contribution to the study of strategy, the discussion in the following paragraphs will show that it is logical and feasible to take a more comprehensive view of the concept of `strategy' as it relates to information systems. This `more comprehensive view of strategy' provides the motivation for the development of the instrument proposed in this study.

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1.2. A comprehensive view of strategy The lack of common understanding of the concept of strategy as it relates to information systems has been very strongly commented on by Earl (1989). He contends that there are, in fact, three levels of strategy as it relates to information systems Ð IM (informationmanagement) strategy, IS strategy (information-systems), and IT (information-technology) strategy and IM strategy deals with management of the entire information systems function, IS strategy with information systems applications, and IT strategy with the technology used for delivery of application systems. He states that there is common confusion between information systems which are ends and IT which is the means, and this confusion exists ªpartly because of the loose terminology of planning and strategy in discourse and literature¼ and partly because senior management tends to be concerned about both technology policy issues and business needs and about both planning information resources and controlling themº (Earl, 1989, p. 62). The conceptualization of information systems strategy proposed by Earl is depicted in Fig. 1 within the box captioned ªThree Levels of Information Systems Strategyº. This ®gure further depicts the alignment of this comprehensive view of information systems strategy with organization strategy. In Earl's conceptualization, IS strategy, one of the three levels of information systems strategy, is concerned primarily with aligning IS development with business needs and with seeking strategic advantage from information system applications. IT strategy is concerned primarily with technology policies including questions of architecture, security

Fig. 1. Information Systems Strategy and Organizational Strategy Linkage STROBE Ð Organizational Strategy Instrument (Venkatraman, 1989), STROEPIS Ð IS Strategy Instrument (Chan et al., 1997), STROIM Ð Information Management Strategy Instrument (Present Research), Alignment Ð (Applegate et al., 1996; Lederer and Mendelow, 1988; Henderson and Sifonis, 1988; Frenzel, 1992; Wiseman, 1988; Floyd and Woolbridge, 1990).

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levels and the like. IM strategy ªis the management framework which guides how the organization should run IS/IT activitiesº (Earl, 1989, p. 117). It is organization-based, relationship-oriented and management-focused. It is a summary of the choices made from an analysis of planning, organization, control and technology issues, and consists of the policies, procedures, aims and actions taken by management to manage the role and structure of the IS function within an organization. IM strategy focuses on relationships between specialists and users, and between the corporate level and divisions or business units. It is concerned with management controls for IS, management responsibilities, performance measurement and management processes. This three-level, comprehensive view of strategy as it relates to information systems provides an appropriate conceptual foundation for developing operational measures of strategy, and for testing various aspects of the linkages between information systems and achievement of organizational goals. The Chan et al. (1997) study, referred to earlier, developed the STROEPIS instrument to measure IS strategy, which focuses on information systems applications. The present study develops a measure of IM strategy (hereinafter referred to as STROIM), which focuses on information systems management processes. It is hoped that future research will lead to the development of a measure of Earl's third component of strategy, namely, IT strategy. The primary motivation for the development of a measure of IM strategy in the present study is that it would contribute to the operationalization of Earl's three-level comprehensive view of strategy. It is hoped that this research provides a response to the call on researchers to facilitate the cause of cumulative theory-building and testing, by developing tools and measures that facilitate validation of current theories, so researchers can advance to the next level of re®nement of theories and theory-building (Cooper, 1988; Keen, 1988). The IM strategy instrument developed in the present study can be seen as a tool for advancing theories of IS strategic alignment. More speci®cally, the instrument can be used to assess the extent to which IS management can facilitate the alignment between information systems and organizational strategies. An additional motivation for the study stems from the importance that IS strategic management is gaining in today's organizations, thereby making the development of a valid instrument to measure IM strategy a useful research effort. It has been said that while, over the last 25 years, the industrialized world has been making the transition from an industrial economy to an information economy, for the next several decades, information Ð rather than land and capital Ð will drive the creation of wealth and creativity. Information systems have dramatically altered the ways organizations perform their operations and design and market their products, and have become strategic, competitive resources for many organizations (Wiseman, 1988). As the role of information systems changes within an organization, leadership, organization design, and management processes also change. To fully realize the competitive advantages created by the strategic use of information systems, organizations must have appropriate information systems management strategies that ®t with their culture, technology status, and business strategy. The need to develop effective strategies for managing an organization's information system has drawn attention in the information systems literature (Cash, McFarlan, McKenney and Applegate, 1992). Given the importance of developing appropriate information management strategies that match the organizational role of information systems,

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Fig. 2.

research that contributes to the development and testing of such strategies becomes critical. The present study ®ts into this stream of research. Section 1.3 elaborates on the nature of the IM strategy concept which is developed as a multi-dimensional construct. 1.3. Dimensionality of the information management strategy construct The dimensions of Information Management (IM) Strategy proposed in this study are grounded in the strategic management literature. This is because there is a lack of substantive literature in this particular area of information system strategy. By basing the conceptualization for the present study on validated conceptualizations in the strategic management literature with its longer tradition of research in the areas of organizational strategy and strategy-goal linkages, the proposed dimensions will have the support of extant theory. The conceptualization of the dimensions of the organizational strategy construct in Venkatraman (1989) is the basis for the proposed dimensions of IM Strategy developed in this study. The Chan et al. (1997) instrument has also used the Venkatraman (1989) study as the primary frame of reference. The relative positioning of all three was depicted in Fig. 1 and the relative differences are presented, by example, in Fig. 2. The example in Fig. 2 shows that the focus of the Venkatraman study is on organizational strategy. The focus of the Chan et al. study is on realized IS strategy (i.e. IS deployments used by the business units and IS applications that provide information input to facilitate organizational strategy), and captures Earl's notion of IS (application) strategy. The focus of the present study is on managerial strategies for managing the IS function and captures Earl's notion of IM strategy. The dimensions of the IM Strategy construct proposed in this study are: ² ² ² ² ² ²

Aggressive Promotion of IS Ð APIS Analysis-based Development of IS Ð ADIS Defensive Management of IS Ð DMIS Future-oriented Development of IS Ð FDIS Proactive Management of IS Ð PMIS Conservative Management of IS Ð CMIS

Since these dimensions represent the orientation of IS management in strategically managing the IS function, this construct is referred to as the Strategic Orientation Of Information Management, STROIM. The dimensions of STROIM are described below.

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Aggressive Promotion of IS. Cash et al. (1992, p. 659) view an organization's IS as a stand-alone `business within a business' and use this analogy to discuss an important aspect of managing the IS `business', namely, strategies for marketing the product of this business among the organization's IS users. This dimension characterizes the stance taken in the `marketing' of IS services through behaviors such as actively encouraging user involvement, promoting user awareness of available technologies, offering user support, and maintaining continuous interaction with users. This dimension is similar to the aggressiveness dimension of the business strategy construct that refers to the aggressive pursuit of market share to improve competitive position and is exhibited in such actions as cutting prices and sacri®cing pro®tability to gain/increase market share. Although both dimensions capture marketing postures, the difference is that since IS is an organization's internal function and its market typically comprises the rest of the organization, its strategies are likely to be constrained by top management directives and organizational needs. Hence, the degree of aggressiveness that may characterize marketing efforts of businesses vis-aÁ-vis the external marketplace may not be evident when IS markets itself within the organization. It is exhibited in such actions as actively trying to promote new users of IS, taking a leadership role on promoting organizational computer usage. Analysis-based Development of IS. This dimension focuses on the nature of management processes in planning, controlling, and making decisions about the IS function. Are these processes re¯ective of comprehensive, well thought-out, structured and systematic approaches to problem solving? Is there a consistent attempt to use comprehensive analysis of available options before actions are taken? Responses to questions such as these capture the essence of this dimension. This focus on the systematic analysis of issues parallels the analysis dimension in the business strategy construct. The characteristics exhibited within this dimension have been noted to be important aspects of strategic management and decision-making (Fredrickson, 1984). The IS literature has also given due recognition to this systematic assessment of capabilities (Raghunathan and Raghunathan, 1991). Framel (1993) refers to Information Value Management as an example of a systematic and well-thought-out information management process. Defensive Management of IS. The traits exhibited in this dimension are re¯ective of IS management's attitude toward the status quo. This dimension addresses management actions that are indicative of attempts to protect existing practices, procedures, and con®gurations, anchor changes around them, and generally defend their domain. Incremental modi®cation rather than replacement of systems, standardization of existing practices and procedures, and use of ef®ciency rather than effectiveness criteria in evaluations, are all characteristics of this dimension. Similar characteristics have been conceptualized as a dimension of the business strategy construct and the dimension has conceptual support in writings such as by Miles and Snow (1978) and Miles and Cameron (1982). Future-oriented Development of IS. This dimension captures the forward-looking posture adopted in managing IS. This posture is exhibited when management ensures that, processes for dealing with the future, such as medium and long-term IS planning systems and mechanisms to track signi®cant future trends in information technology, are in place. It is also exhibited when management makes today's decisions only after giving due consideration to the medium and long-term (in contrast to just the short-term) impact of those decisions. The business strategy construct includes this dimension in recognition

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of the basic premise that the concept of strategy cannot exist independent of the notion of achieving a desired future (Venkatraman, 1989). Proactive Management of IS. Management's attitude toward handling inevitable and evolving changes occurring in the information systems arena is the focus of this dimension. Does the IS function seek out new systems opportunities on its own volition, does it wish to be at the forefront in trying new technologies or is it content to play follow-theleader, and, is it predominantly proactive or reactive with respect to environmental changes and new opportunities that could potentially impact on the way that IS operates? The importance of proactive IS policies where appropriate, and the notion of pre-emptiveness in the management of IS, are well documented in the literature (Kettinger et al., 1994; Sethi and King, 1994). This dimension has its counterpart in the business strategy construct where proactiveness is re¯ected in whether a business chooses to participate in emerging industries, is continuously on the look-out for new market opportunities, and is trying to ®nd new ways of staying ahead of competition (Venkatraman, 1989). Conservative Management of IS. When new systems projects are developed and implemented, the management of these processes includes recognition of the risks associated with these systems. Implementation involves signi®cant risks both from external sources and from the technology and process of implementation (McGaughey, 1994). Cash et al. (1992, p. 105) refer to these potential risks of disastrous organizational and competitive consequences as strategic vulnerabilities. Examples include systems that change the basis of competition in unexpected ways, and to the organization's detriment, and systems that bring on litigation or regulation. IS management has to anticipate the added risks of cost overruns, schedule delays, etc. in the development and implementation of new systems. The Conservative Management of IS dimension captures IS management attitudes to these risks and parallels the riskiness dimension in the business strategy construct which, at the business unit level, captures the level of risk involved in various resource allocation decisions and in the choice of products and markets. The six dimensions described above constitute the IM Strategy construct. The theoretical base for the development of this construct has been ®rmly grounded in the strategic management literature. The discussion in the following paragraphs explores the extent to which the underlying rationale for the emergence of these dimensions ®nds support from an organizational learning perspective. Researchers in the IS area have recently been applying learning theory to study some of the phenomenon in the IS ®eld. This line of research regards learning as a critical factor for IT success and effectiveness in order to advance organizational goals and strategies. Armstrong and Sambamurthy (1999) investigated the in¯uence of senior leadership (knowledge and systems of knowing about IT and business processes), IT infrastructure, and the moderation effect of IT vision on IT assimilation (i.e. IT use in supply chain activities and for business strategies) in ®rms. Fichman and Kemerer (1997) found that when facing the higher knowledge barrier for adoption of software process innovations (SPI), ®rms with a greater scale of activities over which learning costs can be spread, more extensive existing knowledge related to the focal innovation, and a greater diversity of technical knowledge and activities, will have greater propensity to initiate and sustain the assimilation of SPIs in terms of stages (i.e. awareness, interest, evaluation/trial, commitment, limited deployment, and general deployment). Fichman and Kemerer

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Fig. 3.

(1999) also developed the concept and measurement of the assimilation gap (i.e. the gap between acquisition and actual deployment) which has major implications for practice and research. Wastell (2000) applied psychodynamics of learning to investigate the organizational defensive behavior (i.e. the organizational ritual, the sibling horde, and paranoid isolationism) when confronted with anxieties of assimilating new IT or developing new applications. March (1991) developed the notions of exploration and exploitation from an organizational learning perspective. He proposed that organizations divide attention and other resources between two broad kinds of activities, namely, exploration and exploitation. Exploration re¯ects the pursuit of new knowledge and the things that might come to be known. Exploitation refers to the use and development of things already known. On the one hand, organizations engaging exclusively in exploration take the risk of losing the returns of existing knowledge and competence. On the other hand, organizations engaging exclusively in exploitation face the risk of obsolescence. Thus, the basic problem for organizations is to engage in suf®cient exploitation to ensure its current viability and, at the same time, to devote enough energy to exploration to ensure its future viability. Survival and success need a balance between exploitation and exploration. Information systems are key resources for organizations that are competing successfully in the marketplace. The appropriate division of these resources between exploitation and exploration is important for both the short-term survival and the long-term success of organizations; effective management of IS to achieve this balance becomes critical in this environment. Information management strategy can be viewed as the summary of the choices made by management between exploitation and exploration activities. The six dimensions of STROIM are found to be consistent with the exploration and exploitation dimensions proposed by March (1991). This is depicted in Fig. 3 and is discussed below. Aggressive promotion of IS captures the efforts of IS management in promoting user awareness and new uses of information systems, and in furthering organizational computer usage through efforts to enhance user involvement and interaction with the IS function. This dimension thus captures the exploration aspect of IS management. Defensive management of IS seeks to standardize existing procedures, ensure controlled development of IS, and modify existing systems with short-term ef®ciency as a criterion. The underlying goal appears to be the exploitation of current knowledge for survival and success in the immediate future. The Analysis-based development dimension which comprises processes such as assessment of internal capabilities and past performance before making project commitments and projections, is very representative of efforts by IS management at exploitation of current resources. Future-oriented development of IS

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has an exploration ¯avor to it in that it captures IS management's efforts to pursue new knowledge such as through identi®cation of future trends in information technology and development of futuristic scenarios. Proactive management of IS has an exploration focus in that it captures IS management's attitude toward new opportunities, new technologies, etc. The exploitation focus in the last dimension, Conservative management of IS, is evident in actions taken by IS management to reduce the risks associated with IS projects. Thus, the dimensions of STROIM appear to ®nd support in, and to be consistent with learning theory perspectives as they relate to managerial activities. Section 2 describes the research methodology leading to the development of validated operational measures of the dimensions of the STROIM construct. 2. Research methodology Information systems research has been criticized for poor choice of methodology (Jarvenpaa et al., 1985), lack of adequate theoretical foundation (Naumann, 1986), and the absence of a paradigm (Ein-dor, 1986; Wand, 1986). Studies by Cooper (1988) and Sethi and King (1991) highlight the methodological problems associated with IS research due to poor implementation of empirical studies, poor choice of research method, and inadequate attention paid to construct development and validation. These criticisms direct IS researchers to focus their research efforts on the development of empirically validated conceptualizations of constructs and relationships in the IS realm, if IS research results are to draw the attention that they deserve from both academicians and practitioners. The research described in this paper, methodologically, attempts to respond to these criticisms by paying attention to the issues of precision of conceptualization and methodological rigor in testing measurement properties. Data collection. A self-administered questionnaire was mailed to 800 information systems executives chosen at random from a list of 3000 senior IS executives. The list was obtained from a supplier ®rm that selected the names at random from its list of senior IS executives in more than 10,000 different organizations. There were 237 responses of which 231 were complete and hence usable. Table 1 provides an industry classi®cation of Table 1 Types of companies in the sample Industry type

Percentage of respondents

Manufacturing Medicine/law/education Business Services Public utility Transportation Petroleum Finance/insurance Whole sale/retail Government Others Total

32 3 3 7 5 2 25 11 2 10 100

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Table 2 Company sales Sales (US$)

Percentage of respondents

Less than 25 M 25± , 50 M 50± , 100 M 100± , 250 M 250± , 500 M 500± , 1000 M 1000 M and above Others

4 11 7 14 10 18 26 10

the sample companies and Table 2 presents information on company revenues. Companies with revenues of 50 million and above are well represented (85%) in this sample. The results of this study may therefore be more appropriately relevant to companies in these size categories. Manufacturing and ®nance sectors are represented by 57% of the sample. This information is relevant while generalizing the results of this study. 2.1. Measurement model estimation After an extensive survey of both the IS and strategic management literature, operational measures of the six dimensions of the IM Management Strategy construct were developed. Appendices A and B present the multiple items comprising these measures and the conceptual bases for their development. These items were scored on a ®ve-point interval scale. While most items were positively worded, there were some items that were deliberately worded negatively, to capture the respondent's attention and to reduce the likely tendency to automatically check-off all items under the same column. Two IS researchers were requested to check the items for appropriateness and relevance. Two IS executives of major corporations were also requested to comment on the clarity and appropriateness of the items. The measurement properties of the six dimensions of the Information Management Strategy construct were evaluated by assessing key components of construct validity as per the guidelines of Bagozzi (1980), Philips (1981), Segars (1997) and Venkatraman and Grant (1986). These components are: ² ² ² ² ²

Content validity; Unidimensionality (and convergent validity); Reliability; Discriminant validity; Predictive validity.

Detailed discussion of the measurement properties of each one of the Information Management Strategy constructs are given in Appendix C. Values of the measurement properties are given in Table 3 (Unidimensionality), Table 4 (Reliability), Table 5 (Discriminant validity), and Table 6 (Predictive validity). All the constructs exhibit

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Table 3 Assessment of unidimensionality (APIS Ð Aggressive Promotion of IS, ADIS Ð Analysis-based Development of IS, DMIS Ð Defensive Management of IS, FDIS Ð Future-oriented Development of IS, PMIS Ð Proactive Management of IS, CMIS Ð Conservative Management of IS)

APIS ADIS DMIS FDIS PMIS CMIS Performance

Indicators

x2

df

p

GFI

AGFI

RMR

NFI

4 4 4 5 4 4 5

18.27 7.41 0.41 14.34 1.13 1.69 2.58

2 2 2 5 2 2 5

0.000 0.025 0.815 0.014 0.568 0.431 0.760

0.96 0.99 1.00 0.98 1.00 1.00 1.00

0.80 0.93 1.00 0.93 0.99 0.98 0.99

0.035 0.022 0.008 0.031 0.010 0.014 0.012

0.96 0.98 1.00 0.97 1.00 0.99 0.99

good content validity, convergent validity, reliability, and discriminant validity. All the constructs except Conservative Management of IS (CMIS) exhibit acceptable predictive validity. 2.2. Discussion This study has operationalized six dimensions of the IM Strategy construct using a set of indicators developed from the IS and strategic management literature. The statistical tests that were performed established the unidimensionality, reliability, and discriminant validity of the operational measures. A further analysis of the dimensions shows the emergence of some interesting relationships. Table 5 provides information that allows us to assess the strength of these relationships. To facilitate the assessment, information on the signi®cance of phi values is extracted from Table 5 and presented separately in Table 7. This table indicates that the Aggressive Promotion of IS, Analysis-based Development of IS, Future-oriented Development of IS, and Proactive Management of IS dimensions have highly signi®cant relationships to each other …p , 0:01†: The Defensive Management of IS and Conservative Management of IS dimensions, while they are strongly related to each other …p , 0:01†; are either not related to or are less signi®cantly related to the other four dimensions. It is thus possible to discern a dichotomy in the strategies represented by the six dimensions. The information systems function has been variously described as a `business within Table 4 Assessment of reliability Constructs

Indicators

r (reliability)

APIS ADIS DMIS FDIS PMIS CMIS IS Performance

4 4 4 5 4 4 5

0.86 0.86 0.76 0.85 0.82 0.80 0.83

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Table 5 Assessment of Discriminant Validity (*** p values are signi®cant at 0.01, ** p values are signi®cant at 0.05, * p values are signi®cant at 0.10)

x2 unconstrained model (df)

x2 constrained model (df)

x 2(df) difference

6.76*** 1.80* 9.97*** 7.51*** 1.43

39.80(19) 34.92(19) 57.09(26) 37.47(19) 38.12(19)

336.51(20) 237.76(20) 280.77(27) 254.41(20) 293.33(20)

296.71(1)*** 202.84(1)*** 223.68(1)*** 216.94(1)*** 255.21(1)***

0.20 0.60 0.32 0.05

2.53** 11.08*** 5.02*** 20.64

40.90(19) 43.64(26) 31.24(19) 31.77(19)

235.16(20) 240.09(27) 287.94(20) 290.92(20)

194.26(1)*** 196.45(1)*** 256.70(1)*** 259.15(1)***

FDIS PMIS CMIS

0.03 0.03 0.33

0.35 0.32 24.27***

48.98(26) 27.01(19) 14.57(19)

253.80(27) 231.72(20) 184.71(20)

204.82(1)*** 204.71(1)*** 170.14(1)***

FDIS with 13 14

PMIS CMIS

0.64 20.11

12.28*** 1.41

40.26(26) 40.26(26)

180.37(27) 293.97(27)

140.11(1)*** 253.71(1)***

PMIS with 15

CMIS

20.16

2.06**

24.98(19)

271.53(20)

246.55(1)***

Test

Description

ML estimate phi

APIS with 1 2 3 4 5

ADIS DMIS FDIS PMIS CMIS

0.43 0.14 0.56 0.47 20.11

ADIS with 6 7 8 9

DMIS FDIS PMIS CMIS

DMIS with 10 11 12

t-value of phi

a business' (Cash et al., 1992, p. 3) and an `organization within an organization' (Ahituv and Neumann, 1990, p. 198). It is in the business of providing its services to users within the organization who, therefore, may be regarded as its customers; it is also in competition with these same customers for allocation of signi®cant levels of organizational resources. Management of the IS business, therefore, has to be Table 6 Assessment of predictive validity with IS performance (*** p value signi®cant at 0.01, ** p value signi®cant at 0.05, ns p value not signi®cant) IS performance

APIS ADIS DMIS FDIS PMIS CMIS

g

t-value

0.50 0.49 0.21 0.56 0.33 0.08

6.2*** 6.1*** 2.6** 6.9*** 4.2*** 1.00 ns

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Table 7 Signi®cance of phi values (reported in Table 5) (*** p value signi®cant at 0.01, ** p value signi®cant at 0.05, * p value signi®cant at 0.10, ns p value not signi®cant) APIS ADIS DMIS FDIS PMIS CMIS

ADIS

DMIS

FDIS

PMIS

CMIS

**

*** ns

*** ns ***

ns *** Ns **

concerned with providing quality services to its organizational customers while, at the same time, maintaining the function's viability as an organizational unit. The former requires a set of management strategies that are directed toward developing an end product (i.e., information systems) which is sought by users; it is interesting to note that the four inter-related dimensions of Analysis-based Development of IS, Future-oriented Development of IS, Proactive Management of IS, and Aggressive Promotion of IS capture the notion of service by representing, as they do, systematic processes for developing, offering, and marketing enhanced systems services to users. The latter requires a set of strategies which, when taken together, de®ne IS management's overall approach to managing the development of IS; the two inter-related dimensions, Defensive Management of IS and Conservative Management of IS, focus on management's approach to standardizing the existing procedures and systems, monitoring and controlling the development and performance of IS. Further, the relationship of these dimensions to the IS performance effectiveness measure (Table 6) is both positive and signi®cant, except for the Conservative Management of IS dimension. The Aggressive Promotion of IS dimension re¯ects efforts to create/ increase user awareness of the availability of and bene®ts from IS resources, as well as user involvement and interaction with IS (Applegate et al., 1996). Since these efforts have traditionally been associated with IS effectiveness, the positive relationship of this dimension with performance is to be expected. The relationship of the Analysis-based Development of IS dimension to performance, when viewed in terms of its use of formal and systematic approaches to IS development efforts, is consistent with IS literature that has proposed positive linkages between systematic IS processes and IS performance (Raghunathan and Raghunathan, 1994; Raghunathan and King, 1988; Segars and Grover, 1999). Similar research support can be found for the positive relationship of IS performance with the Future-oriented Development of IS and Proactive Management of IS dimensions (King, 1978; Wiseman, 1988; Sethi and King 1994) and with the Defensive Management of IS dimension (Senn, 1989; Whitten et al., 1989; Lucas, 1989). The Conservative Management of IS dimension does not exhibit a signi®cant relationship to IS performance. From the results shown in Table 7 it is clear that while the six constructs together do not have signi®cant common variance to form a single second order `strategy' construct, four of the constructs (APIS, ADIS, FDIS, and PMIS) can be modeled into a single second order construct. To examine this, a single second order model with all the six constructs

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was tested. It was found that although all the model speci®cations were at acceptable levels, the lambda values of the constructs DMIS and CMIS were non-signi®cant thereby indicating no common variance with the other four constructs. In summary, the six dimensions of the IM Strategy construct provide a multidimensional measure of information management strategy and can be used to depict an organization's characterization of its information management strategy. 2.3. Future research This is a ®rst attempt to conceptualize the dimensionality of the IM Strategy construct and propose a measurement scheme for its operationalization. Although careful attention was paid to both theoretical and methodological aspects in the development and operationalization of the construct, alternate methods of conceptualization and operationalization may still exist for further re®ning the construct. While discussing the depiction of information systems strategy by Fig. 1, it was noted that there is no currently available operational measure of IT strategy. If future research should develop such an instrument, it should open up the research arena to the possibility of investigating a variety of empirical relationships linking information systems strategies to organizational outcomes. For example, if IS applications are not providing appropriate information to support business strategies, i.e., if there is a misalignment between IS and business strategies, to what extent is it likely that IM and IT strategies have played a role in the misalignment and can be altered to bring about alignment. Questions such as this can be answered by future research that is directed at investigating the alignment of IS, IM, and IT strategies and the nature of the impact of such alignment on organizational strategy and information systems effectiveness. Further studies on the effects of ®t/misalignment of strategies on both IS functional performance and overall organizational performance can be undertaken. 2.4. Limitations of the current study One limitation of this study is that the measurement items of the IM strategy construct are developed from an internal focus perspective (i.e. as providing services and opportunities for business strategy within an organization, supporting organizational users, regarding IS as business within business). Recent literature (e.g. Venkatraman, 1997) also discusses IS strategy from an external perspective (i.e. provide IS service to outside organizations for pro®ts). Future research should addresses this second perspective. Further, the six dimensions were developed in this study to match the dimensions of strategy dimensions developed by Chan et al. and Venkatraman (1989) in order to offer a consistent set of strategy measures that can be used in future empirical research. These six dimensions, therefore, are not exhaustive in nature and can be expanded. Another limitation is that since the randomly generated mailing list did not contain any other information regarding the organizations, it was not possible to check the non-response bias. Finally, although the IS performance measure was not signi®cantly different between IS managers and top management, due to the small sample set, the power of the test was not signi®cant. Further research with larger sample can address this limitation.

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3. Conclusion This research was an attempt to conceptualize and develop a validated operational measure of an important construct in the ®eld of information systems management. It is hoped that this instrument, developed with substantial theoretical support, and subjected to rigorous tests of validation, will serve as a springboard for further empirical research on IS and organizational strategy linkages. Appendix A Aggressive Promotion of IS Ð APIS We constantly seek to promote user awareness of available IS tools and resources. We have actively tried to promote new uses of IS by user departments. We constantly endeavor to encourage user involvement and interaction with IS. We have taken a leadership role in promoting organizational computer usage. Analysis-based Development of IS Ð ADIS When confronted with a major decision we usually try to develop thorough analysis. We do not assess our internal capabilities before making project commitments. R We use planning methodologies for systems development. We do not review our past performance before making projections for the future. R Defensive Management of IS Ð DMIS We generally seek to modify rather than replace existing systems. We seek to ensure that IS developments are within our control. We seek standardization to ensure the ®t of new systems with the data structures of existing systems. We use ef®ciency rather than effectiveness criteria to monitor IS performance. Future-oriented Development of IS Ð FDIS We often develop medium and long-term measures of IS achievements. Our criteria for resource allocation generally re¯ect short-term considerations. R We encourage development of projects with future potential. We formally track signi®cant future trends in information technology. We tend to develop scenarios of where we want to be. Proactive Management of IS Ð PMIS We constantly seek to identify new opportunities closely related to our operations. We like to be in the forefront when it comes to trying new information technologies. We ensure that systems in the later stages of their life cycle are strategically eliminated. We are constantly on the look-out for new systems applications. Conservative Management of IS Ð CMIS We build systems only when they have de®nite pay-offs. We seem to adopt a rather conservative view when making decisions about major systems. We approve of new systems projects on a stage-by-stage basis rather than with a blanket approval.

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We develop systems only after similar systems have been successfully tested and implemented by others. Performance IS is perceived as facilitating organizational decision-making. The user community is generally satis®ed with IS. The IS function has not achieved its performance goals. R Use of IS has led to better management of organizational activities. Bene®ts of IS has outweighed its costs. Superscript R denotes that responses were reverse code for analytical purposes. Appendix B See Table A1. Appendix C Content validity. A representative collection of items and a sensible method of test construction are regarded as important criteria for ensuring content validity (Nunnally, 1978). Careful attention was paid to these criteria during the process of development of the items that represent the operationalization of the six dimensions. The process included, as stated earlier, an extensive analysis of the literature for the choice of items, request for comments from IS researchers and executives on the appropriateness, completeness, and lack of ambiguity of the items, modi®cations to the items in response to these comments, and a ®nal scrutiny of items by other IS researchers. The comparison between our items and Venkatraman's items in the previous table also con®rm the content validity of these items. Assessment of measurement properties of unidimensionality, discriminant validity and predictive ability was carried out using Joreskog's analysis of covariance structures. Unidimensionality (and Convergent Validity). Unidimensionality has been de®ned as the existence of a single latent trait or construct underlying a set of measures (Anderson, 1987; Sethi and King, 1994). It indicates that all of the items are measuring a single theoretical construct. Fig. 1 presents the measurement model that was the basis for the test of unidimensionality of each of the six dimensions. The results are summarized in Table 3. The table presents the number of items measuring each construct, and statistics for assessing the goodness of ®t of the measurement model. The following statistics are presented: the x 2 statistic and its associated degrees of freedom and level of signi®cance, Goodness of Fit Index (GFI), Adjusted goodness of Fit Index (AGFI), Root Mean Square Residual (RMR), and Normed Fit Index (NFI). Although the chi-square statistic is a global test of a model's ability to reproduce the sample variance/covariance matrix, its signi®cance level is sensitive to sample size and departures from multivariate normality. Therefore, it has been suggested that it must be interpreted with caution in most applications (Joreskog and Sorbom, 1989; Doll et al., 1995); researchers are hence turning to other statistics to evaluate ®t. The GFI indicates the

Analysis-based Development of IS ÐADIS When confronted with a major decision we usually try to develop thorough analysis. We do not assess our internal capabilities before making project commitments(R). We use planning methodologies for systems development. We do not review our past performance before making projections for the future(R)

Aggressiveness

Aggressive Promotion of ISÐAPIS We constantly seek to promote user awareness of available IS tools and resources. We have actively tried to promote new uses of IS by user departments. We constantly endeavor to encourage user involvement and interaction with IS. We constantly endeavor to encourage user involvement and interaction with IS

Analysis: overall problem solving posture Emphasize effective coordination among different functional areas. Information systems provide support for decision-making. When confronted with a major decision, we usually try to develop thorough analysis. Use of planning techniques. Use of the outputs of management information and control systems. Manpower planning and performance appraisal of senior managers

Sacri®cing pro®tability to gain market share. Cutting prices to increase market share. Setting prices below competition. Seeking market share position at the expense of cash ¯ow and pro®tability

Business strategic orientations (STROBE)

Information management strategic orientations (STROIM)

Table A1 Comparison between STOBE and STROIM measurement items

(1) Search deeper for roots of problems. (2) Generate the best possible solution alternatives. (3) Comprehensiveness. (4) Internal consistency achieved in the overall resource allocation for achievement of chosen objectives. (5) Use of appropriate management systems (information and control systems; managerial reward systems; competitive intelligence systems, etc.)

Product innovations. Market development. High investment to improve relative market share and competitive position

Conceptual basis

The ®rst item, the IS management does thorough analysis when making decisions deals with comprehensiveness (3). The third item deals with the use of planning methodologies (5). The second item (assessing internal capabilities) and forth item (reviewing past performance) partially capture the intention of ®nding roots of problems (linking capabilities and past performance) (1) and these items can be considered as a basis for generating best possible solution alternatives (2). At the same time by assessing internal capabilities (i.e. measuring the accumulative development and deployment of assets) and reviewing performance (i.e. the results of the use of those resources), IS management can be seen as a mechanism for internal resource allocation for achieving objectives (4)

Venkatraman's items on this dimension mainly focus on the behavior of reducing prices and pro®tability, thus concentrating mainly on market development. In the case of IM management items, market development effort is re¯ected through capturing the intention to promote awareness and computer usage. Capturing the intention for new uses and encouraging user involvement and interaction partially re¯ects the product innovation view (i.e. new use is a kind of innovation and user involvement and interaction with IS is an effective and ef®cient way to promote IS product innovation)

Linkage between business strategic orientations and information management strategic orientations

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Future-oriented Development of IS Ð FDIS We often develop medium and long-term measures of IS achievements. Our criteria for resource allocation generally re¯ect short-term considerations w. We encourage development of projects with future potential. We formally track signi®cant future trends in information technology. We tend to develop scenarios of where we want to be

Defensiveness

Defensive Management of IS Ð DMIS We generally seek to modify rather than replace existing systems. We seek to ensure that IS developments are within our control. We seek standardization to ensure the ®t of new systems with the data structures of existing systems. We use ef®ciency rather than effectiveness criteria to monitor IS performance

Our criteria for resource allocation generally re¯ect short-term consideration w. We emphasize basic research to provide us with future competitive edge. Forecasting key indicators of operations. Formal tracking of signi®cant general trends. `What-if' analysis of critical issues

Futurity

Signi®cant modi®cations to the manufacturing technology. Use of cost control systems for monitoring performance. Use of production management techniques. Emphasis on product quality through the use of quality circles

Business strategic orientations (STROBE)

Information management strategic orientations (STROIM)

Table A1 (continued)

(1) Relative emphasis on effectiveness (e.g. research) and ef®ciency (application development) criteria. (2) Emphasis on forecasting sales and customer preferences (3) formal tracking of environmental trends

(1) Defending core technology (2) Preservation of one's own products, markets, and technology. (3) Cost reduction and ef®ciency seeking methods

Conceptual basis

The ®rst item (developing medium and long term measures of IS achievement), second item (resource allocation criteria) and third item (projects with future potential) capture the relative emphasis of effective and ef®ciency criteria. The fourth item (tracking signi®cant trends of IT) captures the environmental trends (3). The last item (developing scenarios) re¯ects the emphasis on forecasting IS market (user) needs (2)

The ®rst item captures the degree to which IS management defend current existing IS (1). The second item (IS development under control) and third item (the ®t of new systems into existing system) expected to capture the intention to preserve the existing IS applications (products) and technologies and thus markets (user group) will not be dramatically affected (2). The last item (use of ef®ciency criteria) points out the intention for cost reduction and ef®ciency improvement

Linkage between business strategic orientations and information management strategic orientations

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Conservative Management of IS Ð CMIS We build systems only when they have de®nite pay-offs. We seem to adopt a rather conservative view when making decisions about major systems. We approve of new systems projects on a stage-bystage basis rather than with a blanket approval. We develop systems only after similar systems have been successfully tested and implemented by others

Proactiveness

Proactive Management of IS Ð PMIS We constantly seek to identify new opportunities closely related to our operations. We like to be in the forefront when it comes to trying new information technologies. We ensure that systems in the later stages of their life cycle are strategically eliminated. We are constantly on the look-out for new systems applications

Our operations can be generally characterized as high-risk. We seem to adopt a rather conservative view when making major decisions (rev). New products are approved on a stage-by-stage basis rather than with blanket approval (rev). A tendency to support projects where the expected returns are certain (rev). Operations have generally followed the tried and true paths (rev)

Riskness

Constantly seeking new opportunities related to the present operations. Usually the ®rst ones to introduce new brands or products in the market. Constantly on the look out for business that can be acquired. Competitors generally preempt us by expanding capacity ahead of them (r). Operations in late stages of life cycle are strategically eliminated

Business strategic orientations (STROBE)

Information management strategic orientations (STROIM)

Table A1 (continued)

Riskness in (1) resource allocation decisions and (2) choice of products and markets

(1) Participation in emerging industry, (2) continuous search of market opportunities and (3) experimentation with potential responses to changing environmental trends

Conceptual basis

Item one (building system with de®nite pay off,) item two (rather conservative view), and item four (similar systems have been successful) capture conservativeness in product choice (2). Item 3 (stage by stage basis) captures conservative attitude in resource allocation

Item (identifying new opportunities) captures the continuous search for market opportunities (2). Item two (in the forefront of trying new technologies) and item four (look out for new system applications) partially capture the intention of participation in emerging industry (i.e. new IT and system applications as new area for IS) (1) and experimentation with potential technologies (3). Item three (eliminating later stage system) is a response to environmental change (3)

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relative amount of variance and covariance jointly explained by the model. The AGFI differs from the GFI in that it adjusts for the number of degrees of freedom in the model. GFI and AGFI values range from 0 to 1, with higher values indicating better ®t (Byrne, 1989). GFI and AGFI scores in the 0.80±0.89 range are generally interpreted as representing reasonable ®t; scores of 0.90 and above represent good ®t (Doll et al., 1995). The RMR indicates the average discrepancy between the elements in the sample covariance matrix and the model-generated covariance matrix. RMR values range from 0 to 1, with smaller values indicating better models; values below 0.05 signify good ®t (Byrne, 1989). The NFI assesses the ®t of the model that is being studied in comparison to the ®t of a null model (Bentler and Bonnet, 1980). It indicates the practical signi®cance of the model in explaining the data. NFI values range from 0 to 1, with larger values indicating better models. NFI values of 0.90 and above indicate good model ®t since only a small a amount of variance remains unexplained by the model (Harvey et al., 1985). The results presented in Table 3 indicate that GFI and NFI values are greater than 0.95 in all cases, AGFI values are greater than 0.90 in all cases except one, and RMR values are less than 0.05 in all cases. Based on the guidelines for judging goodness of ®t discussed earlier, these results indicate very good model ®t. It is therefore possible to conclude that each of the six dimensions achieves unidimensionality and convergent validity. Reliability. Reliability values indicate the degree to which operational measures are free from random error and measure the construct in a consistent manner. Traditionally, the Cronbach a coef®cient (Cronbach, 1951) has been used to evaluate reliability. It has however been noted that Cronbach a uses restrictive assumptions regarding equal importance of all indicators and an alternate composite reliability measure has been suggested (Werts et al., 1974). This reliability measure r c can be calculated as follows: !2 !2 X X X rc ˆ li Variance…A†= li Variance…A† 1 ud … iˆ1

iˆ1

where r c is the composite measure reliability, n is the number of indicators, and li is the factor loading which relates item i to the underlying theoretical dimension (A). When r c is greater than 0.50 it implies that the variance captured by the trait is more than that captured by the error components (Bagozzi, 1981). r c values presented in Table 4 are all greater than 0.75, indicating good construct reliability. Discriminant validity. This refers to the independence of the dimensions, i.e. the extent to which measures of the six dimensions are distinctly different from each other. A test of discriminant validity was performed, taking two dimensions at a time; the dimensions are considered to be distinct if the hypothesis that the two dimensions together form one single construct is rejected. To test this hypothesis a pair-wise comparison of models was performed by comparing the correlations between the pairs of dimensions. A difference between the x 2 values (df ˆ 1) of the two models that is signi®cant at the p , 0:05 level would indicate support for the discriminant validity criterion (Joreskog, 1971). Table 5 reports the results of the 15 pair-wise tests of discriminant validity. Every one of the 15 values of x 2 differences for each of these tests was highly signi®cant, indicating strong support for the discriminant validity criterion. Predictive validity. This criterion seeks to ®nd support for the validity of the construct

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by investigating whether it exhibits relationships with other constructs that are in accordance with theory. The rationale for this approach is found in Bagozzi and Fornell's (1982) directive that the conceptual meaning of a construct should be determined not only by its de®nition and operationalization but also by its relationship to antecedents and consequents, and is used by Sethi and King (1994) to assess the predictive validity of their strategy dimensions. Following Sethi and King (1994), this study uses an IS performance effectiveness measure to evaluate the predictive validity of the dimensions. IS performance was measured on a ®ve point Likert type scale with ®ve items. 1 The items are presented in the appendix. Results of tests of unidimensionality and reliability for this construct are provided in Tables 3 and 4, respectively. Table 6 presents the results of the tests of predictive validity. These results provide support for predictive validity for all of the dimensions except riskiness. References Ahituv, N., Neumann, S., 1990. Principles of Information Systems for Management. Wm.C. Brown Publishers, IA. Anderson, J.C., 1987. An approach for con®rmatory measurement and structural equation modeling of organizational properties. Management Science 33 (4), 525±541. Applegate, L.M., McFarlan, F.W., McKenney, J.L., 1996. Corporate Information Systems Management: The Issues Facing Senior Executives. Irwin, Chicago, IL. Armstrong, C.P., Sambamurthy, V., 1999. Information technology assimilation in ®rms: the in¯uence of senior leadership and IT infrastructures. Information Systems Research 10 (4). Bagozzi, R.P., 1980. Causal Models in Marketing. Wiley, New York. Bagozzi, R.P., 1981. An examination of the validity of two models of attitude. Multi variate Behavioral Research 16, 323±359. Bagozzi, R.P., Fornell, C., 1982. In: Fornell, C. (Ed.). Theoretical Concepts, Measurements, and Meaning. A Second Generation of Multivariate AnalysisPraeger, New York, pp. 24±38. Bentler, P.M., Bonett, D.G., 1980. Signi®cance tests and goodness of ®t in analysis of covariance structures. Psychological Bulletin 88, 588±606. Byrne, B.M., 1989. A Primer of LISREL: Basic Applications and Programming for Con®rmatory Factor Analytic Models. Springer, New York. Cash, J.I., McFarlan, F.W., McKenney, J.L., Applegate, L.M., 1992. Corporate Information Systems Management: Text and Cases.. Irwin, Homewood, Illinois. Chan, Y.E., Huff, S.L., Barclay, D.W., Copeland, D.G., 1997. Business strategic orientation, information systems strategic orientation, and strategic alignment. Information Systems Research 8 (2), 125±150. Cooper, R.B., 1988. Review of management information systems research: A management support emphasis. Information Processing and Management 24 (1), 73±102. Cronbach, L.J., 1951. Coef®cient alpha and internal structure of tests. Psychometrika 16, 297±334. Doll, W.J., Raghunathan, T.S., Lim, J., Gupta, Y.P., 1995. Con®rmatory factor analysis of the user information satisfaction instrument. Information Systems Research 6 (2), 177±188. Earl, M.J., 1989. Management Strategies for Information Technology. Prentice Hall, New York. Ein-dor, P, 1986. An epistemiological approach to theory of knowledge, Proceedings of the Decision Science Institute Annual Meeting, Atlanta, 1986. 1

To detect likely self-reporting bias in the response of IS executives to questions on IS performance, CEOs / top managers in the sample organizations were also requested to respond to the same ®ve questions measuring IS performance. A matched data set of 64 responses was obtained. T-tests of means revealed that there were no statistically signi®cant differences between the mean values of IS performance as reported by the IS executives and as reported by their CEOs / top manager. However, the power of the test is not signi®cant due to small sample size.

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Fichman, R.G., Kemerer, C.F., 1997. The assimilation of software Process innovations; an organizational learning perspective. Management science 10 (10), xxxxx. Fichman, R., Kemerer, C.F., 1999. The Illusory Diffusion of Innovation: An Examination of Assimilation Gaps. Information Systems Research 10 (3). Floyd, S.W., Woolbridge, B., 1990. Path analysis of the relationship between competitive strategy, information technology, and ®nancial performance. Journal of Management Information Systems 7 (1), 47±64. Framel, J.E., 1993. Information value management. Journal of Systems Management 44 (12), 16±21. Fredrickson, J., 1984. The comprehensiveness of strategic decision process: extension, observations, and future directions. Academy of Management Journal 27, 445±466. Frenzel, C.W., 1992. Management of Information Technology. Boyd & Fraser, Boston. Grover, V., Ramanlal, P., 1999. Six myths of information and markets: information technology networks, electronic commerce, and the battle for consumer surplus. MIS Quarterly December. Harvey, R.J., Billings, R., Nilan, K.J., 1985. Con®rmatory factor analysis of the job diagnostic survey: good news and bad news. Journal of Applied Psychology 70 (3), 461±468. Henderson, J.C., Sifonis, J.G., 1988. The value of strategic IS planning: understanding consistency, validity, and IS markets. MIS Quarterly 12 (2), 187±201. Henderson, J.C., Venkatraman, N., 1993. Strategic alignment: leveraging information technology for transforming organizations. IBM Systems Journal 32 (1), 4±16. Jarvenpaa, S.L., Dickson, G.W., DeSanctis, G., 1985. Methodological issues in experimental IS research: experiences and recommendations. MIS Quarterly 9 (2), 141±156. Joreskog, K.G., 1971. Statistical analysis of congeneric tests. Psychometrica 36, 109±133. Joreskog, K.G. Sorbom, D., 1989. LISREL VII User's Guide, Scienti®c Software, Inc., Mooresville, Indiana. Keen, P.G.W., 1988. Competing in time: Using Telecommunications for competitive advantage. Ballinger, Cambridge, MA. Kettinger, W.J., Grover, V., Guha, S., Segars, A.H., 1994. Strategic information systems revisited: a study in sustainability and performance. MIS Quarterly 18 (1), 31±58. King, W.R., 1978. Strategic Planning for Management Information Systems. MIS Quarterly 2 (1), 27±37. King, W.R., Teo, T.S.H., 1997. Integration between business planning and information systems planning: validating a stage hypothesis. Decision Sciences 28 (2). Lederer, A.L., Mendelow, A.L., 1988. Convincing top management of the strategic potential of information systems. MIS Quarterly 4, 525±534. Lucas, H.C., 1989. Managing Information Services. Macmillan, New York. March, J., 1991. Exploration and exploitation. Organizational Learning Organization Science 2 (1). McGaughey, R.E., 1994. Implementing information technology for competitive advantage: risk management issues. Information and Management 25 (5), 273±280. Miles, R.E., Cameron, K.S., 1982. Cof®n Nails and Corporate Strategies. Prentice-Hall, Englewood Cliffs, NJ. Miles, R.E., Snow, C.C., 1978. Organizational Strategy, Structure, and Process. McGraw-Hill, New York. Naumann, J D., 1986. The role of frameworks in MIS research. Proceedings of the Decision Science Institute Annual Meeting, Atlanta, 1986, pp. 569±571. Nunnally, J., 1978. Psychometric Theory. McGraw-Hill, New York. Parsons, G.L., 1983. Information technology: a new competitive weapon. Sloan Management Review 25 (1), 314. Philips, L.W., 1981. Assessing measurement error in key informant reports: a methodological note on organizational analysis in marketing. Journal of Marketing Research 18, 395±415. Raghunathan, T.S., King, W.R., 1988. Assessing the impact of information systems planning on the organization. OMEGA International Journal of Management Science 16 (2), 85±93. Raghunathan, B., Raghunathan, T.S., 1991. Information systems planning and effectiveness: an empirical analysis. OMEGA International Journal of Management Science 19 (2/3), 125±135. Raghunathan, B., Raghunathan, T.S., 1994. Adoption of planning systems success model to information systems planning. Information Systems Research 5 (3), 326±340. Segars, A.H., 1997. Assessing the unidimensionality of measurement: a paradigm and illustration within the context of information systems research. OMEGA International Journal of Management Science 25 (1), 107±121. Segars, A.H., Grover, V., 1998. Strategic information systems planning success: an investigation of the construct and its measurement. MIS Quarterly June.

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Segars, A.H., Grover, V., 1999. Pro®les of strategic information systems planning. Information Systems Research 10 (3). Senn, J.A., 1989. Analysis and Design of Information Systems. McGraw-Hill, New York. Sethi, V., King, W.R., 1991. Construct measurement in information systems research: an illustration in strategic systems. Decision Sciences 22 (3), 447±455. Sethi, V., King, W.R., 1994. Development of measures to assess the extent to which an information technology application provides competitive advantage. Management Science 40 (12), 1601±1627. Straub, D.W., 1989. Validating instrument in MIS research. MIS Quarterly 13 (2), 147±169. Teo, T.S.H., King, W.R., 1997. Integration between business planning and information systems planning: an evolutionary-contingency perspective. JMIS 14 (1), 185±214. Venkatraman, N., 1989. Strategic orientation of business enterprises; the construct, dimensionality, and measurement. Management Science 35 (8), 942±962. Venkatraman, N., 1994. IT-enabled business transformation: from automation to business scope rede®nition. Sloan Management Review Winter. Venkatraman, N., 1997. Beyond Outsourcing: managing IT resources as a value center. Sloan Management Review Spring. Venkatraman, N., Grant, J.H., 1986. Construct measurement in strategy research: a critique and proposal. Academy of Management Review 11, 71±86. Wand, Y., 1986. On paradigms in IS discipline: The problem of the problem, Proceedings of the Decision Science Institute Annual Meeting, Atlanta. Warner, T.N., 1987. Information technology as a competitive burden. Sloan Management Review 29 (1), 55±61. Werts, C.E., Linn, R.L., Joreskog, K.G., 1974. Interclass reliability estimates: testing structural assumptions. Educational and Psychological Measurement 34, 25±33. Wastell, D.G., 2000. Learning dysfunctions in information systems development: overcoming the social defenses with transitional objects. MIS Quarterly March. Whitten, J.L., Bentley, L.D., Barlow, V.M., 1989. Systems Analysis and Design Methodologies. 2nd ed. Irwin, Homewood, IL. Wiseman, C., 1988. Strategic Information Systems. Irwin, Homewood, IL. Bhanu Ragu-Nathan is Professor of Accounting in the College of Business Administration at the University of Toledo. She holds a PhD from the University of Pittsburgh. She has published in Information Systems Research, Decision Sciences, OMEGA: International Journal of Management Science, Journal of MIS, Research in Accounting Regulation, Accounting Horizons, and Journal of Strategic Information Systems. Her current research interests are in information systems strategy, ethical issues in information systems, and behavioral issues in managerial accounting and control systems.

T.S. Ragu-Nathan is Professor of Information Systems and Operations Management in the College of Business Administration at the University of Toledo. He holds a PhD in Management Information Systems from the University of Pittsburgh. Has published in several journals including Information Systems Research, Decision Sciences, OMEGA: International Journal of Management Science, Journal of MIS, Journal of Information Systems, and Journal of Strategic Information Systems.His current research interests are in information systems strategy, quality issues in information systems, and use of information technology in manufacturing.

Qiang Tu is an Assistant Professor of Rochester Institute Technology. He holds a PhD in Information Systems and Operations Management from the College of Business Administration, The University of Toledo. He received his bachelor's degree in Management Engineering and master's degree in Systems Engineering from Jiaotong University, China. He has published in Information Systems Research, OMEGA: International Journal of Management Science, Journal of Information Technology Management, and the Computers and Industrial Engineering Journal. His research interests include information systems strategy, production scheduling, and behavioral issues in information systems and manufacturing management.

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Zhengzhong Shi is a PhD candidate in the Information Systems and Operations Management department at the College of Business Administration, The University of Toledo. He will be an Assistant Professor of Management Information Systems in the College of Business Administration at North Dakota State University. He received his bachelor's degree in Process Control in Chemical Engineering and master's degree in Computer Simulation in Chemical Engineering from Zhejiang University, China. He has published in Journal of Intelligent Manufacturing. His research interests include information systems strategy, inter-organizational information systems, and manufacturer and supplier relationship.