System Engineering and Productivity

System Engineering and Productivity

Evaluation and Selection of Sustainable Suppliers by Providing a Decision Support System Based on a New Data Envelopment Analysis Model and Cumulative Star Utility

Document Type : Research Paper

Author
Lecturer, Department of Industrial Engineering, Payame Noor University, Tehran, Iran
Abstract
Decision-making around sustainable supplier selection is a key issue in supply chain management that has become an important goal for Sapco in recent years. The supplier selection problem is considered a decision-making problem due to the consideration of multiple criteria. As a result, some of the most widely used decision-making approaches known in this field can be used to solve these problems. In this regard, considering the importance of the problem, the present study attempts to present a decision support system based on data envelopment analysis and cumulative star utility by studying some decision-making techniques and examining study gaps. The new decision support system uses three steps to evaluate and select suppliers of the problem. In the first step, decision-making indicators and options were extracted by reviewing the research background, interviewing experts, and reviewing documents available in the organization. In the second step, the decision-making options were ranked and efficient units were identified by implementing the data envelopment analysis model. Finally, in the third step, by implementing the cumulative utility star method (UTASTAR), the utility of Sapco's efficient units was determined to select the most desirable supplier. According to the results obtained from the present study, Sapco's suppliers can be evaluated and their utility can be measured, and with a decision support system, the results can be presented with greater confidence for decision-making.

Highlights

  • The issue of choosing a supplier is considered a decision due to the consideration of multiple criteria.
  • The current research studies decision-making techniques.
  • According to the results obtained from the present research, it is possible to evaluate and measure the desirability of Sapco's suppliers.

Keywords
Subjects

Copyright ©, Seyyed Akbar Gholamian

 

License

This article is released under the Creative Commons Attribution (CC BY 4.0) license. Anyone is free to copy, share, translate, and adapt this article for any purpose, whether commercial or non-commercial, as long as proper citation is given to the authors and original publication.

Azadi, M., Jafarian, M., Saen, R. F., & Mirhedayatian, S. M. (2015). A new fuzzy DEA model for evaluation of efficiency and effectiveness of suppliers in sustainable supply chain management context. Computers & operations research54, 274-285. DOI: https://doi.org/10.1016/j.cor.2014.03.002
Bai, C., & Sarkis, J. (2010). Integrating sustainability into supplier selection with grey system and rough set methodologies. International journal of production economics124(1), 252-264. DOI: https://doi.org/10.1016/j.ijpe.2009.11.023
Ballew, P. D., & Schnorbus, R. H. (1994). The impact of the auto industry on the economy. Chicago Fed Letter79, 1-4.
Chaharsooghi, S. K., & Ashrafi, M. (2014). Sustainable supplier performance evaluation and selection with neofuzzy TOPSIS method. International scholarly research notices2014(1), 434168. DOI: https://doi.org/10.1155/2014/434168
Chai, J., Liu, J. N., & Ngai, E. W. (2013). Application of decision-making techniques in supplier selection: A systematic review of literature. Expert systems with applications40(10), 3872-3885. DOI: https://doi.org/10.1016/j.eswa.2012.12.040
Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European journal of operational research2(6), 429-444. DOI:  https://doi.org/10.1016/0377-2217(78)90138-8
Ehsanifar, M., Wood, D. A., & Babaie, A. (2021). UTASTAR method and its application in multi-criteria warehouse location selection. Operations Management Research14, 202-215. DOI: https://doi.org/10.1080/713682767
Handfield, R. B., & Nichols Jr, E. L. (1999). Introduction to. Supply Chain Management, Prentice Hall, Englewood Cliffs, NJ, 1-29.
Izadikhah, M., & Farzipoor Saen, R. (2015). A new data envelopment analysis method for ranking decision making units: an application in industrial parks. Expert Systems32(5), 596-608. DOI: https://doi.org/10.1111/exsy.12112
Jakhar, S. K. (2015). Performance evaluation and a flow allocation decision model for a sustainable supply chain of an apparel industry. Journal of cleaner production87, 391-413. DOI: https://doi.org/10.1016/j.jclepro.2014.09.089
Portela, M. C., & Thanassoulis, E. (2010). Malmquist-type indices in the presence of negative data: An application to bank branches. Journal of banking & Finance34(7), 1472-1483. DOI: https://doi.org/10.1016/j.jbankfin.2010.01.004
Portela, M. S., Thanassoulis, E., & Simpson, G. (2004). Negative data in DEA: A directional distance approach applied to bank branches. Journal of the operational research society55(10), 1111-1121. DOI: https://doi.org/10.1057/palgrave.jors.2601768
Ruggiero, J. (1996). On the measurement of technical efficiency in the public sector. European journal of operational research90(3), 553-565. DOI: https://doi.org/10.1016/0377-2217(94)00346-7
Seuring, S., & Müller, M. (2008). From a literature review to a conceptual framework for sustainable supply chain management. Journal of cleaner production16(15), 1699-1710. DOI: https://doi.org/10.1016/j.jclepro.2008.04.020
Syrjänen, M. J. (2004). Non-discretionary and discretionary factors and scale in data envelopment analysis. European journal of operational research158(1), 20-33. DOI: https://doi.org/10.1016/S0377-2217(03)00362-X