Accurately predicting the success of B2B e-commerce in small and medium enterprises |
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| Authors: | Tien-Chin Wang Ying-Ling Lin |
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| Affiliation: | 1. Department of Information Management, I-Shou University, 1, Section 1, Hsueh-Cheng Road, Ta-Hsu, Kaohsiung County 840, Taiwan;2. Department of Information Engineering, I-Shou University, 1, Section 1, Hsueh-Cheng Road, Ta-Hsu, Kaohsiung County 840, Taiwan;1. School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, PR China;2. State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences, Beijing 100190, PR China;1. South Tehran Branch – Islamic Azad University, Faculty of Management and Accounting, Department of Information Technology Management, Shariati Ave., Tehran, Iran;2. South Tehran Branch – Islamic Azad University, Tehran, Iran;1. School of Information, Systems and Modelling, Faculty of Engineering and IT, University of Technology Sydney (UTS), Australia;2. Centre for Artificial Intelligence, Faculty of Engineering and IT, University of Technology Sydney (UTS), Australia;3. School of Computing, University of Jaen, Jaen, Spain;1. School of Business, Jadara University, 733, Irbid, Jordan;2. School of Accountancy, Universiti Utara Malaysia, 06010, UUM, Kedah, Malaysia;3. Othman Yeop Abdullah Graduate School of Business, Universiti Utara Malaysia, 06010, UUM, Kedah, Malaysia;1. Department of Information Technology Management, Academic Institute of Mizan, Tabriz, Iran;2. Department of Computer Engineering, Tabriz Branch, Islamic Azad University, Tabriz, Iran |
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| Abstract: | 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. |
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