An MCDM Framework for Assessing ISPs: The Fuzzy Synthesis Decisions of Additive and Non-Additive Measurements

10.6382/JIM.200201.0175

Tzung-I Tang；Daniel Y. Shee；Gwo-Hshiung Tzeng

Information Service Provider ISP ； Electronic Commerce EC ； Multiple Criteria Decision Making MCDM ； Analytic Hierarchy Process AHP ； Fuzzy Measure ； Fuzzy Integral

資訊管理學報

8卷2期（2002 / 01 / 01）

175 - 192

英文

During the early years of their establishment, information service providers (ISPs) were viewed simply as 'suppliers of information'. Nowadays, however, the commercialization of the Internet coupled with the progressive advancements in information technology (IT) have seen the business paradigm evolve into so-called electronic commerce (EC), with the result of an ever-increasing demand from enterprises for new types of information services (IS) to facilitate and coordinate their daily operations. Now, as the role of the ISP is continually changing, and the content of IS becomes ever broader, an effective means of the assessment of ISPs has become a critical issue in any enterprise's decision on the eventual selection of a competent ISP. Hence, the purpose of this paper is to establish a multiple criteria decision-making (MCDM) framework for assessing and evaluating ISPs. Through a review of the literature of previous works on relevant topics, this paper begins by proposing a hierarchy structure for the problems involved in ISP assessment. Based on the hierarchy structure, both additive (analytic hierarchy process) and non-additive (fuzzy measure and fuzzy integral) MCDM methods are used in this study to show the relative importance of the selection criteria and the dimensions of those criteria. Ten real cases are then employed as illustrative alternatives to demonstrate the synthesis decisions under the application of both MCDM methods, so as to show the applicability of the framework. Finally, we find that there is a distinction between the results of alternative rankings produced by the two MCDM methods, thus the ten alternatives are categorized into four groups.

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