دقت پیش بینی موفقیت تجارت الکترونیک B2B در شرکت های کوچک و متوسط

Since implementing B2B e-commerce in small and medium enterprises (SMEs) is a long-term commitment and such enterprises are more limited in terms of resources than large enterprises, the predicted value of successful implementation is extremely useful in deciding whether to initiate B2B e-commerce. This investigation establishes an analytical hierarchy framework to help SMEs predicting implementation success as well as identifying the actions necessary before implementing B2B e-commerce to increase e-commerce initiative feasibility. The consistent fuzzy preference relation is used to improve decision-making consistency and effectiveness. A case study involving six influences solicited from a Taiwanese steel company is used to illustrate the feasibility and effectiveness of the proposed approach. The analytical results show that the three most influential factors are management support, industry characteristics and government policies; meanwhile, the three least influential factors are organizational culture, IT integration and firm size.

Rapidly developing communications technology and increasing internet penetration have contributed to the growth of electronic commerce (e-commerce) worldwide. The term “e-commerce” emerged only in recent years as businesses became aware of the potential role of the Internet as a powerful medium for conducting business. In the past decade, e-commerce has substantially affected the business world and is expected to increase in importance. E-commerce has prompted the rise of virtual business relationships including business-supplier, business-client, business-to-end consumer and strategic alliance (Speier, Harvey, & Palmer, 1998). Based on the parties involved in the business transaction, e-commerce can be classified as business-to-customer (B2C) or business-to-business (B2B). The benefits of e-commerce are apparent not only for large firms but also for small and medium enterprises (SMEs) (Grandon & Pearson, 2004). However, some governments have noted the relatively slow uptake of electronic commerce in the SME sector (Barry and Milner, 2002 and Darch and Lucas, 2002). Deciding whether to implement B2B is difficult in many organizations and particularly in SMEs. This vital decision may promote growth in an organization or lead to its downfall; consequently, all aspects of implementation must be considered before reaching a consensus within an organization. Although cases of successful B2B e-commerce implementation have been widely reported, several noteworthy failures have also occurred worldwide. Implementing B2B e-commerce is time consuming, and the long-term impact on an organization may be unclear for some time. Since implementing B2B e-commerce in SMEs is a long-term commitment and is more limited in resources than large enterprises, the predicted value of successful implementation would be extremely useful when deciding whether to initiate B2B e-commerce. Therefore, the likelihood of successful implementation and an effective decision-making process can facilitate implementation of B2B e-commerce in SMEs. Additionally, although previous studies of e-commerce adoption have examined user acceptance, consumer behavior, e-commerce software, investment decision making factors in adopting e-commerce, selection of e-commerce sites by the consumer, the impact of innovation and pricing strategies (Aldin and Stahre, 2003, Basu and Muylle, 2002, Chun and Kim, 2005, Huang et al., 2005, Li and Buhalis, 2006, Liao et al., 2006, Lin and Jou, 2005, Liu et al., 2005, Luarn and Lin, 2005, Poel and Buckinx, 2005, Salmeron and Hurtado, 2006, Sarkis and Talluri, 2004, Shin, 2004, Wu and Hisa, 2004 and Wu and Wang, 2006), few studies have investigated the magnitude of all these factors on B2B e-commerce implementation in SMEs. Thus, elucidating the factors required for successful electronic commerce, particularly in the SME sector, is a worthwhile endeavor. The focus on B2B e-commerce in SMEs has become an increasingly important topic for both researchers and SME managers. The proposed prediction model based on the reciprocal additive consistent fuzzy preference relation (Herrera-Viedma, Herrera, Chiclana, & Luque, 2004) in this study can help organizations identify key factors affecting B2B e-commerce implementation in SMEs and remedial action necessary to ensure successful implementation. The rest of this paper is organized as follows. The following section discusses the reciprocal additive consistent fuzzy preference relation. Section 3 then presents an analytical hierarchy framework based on additive reciprocity transitivity for predicting B2B e-commerce implementation in SMEs. Next, Section 4 introduces an empirical case study of B2B e-commerce implementation in Taiwan SMEs. Finally, a discussion and conclusions are presented in Section 5.

This study surveyed 12 evaluators in a Taiwan steel company as an example to identify their prioritization of the goals and assessment factors discussed above. Based on the opinions of all survey respondents, the following findings were obtained: Analytical results indicate that management support, industry characteristics and government policies are more important than other factors. Meanwhile, the prediction weights for six influential factors affecting probability of failure were: management support (0.413), firm size (0.434), IT integration (0.587), organizational culture (0.469), government policies (0.381) and industry characteristics (0.424). Notably, other than government policies, the probability of failure for all influential factors exceeded 0.4. This analytical result also demonstrates that B2B e-commerce implementation in this company may break down. The company should be more concerned with seeking support from top managers, increasing firm size, improving IT integration and IT sophistication or changing the organizational culture to increase the likelihood of success in implementing B2B e-commerce. The multi-criteria decision-making model for predicting the success of B2B e-commerce implementation presented here is clearly applicable to the evaluation process. The proposed approach is based on the reciprocal additive consistent fuzzy preference relation rather than conventional multiplicative preference relation. Namely, this method considers only n − 1 judgments whereas the traditional analytic hierarchy approach (that is AHP or FAHP) uses View the MathML sourcen(n-1)2 judgments in a preference matrix with n attributes or alternatives. Application of the proposed approach is clearly faster and more efficient than the conventional analytic hierarchy methodologies. This advantage is a key contribution of this study. The findings of this study provide a reference for managers and decision makers considering implementation of B2B e-commerce in small and medium enterprises.