نقش یادگیری و توانایی های فنی در پیش بینی انطباق اتخاذ و انطباق فناوری B2B

Using the resource-based view and the learning organization as its theoretical framework, this study hypothesized that organizations which possessed not only the technical capabilities for automation but also the ability to learn and share information would be most likely to automate their supply chain processes. An empirical study with the top suppliers of a major airline supported this hypothesis. As predicted, both learning capabilities and certain technical capabilities were important in predicting the likelihood of adoption of Ariba, a web-based e-procurement tool.

In his 1997 Computerworld Leadership Series, Davenport (1997) offered some insights into why IT practitioners continue to develop applications that are not adopted by users. Among his laundry list of items, Davenport began with the notion that systems are largely governed around how information flows within and around an organization. To this end, antiquated frameworks of data management have proven to be dysfunctional—thereby resulting in failures to meet customer demands, challenges to internal and interface integration, extreme cost overruns, and resistance to change Goodhue et al., 1992 and Truman, 2000. As organizations strive to electronically integrate not only their immediate customers and suppliers, but multiple tiers of customers and suppliers, adoption of these new technologies across global supply chains continues to be a major barrier (Handfield & Nichols, 1999, Chap. 1). As supply chain members begin to work together, integration must occur between functions both internal to the organization (purchasing, engineering, manufacturing, marketing, logistics, accounting, etc.) and external to the organization (end customers, third-party logistics, retailers, distributors, warehouses, transportation providers, suppliers, agents, financial institutions, etc.). Each goal contains its own set of challenges. For instance, internal strategic integration requires that all company members have access to an integrated information system spanning multiple functions and locations. This integration is most often accomplished through a company-wide ERP (Enterprise Resource Planning) system, which links internal groups via a single integrated set of master records. External integration refers to the systems that link external suppliers and customers to the focal company. External integration allows all supply-chain members to share critical information such as forecast demand and inventory levels across the supply chain. Systems used to integrate supply-chain members include e-procurement and e-logistics systems, trade exchanges, network communications, and Electronic Data Interchange (EDI) (Handfield & Nichols, 1999, Chap. 1). This study is motivated in part by the very practical concerns of a large airline as it moved forward in its supply chain automation efforts. This airline was in the processes of implementing an e-procurement system in a parallel mode. The system, Ariba, is a web-based e-procurement tool that allows users to order items directly from supplier catalogs from a secure Internet website, thereby automating the order requisition, purchase order, and accounts payable processes. Other software alternatives to Ariba include Commerce One, Lawson, Lonesource, and other providers that provide electronic tools and documents for purchase requisition, request for quotation, approval, purchase order, and accounts payable processes. These systems do not require suppliers to make a major investment in the technology. However, the systems do require that suppliers invest in alternative businesses processes in bidding, providing requests for quotation, and invoice submittal procedures. Supplier automation systems also require some baseline level of technical expertise, as suppliers may need to submit materials via online systems, develop electronic catalogs of item availability to the customer. Once a buying company implements a system such as Ariba, it is relatively difficult to switch to another system, as the compatibility with other purchasing systems may be relatively low. Systems such as Ariba or Commerce One, are, however, compatible with many ERP systems currently in use. In this case, as Ariba was implemented, the airline continued to use a traditional manual process for purchase orders and invoices with many of its larger suppliers. As the airline moved forward with Ariba, executives were faced with the task of selecting supplier candidates for the pilot stage of the system. Executives eliminated many suppliers based on the criteria to include only large strategic supplier partners; however, this decision still left them with a total of 96 potential suppliers. Executives noted that the success of the pilot was critical to the success of the entire Ariba implementation. If the pilot was successful, the likelihood of other suppliers “jumping on board” was more probable. The selection decision needed to be made quickly, as the time frame for implementation was perceived to be rather short. This paper first presents several key theoretical frameworks used to develop a model for the likelihood of adoption of B2B technologies by suppliers. The literature review suggests the hypothesis that suppliers can be clustered into four groups on the basis of technological and learning dimensions, and also suggests that these clusters will vary in terms of their likelihood of adoption and cycle time improvements. This paper then discusses the constructs and scales that were developed to test these hypotheses and the methodology used to analyze the resulting data. Finally, the results and managerial implications of the study are presented.

This research provides a piloted methodology to segment an organizational supply base into clusters that have a high potential for success in implementing B2B technology pilot implementations. The methodology has been applied in a real-world setting to evaluate high-potential suppliers for a pilot implementation of Ariba, an e-procurement methodology. From a theoretical standpoint, the research, in part, replicates prior results on organizational learning and information processing in the supply chain in a specific company context. This study also documents the importance of considering learning, information processing and technology capabilities in conducting supplier analysis and selection processes in managing supply chain initiatives, something managers are prone to overlook in their rush to get suppliers to adopt new technology. This research has some limitations as to the generalizability of the results, since the analysis was conducted in one company's supply base, but holds rich promise for future research in this area. Fig. 6 illustrates the results of examining the correlation matrix and performing regression analysis (not reported here in detail) to determine the relationship between the variables as they might be studied in a structural equation model in the next phase of the research with a larger sample. (Please note that this figure represents the relationships in the data and has not been subjected to tests for model identification and other rigors of structural equation modeling). Overall, these data reinforce the relationship between learning orientation and cycle time improvements Hult, 1998 and Hult et al., 2000, aided by information management capability (Hult et al., 2000). These results in fact indicate that the ability to share specific types of information with manufacturing and distribution might be more important to distinguish between suppliers in an implementation effort than general learning capabilities.