Spearman & apos; 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.
How to cite this paper
Soloukdar, A & Parpanchi, S. (2015). Comparing fuzzy AHP and fuzzy TOPSIS for evaluation of business intelligence vendors.Decision Science Letters , 4(2), 137-164.
Refrences
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Chan, K. Y., Kwong, C. K., & Dillon, T. S. (2012). An Enhanced Fuzzy AHP Method with Extent Analysis for Determining Importance of Customer Requirements. In Computational Intelligence Techniques for New Product Design, Studies in Computational Intelligence , Springer, 403,79–93.
Chen, C. T., Lin, C. T., & Huang, S. F. (2006). A fuzzy approach for supplier evaluation and selection in supply chain management. International Journal of Production Economics, 102, 289–301.
Cheng, H., Lu, Y., & Sheu, C. (2009). An ontology-based business intelligence application in a financial knowledge management system. Expert Systems with Applications, 36, 3614–3622.
Cooper, W., Seiford, L., Tone, K. (2000). Data Envelopment Analysis. A Comprehensive Text with Models, Applications, References and DEA-Solver Software. Springer.
Csutora, R., & Buckley, J. J. (2001). Fuzzy hierarchical analysis: the Lambda-Max method & apos; s, Fuzzy Sets and Systems, 120(2), 181–95.
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Hastie, T., Tibshirani, R., Friedman, J. (2001). The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Springer.
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Inmon, W. (2005). Building the Data Warehouse. 4th ed., John Wiley & Sons.
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Kaufmann, A., & Gupta, M. (1988). Fuzzy mathematical models in engineering and Management Science. North- Holland Amsterdam.
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Krohling, R. A., & Campanharo, V. C. (2011). Fuzzy TOPSIS for group decision making: A case study for accidents with oil spill in the sea. Expert Systems with Applications, 38(4), 4190–4197.
Kumar, S., Parashar, N., & Haleem, A. (2009). Analytical hierarchy process applied to vendor selection problem: Small scale, medium scale and large scale industries. Business Intelligence Journal. 2(2), 352-362.
Laarhoven, P. J. M., & Pedrycz, W. (1983). A fuzzy extension of Saaty’s priority theory. Fuzzy Sets and Systems, 11, 229–41.
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Liao, C. N., & Kao, H. P. (2011). An integrated fuzzy TOPSIS and MCGP approach to supplier selection in supply chain management. Expert Systems with Applications, 38(9), 10803–10811.
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Bayer, H., Volmer, C., Krauss, A., Stephan, R., & Hein, M. A. (2010, August). Tracking antenna for mobile bi-directional satellite communications in Ka-band. In Wireless Information Technology and Systems (ICWITS), 2010 IEEE International Conference on (pp. 1-4). IEEE.
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Berzal, F., Cubero, J., & Jiménez, A. (2008). The design and use of the TMiner component-based data mining framework. Expert Systems with Applications, 36(4), 7882-7887.
Bolloju, N., Khalifa, M., & Turban E. (2002). Integrating knowledge management into enterprise environments for the next generation decision support. Decision Support Systems, 33, 163–176.
Bose, R. (2009). Advanced analytics: Opportunities and challenges. Industrial Management & Data Systems, 109(2), 155–172.
Br?utigam, D., Gerlach, S., & Miller, G. (2006). Business Intelligence Competency Centers. Hoboken: John Wiley & Sons, Inc.
Bross, M. E. & Zhao, G. (2004). Supplier selection process in emerging markets – The case study of Volvo Bus Corporation in China. School of Economics and Commercial Law, G?teborg University.
Chan, K. Y., Kwong, C. K., & Dillon, T. S. (2012). An Enhanced Fuzzy AHP Method with Extent Analysis for Determining Importance of Customer Requirements. In Computational Intelligence Techniques for New Product Design, Studies in Computational Intelligence , Springer, 403,79–93.
Chen, C. T., Lin, C. T., & Huang, S. F. (2006). A fuzzy approach for supplier evaluation and selection in supply chain management. International Journal of Production Economics, 102, 289–301.
Cheng, H., Lu, Y., & Sheu, C. (2009). An ontology-based business intelligence application in a financial knowledge management system. Expert Systems with Applications, 36, 3614–3622.
Cooper, W., Seiford, L., Tone, K. (2000). Data Envelopment Analysis. A Comprehensive Text with Models, Applications, References and DEA-Solver Software. Springer.
Csutora, R., & Buckley, J. J. (2001). Fuzzy hierarchical analysis: the Lambda-Max method & apos; s, Fuzzy Sets and Systems, 120(2), 181–95.
Desisto, R. P. (2012).Magic Quadrant for Sales Force Automation. Gartner Inc. G00234940.
Donald, R. & Warner, J. R. ( 2007). Effective and Innovative Use of IT Business Intelligence Tools to Reduce Manufacturer & apos; s Warranty Costs. Lawrence Technological University.92 -109.
Dyche, J. (2000). E-data: Turning Data into Information with Data Warehousing. Addison-Wesley.
Evers, M. (2008).An analysis of the requirements for DSS on integrated river basin management. Management of Environmental Quality: An International Journal, 19(1), 37-53.
Falk, T. & Olve, N-G. (1996). IT som en Strategisk Resurs: F?retagsekonomiska Perspektiv och Ledningens Ansvar. Malm?: Liber-Hemonds.
Galasso, F., & Thierry, C. (2009). Design of cooperative processes in a customer supplier relationship: An approach based on simulation and decision theory. Engineering Applications of Artificial Intelligence, 22(6), 865-88.
Gao, S. & Xu, D. (2009). Conceptual modeling and development of an intelligent agent-assisted decision support system for anti-money laundering. Expert Systems with Applications, 36, 1493–1504.
Han, J., Kamber, M. (2005). Data Mining: Concepts and Techniques. Morgan Kaufmann.
Hand, D., Mannila, H., & Smyth, P. (2001). Principles of Data Mining. MIT Press.
Hastie, T., Tibshirani, R., Friedman, J. (2001). The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Springer.
Hedgebeth, D. (2007). Data-driven decision making for the enterprise: An overview of business intelligence applications. The Journal of Information and Knowledge Management Systems, 37(4), 414–420.
Herschel, R.T. & Jones, N.E., (2005). Knowledge management and business intelligence: the importance of integration. Journal of Knowledge Management, 9 (4).45-55
Howson, C. (2008) Successful Business Intelligence: Secrets to Making BI a Killer App, McGraw-Hill.
Hwang, C. L., & Yoon, K. (1981). Multiple Attribute Decision Making: Methods and Applications. Berlin: Springer.
Hypathia Reasearch & Consulting (2009) Business Intelligence: Connectivity Options & Evaluation Criteria for SaaS. Hypatia Research, LLC.
Imhoff, C.(2010). Business Intelligence as a Service: Key Evaluation Criteria for ISVs to Consider. Intelligent Solutions, Inc.
Inmon, W. (2005). Building the Data Warehouse. 4th ed., John Wiley & Sons.
I??k, O. (2010). Business Intelligence Success: An empirical evaluation of the role of BI capabilities and the decision environment (Doctoral dissertation). University Of North Texas.
Kaufmann, A., & Gupta, M. (1988). Fuzzy mathematical models in engineering and Management Science. North- Holland Amsterdam.
Kelemenis, A., Ergazakis, K., & Askounis, D. (2011). Support managers’ selection using an extension of fuzzy TOPSIS. Expert Systems with Applications, 38(3), 2774–2782.
Kimball, R., Thornthwaite W., Reeves L., & Ross, M. (1998). The Data Warehouse Lifecycle Toolkit . Wiley.
Kimball, R., & Ross, M. (2002). The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling. Wiley.
Krohling, R. A., & Campanharo, V. C. (2011). Fuzzy TOPSIS for group decision making: A case study for accidents with oil spill in the sea. Expert Systems with Applications, 38(4), 4190–4197.
Kumar, S., Parashar, N., & Haleem, A. (2009). Analytical hierarchy process applied to vendor selection problem: Small scale, medium scale and large scale industries. Business Intelligence Journal. 2(2), 352-362.
Laarhoven, P. J. M., & Pedrycz, W. (1983). A fuzzy extension of Saaty’s priority theory. Fuzzy Sets and Systems, 11, 229–41.
Lau, H. C. W., Ning, A., Ip, W. H., & Choy, K. L. (2004). A decision support system to facilitate resources allocation: An OLAP-based neural network approach. Journal of Manufacturing Technology Management, 15(8), 771–778.
Lee, C. K. M., Lau, H. C. W., Hob, G. T. S., & Ho, W. (2009). Design and development of agent-based procurement system to enhance business intelligence. Expert Systems with Applications, 36, 877–884.
Leung, L. C., & Cao, D. (2000). On consistency and ranking of alternatives in fuzzy AHP. European Journal of Operational Research, 124(1), 102–113.
Liao, C. N., & Kao, H. P. (2011). An integrated fuzzy TOPSIS and MCGP approach to supplier selection in supply chain management. Expert Systems with Applications, 38(9), 10803–10811.
Lin, M. C., Wang, C. C., Chen, M. S., & Chang, C. A. (2008). Using AHP and TOPSIS approaches in customer-driven product design process. Computers in Industry, 59, 17–31.
Lin, Y., Tsai, K., Shiang, W., Kuo, T., & Tsai, C. (2009). Research on using ANP to establish a performance assessment model for business intelligence systems. Expert Systems with Applications, 36, 4135–4146.
Macgllivray, A. E. (2000). Using Business Intelligence (Information Technology) Tools To Facilitate Front-Line-Priority- Setting In A Public Sector Organization. Royal Roads University. 5-15.
Malone, T., Crowston, K., & Herman A. (2003). Organizing Business Knowledge: The MIT Process Handbook. The MIT Press.
Mojdeh, S. (2007) Business Intelligence Vendor Selection Based on BI Life Cycle: A Fuzzy AHP Approach A Case Study in IranKhodro Automobile Manufacturing Co. The Third National Conference on Performance Management, 15 -16.
Moss, T. M., & S. Atre, S. (2003). Business Intelligence Roadmap: The Complete Project Lifecycle for Decision-Support Applications. Addison-Wesley Professional.
Naimuzzaman, M. D. (2009). Dynamic Report Views Implementation of Business Intelligence and Reporting Tools. Department of Computer Science and Engineering Chambers, University of Gothenburg. 15-34.
Nemati, H., Steiger, D., Iyer, L., & Herschel, R. (2002). Knowledge warehouse: an architectural integration of knowledge management, decision support, artificial intelligence and data warehousing. Decision Support Systems, 33, 143–161.
Opricovic, S. & Tzeng, G. H. (2003). Defuzzification within a multicriteria decision model. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 11(5), 635–652.
Pagels-Fick, G. (2000). Business Intelligence, Om Organization, metorder och till?mpning. Katrineholm: Industrilitteratur AB.
Pirttim?ki, V., & Hannula, M. (2003). Process models of business intelligence. Frontiers of E-Business Research, 250-260.
Power, D., & Sharda, R. (2007). Model-driven decision support systems: Concepts and research directions. Decision Support Systems, 43, 1044–1061.
Pyle, D. (2003). Business Modeling and Data Mining. Morgan Kaufmann.
Qian-cheng, Y. (2007). Metadata management plan research in business intelligence system. Computer Knowledge and Technology (Academic Exchange), 22.
Ranjan, J. (2009). Business intelligence: Concepts, components, techniques and benefits. Journal of Theoretical and Applied Information Technology, 9(1).
Reich, Y., & Kapeliuk, A. (2005). A framework for organizing the space of decision problems with application to solving subjective, context-dependent problems Decision Support Systems, 41, 1–19.
Rezaie, K. , Ansarinejad, A., Haeri, A., & Nazari-Shirkouhi, A. (2011).Evaluating the Business Intelligence Systems Performance Criteria Using Group Fuzzy AHP Approach, UKSim 13th International Conference on Modeling and Simulation, 360-364.
Rivest, S., Bédard, Y., Proulx, M.-J., Nadeau, M., Hubert, F. & Pastor, J. (2005). SOLAP technology: Merging business intelligence with geospatial technology for interactive spatio-temporal exploration and analysis of data. Journal of Photogrammetry and Remote Sensing (ISPRS), 60, 17 - 33.
Rouhani, S., Ghazanfari, M., & Jafari, M. (2012). Evaluation model of business intelligence for enterprise systems using fuzzy TOPSIS. Expert Systems with Applications. 39(3), 3764-3771.
Saadi, S. (2012). Survey on Business Intelligence Softwares. The Fifth Conference of Electronic Administrative System.
Saaty, T. L. (1990). An exposition of the AHP in reply to the paper: Remarks on the analytic hierarchy process. Management Science, 36(3), 259–268.
Sabanovic, A. (2008). Business Intelligence Software Customer & apos; s Understanding, Expectations and Needs. University of Kristianstad. 25.
Sas Institute Inc (2004). How to Select a Business Intelligence Vendor.
Shaw, K., Shankar, R., Yadav, S. S., & Thakur, L. S. (2012). Supplier selection using fuzzy AHP and fuzzy multi-objective linear programming for developing low carbon supply chain. Expert Systems with Applications. 39(9), 8182-8192
Shi, Z., Huang, Y., He, Q., Xu, L., Liu, S., Qin, L., Jia, Z., Li, J., Huang, H., & Zhao, L. (2007). MSMiner—A developing platform for OLAP. Decision Support Systems, 42(4), 2016–2028.
Shmueli, G., Patel, N. R., & Bruce, P. C. (2010). Data Mining for Business Intelligence: Concepts, Techniques, and Applications in Microsof Office Excel with XLMiner. John Wiley and Sons.
Solberg S?ilen, K. (2008). Management implementation of Business Intelligence Systems. Hammamet 14 – 16 February: 1st International Conference on Information System and Economic Intelligence SIIE?2008.
Stackowiak, R., Rayman, J., & Greenwald, R. (2007). Oracle data warehousing and business intelligence solutions. Hoboken, N.J: Wiley.
Stair, R.M., & Reynolds, G.W. (2011) Fundamentals of Information Systems, 6th ed., USA: Cengage Learning.
Stipic, A., & Bronzin, T. (2011). Mobile BI: The past, the present and the future. MIPRO, 2011 Proceedings of the 34th International Convention, 1560 – 1564.
Tan, X., Yen, D.C., & Fang, X. (2003). Web warehousing: Web technology meets data warehousing. Technology in Society, 25(1), 131–148.
Tesfamariam, S., & Sadiq, R. (2006). Risk-based environmental decision-making using fuzzy analytic hierarchy process (F-AHP). Stochastic Environmental Research and Risk Assessment, 21(1), 35–50.
Thanassoulis, E. (2001). Introduction to the theory and application of data envelopment analysis: A foundation text with integrated software. Norwell, Mass: Kluwer Academic Publishers.
Torlak, G., Sevkli, M., Sanal, M., & Zaim, S. (2011). Analyzing business competition by using fuzzy TOPSIS method: An example of Turkish domestic airline industry. Expert Systems with Applications, 38(4), 3396–3406.
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