An Evaluation Model of Business Intelligence for Enterprise Systems with Interval-Valued Intuitive Fuzzy ARAS

Jalil Heidary Dahooie (), Hamid Reza Firoozfar and Amir Salar Vanaki

Chapter Chapter 9 in R&D Management in the Knowledge Era, 2019, pp 261-282 from Springer

Abstract: Abstract Due to the growing role of business intelligence (BI) as one of the fundamental components of information system resources as well as the essential requirements for an organization’s success, to assess the intelligence level of enterprise systems among the primary practices of major importance prior to the system implementation. Therefore, this study provides a novel assessment framework of BI for enterprise systems, using an interval-valued intuitive fuzzy ARAS technique. The ARAS is a new method for multiple attribute decision making (MADM) problems. In the proposed model, a number of 34 criteria from the most important BI indexes are identified and, accordingly, five enterprise systems are evaluated through expert discussions. The results reveal that the most important assessment criteria defined by expert panels include visual graph display, dashboard design, capable of data storage, meeting stakeholder needs, and the possibility for detailed realistic analysis. Then, one alternative is defined as the final selection which provides an outstanding performance on the criteria of groupware programs, group decision-making tools, training techniques, data transfer capability, knowledge inference, supporting fuzzy concepts under ambiguity and uncertainty, real-time analytical processing, managing email channels, and achieving stakeholder satisfaction.

Date: 2019
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DOI: 10.1007/978-3-030-15409-7_9

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