A Fuzzy-MOORA approach for ERP system selection


Prasad Kar and Shankar Chakraborty


In today’s global and dynamic business environment, manufacturing organizations face the tremendous challenge of expanding markets and meeting the customer expectations. It compels them to lower total cost in the entire supply chain, shorten throughput time, reduce inventory, expand product choice, provide more reliable delivery dates and better customer service, improve quality, and efficiently coordinate demand, supply and production. In order to accomplish these objectives, the manufacturing organizations are turning to enterprise resource planning (ERP) system, which is an enterprise-wide information system to interlace all the necessary business functions, such as product planning, purchasing, inventory control, sales, financial and human resources into a single system having a shared database. Thus to survive in the global competitive environment, implementation of a suitable ERP system is mandatory. However, selecting a wrong ERP system may adversely affect the manufacturing organization’s overall performance. Due to limitations in available resources, complexity of ERP systems and diversity of alternatives, it is often difficult for a manufacturing organization to select and install the most suitable ERP system. In this paper, two ERP system selection problems are solved using fuzzy multi-objective optimization on the basis of ratio analysis (MOORA) method and it is observed that in both the cases, SAP is the best solution.


DOI: j.dsl.2012.07.001

Keywords: ERP system ,MOORA method ,Fuzzy theory ,Triangular membership function

How to cite this paper:

Kar, P & Chakraborty, S. (2012). A Fuzzy-MOORA approach for ERP system selection.Decision Science Letters, 1(1), 11-22.


References

Asgari, M., Allahverdiloo, M., & Samkhani, S. (2011). A comprehensive framework for selecting the ERP system in Iran Khodro company. European Journal of Economics, Finance and Administrative Sciences, 38, 7-19.

Ayağ, Z., & Özdemir, G. (2007). An intelligent approach to ERP software selection through fuzzy ANP. International Journal of Production Research, 45(10), 2169-2194.

Bernroider, E.W.N., & Mitlöhner, J. (2005). Characteristics of the multiple attribute decision making methodology in enterprise resource planning software decisions. Communications of the IIMA, 5(1), 49-58.

Brauers, W.K.M., & Zavadskas, E.K. (2006). The MOORA method and its application to privatization in transition economy. Control and Cybernetics, 35(2), 443-468.

Brauers, W.K.M., Zavadskas, E.K., Peldschus, F., & Turskis, Z. (2008), Multi-objective decision-making for road design. Transport, 23(3), 183-193.

Brauers, W.K.M., Zavadskas, E.K., Turskis, Z., & Vilutiene, T. (2008). Multi-objective contractor’s ranking by applying the MOORA method. Journal of Business Economics and Management, 9(4), 245-255.

Brauers, W.K.M., & Ginevicius, R. (2009). Robustness in regional development studies: The case of Lithuania. Journal of Business Economics and Management, 10(2), 121-140.

Brauers, W.K.M., & Zavadskas, E.K. (2010). Project management by MULTIMOORA as an instrument for transition economies. Technological and Economic Development of Economy, 16(1), 5-24.

Brauers, W.K.M., & Zavadskas, E.K. (2012). Robustness of MULTIMOORA: A method for multi-objective optimization. Informatica, 23(1), 1-25.

Cebeci, U. (2009). Fuzzy AHP-based decision support system for selecting ERP systems in textile industry by using balanced scorecard. Expert Systems with Applications, 36(5), 8900-8909.Chakraborty, S. (2010). Application of the MOORA method for decision making in manufacturing environment. International Journal of Advanced Manufacturing Technology, 54(9-12), 1155-1166.

Forslund, H., & Jonsson, P. (2010). Selection, implementation and use of ERP systems for supply chain performance management. Industrial Management & Data Systems, 110(8), 1159-1175.

Huiqun, H., & Guang, S. (2012). ERP software selection using the rough set and TOPSIS methods under fuzzy environment. Advances in Information Sciences and Service Sciences, 4(3), 111-118.

Karaarslan, N., & Gundogar, E. (2009). An application for modular capability-based ERP software selection using AHP method. International Journal of Advanced Manufacturing Technology, 42(9-10), 1025-1033.

Karsak, E.E., & Özogul, C.O. (2009). An integrated decision making approach for ERP system selection. Expert Systems with Applications, 36(1), 660-667.

Khaled, A., & Idrissi, M.A.J. (2011). A learning driven model for ERP software selection based on the Choquet integral: small and medium enterprises context. In Ariwa, E. and El-Qawasmeh, E. (Eds.): 358-371, Springer-Verlag, Berlin.

Kracka, M., Brauers, W.K.M., & Zavadskas, E.K. (2010). Ranking heating losses in a building by applying the MULTIMOORA. Engineering Economics, 21(4), 352-359.Liang, S-K., & Lien, C-T. (2007). Selecting the optimal ERP software by combining the ISO 9126 standard and fuzzy AHP approach. Contemporary Management Research, 3(1), 23-44.

Liao, X., Li, Y., & Lu, B. (2007). A model for selecting an ERP system based on linguistic information processing. Information Systems, 32(7), 1005-1017.

Lien, C-T., & Liang, S-K. (2005). An ERP system selection model with project management viewpoint – A fuzzy multi-criteria decision-making approach. International Journal of the Information Systems for Logistics and Management, 1(1), 39-46.

Lien, C-T., & Chan, H-L. (2007). A selection model for ERP system by applying fuzzy AHP approach. International Journal of The Computer, the Internet and Management, 15(3), 58-72.

Nazemi, E., Tarokh, M.J., & Djavanshir, G.R. (2012). ERP: A literature survey. International Journal of Advanced Manufacturing Technology, DOI 10.1007/s00170-011-3756-x.

Nikjoo, M.A., Khah, M.M., & Moghimi, A. (2011). Fuzzy TOPSIS and GP application for evaluation and selection of a suitable ERP. Australian Journal of Basic and Applied Sciences, 5(11), 1358-1367.

Onut, S., & Efendigil, T. (2010). A theorical model design for ERP software selection process under the constraints of cost and quality: A fuzzy approach. Journal of Intelligent & Fuzzy Systems, 21(6), 365-378.

Rouyendegh, B.D., & Erkan, T.E. (2011). ERP system selection by AHP method: Case study form Turkey. International Journal of Business and Management Studies, 3(1), 39-48.

Shyur, H-J. (2003). A semi-structured process for ERP systems evaluation: Applying analytic network process. Journal of e-Business, 5(1), 33-49.

Stanujkic, D., Magdalinovic, N., Stojanovic, S., & Jovanovic, R. (2012). Extension of ratio system part of MOORA method for solving decision-making problems with interval data. Informatica, 23(1), 141-154.

Wei, C-C., & Wang, M-J.J. (2004). A comprehensive framework for selecting an ERP system. International Journal of Project Management, 22(2), 161-169.

Wei, C-C., Chien, C-F., & Wang, M-J.J. (2005). An AHP-based approach to ERP system selection. International Journal of Production Economics, 96(1), 47-62.

Yazgan, H.R., Boran, S., & Goztepe, K. (2009). An ERP software selection process with using artificial neural network based on analytic network process approach. Expert Systems with Applications, 36(5), 9214-9222.Zadeh, L.A. (1965). Fuzzy sets. Information and Control, 8(3), 338–353.