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A Combined Fuzzy Method for Evaluating Criteria in Enterprise Resource Planning Implementation

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  • Hodjat Hamidi

    (Department of Industrial Engineering, Information Technology Engineering Group, K. N. Toosi University of Technology, Tehran, Iran)

Abstract

Enterprise resource planning (ERP) system is an information system that supports and integrates many facets of a business, sales, and marketing. ERP system success depends on the rigor of the ERP Implementation processes. Scope creep, inadequate allocation of human resources over time, and vendor management are some common problems associated with the implementation of an enterprise system. This paper evaluates critical elements of ERP system that contributed to the success of the ERP implementation. For those organizations adopting ERP, the findings provide a roadmap to follow in order to avoid making critical, ERP Implementation mistakes. In this study, the combined fuzzy method is applied to assess ERP implementation factors. The combined fuzzy method is also capable of taking into consideration both tangible and intangible criteria. This method not only leads to a logical result but also visualizes the impact of various criteria on the final result. Applying the characteristics of dependence and feedback to combined fuzzy method could result in assessments that are more precise than those possible with other multiple criteria decision making approaches. The combined fuzzy method provides a useful assessment approach to this study. The benefits of using the combined fuzzy method for evaluating the ERP implementation come from the clear priority weights between alternatives. Also, a real case study from Iran is also presented to demonstrate efficiency of this method in practice.

Suggested Citation

  • Hodjat Hamidi, 2016. "A Combined Fuzzy Method for Evaluating Criteria in Enterprise Resource Planning Implementation," International Journal of Intelligent Information Technologies (IJIIT), IGI Global, vol. 12(2), pages 25-52, April.
    • Handle: RePEc:igg:jiit00:v:12:y:2016:i:2:p:25-52
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