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International Journal of Production Research Vol. 47, No. 10, 15 May 2009, 2535–2563 Alignment of operations strategy, information strategic orientation, and performance: an empirical study a b M. Schniederjans* and Q. Cao a b University of Nebraska-Lincoln, Lincoln, NE 68588-0491, USA; Management Information Systems, H.W. Bloch School of Business, University of Missouri-Kansas City, Bloch 230, 5110 Cherry Street, Kansas City, MO 64110-2499 (Received 3 December 2006; final version received 16 August 2007) Functional-level strategic planning should align with and support business-level strategies. Alignment of strategies is presumed to be a positive contributor to business performance just as misalignment is presumed to be a negative contributor. These presumptions should be true for all types of business environments including the e-commerce environment. This study develops and tests these presumptions by examining managers’ perceptions of strategy. Drawing on both operations strategy and information systems strategy literature, this research compares how these managers’ perceptions of operations strategy and information system strategic orientation are aligned in an e-commerce setting. Based on a sample of matched pairs of general managers and operations managers from 176 organisations in the e-commerce industry, hypotheses relating strategy and business performance are tested. The influence of other organisa- tional variables (i.e. operations manager tenure and years of associations with general manager) to moderate the results were also tested. The results support the hypotheses that organisational variables moderate the relationship between operations managers’ and general managers’ perceptions of operations strategy, IS strategy orientation, and the fit between them in e-commerce organisations. Keywords: operations strategy; e-commerce; information systems strategic orientation; hierarchical regression 1. Introduction The concept of alignment is an important theme in the field of strategic management (Venkatraman and Camillus 1984, Venkatraman 1989). Likert (1961) underlined the importance of aligning business and functional priorities with strategies of the firm. The importance of fitting, or aligning, business strategy with internal organisation strengths and external environmental opportunities/threats was emphasized by Ansoff (1965) and Andrews (1971). While Hrebiniak and Joyce (1984) and Lingle and Schiemann (1996) have shown the connection between alignment and business performance, strategic management literature presumes misalignment will undermine business performance (Ward and Bickford 1996). *Corresponding author. Email: firstname.lastname@example.org ISSN 0020–7543 print/ISSN 1366–588X online ß 2009 Taylor & Francis DOI: 10.1080/00207540701673465 http://www.informaworld.com 2536 M. Schniederjans and Q. Cao Research on alignment in the operations strategy literature can be classified under two categories: internal fit and external fit. Skinner (1974) generally refers to internal fit as the consistency among task, policies, and practices. For example, Safisadeh et al. (1996) addressed fit between manufacturing task and process choice. Kathuria and Davis (2001) looked at fit between manufacturing priorities and work force practices used by managers. External fit literature extends from Skinner’s (1969) seminal work which focused on the need for aligning operations strategy with business and corporate strategies. External fit can be examined in terms of its presence or absence, such as in Schroeder et al. (1986) where there was a need for manufacturing strategy to be consistently aligned with the business strategy of the firm. Alternatively, Swamidass (1986) using respondents from different managerial levels, observed a lack of alignment of strategic priorities at the manufacturing and business levels. Making the connection between the external fit literature and alignment and business performance relationships, Youndt et al. (1996) found certain types of human resource systems were directly related to operational performance measures. They also found competitive priorities moderated this relationship. In another study, Smith and Reece (1999) found business strategy based on operations management aspects of inventory, logistics, workforce, and organisations issues could lead to improved business performance. Papke-Shields and Malhotra (2001) extended operations alignment research by determining factors that lead to a greater degree of alignment between business and manufacturing strategies. Factors such as influence and involvement of manufacturing executives were found to affect alignment, which in turn affected business performance. Based on the prior research, Joshi et al. (2003) identified two gaps in the alignment- performance operations strategy literature. The first, supported by Boyer and McDermott (1999) suggested that few studies focused on strategy alignment in a manufacturing setting. The second was that fewer studies focused on the impact of a manufacturing unit’s performance. To address these gaps Joshi et al. (2003) focused their study on the interface between strategy-makers at the business and manufacturing manager levels. They examined if the strategy alignment between the organisation levels (i.e. general managers versus manufacturing managers) were reflected in the practice of managers at the business and manufacturing levels. Their sample was comprised of manufacturers from 17 different industries. Based on their sample they found that the business performance of a manufacturing unit was not directly enhanced when the strategy priorities of the general managers (GM) and manufacturing managers (MM) were aligned but, when moderating organisational factors were considered, enhancement was possible. To better identify the circumstances under which business performance can be enhanced they explored the influence of two moderating organisational factors (i.e. organisation tenure of the MM and years of association between the GM and MM). They found alignment and performance are significantly related when MMs are new to an organisation and when they have not yet developed a relationship with the GM. They also found that once a relationship with a GM was established and that the MM had achieved some tenure, alignment was not significantly related to business performance. Contrary to Joshi et al. (2003), Tarigan (2005) examined the alignment of GM and MM strategic priorities in a sample of 84 manufacturing firms in a variety of differing manufacturing industries and found a direct positive relationship between alignment and unit business performance. Tarigan (2005) also found that an organisational moderating International Journal of Production Research 2537 factor of unit decentralisation impacted business performance and manufacturing unit decentralisation strengthened the positive alignment-performance relationship. The contrary alignment-performance results between the Joshi et al. (2003) and Tarigan (2005) studies that demonstrate differences in perception between upper-level general managers and middle-level manufacturing managers can exist. Also, results vary when considering moderating variables in manufacturing industries. This opens up the possibility that industries other than manufacturing where operations managers are employed might reveal differing results and these results might be critical to achieving successful business performance in those industries. For purposes of the present paper and as a departure from prior research, we will examine alignment-performance issues within the electronic commerce industry. Electronic commerce or e-commerce as suggested by Riggins and Rhee (1998) is defined as involving not only buying and selling over the Internet, but also includes broader e-commerce related issues of strategic orientation toward servicing customers, collaborating with business partners, and conducting electronic transactions within an organisation. According to Feeny (2001), e-commerce operations offer opportunities for uses of Internet technology that can be directed at strategic change. As such, an operations management approach to e-commerce strategy can greatly benefit business (Riggins and Rhee 1998). Operations management literature also suggests the need to investigate its role in e-commerce (Geoffrion and Krishnan 2001). Shaw et al. (1997) and Han and Noh (2000) have called for the integration of operations management and management information systems research studies addressing e-commerce strategy from the operations perspective. Notably Venkatraman (2000) recognised the importance of alignment between business environment, operations strategy, and information system (IS) strategic orientation for business success in e-commerce. While the IS literature abounds with strategic orientation studies, few studies combine operations strategy in e-commerce. One study, Cao and Schniederjans (2004), found IS strategic orientation is a critical success factor leading to enhanced operations management business performance in e-commerce. Their research established a connection between operations strategy, IS strategic orientation, and business performance. In this present paper we seek to extend the Joshi et al. (2003) alignment model to look at perceptual differences in strategy between general managers (GMs) and operations managers (OMs) in the e-commerce industry. We focus on the alignment-performance relationship, investigating whether GMs and OMs agree on strategic characteristics (i.e. flexibility, quality, delivery, and cost) of their business units. These relationships are depicted in Figure 1. Heeding the call of Venkatraman (2000), we also broaden prior research to examine the GMs’ and OMs’ perceptions of the alignment-performance relationship of IS strategic orientation construct. We also examine the GMs’ and OMs’ perceptual fit of alignment between operations strategy and IS strategic orientation. We further study whether organisational factors (i.e. organisation tenure of OM and years of association) influence the alignment-performance relationships. 2. Literature review This paper’s proposed model is based on three streams of prior strategic alignment research. These streams relate to operations strategy, information systems strategy, and e-commerce. Relevant prior research is used here to introduce model constructs. 2538 M. Schniederjans and Q. Cao CEO’s perception of operations strategy Alignment of operations OM’s perception of strategy operations strategy CEO’s perception of IS strategic orientation Alignment of IS Business OM’s perception of strategic orientation performance IS strategic orientation CEO’s perception of the fit between Organisational Factors: operations strategy and IS strategic Org. Tenure of OM Alignment between Years of Association orientation operations strategy and IS strategic OM’s perception of orientation the fit between operations strategy and IS strategic orientation Figure 1. Alignment model for operations strategy, IS strategic orientation, and alignment fit. 2.1 Operations strategy The operations strategy alignment research originates with the conceptual framework for operations strategy research by Skinner (1969). This research supports the alignment relationships of the business environment, operations strategy, and business performance. Vickery et al. (1993) identified an ‘alignment fit’ (i.e. relational coherence) between environment factors and operations strategy, and its impact on business performance. Nath and Sudharshan (1994) examined coherence or alignment and found a monotonic relationship between alignment and business performance. They urged others to examine the relationship of a firm’s environment and business strategy, and a fit between a firm’s business strategy with its functional strategies, like operations. Ward et al. (1995) found the business environment appeared to have a tangible impact on operations strategic choices in operations. They suggested that ignoring environmental effects in the operations strategy model was likely to result in erroneous research findings. Other strategy literature suggests that operations strategy has a positive impact on business performance (Smith and Reece 1999), and that strategies based on organisation flexibility positively affected business performance (D’Souza and Williams 2000, Badri et al. 2000). International Journal of Production Research 2539 Recent manufacturing case studies (Baines et al. 2005) and empirical research (Chenhall, 2005), further support the connection between operations strategy and business performance. In summary, these and other studies like Joshi et al. (2003) empirically support the claim that alignment between the business environment and operations strategy is a central tenet of major strategic management paradigms. In addition to the alignment construct, other environmental factors, such as organisation tenure and years of association were found important moderating variables in the strategy literature. Collectively, these studies support the notion that operations strategy literature is a well-established research stream and is well suited as the theoretical foundation for operations strategy research used in e-commerce. It is noteworthy that these confirmatory studies focused only on the manufacturing strategy model without detailing the broader operations strategy constructs, such as quality and delivery service. Moreover, these studies only investigated the financial aspects of performance (e.g. return on investment) and omitted other dimensions, such as marketing growth (e.g. sales growth) and innovation performance measures (e.g. developments in business operations and services). 2.2 Information systems strategy The relationship of aligning IS strategy and operations strategy is an important construct of this paper. Chan et al. (1997) proposed the conceptual framework that established links between the business strategy orientation, the IS strategy orientation, and business performance. This framework indicates IS strategic orientation directly influences business performance, business strategy influences IS strategic orientation, and alignment of IS strategic orientation with operations strategy has a positive impact on business performance. The literature also suggests operations strategy positively influences the IS strategic orientation and vice versa. For example, Chan et al. (1998) found that companies with high IS strategic alignment were better performing companies. Sambamurthy (1999) argued that the operations strategy affected firms’ IS strategic orientation. Sabherwal and Chan (2001) and Chan (2002) found IS strategic orientation positively influenced firms’ operations strategy choices and alignment between business strategy and IS strategy positively affected perceived business performance. Pollais (2003) found that successful business performance in operations of information technology intensive organisations could only be achieved if the IS strategies were a part of a well-integrated organisational system of planning that included all functional areas. Booth and Philip (2005) found that significant strategic and operational benefits are possible when a firm’s IS strategies were aligned with organisational needs. Cao and Dowlatshahi (2005) established linkages between agile manufacturing operations strategy constructs and IS strategic orientation constructs within a manufacturing environment. They found positive relations with business performance when operations strategy and IS strategic orientation were aligned. They also found that moderating constructs (e.g. information technology) had more of an impact on business performance when they were strategically aligned. Other IS alignment research continues to reinforce the prior results that positively links business performance with an aligned IS strategic planning effort (Byrd et al. 2006, Chan et al. 2006). 2540 M. Schniederjans and Q. Cao In summary, the IS strategic alignment literature provides a substantial stream of theoretical support for the purposes of this paper. Specially, the IS strategic orientation and alignment of IS strategies are related to operations strategy and business performance. 2.3 E-commerce strategy research There is a substantial body of research that relates strategic planning with e-commerce. For example, Kao and Decou (2003) proposed a strategy-based model for e-commerce planning. While some research focuses on e-commerce failures (Razi and Tarn 2004), others make the connection to strategic planning as an enabler to e-commerce business performance success (Piris et al. 2004, Lumpkin and Dess 2004, Levy et al. 2005). Other research links IS strategic planning with the importance of alignment in e-commerce. Atieno (2004) found that strategic alignment of IS technology is a critical element in organisational strategic planning, necessary for enhanced business performance. Other e-commerce strategy research focuses on linkages with operations manage- ment. For example, Da Silveria (2003), using exploratory case studies, developed a framework combining operations management strategic planning with e-commerce strategic planning. Chang et al. (2003) showed how e-commerce strategic orientation of a firm and strategic opportunities can improve operations. Barnes et al. (2004) connecting operations strategies and e-commerce business performance found that a mismatch or misalignment between the operations strategy and e-commerce strategy can hamper business performance. The study by Cao and Schniederjans (2004) combines an e-commerce setting with both the operational strategic planning and IS strategic orientation impact on business performance. While their study shows general linkages between the operations strategy and IS strategic orientation in an e-commerce environment, they did not focus on unit differences between upper-level managers who originate strategy and middle-level managers who must carry it out. Nor did they examine whether organisational factors (i.e. organisation tenure of OM and years of association) influence the alignment-performance relationship as did Joshi et al. (2003) in a manufacturing setting. In summary, the e-commerce literature provides a substantial basis for supporting the theoretical linkages between IS strategic orientation and operations strategic planning in an e-commerce environment. 3. Research hypotheses The present paper seeks to research three types of relationship linkages presented in the model in Figure 1. Specifically to test GM and OM perceptions of strategy alignment and organisational factors based on Joshi et al. (2003) model but within the e-commerce environment. The upper portion of the alignment model in Figure 1 for operations strategy focuses on establishing a linkage between the operations strategy perceptions of GMs and OMs and business performance. The middle portion of the alignment model for IS strategic orientation focuses on establishing a linkage between the IS strategic orientation perceptions of GMs and OMs and business performance. The lower portion of the alignment model for fit between operations strategy and IS strategic orientation International Journal of Production Research 2541 focuses on establishing a linkage between the IS strategic orientation, operations strategy and business performance. Each of the three model linkages will also be tested for moderating organisational factors. 3.1 Operations strategy alignment model hypotheses ‘Business unit’ is defined as a single business, division, or subsidiary of a parent company (Cao and Dowlatshahi 2005). ‘Operations strategy’ is defined as the perception of how a business unit supports multiple goals in areas of operations flexibility, quality, delivery, and costs. For operations strategy we seek to determine if the alignment between the GMs perception of the operations strategy and the OMs’ perception of operations strategy enhances business performance. Thus, we have the following hypothesis. H1. As alignment between operations strategy perceptions of general managers (GMs) and operations managers (OMs) increases, the performance of the business unit increases. Prior research on this relationship is generally supportive. Papke-Shields and Malhotra (2001), Baines et al. (2005) and Chenhall (2005) all found alignment of strategies positively affected the business performance. Joshi et al. (2003) did find a relationship between operations strategy and business performance once moderating variables were included in their model. Tarigan (2005) in manufacturing and Cao and Schniederjans (2004) in e-commerce showed a positive relationship with business performance when the operations strategy was aligned. Therefore, we expect the relationships in this hypothesis to be proven true. The two organisational variables used in this study are OM organisational tenure and years of association. The selection of the OM’s ‘organisation tenure’ moderator variable is based on a proposition by Tesluk and Jacobs (1998) that knowledge and experience translates into successful business performance. Since GMs more clearly define the strategy formulation process according to Nutt (1987), Joshi et al. (2003) focused on the organisational tenure of the OMs. They found factoring for organisational tenure moderated the constructs of operations strategy and business performance from an insignificant to a significant result. The moderator variable ‘years of association’ was selected as a measure of length of time an OM worked with a GM to further represent work experience. Unlike organisation tenure which measures time with an organisation, Adkins etal. (1996)contends years ofassociation helps align the GMs and OMs with a common belief system and goals, impacting the relationship between alignment and business performance. We also contend, as did Joshi et al. (2003), that length of association between GMs and OMs reduces differences and in turn leads to a coherence in thinking resulting in enhances business performance. To examine the moderating effects of the two organisational variables within the operations strategy construct we have the following hypotheses. H1a. As the organisation tenure of OMs increases, the positive impact of alignment of operations strategy perceptions between GMs and OMs on performance of the business unit increases. 2542 M. Schniederjans and Q. Cao H1b. As the years of association between GMs and OMs increase, the positive impact of alignment of operations strategy perceptions between GMs and OMs on performance of the business unit increases. Ginsberg and Venkatraman (1985) and Homburg et al. (1999) noted that strategy research in the past experienced inconsistencies in identifying clear-cut relationship between alignment and business performance. The inconsistent results were attributed to a lack of moderator variables in the alignment-performance studies. We feel the inclusion of these two moderator variables will strengthen the results and both will be supported. 3.2 IS strategic orientation alignment model hypotheses Similar to Cao and Schniederjans (2004) and Cao and Dowlatshahi (2005) ‘IS strategic orientation’ is defined here as a perception of IS support for cost, quality, delivery, and flexibility strategies. For IS strategic orientation we seek to determine if the alignment between the GMs perception of the IS strategic orientation and the OMs perception of the IS strategic orientation impacts business performance. Thus, we have the following hypothesis. H2. As alignment between IS strategic orientation perceptions of general managers (GMs) and operations managers (OMs) increases, the performance of the business unit increases. We know from prior research there exists a positive relationship between IS strategy and business performance (Chan et al. 1997), and that aligned IS strategies are positively related to business performance (Chan et al. 1998, Sabherwal and Chan 2001, Chan 2002). We also know from Cao and Dowlatshahi (2005) that a positive relationship between an aligned IS strategic orientation and operations strategy will result in enhanced business performance in an e-commerce environment. While none of these studies focused on differences between GMs and OMs, they tend to support the likelihood that H2 will be proven to be true. To include the organisational moderating variables for the IS strategy orientation construct we have the following two hypotheses. H2a: As the organisation tenure of OMs increases, the positive impact of alignment of IS strategic orientation between the perceptions of GMs and OMs on performance of the business unit increases. H2b: As the years of association between GMs and OMs increase, the positive impact of alignment of IS strategic orientation between the perceptions of GMs and OMs on performance of the business unit increases. Cao and Schniederjans (2004) found that an aligned IS strategic orientation in e-commerce can positively impact business performance. Cao and Dowlatshahi (2005) found that moderating variables (e.g. IS technology) can have a significant positive impact on establishing a connection to IS strategic orientation and business performance. Based on these related studies, we feel that both H2a and H2b will be supported. International Journal of Production Research 2543 3.3 IS strategy and operations strategy alignment model hypotheses For alignment fit we seek to determine if the alignment between the GMs’ and OMs’ perceptions of IS strategic orientation and operations strategy impacts business performance. Thus, we have the following hypothesis. H3. As perceptual alignment fit between IS strategic orientation and operations strategy for general managers (GMs) and operations managers (OMs) increases, the performance of the business unit in creases. Based on the conclusions in Cao and Schniederjans (2004) in e-commerce and Cao and Dowlatshahi (2005) in manufacturing that generally alignment fit between operations strategy and IS strategic orientation will result in improved business performance, we expect H3 to be true. To examine the organisational moderating variables we have the following two hypotheses. H3a. As the organisation tenure of OMs increases, there is a positive impact of perceptual alignment fit between GMs and OMs of operations strategy and IS strategic orientation on performance of the business unit increases. H3b. As the years of association between GMs and OMs increase, there is a positive impact of perceptual alignment fit between GMs and OMs of operations strategy and IS strategic orientation on performance of the business unit increases. Based on Tarigan (2005) who found alignment of operations strategy between upper- level and lower-level managers enhanced business performance and by Joshi et al. (2003) who found the addition of these two moderating variables in an operations strategy model would improve business performance we expect H3a and H3b to be supported. 4. Methodology Using the same methodology as Joshi et al. (2003) to determine main and moderating effects, models are developed and analysed for each of the three sets of hypotheses. For comparative purposes with Joshi et al. (2003) results, we have selected a hierarchical regression model for testing the hypotheses (Vittinghoff et al. 2005). Hierarchical regression’s selection for hypotheses testing in this research is based on the two step testing processes involved. The first step is to test whether alignment (i.e. operations alignment, IS strategic orientation alignment, and alignment between operations and IS strategic orientation) is significantly related to the performance of the manufacturing units. Step 2 tests the relationships between performance and various alignments as moderated by organisational variables to see if there is any significant improvement over the first step. 4.1 Questionnaire construction The unit of analysis in this study is a business unit that is actively involved in e-commerce. Both research instruments used to obtain information for analysis were 2544 M. Schniederjans and Q. Cao survey questionnaires. One questionnaire was designed for GMs and the other designed for OMs (see Appendix 1). The preliminary questionnaires were developed from prior surveys and subsequent interviews with managers of several national e-commerce companies. A preliminary set of questionnaire items were developed to corresponding constructs, reviewed and edited using a Delphi revision approach by managers for a final draft. All opinion responses were measured on a five-point Likert scale, adapted from previous studies with modifications for the e-commerce setting. In this study, the operations strategy construct consists of four dimensions (i.e. flexibility strategy, quality strategy, delivery strategy, and cost strategy) used by Skinner (1974) and is also based on four of the five dimensions used by Joshi et al. (2003). The IS strategic orientation strategy construct is a revised version of the Chan et al. (1997) instrument, which was based on the notion that information systems strategy complements operations strategy. The questions used in the questionnaires for all constructs were adapted from Joshi et al. (2003) and Chan et al. (1997). Business performance information construct data were also collected in this study. The business performance data were collected in the GMs survey and includes three dimensions: market growth, financial performance, and innovation/reputation. This research combines the product-service innovation, and company reputation dimensions of Chan et al. (1997) for the business performance instrument into one dimension named innovation/reputation. These measures have also been reliably used in information systems strategy research by Sabherwal and Chan (2001). In addition to the construct measures, general information questions were also included in the survey instrument. This information included numerous questions on the respondent’s title, years of experience, types of e-commerce businesses and technology used, core competences, level of competition, importance of operations strategy, and reasons for the use of e-commerce. Several tests were conducted during the instrument validation and these included descriptive statistics analysis, tests of scale reliability, criterion-related validity, construct validity, unidimensionality, tests of convergence and discriminant in measurements and constructs. Generally speaking, these tests and analyses are widely used in instrument development in operations management research (Flynn et al. 1990). Summary results of these tests are presented Section 4.3. 4.2 Data collection, sample, and respondent profiles An initial sample of candidates for inclusion in this study was randomly selected from the 2002 North American Industry Classification System (NAICS) Manual. An invitation letter was sent to the 1200 potential candidate companies to determine their willingness to participate in the study. A total of 343 companies responded who were sent the questionnaires used in this study. Due to the study’s comparative nature the questionnaires were sent in paired versions, one for GMs and one for OMs. Of the 343, only a total of 176 (51%) companies eventually responded sufficiently to all the questions to be used as the sample in this study. A total of 352 usable or 176 paired questionnaires from the 176 companies were returned by the cut-off for the survey. Such a response rate is not unusual when the unit of analysis is the firm and when it involves an extensive organisational level survey (Griffin 1997). The resulting frequency and profile results of the participating companies are presented in Table 1. The resulting firms represent six different NAICS categories. International Journal of Production Research 2545 Table 1. Profile of participating companies. Number of Company profiles respondents Percentage Type of industry Computer and electronic product manufacturing (NAICS 334) 27 15% Electronics and appliance stores (NAICS 443) 39 22% Publishing industries (NAICS 511) 35 20% Credit intermediation and related activities (NAICS 522) 30 17% Professional, scientific, and technical services (NAICS 5426 15% Accommodation (NAICS 721) 19 11% E-commerce strategy Open strategy 105 60% Proprietary strategy 71 40% Number of employees Less than 200 19 11% 200–399 48 27% 400–699 52 30% 700–999 44 25% 1000 or more 13 7% Annual sales millions Less than 20 18 10% 20–99 26 15% 100–299 49 28% 300–499 45 26% 500–999 30 17% 1 billion or more 8 5% Types of electronic commerce technology are used in this organisation Internet 176 100% Intranet 176 100% Extranet 176 100% Traditional EDI 57 32% Internet-based EDI 132 75% Virtual organisation 176 100% Groupware technology 125 71% Others 37 21% To ensure that the respondents were all from e-commerce firms, the survey questionnaire contained a scanning question based on the e-commerce criteria proposed by Bauer and Colgan (2001). The subjects of this research who meet the criteria of e-commerce classification are regarded as actively involved in an e-commerce and are included in the study. The final sample represents a fairly even distribution of respondents from six different types of US industries (as listed by NAICS code on Table 1). Based on Storey et al. (2000) criteria we feel the industries in the sample are representative of e-commerce operations in the USA. To rule out the possibility of non-response bias a comparison of the companies that responded in the sample with a random sample of non-participating companies was conducted. Data were collected on non-participating companies and compared to the Table 1 frequencies. A non-respondent comparison suggested by Flynn et al. (1994) of 2546 M. Schniederjans and Q. Cao the distributions for the number of employees and sales between responding and non-responding participates showed no statistically significant (p50.001) differences. The companies in our sample had average annual sales of US$363 million and an average number of employees of 578. An important profile in this study is the organisation’s e-commerce technology usage. The types of e-commerce technology used by the companies are presented in Table 1. The participant frequency of e-commerce technology usage, their experience and reasons for its use are presented in participant profiles in Table 2. In other general questions in Table 2. Profiles of participating GM and OM respondents. Respondent profiles Number of respondents Percentage Your position title General manager – GM 49 28% Chief operations officer – GM 55 31% Chief executive officer – GM 72 41% Director of operations – OM 43 24% Operations manager – OM 74 42% Service/manufacturing manager – OM 59 34% Your business unit name Single business 81 46% Division/subsidiary 95 54% What is your functional area of expertise? – OM only Information systems 46 26% Operations management 33 19% Logistics 29 16% Accounting and finance 32 18% Customer services 24 14% Other 12 7% Five most important reasons that electronic business is used. Increase productivity 156 89% Communications between employees 141 80% Efficient connection of organisational resources 129 73% Reduce geographic distance 124 70% Cost reduction 103 59% Average years How long has your business unit been offering electronic commerce services to the public? Average years 12.94 – How long have you worked in your business unit? Average years – GM 4.67 – Average years – OM 7.34 – How long have you worked with the same subordinate? Average years – GM 4.22 – How long have you worked with the same supervisor? Average years – OM 3.97 – How many years of experience do you have in electronic commerce? Average years – GM 8.87 – Average years – OM 9.51 – International Journal of Production Research 2547 Table 2 respondent’s organisational tenure and years of experience are also captured for testing purposes. 4.3 Measurement of variables, scale reliability, and instrument validity 4.3.1 Alignment According to Venkatraman (1989) the concept of alignment has served as an important building block for theory development in strategic management research. Euclidean distance method was employed in this study to compute alignment scores between GMs and OMs in terms of operations strategy, IS strategic orientation, and fit between operations strategy and IS strategic orientation. The scoring process to measure variables is presented in Appendix 2. The computation of the alignment score in this study involves two steps. First, the misalignments between the matched pairs of GMs and OMs on operations strategy, IS strategic orientation, and fit between operations strategy and IS strategic orientation were calculated respectively using the Euclidean distance method used in Joshi et al. (2003), Sabhewal and Chan (2001) and Venkatraman (1989). In the second step the alignment score is computed by subtracting the respective misalignment score from the maximum misalignment score of the whole sample of each respective group, similarly used by Cao and Dowlatshahi (2005). 4.3.2 Business performance We have adopted perceptual measures of business performance for our study because of the same difficulties observed by Swamidass and Newell (1987) in trying to obtained objective measures like financial data at the business unit level. Perceived measures have been used and recommended as a substitute when objective measures are not readily available (Venkatraman and Ramanujam 1987, Homburg et al. 1999). The business performance of a business unit was measured based on the GMs’ perception on a total of 11 items. The scale was based on a 1-low to 5-high perceived achievement on the 11 items. This listing is based on general marketing, financial, and innovation/reputation criteria, similar to Cao and Schniederjans (2004) and Cao and Dowlatshahi (2005). 4.3.3 Organisational variables The GMs and OMs were asked for data on the organisational variables. The organisational tenure variable was determined by the response to the OM survey question: How long have you worked in your business unit? The years of association variable between the GM and OM was measured by the response to the OM survey question: How long have you worked with the same supervisor (i.e. GM, COO, and CEO)? 4.3.4 Scale reliability Scale reliability tests include Cronbach’s alpha, corrected item-to-total correlation, and split-half test. Cronbach’s alpha is a commonly used method for assessing scale reliability in empirical studies (Rosnow and Rosenthal 1998). In this research, Cronbach’s alphas were calculated for each dimension of its construct (Flynn et al. 1990). These Cronbach’s 2548 M. Schniederjans and Q. Cao alpha values for GMs and for OMs all exceed the suggested alpha value of 0.70 rule generally considered as ‘adequate’ for assessing reliability in empirical research (Nunnally 1978). Thus, it is assumed that the scale items used in this research can be considered reliable. Corrected item-total correlations (CITC) were used for purification purposes because ‘garbage’ items may confound the interpretation of the factor analysis (Koufteros et al. 2001). The CITC of all scale items ranged from 0.437 to 0.858 for GMs and ranged from 0.506 to 0.879 for the OMs, which is above the suggested 0.30 rule for this reliability test. The lower bound of this range is in line with those in other operations management and information systems studies (Koufteros et al. 2001) and is assumed that all scale items in this study cover the various dimensions and are adequate measures of their corresponding constructs. In a split-half reliability test all items that purport to measure the same construct are randomly divided into two sets to assess reliability by measuring homogeneity. The split-half test was also employed in this study to assess the homogeneity aspect of the scale reliability. The split-half alpha values ranged from 0.772 to 0.894 for the GMs and 0.708 to 0.984 for the OMs. These values are generally considered adequate for empirical research (Nunnally 1978). 4.3.5 Instrument validity In this study instrument validity is comprised of the results of content validity, criterion- related validity, convergent validity, and construct validity. Cooper and Schindler (1998) suggested two ways of determining content validity: 1. Through a careful definition of the topic of concern, the items to be scaled, and the scales to be used. 2. Using a panel of experts to judge how well the instrument meets the standard. Our study’s survey questionnaires were based on operations strategy theory and information systems strategy research literature, which covers all major aspects of the content areas. Moreover, the items to be scaled and the scales to be used in this research are adapted from previous operations strategy and information systems strategy empirical studies. The preliminary questionnaires were sent to and examined by a panel of experts in both the operations and information technology/information systems fields. The final questionnaires were modified to meet the standards based on the input of the panel of experts. Criterion-related validity is the degree to which the survey instrument correlates with one or more criteria. The expected cross validity index (ECVI) is one measure for criterion- related validity (Kline 1998). The ECVI values of all three constructs (largest being 0.72) in this research are well below value of 1 rule for ‘adequate’ in a criterion-related validity test. As a result, it is assumed that all scale items have high probability of correspondence between sample and population model fit. The unidimensionality test provides evidence of a single latent construct (Flynn et al. 1990). In this research, the more rigorous confirmatory factor analysis (CFA) approach was employed. The use of CFA requires the researcher to specify a conceptual model prior to analysing the data. In this research, the three constructs were specified. All scale items loaded on their intended dimensions. Standardised loadings for scale items ranged from 0.61 to 0.92. These CFA loading results were in the moderate-to-high level. International Journal of Production Research 2549 Moreover, t-values for scale items ranged from 6.61 to 14.33 exceeding the 2.0 rule of thumb. As a result, all loadings for scale items were significant (p50.05). All four dimensions then loaded on the business performance construct. Overall, dimensions loaded strongly on this construct with the lowest standardised loading at 0.81. All t-values for various dimensions were much higher than the 2.0 rule of thumb revealing the loadings for the dimensions were significant (p50.05). Convergent validity concerns the degree to which multiple methods of measuring a variable provide the same results (Churchill 1979). Stand-alone indices are used to test convergent validity. They are based on the maximum likelihood fitting function, which performs much better than those indices derived from the generalised least squares approach (Hu and Bentler 1998). Stand-alone indices include standardised root- mean-square residual (SRMR), competitive fit index (CFI), root-mean-square-error of approximation (RMSEA), ▯ 2/df, and Critical N (Marsh et al. 1988). Hu and Bentler (1998) recommended a maximum value close to 0.08 for SRMR; and a maximum cutoff value close to 0.06 for RMSEA. A minimum cutoff value close to 0.9 is suggested for CFI (Bollen 1989). Kline (1998) suggested a maximum cutoff of ▯ 2/df ratio of 3.0. Critical N allows research to assess the fit of a model relative to identical hypothetical models estimated with different sample sizes (Hoelter 1983). Critical N is computed based on the chi square (▯ 2) and its degrees of freedom. A Critical N that is lower than the actual sample size in CFA shows that CFA has sufficient power to detect some trivial problems causing a poor fit (Jore¨kog and Sorbom 1¨93). A CFA stand-alone index for each construct supports the convergent validity of the instrument. If a construct has discriminant validity, scale items measuring different constructs should have low correlations (Spector 1992). CFA was employed in this research to assess 2 the discriminant validity (i.e. ▯ difference test using a significance of p50.01 level). In this test each of the combinations of the three constructs taken two at a time for comparison create pair-wise comparisons. The ▯ 2difference between the unconstrained model and the constrained model is tested at a given probability. These tests were significant (p50.01), and it can be concluded that the three constructs were related but represented conceptually distinct traits (i.e. possessing discriminant validity). In summary, all constructs and all scale items used in this research met the test requirements for adequate scale reliability and instrument validation. 5. Results In Table 3, the descriptive statistics and correlation matrix for the study variables are presented for each of the three sets of hypotheses. Similar to Joshi et al. (2003) the business performance and organisational tenure variables were significantly correlated to business performance. Unique to this study, the significant relationship held true for all three sets of hypotheses comparisons of operations strategy, IS strategic orientation, and the fit between them. Hypothesis 1 seeks to test whether the perceived alignment in the operations strategy between the GMs and OMs is significantly related to the performance of the business unit. H1a and H1b test the relationship between business performance and the alignment as moderated by organisational variables. Results of these hypotheses are presented in Table 4. 2550 M. Schniederjans and Q. Cao Table 3. Descriptive statistics: mean, standard deviation and correlation. Business Organisation Years of Variable Mean SD Alignment performance tenure association Alignment model for operations strategy (sample size¼176) Alignment 2.51 0.82 1.00 0.10 0.09 0.12 Business performance 3.26 0.71 1.00 0.20* 0.43y Organisation tenure 11.45 8.54 1.00 0.31y Years of association 4.60 3.42 1.00 Alignment model for IS strategic orientation (sample size¼176) Alignment 2.26 0.67 1.00 0.06 ▯0.11 0.07 Business performance 3.26 0.71 1.00 0.19* 0.37y Organisation tenure 11.45 8.54 1.00 0.28y Years of association 4.60 3.42 1.00 Alignment model for fit between operations strategy and IS strategic orientation (sample size¼176) Alignment 2.76 0.86 1.00 0.18* 0.06 0.11 Business performance 3.26 0.71 1.00 0.21y 0.34y y Organisation tenure 11.45 8.54 1.00 0.26 Years of association 4.60 3.42 1.00 *Significant at p50.05. ySignificant at p50.01.SD, standard deviation. Table 4. Hierarchical regression results for operations strategy alignment. Step 1 Step 2 Variable b T p b t p Alignment 0.10 0.94 0.327 0.390 2.28 0.010 Organisation tenure 0.520 2.46 0.014 Years of association 0.460 2.01 0.032 Alignment ▯ Organisation tenure ▯0.550 ▯2.65 0.019 Alignment ▯ Years of association ▯0.200 ▯1.00 0.187 r2 0.01 0.220 F-value 3.932 p-value 0.027 Overall F (p-value) 4.007 (0.002) Note: all p-values are one-tailed except for those associated with the F statistics. The results in Table 4 reveal the direct effect of alignment on business performance is absent (in Step 1: ▯¼0.1, t¼0.94, p¼0.327) from the regression-based alignment model for operations strategy but for the focus of this study it is the overall model which yields significant results (in Step 2: F¼4.007, p¼0.002). While the correlation coefficients are significantly improved (see Table 4) by the addition of the interaction variables into the model, a review of the correlation matrix for all variables revealed no presence of multicollinearity. Since the interaction terms introduced in the second step of the regression significantly improved the model’s results over the first step, the International Journal of Production Research 2551 incremental variance in the dependent variable provides evidence to support the moderating effect of organisational variables proposed under H1a and H1b. This result is the same that Joshi et al. (2003) experienced with GMs and MMs in their alignment of production priorities. Joshi et al. (2003) utilised Jaccard et al. (1990, pp. 26–27) to interpret the regression coefficient estimates. Specifically, when organisational variables (i.e. organisational tenure and years of association) are equal to zero, the alignment of GM and MM priorities are positively related to performance. Relating their interpretation to our study, we can conclude that operations strategy alignment and business performance have a positive relationship when the OMs have not yet developed a working relationship with GMs (i.e. zero tenure) and are new to the organisation (i.e. zero years of association). On the other hand, alignment of the operations strategy and business performance appears not to have a relationship when the OM has been with the organisation for sometime (i.e. organisational tenure greater than zero) and established a relationship with a GM over time (i.e. years of association greater than zero). The negative sign in the variable (i.e. alignment ▯ organisation tenure) might be interpreted as after establishing relationship between GM and MM and after staying in the organisation for a while, tenure curtails the relationship between alignment and performance. One explanation for the lack of significance (i.e. alignment ▯ years of association) is that after establishing relationship between GM and MM and after staying in the organisation for a while, alignment’s relationship with performance gradually weakens to a point becoming insignificant. In summary, H1 is not supported unless the moderating variables are included in establishing the relationship in the overall model. In terms of H1a and H1b, we can examine both the strength and nature of the interaction as suggested by Jaccard et al. (1990). In step 2 of Table 4 for the portion (in Figure 1) of the alignment model for operations strategy the interaction terms account for a significant increase in r , from 0.01 to 0.22. A significant increase in the variance explained by the interaction terms (F¼3.932, p¼0.027) supports the moderating effect of the organisational variables of organisational tenure and years of association. To further support the results for H1 and rule out the possibility of erroneous results due to use of composite measures, we conducted individual hierarchical regression analyses for each of the four dimensions with respect to the dependent variable business performance. The flexibility dimension consisted of six survey items; the quality strategy dimension consisted of six items; the delivery strategy dimension of four items; and the cost strategy of five items. The results of the four regression analyses are presented in Table 5. In each of the four dimensions the results are consistent with the initial findings that resulted from the use of the composite measures. Specifically, that the overall models F-tests and their p-values in step 2 of the analyses are all significant (p50.05) with changes to r . This further supports the initial results of the affect of moderating organisational variables of organisational tenure and years of association. Hypothesis 2 seeks to test whether the perceived alignment of the IS strategic orientation between the GMs and OMs is significantly related to the performance of the business unit. H2a and H2b test the relationship between business performance and the alignment as moderated by organisational variables. The regression results for H2 are similar to those of H1. They reveal the direct effect of alignment on business performance is absent (in Step 1: ▯¼0.06, t¼0.53, p¼0.168) from the portion (in Figure 1) of the alignment model for IS strategic orientation regression model but the overall model yields significant results (in Step 2: F¼3.948, p¼0.004). Similar to H1, the interpretation of this result allows us to conclude that 2552 M. Schniederjans and Q. Cao 0.02046 ▯ ▯ 0.73320 0.006 ▯ ▯ 0.2900 0.017 ▯ 0.58270 0.06248 ▯ ▯ 0.0700 0.400 0.41003 0.0200 0.290 0.048 ▯ 0.0.023 ▯ ▯ 0.0.180 0.031 ▯ ▯ 0.2700 0.0.092 ▯ ▯ 0.0.130 0.012 ▯ ▯ b b p b b p b b p b b p Flexibility strategy 0.0Quality strategy 0.Delivery strategy 0.Cost strategy OrYears of as-value)on 3.245 (0.012) ▯ ▯ ( F -v-value 3.889 Table 5. VReniselsionlOrgaeaiAlirgnF p Overalltrete1y alintepe2t base0d0.5.4400.i0.01008ns.0 0.430 International Journal of Production Research 2553 perceptions of IS strategic orientation alignment and business performance have a relationship when the OMs are new to the organisation and have not yet developed a working relationship with GMs. On the other hand, alignment of the perceptions of IS strategic orientation and business performance appears not to have a relationship when the OM has been with the organisation for sometime and has established a relationship with a GM over time. These results fail to support acceptance of H2. In terms of H2a and H2b, we can again examine both the strength and nature of the interaction. The step 2 for the alignment model for IS strategic orientation interaction 2 terms account for a significant increase in r , from 0.0036 to 0.30. A significant increase in the variance explained by the interaction terms (F¼3.932, p¼0.027) supports the moderating effect of the organisational variables of years of association and tenure, supporting the acceptance of H2a and H2b. To again rule out the possibility of erroneous results due to the use of composite measures and further support H2, we conducted individual hierarchical regression analyses for each of the four items (i.e. cost strategy, quality strategy, delivery strategy, and flexibility strategy) used in the IS strategic orientation dimension with respect to the dependent variable business performance. For each of the four items, the results are consistent with the initial findings that the overall models F-tests and their p-values in step 2 of the analyses are all significant (p50.05) with changes to r 2. This further supports the initial results of the affect of moderating organisational variables. Hypothesis 3 seeks to test whether the perceived fit between the operations strategy and the IS strategic orientation of the GMs and OMs is significantly related to the performance of the business unit. Hypotheses 3a and 3b tests this alignment relationship between business performance and the alignment as moderated by the two organisational variables. These results are presented in Table 6. The results for H3 in Table 6 are different from those of H1. They reveal the direct effect of alignment on business performance is significant in step 1 (▯¼0.18, t¼1.93, p¼0.049), but clearly with the inclusion of the moderating variables in step 2, the fit between operations strategy and IS strategic orientation overall alignment model yields significant results (F¼4.435, p¼0.001). These findings might be interpreted to mean that perceptions in the fit between operations strategy and IS strategic orientation have a relationship to business performance when the OMs are new to the organisation and Table 6. Hierarchical regression results for fit between operations strategy and IS strategic orientation alignment. Step 1 Step 2 Variable b t p b t p Alignment 0.1800 1.93 0.049 0.450 2.30 0.008 Organisation tenure 0.460 2.49 0.023 Years of association 0.510 1.96 0.045 Alignment ▯ Organisation tenure ▯0.490 ▯2.61 0.021 Alignment ▯ Years of association ▯0.180 ▯1.01 0.304 2 r 0.0324 0.320 F-value
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