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Cause and effect analysis of business intelligence (BI) benefits with fuzzy DEMATEL

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  • Reza Kiani Mavi
  • Craig Standing

Abstract

Business intelligence (BI) is a process in which data collected from disparate sources inside and outside the organisation are combined in order to provide meaningful information for making better and quicker decisions. Many businesses have adopted BI technologies and have obtained significant value from its application, contributing to increased organisational productivity and competitiveness. The aim of this paper is to identify the cause and effect relationship for BI benefits. Fuzzy decision-making trial and evaluation laboratory (fuzzy DEMATEL) technique is applied to diagnose the interrelationships among BI benefits. For this purpose, 10 expert professionals participated in this research. Eighteen BI benefits in four dimensions of organisational benefits, business supplier/partner relation benefits, internal processes efficiency benefits, and customer intelligence benefits are investigated. Findings show that “improved coordination with business partners/suppliers” and “increased revenue” are the highest cause and effect benefits, respectively. This reveals that, better partnership and collaboration with upstream suppliers and downstream customers lead to revenue growth and improved competitiveness. This paper presents insights about the interrelationships among BI value in industrial organisations. The findings will help managers to focus on what causes the benefits related to BI implementation that lead to greater competitive advantage. In addition, it demonstrates that fuzzy DEMATEL is a useful managerial technique when applied to software system evaluation for identifying the critical relationships between benefits.

Suggested Citation

  • Reza Kiani Mavi & Craig Standing, 2018. "Cause and effect analysis of business intelligence (BI) benefits with fuzzy DEMATEL," Knowledge Management Research & Practice, Taylor & Francis Journals, vol. 16(2), pages 245-257, April.
  • Handle: RePEc:taf:tkmrxx:v:16:y:2018:i:2:p:245-257
    DOI: 10.1080/14778238.2018.1451234
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    Cited by:

    1. Tsai, Pei-Hsuan & Kao, Ya-Ling & Tang, Jia-Wei, 2023. "Key factors influencing mass willingness to use CESPs under green concept: ECOCO smart recyclers as a case study," Technological Forecasting and Social Change, Elsevier, vol. 195(C).

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