Comparing fuzzy AHP and fuzzy TOPSIS for evaluation of business intelligence vendors

Alireza Soloukdar,Seyedeh Akram Parpanchi

doi:10.5267/j.dsl.2015.1.002

Abstract

Article history: Received July 10, 2014 Accepted December 31, 2014 Available online January 3 2015 The main objective of this study is to identify the most important criteria and indicators in selection of business intelligence vendors, and ranking the vendors of such tools using Fuzzy Analytical hierarchy Process (FAHP) and Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS), to compare results of these two methods and to provide appropriate solutions for the sample company, namely National Iranian Oil Company (NIOC). Spearman's rank correlation test was used for comparing the methods and determining their correlation. A strong positive correlation was observed between the ranks of business intelligence tools at the significance level of 0.05 in both methods. The results of the ranking by means of FAHP method show that IBM Company was the best one, followed by Oracle, SAS, QlikTech, SAP and Microsoft. However, based on the FTOPSIS method, Oracle was the leading company, followed by IBM, SAS and SAP and finally Microsoft. . Growing Science Ltd. All rights reserved 5 © 201

Highlights

Business intelligence (BI) is an IT approach that assists many organizations in making accurate and timely decisions, improving supervision process to provide better support for their own operational activities, strategic and tactical planning, and forecasting and analyzing market segments
The same organizations unintentionally call a small portion of some systems as “business intelligence systems”, such as customer relationship management (CRM) and knowledge management that focuse exclusively on clients and knowledge, while a business intelligence system mainly deals with the data (Solberg Soilen, 2008)
For evaluation of criteria and sub-criteria and alternatives of business intelligence vendors, fuzzy TOPSIS method was used according to the following steps

Summary

Introduction

Business intelligence (BI) is an IT approach that assists many organizations in making accurate and timely decisions, improving supervision process to provide better support for their own operational activities, strategic and tactical planning, and forecasting and analyzing market segments. Substantial increase in value of business, better decision-making and high returns on investment are only some of the arguments offered by its vendors. Because of such promises, many organizations have invested in business intelligence. The current picture of business intelligence is a multifaceted concept, which may include processes, techniques and tools to support better and faster decision-making (Pirttimak & Hannula, 2003). Some firms are using business intelligence tools or solutions, but under various names such as management information systems (MIS), decision support systems (DSS), executive information systems (EIS), and so on (Pagels-Fick, 2000). The same organizations unintentionally call a small portion of some systems as “business intelligence systems”, such as customer relationship management (CRM) and knowledge management that focuse exclusively on clients and knowledge, while a business intelligence system mainly deals with the data (Solberg Soilen, 2008)

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Conclusion