A Novel Integrated Provider Selection Multicriteria Model: The BWM-MABAC Model

Dmitri Muravev; Nemanja Mijic

doi:10.31181/dmame2003078m

Authors

Dmitri Muravev School of Naval Architecture, Ocean and Civil Engineering and State Key Laboratory of Ocean Engineering, Shanghai Jiao Tong University, Shanghai, China; Nosov Magnitogorsk State Technical University, Department of Logistics and Transportation Systems Management, Mining Engineering and Transport Institute, Magnitogorsk, Russia
Nemanja Mijic University of defence in Belgrade, Department of logistics, Belgrade, Serbia

DOI:

https://doi.org/10.31181/dmame2003078m

Keywords:

Multicriteria decision-making, BWM, MABAC, MAIRCA, VIKOR, Supply chain

Abstract

The supply chain is a very complex area aimed at obtaining the optimum from the point of view of all participants. In order to achieve the overall optimum and satisfaction of all participants, it is necessary to make an adequate evaluation and selection of providers at the initial stage. In this paper, the selection of providers is based on a new approach in the field of multicriteria decision-making. The weight coefficients were determined using the Best-Worst Method (BWM), whereas provider evaluation and selection were performed using the Multi-Attributive Border Approximation Area Comparison (MABAC) method, which is one of more recent methods in this field. In order to determine the stability of the model and the applicability of the proposed hybrid BWM-MABAC model, the results were compared with the MAIRCA and VIKOR models, and the results of the comparative analysis are presented herein. In addition, a total of 18 different scenarios were formed in the sensitivity analysis, in which the criteria change their original value. At the end of the sensitivity analysis, the statistical dependence of the results was determined using Spearman's correlation coefficient, which confirmed the applicability of the proposed multicriteria approaches.

Downloads

Download data is not yet available.

References

Ahmadi, S., & Amin, S. H. (2019). An integrated chance-constrained stochastic model for a mobile phone closed-loop supply chain network with provider selection. Journal of Cleaner Production, 226, 988-1003.

Alikhani, R., Torabi, S. A., & Altay, N. (2019). Strategic provider selection under sustainability and risk criteria. International Journal of Production Economics, 208, 69-82.

Azadnia, A. H., Saman, M. Z. M., & Wong, K. Y. (2015). Sustainable provider selection and order lot-sizing: an integrated multi-objective decision-making process. International Journal of Production Research, 53(2), 383-408.

Bai, C., & Sarkis, J. (2010). Integrating sustainability into provider selection with grey system and rough set methodologies. International Journal of Production Economics, 124(1), 252–264.

Bai, C., & Sarkis, J. (2011). Evaluating provider development programs with a grey based rough set methodology. Expert Systems with Applications, 38(11), 13505-13517.

Barata, J. F. F., Quelhas, O. L. G., Costa, H. G., Gutierrez, R. H., de Jesus Lameira, V., & Meiriño, M. J. (2014). Multicriteria indicator for sustainability rating in providers of the oil and gas industries in Brazil. Sustainability, 6(3), 1107-1128.

Buyukozkan, G., & Gocer, F. (2017). Application of a new combined intuitionistic fuzzy MCDM approach based on axiomatic design methodology for the provider selection problem. Appl. Soft Comput., 52, 1222-1238.

Chatterjee, K., Pamucar, D., & Zavadskas, E. K. (2018). Evaluating the performance of providers based on using the R'AMATEL-MAIRCA method for green supply chain implementation in electronics industry. Journal of Cleaner Production, 184, 101-129.

Cox, A., & Ireland, P. (2002). Managing construction supply chains: the common sense approach. Engineering Construction and Architectural Management, 9(5‐6), 409-418.

Dai, J., & Blackhurst, J. (2012). A four-phase AHP–QFD approach for provider assessment: a sustainability perspective. International Journal of Production Research, 50(19), 5474-5490.

Dargi, A., Anjomshoae, A., Galankashi, M. R., & Memari, A. (2014). Provider slection: A fuzzy-ANP approach. Proc. Comput. Sci., 31, 691-700.

Das, R., & Shaw, K. (2017). Uncertain supply chain network design considering carbon footprint and social factors using two-stage approach. Clean Technologies and Environmental Policy, 19(10), 2491-2519.

Dobos, I., & Vorosmarty, G. (2019). Inventory-related costs in green provider selection problems with Data Envelopment Analysis (DEA). International Journal of Production Economics, 209, 374-380.

Entezaminia, A., Heydari, M., & Rahmani, D. (2016). A multi-objective model for multi-product multi-site aggregate production planning in a green supply chain: Considering collection and recycling centers. Journal of Manufacturing Systems, 40, 63-75.

Erol, I., Sencer, S., & Sari, R. (2011). A new fuzzy multicriteria framework for measuring sustainability performance of a supply chain. Ecological Economics, 70(6), 1088-1100.

Fallahpour, A., Olugu, E. U., Musa, S. N., Wong, K. Y., & Noori, S. (2017). A decision support model for sustainable provider selection in sustainable supply chain management. Computers & Industrial Engineering, 105, 391-410.

Fashoto, S. G., Akinnuwesi, B., Owolabi, O., & Adelekan, D. (2016). Decision support model for provider selection in healthcare service delivery using analytical hierarchy process artificial neural network. African journal of business Management, 10, 209–232.

Fu, Y. K. (2019). An integrated approach to catering provider selection using AHP-ARAS-MCGP methodology. Journal of Air Transport Management, 75, 164-169.

Gigovic, LJ., Pamučar, D., Božanić, D., & Ljubojević, S. (2017). Application of the GIS-DANP-MABAC multicriteria model for selecting the location of wind farms: A case study of Vojvodina, Serbia. Renewable Energy, 103, 501-521.

Govindan, K., Khodaverdi, R., & Jafarian, A. (2013). A fuzzy multi criteria approach for measuring sustainability performance of a provider based on triple bottom line approach. Journal of Cleaner production, 47, 345-354.

Gupta, A. K., Singh, O. P., & Garg, R. K. (2015). Analytic network process (ANP): An approach for provider selection in an automobile organization. European journal of advances in engineering and technology, 2, 83-89.

Hsu, C. W., Kuo, T. C., Shyu, G. S., & Chen, P. S. (2014). Low carbon provider selection in the hotel industry. Sustainability, 6(5), 2658.

Kuo, T. C., Hsu, C. W., & Li, J. Y. (2015). Developing a green provider selection model by using the DANP with VIKOR. Sustainability, 7(2), 1661.

Kusi-Sarpong, S., Gupta, H., & Sarkis, J. (2018). A supply chain sustainability innovation framework and evaluation methodology. International Journal of Production Research, 1-19.

Lima-Junior, F. R., & Carpinetti, L. C. R. (2016). Combining SCOR model and fuzzy TOPSIS for provider evaluation and management. International Journal of Production Economics, 174, 128-141.

Lin, C. T., Chen, C. B., & Ting, Y. C. (2011). An ERP model for provider selection in electronics industry. Expert Systems With Applications, 38 (3), 1760-1765.

Liu, A., Xiao, Y., Ji, X., Wang, K., Tsai, S. B., Lu, H., & Wang, J. (2018). A Novel Two-Stage Integrated Model for Provider Selection of Green Fresh Product. Sustainability, 10(7), 2371.

Liu, H. C., Quan, M. Y., Li, Z. W., & Wang, Z. L. (2019). A new integrated MCDM model for sustainable provider selection under interval-valued intuitionistic uncertain linguistic environment. Information Sciences, 486, 254-270.

Luthra, S., Govindan, K., Kannan, D., Mangla, S. K., & Garg, C. P. (2017). An integrated framework for sustainable provider selection and evaluation in supply chains. Journal of Cleaner Production, 140, 1686-1698.

Luthra, S., Mangla, S. K., Chan, F. T., & Venkatesh, V. G. (2018). Evaluating the Drivers to Information and Communication Technology for Effective Sustainability Initiatives in Supply Chains. International Journal of Information Technology & Decision-making, 17(01), 311-338.

Memari, A., Dargi, A., Jokar, M. R. A., Ahmad, R., & Rahim, A. R. A. (2019). Sustainable provider selection: A multicriteria intuitionistic fuzzy TOPSIS method. Journal of Manufacturing Systems, 50, 9-24.

Padhi, S. S., Pati, R. K., & Rajeev, A. (2018). Framework for selecting sustainable supply chain processes and industries using an integrated approach. Journal of Cleaner Production, 184, 969-984.

Pamucar D, Stević, Ž., & Sremac, S. (2018a). A New Model for Determining Weight Coefficients of Criteria in MCDM Models: Full Consistency Method (FUCOM). Symmetry, 10(9), 393, 1-22.

Pamucar, D., Badi, I., Korica, S., & Obradović, R. (2018b). A novel approach for the selection of power generation technology using an linguistic neutrosophic combinative distance-based assessment (CODAS) method: A case study in Libya. Energies, 11(9), 2489, 1-25.

Pamucar, D., & Cirovic, G. (2015). The selection of transport and handling resources in logistics centres using Multi-Attributive Border Approximation area Comparison (MABAC), Expert Systems with Applications, 42, 3016- 3028.

Parkouhi, S. V., Ghadikolaei, A. S., & Lajimi, H. F. (2019). Resilient provider selection and segmentation in grey environment. Journal of Cleaner Production, 207, 1123-1137.

Ramanathan, R. (2007). Provider selection problem: Integrating DEA with the approaches of total cost of ownership and AHP. Supply Chain Management: An International Journal, 12(4), 258–261.

Rezaei, J. (2015). Best-worst multicriteria decision-making method. Omega, 53, 49-57.

Rezaei, J., & Haeri, S. A. S. (2019). A grey-based provider selection model for uncertain environments. Journal of Cleaner Production, 221, 768-784.

Rezaei, J., Nispeling, T., Sarkis, J., & Tavasszy, L. (2016). A provider selection life cycle approach integrating traditional and environmental criteria using the best worst method. Journal of Cleaner Production, 135, 577-588.

Rouyendegh, B. D., & Saputro, T. E. (2014). Provider selection using integrated fuzzy TOPSIS and MCGP: A case study. Procedia - Social and Behavioral Sciences, 116, 3957-3970.

Sarkar, S., Lakha, V., Ansari, I., & Maiti, J. (2017). Provider selection in uncertain environment: A fuzzy MCDM approach, in: Proceedings of the First International Conference on Intelligent Computing and Communication, in: Advances in Intelligent Systems and Computing, Springer, Singapore, 257-266.

Soheilirad, S., Govindan, K., Mardani, A., Zavadskas, E. K., Nilashi, M., & Zakuan, N. (2017). Application of data envelopment analysis models in supply chain management: a systematic review and meta-analysis. Annals of Operations Research, 1-55.

Stojicic, M., Kazimieras Zavadskas, E., Pamucar, D., Stevic, Z., Mardani, A. (2019). Application of MCDM Methods in Sustainability Engineering: A Literature Review 2008–2018. Symmetry, 11(3), 350, 1-24.

Su, C. M., Horng, D. J., Tseng, M. L., Chiu, A. S., Wu, K. J., & Chen, H. P. (2016). Improving sustainable supply chain management using a novel hierarchical grey-DEMATEL approach. Journal of Cleaner Production, 134, 469-481.

Validi, S., Bhattacharya, A., & Byrne, P. J. (2014). A case analysis of a sustainable food supply chain distribution system—A multi-objective approach. International Journal of Production Economics, 152, 71-87.

Wu, Y., Ke, Y., Xu, C., & Li, L. (2019). An integrated decision-making model for sustainable photovoltaic module provider selection based on combined weight and cumulative prospect theory. Energy, 181, 1235-1251.

Yu, C., Shao, Y., Wang, K., & Zhang L. (2019). A group decision-making sustainable selection approach using extended TOPSIS under interval-valued Pythagorean fuzzy environment. Expert Systems With Applications, 121, 1-17.

Zavadskas, E. K., Turskis, Z., & Kildienė, S. (2014). State of art surveys of overviews on MCDM/MADM methods. Technological and Economic Development of Economy, 20(1), 165–179.

Zhang, X., Deng, Y., Chan, F. T., & Mahadevan, S. (2015). A fuzzy extended analytic netwoek process-based approach for global provider selection. Application Intelligence, 43 (4), 760-772.

Zhao, H., & Guo, S. (2014). Selecting green provider of thermal power equipment by using a hybrid MCDM method for sustainability. Sustainability, 6(1), 217.

Zhong, L., & Yao, L. (2017). An ELECTRE I-based multicriteria group decision-making method with interval type-2 fuzzy numbers and its application to provider selection. Applied Soft Computing, 57, 556-576.

Zolfani, S. H., Chen, I. S., Rezaeiniya, N., & Tamošaitienė, J. (2012). A hybrid MCDM model encompassing AHP and COPRAS-G methods for selecting company provider in Iran. Technological and economic development of economy, 18(3), 529-543.