IT alignment in supply chain relationships: a study of supplier benefits.
Supply chain management (SCM), based on the need for coordination between supply chain partners (Narasimhan and Jayaram 1998; Vakharia 2002; Prahinski and Benton 2004), has been particularly impacted by the growth and development of information technology (IT). IT has enabled buyers and suppliers to share large amounts of information, such as operations, logistics and strategic planning data. This has fostered real-time collaboration and integration between supply chain partners, has provided forward visibility and has resulted in improvements in production planning, inventory management and distribution. IT, which allows for the transmission and processing of information necessary for synchronous decision making between firms, can be viewed as the backbone of the supply chain business structure (Mabert and Vankataramanan 1998; Grover and Malhotra 1997; Kearns and Lederer 2003).
Deployment of interorganizational IT throughout supply chain networks has usually been championed by supply chain network leaders. Network leaders are typically large firms that dominate a supply chain network and orchestrate the activities of their suppliers. For example, network leaders such as Chrysler, Dell, Ford and Wal-Mart have each chosen to use a particular form of interorganizational IT to coordinate and collaborate with their suppliers, from which they have derived benefits (Subramani 2004). In such situations, supplier firms must acquire the requisite ITs in order to participate in the particular network. The decision to acquire such technologies and develop the organizational skills necessary is an important one for managers of supplier firms. These firms are often smaller in size than their network leaders and must allocate larger portions of their budgets to develop such a capability. Further, some studies suggest that there is an imbalance of power between buyers and suppliers, placing an additional burden on supplier firms to participate (Maloni and Benton 2000).
Although network leaders are usually the ones to champion the introduction of IT in their networks, there is a question whether the benefits from these ITs are evenly distributed and may be skewed in favor of the network leader (Riggins and Mukhopadhyay 1994). Some studies even suggest that the benefits accrued to the network leader may elude the supplier (Carter 1990; Clemons, Reddi and Row 1993). The benefits of IT investment have typically been examined from the viewpoint of network leaders, with smaller amounts of attention given to the benefits accrued to suppliers. The studies that have examined supplier benefits from interorganizational IT have focused on systems that were actually developed by large supplier firms (Lee, Clark and Tam 1999; Mukhopadhyay and Kerke 2002). One exception is a study by Subramani (2004) that looked at the impact of the pattern of IT use in business processes by suppliers of a large Canadian retailer. The results of that study support the proposition that supplier IT use results in closer buyer-supplier relationships. Therefore, a greater understanding of the benefits that these systems provide. to supplier firms is an issue of interest to both researchers and practitioners.
Using empirical data, a model of the relationship between the alignment of supplier IT applications with that of their primary buyer, buyer-supplier integration, and performance benefits attained by the supplier is tested. The tested model is developed based on findings from the literature and the constructs are those used in past studies. Findings show that supplier IT alignment with their primary buyer has a positive impact on supplier performance measures. This impact on performance is both direct and indirect, mediated by firm integration. The performance benefits attained by the supplier are found to be both strategic and operational. These are important findings for supplier firms as they document the benefits they can attain when investing in IT applications that are directly aligned with that of their network leader.
Numerous studies have looked at how IT impacts the firm as a whole (Davenport 1993; Brynjolfsson and Hitt 1996) and include a wide range of studies. Some have looked at the value of aligning specific IT applications with the firm's organizational competitive priorities and strategic objectives (Kathuria, Anandarajan and Igbaria 1999; Kearns and Lederer 2003). Others have compared the effectiveness of specific IT applications (Raghunathan 1999) or looked at how IT is used within the organization (Subramani 2004). Collectively, these studies show that IT has a powerful impact on various aspects of organizational functioning and performance. A summary of these findings that pertain to the current study is shown in Table I and is discussed in this section.
Research looking at the direct impact of IT on specific performance measures, however, has shown mixed results. The literature suggests that there is a "productivity paradox," with some studies showing a strong positive impact and others offering contradictory evidence (Lim, Richardson and Roberts 2004; Sriram and Stump 2004). Numerous explanations have been offered for this paradox, such as management's failure to leverage the full potential of IT (Dos Santos and Sussman 2000), ineffective implementation (Stratopoulos and Dehning 2000), poor measures of performance (Bharadwaj, Bharadwaj and Konsynski 1999), and the presence of a time lag between IT investment and its actual impact on performance (Rai, Patnayakuni and Patnayakuni 1996; Deveraj and Kohli 2000). Others have tried to explain the apparent paradox by noting the differences between the research methodologies among disciplines conducting the studies, such as economics, production and strategy (Sircar, Turnbow and Bordoloi 2000; Sriram and Stump 2004). One view of how IT may impact performance is by fostering interfirm relationships (Hammer and Mangurian 1987), rather than having a direct impact. Many researchers agree with this view and suggest that IT may in fact impact performance by enabling relational outcomes (Wen, Yen and Lin 1998). The conclusion drawn from these studies is that the effectiveness of IT in bringing about performance benefits within the organization is complex. The impact of IT on performance is likely both direct and indirect, through the promotion of certain firm capabilities such as integration.
Firm integration is a fundamental element of SCM and is accomplished through coordination of activities throughout the network of buyers and suppliers (Handfield and Nichols 1999). Integration, in turn, is expected to result in reduced costs because of the elimination of operational duplication and resource waste (Andraski 1998; Stank, Keller and Daugherty 2001). Other literature also documents that IT has significantly improved collaboration between buyers and suppliers in areas such as inventory planning, demand forecasting, order scheduling and customer relationship management (Feeny 2001). This argument is also supported by transaction cost economics, which is based on the premise that cooperation and coordination among firms is limited by the transaction costs of managing the interaction (Coase 1937; Williamson 1975; Stroeken 2000). As transaction costs increase, market transaction efficiency decreases, resulting in higher market prices. IT has been shown to decrease transaction costs, resulting in an increase in firm cooperation and coordination (Clemons and Row 1992; Clemons et al. 1993).
A number of studies provide support for the link between IT use and firm integration. Ragatz et al. (1997) identified the use of linked information systems such as EDI to be a key success factor for the integration of suppliers into the process of new product development. Similarly, a study by Tallon et al. (1997) established that IT promotes coordination of value-added activities, a key aspect of supply chain integration. A later study by Stroeken (2000) found that IT is an essential element for supply chain innovation and has a positive impact on process innovation. Further, a study of first-tier automotive suppliers finds a direct relationship between integrative ITs and supply chain integration (Vickery, Jayaram, Droge and Calantone 2003).
SCM embraces a systems view regarding all activities and functions that are needed to bring a product or service to market. This view, which can be traced back to Porter's (1980, 1985) Value Chain Model, recognizes that the value creation process extends beyond the boundaries of the firm and involves integrated business processes among entities of the chain, such as suppliers, manufacturers and customers (Stevens 1989; Tan, Kannan and Handfield 1998). This requires integration, collaboration and coordination across individual firm functions and throughout the supply chain. Research consistently supports the idea that integration between firms improves firm performance (Stevens 1989; Lee, Padmanadhan and Whang 1997; Metters 1997; Anderson and Katz 1998; Hines, Rich, Bicheno, Brunt, Taylor, Butterworth and Sullivan 1998; Lummus, Vokurka and Albert 1998; Narasimhan and Jayaram 1998; Johnson 1999; Frohlich and Westbrook 2001; Vickery et al. 2003). Non-integration between firms results in problems that have been well documented, beginning with Forrester's (1961) seminal work (Lee and Billington 1992; Hammel and Kopczak 1993; Frohlich and Westbrook 2001). Lack of coordination has been shown to create the classic magnification of demand up the supply chain, known as the bullwhip effect, which results in alternating excess inventory and stockouts (Metters 1997). Having an integrated supply chain has been shown to provide a significant competitive advantage relative to both price and delivery (Lee and Billington 1992).
Today's most successful manufacturers have a tight coordination with their suppliers, permitting real-time information to travel immediately up and down the supply chain. The results are well-coordinated movements of inventories, products that are delivered quickly and reliably when and where they are needed, high responsiveness to short leadtimes, the elimination of the bullwhip effect, and improved firm performance (Lee et al. 1997). One example of this is offered by the relationship between Sears and Michelin, which relies on the collaborative practice of "collaborative planning and forecasting for replenishment." This has resulted in a 25 percent reduction in inventories for both companies (Steerman 2003).
DEVELOPMENT OF HYPOTHESES AND THEORETICAL MODEL
The above review of the literature documents the IT-integration linkage and that integration between supply chain partners improves firms' performance (Frohlich and Westbrook 2001; Vickery et al. 2003). Most of these studies, however, have focused on integration from the perspective of the buyer or the supply chain network leader. Few studies have provided confirmatory evidence on the impact of supply chain integration from the supplier viewpoint (Vickery et al. 2003). Further, none of these studies have looked at the benefits to the supplier that would result from the alignment of IT systems with their buyers. In addition, most studies in this area measure performance as a composite of operations performance measures (Scannell, Shawnee and Droge 2000; Narasimhan and Das 2001), rather than separately isolating strategic and operational performance measures that may accrue to the supplier as a result of the alliance with the buyer. These research questions are the focal issues of this current research. The specific hypotheses are derived next.
The relationship between IT use and firm integration has been examined in past studies (Raghunathan 1999; Vickery et al. 2003; Subramani 2004). Studies have also tested the relationship between general IT use and other constructs that are related to integration (Gaski 1984; Mohr and Nevin 1990), such as relationship commitment (Kent and Mentzer 2003). For example, a study by Kent and Mentzer (2003) found a strong and positive relationship between investment in ITs and relationship commitment between channel partners. Researchers have demonstrated that IT use can decrease coordination costs (Clemons and Row 1992; Clemons et al. 1993) and is expected to bring about increased coordination (Vickery et al. 2003). Although studies have not specifically focused on the value of IT alignment between buyers and suppliers, the extant research collectively supports the development of our first hypothesis that assumes a positive impact of IT alignment on firm integration:
H1: Supplier alignment of IT applications with their primary buyer has a direct and positive impact on buyer-supplier integration.
Greater coordination and integration between firms is expected to result in improved organizational performance. A study by Vickery et al. (2003), for example, provided empirical support for the link between firm integration and, specifically, customer service performance. Their study, focusing on firms in the auto industry, found that supply chain integration significantly impacts elements of customer service performance. A study by Stank et al. (2001) also found collaboration to positively impact firm performance. This leads to the development of our next two hypotheses:
H2: Buyer-supplier integration has a direct and positive impact on strategic performance measures of the supplier.
H3: Buyer-supplier integration has a direct and positive impact on operational performance measures of the supplier.
The review of the literature found mixed results with respect to the impact of IT on firm performance (Hu and Plant 2001). The majority of studies, however, do provide support for the direct impact of IT on firm financial performance (Bharadwaj 2000; Kearns and Lederer 2003; Santhanam and Hartono 2003). This leads us to expect that the alignment of IT between suppliers and buyers will have a significant and positive impact on both measures of firm performance. This leads to our last two hypotheses:
H4: Supplier alignment of IT applications with their primary buyer has a direct and positive impact on strategic performance measures of the supplier.
H5: Supplier alignment of IT applications with their primary buyer has a direct and positive impact on operational performance measures of the supplier.
In order to test the developed hypotheses, a conceptual model is proposed of the relationship between the degree of supplier IT alignment with their primary buyer, buyer-supplier integration, and both strategic and operational performance measures of the supplier. This is shown in Figure 1. This study defines IT as the technological capability used to acquire, process and transmit information for more effective decision making (Grover and Malhotra 1997). Buyer-supplier integration is a construct defined as an effective, mutually shared process where two or more departments work together, have mutual understanding, have a common vision, share resources and achieve collective goals (Schrage 1990). Our model shows buyer-supplier alignment of IT as a factor having a direct impact on both firm performance and buyer-supplier integration. The model further shows that buyer-supplier integration has a direct impact on both types of performance measures.
Data used in this study were derived from a mail survey of first-tier suppliers to OEM firms in the computer industry. Prior to the mailing, the survey instrument was pretested by four executives and five academics in order to review the questionnaire for readability and ambiguity (Dillman 2000). Small changes were made to select questionnaire items based on the pretest, and the instrument was mailed to 1,000 U.S. first-tier OEM suppliers. The survey was specifically targeted to CEOs as we felt they would be most likely to have the required knowledge. This logic is supported by a study by Phillips (1981) that found high-ranking informants to be more reliable sources of information than low-ranking company informants. The database and specific contact information were purchased from an outside firm with the above criteria specified.
In order to maximize the response rate, we followed a variation of Dillman's (2000) total design method. The survey mailing was carried out in two waves, 30 days apart. The initial mailing included a cover letter and the survey instrument, with the survey instrument designed to be folded and returned, with postage prepaid. Approximately 10 days following the initial mailing, reminder postcards were sent. This was followed by a second survey mailing approximately 30 days later with a note to those who had already responded to ignore the mailing. Fourteen incomplete responses were received and discarded. The mailings yielded 241 usable responses, for a response rate of 24.1 percent. This response rate is in line with past surveys of this type and deemed appropriate. Specific demographic information of the responding firms is shown in Table II. The survey respondents held a range of titles such as CEO (4.6 percent), Senior Vice President (40.2 percent), Vice President (36.0 percent) and Director (7.1 percent), with other titles comprising 1.7 percent. These titles help verify that the survey was completed by senior officers of their firms.
[FIGURE 1 OMITTED]
To ensure adequacy of the response sample, it was tested for non-response bias. This was accomplished by testing for significant differences between early and late survey respondents (Armstrong and Overton 1977). T-tests were performed on all questionnaire items used in this study between the first and second waves of survey respondents. No significant differences were found between the two samples, suggesting that non-response bias is not present in the data.
Table III shows the four factors used in our model and the multiple variables used to measure each factor. The scale items used to measure each factor are specifically derived from past studies and their effectiveness was tested using the procedures outlined by Churchill (1979) and DeVellis (1991). One of the most important measures of scale adequacy is scale reliability, which is the percent of variance in an observed variable that is accounted for by the true score of the latent factor or underlying construct (DeVellis 1991). High-scale reliability means that all variables that measure a single factor share a high degree of common variance. Although there are different methods to measure scale reliability, the more commonly used statistic is Cronbach's coefficient [alpha]. Cronbach's [alpha] measures the degree of interitem correlation in each set of items and indicates the proportion of the variance in the scale scores that is attributable to the true score. [alpha] levels below 0.7 are considered unacceptable (DeVellis 1991). As can be seen in Table III, all four factors have a value of Cronbach's [alpha] above 0.7.
The first factor shown in Table III--Factor 1--measures the degree of alignment between the IT applications of the supplier with their primary buyer. The development of scale items for this factor first needed to take into account the definition of IT that we term as technology used to acquire, process and transmit information for more effective decision making (Grover and Malhotra 1997). Three scale items were used to evaluate the extent of IT alignment: the extent to which IT applications for transaction processing (e.g., order tracking, invoicing, billing, etc.) were similar to that of the buyer; the extent to which IT applications used in operations processes (e.g., production planning, inventory management, etc.) were similar to that of the buyer; and the extent to which IT applications used for communication (e.g., electronic conferencing, e-mail system, electronic forums, etc.) were similar to that of the buyer. Comparable scale items were used in a study by Subramani (2004), from which our scale items were derived. The primary difference is that the scale items in the Subramani (2004) study focused on alignment of administrative procedures, operating procedures and software applications between buyer and supplier. Our study focuses specifically on alignment of IT applications needed for performance of specific functions.
The second factor--Factor 2--measures firm integration, a key element of SCM (Zaheer, McEvily and Perrone 1995; Choi and Hartley 1996; Tan et al. 1998). SCM enhances competitive performance through internal cross-functional collaboration that is linked with the functions of suppliers and channel members (Monczka, Robert, Petersen, Handfield and Ragatz 1998; Vickery, Calantone and Droge 1999). Three scale items are used to measure this factor: partnering with buyer, cross-functional teams with buyer, and engaging in collaborative planning with buyer. The first scale item addresses buyer-supplier partnering from the very beginning of the product life cycle to ensure that each entity is providing input into each other's processes. The second scale item, cross-functional teams between buyer and supplier, addresses issues of using joint task force teams to engage in activities that support strategic objectives. The last scale item, collaborative planning between buyer and supplier, involves the joint development and planning of strategic objectives. Comparable scale items have been used in other studies to measure supply chain integration (Vickery et al. 2003).
The last two factors--Factor 3 and Factor 4--measure firm performance. Past studies have measured firm performance in numerous ways (Handfield and Nichols 1999; Narasimhan and Das 1999; Wisner 2003). One of the more common ways has been to measure performance as a composite of various operations performance measures (Scannell et al. 2000; Narasimhan and Das 2001). This study chose to separate the measure of performance into two constructs--one measuring strategic performance and another measuring operational performance (Subramani 2004). Each factor is measured by three scale items used in previous studies (Subramani 2004).
Test of the Measurement Model
The proposed measurement model was evaluated using structural equation modeling following the approach recommended by Anderson and Gerbing (1988), using EQS software (Bentler 1997). In the first step, an acceptable measurement model was developed through the use of confirmatory factory analysis. This first stage involved identifying the latent factors of interest and testing the relationship between the observed variables and their respective latent factors.
When evaluating the measurement model, multiple fit criteria were considered in order to rule out measurement biases (Hu and Bentler 1999). We considered fit indices most commonly recommended for this type of analysis (Byrne 1994; Bagozzi and Yi 1998). All the indices were within the recommended range, including ratio of [chi square] to degrees of freedom ([chi square]/df=1.93), root mean square error of approximation (RMSEA=0.05), root mean square residual (RMR=0.04), goodness of fit index (GFI=0.96), normed fit index (NFI=0.96), comparative fit index (CFI=0.96), and incremental fit index (IFI=0.96). Based on these statistics, we judged the overall measurement model fit as satisfactory (Byrne 1994).
Tests of Convergent and Discriminant Validity
To further ensure adequacy of the measurement model and the meaningfulness of our findings, we conducted tests for additional empirical properties. The first of these was a test for convergent validity, which is the degree to which individual questionnaire items measure the same underlying construct. There are many ways to test for convergent validity; however, one way is to evaluate whether the individual item's standardized coefficient from the measurement model is significant, namely greater than twice its standard error (Anderson and Gerbing 1988). Coefficients for all items in our study greatly exceeded twice their standard error, providing evidence of convergent validity for the tested items.
In addition to convergent validity, it is also important to test that groups of variables intended to measure different latent constructs display discriminant validity. Discriminant validity addresses the extent to which individual items intended to measure one latent construct do not at the same time measure a different latent construct (DeVellis 1991). This study tested for discriminant validity in two ways. We first computed interfactor correlations for all factors and found them to be low. This was important as very high interfactor correlations, say approaching 1.00, indicate that the items are measuring the same construct, although significant interfactor correlations may be observed between theoretically related constructs.
Discriminant validity was further evaluated through a confidence interval test. A confidence interval was computed around the correlation estimates of plus or minus two standard errors. We then determined whether this interval included 1.0. Tests found that none of the confidence intervals contained 1.0, demonstrating discriminant validity (Anderson and Gerbing 1988).
[FIGURE 2 OMITTED]
The five hypotheses between the four factors of buyer-supplier IT alignment, buyer-supplier integration, and strategic and operational performance measures were analyzed using structural equation modeling using EQS (Bentler 1997). Figure 2 and Table IV present the results of the structural model tested. Overall model fit indices are as follows: [chi square]/df=1.93, RMSEA=0.05, RMR=0.04, GFI=0.97, NFI=0.97, CFI=0.96, and IFI=0.97. A comparison of these values against those recommended in the literature suggests that the model is satisfactory (Hu and Bentler 1999). All paths are statistically significant at the 0.05 level. This results in the support of our five hypotheses.
Buyer-Supplier IT Alignment
The results of this study show that buyer-supplier IT alignment impacts firm performance both directly and indirectly, by promoting firm integration. The direct and positive impact on performance includes both strategic and operational performance measures. This is an important finding as it demonstrates the value for suppliers when investing in IT that is aligned with their primary buyer or network leader. The alignment likely improves data and information sharing, and hence coordination by facilitating these activities. This appears to result in increased sales, profitability, and improvements in current and new processes. This also appears to affect strategic dimensions, such as the creation of new products, learning about new markets, and development of new business opportunities. The dual direct and indirect impact of buyer-supplier IT alignment is supported by the literature and documents the ways in which IT use impacts the operations of the firm.
The results of this study document that buyer-supplier integration has a direct and positive impact on the strategic and operational performance measures of the supplier. Although this finding is not a surprise, it provides important documentation of the benefits of buyer-supplier integration on both performance dimensions. It is particularly important given that the majority of past studies have focused on operational dimensions of performance, rather than strategic. It provides further evidence of the benefits of supply chain integration and provides evidence that IT is a tool that facilitates such integration.
MANAGERIAL AND RESEARCH IMPLICATIONS
The purpose of this article was to propose and test a model of the relationship between supplier alignment of IT applications with that of their primary buyer, buyer-supplier integration, and strategic and operational performance measures of the supplier. All tested relationships were found to be positive, leading to important managerial and theoretical implications. A significant contribution of this study is the empirical test of theoretical assumptions in the extant literature of the impact that buyer-supplier IT alignment has on firm integration from the supplier's perspective, and on the supplier's performance measures. Findings show that buyer-supplier IT alignment indeed impacts performance both directly and indirectly by encouraging firm integration. The benefits accrued to the supplier are shown to be both strategic and operational. These findings provide confirmatory evidence for the value gained by suppliers when investing in IT applications that are directly aligned with that of their primary buyer. This is a significant finding for managers as the decision for supplier firms to acquire the requisite ITs in order to participate in a particular network is important. Supplier firms are typically smaller than their network leaders and must appropriate larger portions of their budgets to acquire the necessary IT.
This research also suggests that firm integration is not synonymous with merely acquiring IT. Alignment needs to exist between buyer and supplier, which is in essence a separate construct that encourages coordination and integration. This is noted as occasionally companies presume that having IT automatically ensures that integration is in place. Supply chain integration involves collaboration and is a result of human interactions that can only be supported by IT, but not replaced. This is an important point for managers as they consider funding for various IT initiatives and implementation of acquired IT. Based upon the findings of this study, ITs that are aligned between buyers and suppliers should be given greater consideration. In fact, in a recent London School of Economics survey, CEOs rated IT as the firm's top strategic tool. They asserted, however, that the source of competitive advantage was not technology per se, but superior information sharing provided by these systems (Compass Group 1998).
It should be noted that our study focused on the benefits accrued to suppliers by aligning their IT with that of their primary buyer. One limitation of the current study is that it does not test for negative consequences of IT alignment by supplier firms with their primary buyer. An example of this might be high specificity and uniqueness of the IT where the technology may not be adaptable to use with other buyers. This has the potential of creating high dependence of the supplier on the buying firm and may be a risk factor that needs to be considered in the decision.
Another limitation of the current study is that it only tested buyer-supplier alignment of IT in general, without considering the impact of specific types of ITs. There are many types of IT, such as e-business technologies and wireless technologies, each likely having differing levels of impact on performance measures. One functional classification of IT is provided by Barki, Rivard and Talbot (1993), which classifies IT into six unique categories: transaction processing systems, decision support systems, interorganizational systems, communication systems, storage and retrieval systems, and collaborative work systems. Kendall (1997) provides another classification of IT, dividing it into two categories: production-oriented ITs and coordination-oriented ITs. It can be assumed that some ITs have a greater impact on integration and performance than others, and future studies may want to consider them.
Given the large expenditures IT investments require, it may be important for future work to consider the impact of different types of ITs on firm integration and performance, particularly from the standpoint of the supplier. This would better enable supplier firms to make an educated decision whether to invest in a particular IT and participate in a network or not. Future research should elaborate on our initial findings to consider the impact of specific ITs, particularly from the viewpoint of the supplier.
Our research considers first-tier OEM suppliers from only one environment, namely the computer industry. It can be argued that members of that industry are technologically savvy and thus may not represent the manufacturing sector as a whole. Future research should expand this type of analysis to include and compare multiple industries. IT sophistication may well prove to be an important factor that needs to be given consideration.
Investments in IT are important decisions for companies as they involve large capital expenditures. Deployment of interorganizational IT throughout supply chain networks has usually been championed by supply chain network leaders who dominate a supply chain network. Supplier firms are typically faced with the decision of whether to acquire the requisite IT that will serve to align them technologically with the network leader. This is an important decision for supplier firms that are often disproportionately smaller than their network leaders and must appropriate larger portions of their budgets to acquire the necessary IT. Although most suppliers realistically do not have a fair choice in this decision because of the fact that acquiring the IT is a requirement for participating in the network, little confirmatory evidence has been provided on the types of benefits suppliers can expect.
The benefits of IT investment have most often been examined from the viewpoint of network leader firms, with less attention given to the benefits accrued to suppliers. Using data from 241 first-tier OEM suppliers in the computer industry, we tested a model of the relationship between supplier IT alignment with that of their primary buyer, buyer-supplier integration, and benefits accrued to the supplier. Our findings show that IT alignment indeed impacts performance both directly and indirectly by encouraging buyer-supplier integration. The benefits accrued to the supplier are shown to be both strategic and operational. These findings provide confirmatory evidence for the value gained by suppliers when investing in IT applications that are directly aligned with that of their primary buyer.
Table 1 THE IMPACT OF IT ON FIRM INTEGRATION AND PERFORMANCE--SUMMARY OF RESEARCH FINDINGS Main Findings Supporting Studies IT has a powerful impact on organizational Brynjolfsson and Hitt functioning and performance (1996), Kathuria et al. (1999), Raghunathan (1999), Kearns and Lederer (2003), Subramani (2004) The impact of IT on firm performance is Hammer and Mangurian (1987), direct, indirect and complex Wen et al. (1998), Bharadwaj et al. (1999) IT is a key element of firm integration Feeny (2001), Ragatz et al. (1997), Stroeken (2000), Tallon et al. (1997), Vickery et al. (2003) Firm integration has a positive impact Stevens (1989), Lee et al. on performance (1997), Metters (1997), Anderson and Katz (1998), Hines et al. (1998), Johnson (1999), Lummus et al. (1998), Narasimhan and Jayaram (1998), Frohlich and Westbrook (2001), Rosenzweig, Roth and Dean (2003), Vickery et al. (2003) IT, information technology. Table II DEMOGRAPHIC INFORMATION OF SURVEY RESPONDENTS Annual Sales (US$ Number of million) Firms Percentage (A) Distribution of annual sales of survey respondents 1-249.99 77 32.0 250-499.99 69 28.6 500-999.99 44 18.3 1,000-1,499.99 37 15.3 1,500 and above 14 5.8 241 100 Number of Number of Employees Firms Percentage (B) Distribution of number of employees of survey respondents 1-999 64 26.6 1,000-1,999 68 28.2 2,000-2,999 52 21.6 3,000-3,999 20 8.3 4,000-4,999 28 11.6 5,000 and above 9 3.7 241 100 Table III FACTOR MEASURES Factor 1: buyer-supplier IT alignment (Cronbach's [alpha]=0.861) Alignment of applications used in transaction processing Alignment of applications used in operations Alignment of applications used for communication Factor 2: buyer-supplier integration (Cronbach's [alpha]=0.748) Partnering with buyer Cross-functional teains with buyer Collaborative planning with buyer Factor 3: strategic performance measures (Cronbach's [alpha]=0.842) Learning about customers and markets for our products Creation of new products, product enhancements Development of new business opportunities Factor 4: operational performance measures (Cronbach's [alpha]=0.762) Cost efficiencies from higher sales volumes Improvements to current processes or creation of new processes Increased profitability Note: [chi square]/df=1.93, RMSEA=0.05, RMR=0.04, GFI=0.96, NFI=0.96, CFI=0.96, and IFI=0.96. IT, information technology. Table IV TESTS OF BUYER-SUPPLIER IT ALIGNMENT HYPOTHESES Hypothesis Results H1: Supplier alignment of IT applications with their primary Support buyer has a direct and positive impact on buyer-supplier integration H2: Buyer-supplier integration has a direct and positive impact Support on strategic performance measures of the supplier H3: Buyer-supplier integration has a direct and positive impact Support on operational performance measures of the supplier H4: Supplier alignment of IT applications with their primary Support buyer has a direct and positive impact on strategic performance measures of the supplier H5: Supplier alignment of IT applications with their primary Support buyer has a direct and positive impact on operational performance measures of the supplier Note: All paths are significant at p [less than or equal to] 0.05. [chi square]/df=1.93, RMSEA=0.05, RMR=0.04, GFI=0.97, NFI=0.97, CFI= 0.96, IFI=0.97. IT, information technology.
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Nada R. Sanders is a professor of operations management and logistics in the Raj Soin College of Business at Wright State University in Dayton, Ohio.
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|Author:||Sanders, Nada R.|
|Publication:||Journal of Supply Chain Management|
|Date:||Mar 22, 2005|
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