Abstract
In this research, a new method to determine the supply chain performance based on its sustainable strategies is proposed. This method consists of a balanced scorecard, path analysis, and hybrid Shapley value and Multimoora method. The main contribution of this research is to design an intelligent performance evaluation system for different supply chains. In this intelligent performance evaluation method, first, a set of strategies are determined through the balanced scorecard, next, by applying the path analysis method, the best strategic paths are specified, and then the Shapely value of the listed paths is calculated. Among these, five with the highest Shapley value are selected through the hybrid Dematel-based analytical network process and Multimoora method. This method is implemented in the petrochemical supply chain in Iran, and the results are analyzed. This application revealed that the best policy in organizational–operational management optimization is subject to applying this up-to-date technological apparatus at its best. In this approach, the production and delivery time cycle would be reduced. This intelligent system reduces production costs as well. The findings here can be applied in any industry of concern as to improve operations.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Amaratunga, D., Kulatunga, U., Liyanage, C., Bigliardi, B. & Bottani, E. (2010). Performance measurement in the food supply chain: a balanced scorecard approach. Facilities.
Bhagwat, R., & Sharma, M. K. (2007). Performance measurement of supply chain management: A balanced scorecard approach. Computers & Industrial Engineering, 53(1), 43–62.
Cai, J., Liu, X., Xiao, Z., & Liu, J. (2009). Improving supply chain performance management: A systematic approach to analyzing iterative KPI accomplishment. Decision Support Systems, 46(2), 512–521.
Cho, D. W., Lee, Y. H., Ahn, S. H., & Hwang, M. K. (2012). A framework for measuring the performance of service supply chain management. Computers & Industrial Engineering, 62(3), 801–818.
Chomchaiya, S. & Esichaikul, V. (2016). Consolidated performance measurement framework for government e-procurement focusing on internal stakeholders. Information Technology & People.
El-Baz, M. A. (2011). Fuzzy performance measurement of a supply chain in manufacturing companies. Expert Systems with Applications, 38(6), 6681–6688.
Erol, I., Sencer, S., & Sari, R. (2011). A new fuzzy multi-criteria framework for measuring sustainability performance of a supply chain. Ecological Economics, 70(6), 1088–1100.
Fahimnia, B., Sarkis, J., Gunasekaran, A., & Farahani, R. (2017). Decision models for sustainable supply chain design and management. Annals of Operations Research, 250(2), 277–278.
Ganga, G. M. D., Carpinetti, L. C. R., & Politano, P. R. (2011). A fuzzy logic approach to supply chain performance management. Gestão & Produção, 18(4), 755–774.
Gunasekaran, A., Patel, C., & McGaughey, R. E. (2004). A framework for supply chain performance measurement. International Journal of Production Economics, 87(3), 333–347.
Gupta, S., & Tripathi, A. (2020). Performance measurement of micro & small scale enterprises in developingcountries-astudyin Ethiopia. SMART Journal of Business Management Studies, 16(1), 55–63.
Hervani, A.A., Helms, M.M. & Sarkis, J. (2005). Performance measurement for green supply chain management. Benchmarking. An International Journal.
Kazancoglu, Y., Ekinci, E., Mangla, S. K., Sezer, M. D., & Kayikci, Y. (2021). Performance evaluation of reverse logistics in food supply chains in a circular economy using system dynamics. Business Strategy and the Environment, 30(1), 71–91.
Liu, J., Love, P. E., Davis, P. R., Smith, J., & Regan, M. (2015). Conceptual framework for the performance measurement of public-private partnerships. Journal of Infrastructure Systems, 21(1), 04014023.
Min, H., Chia, A., Goh, M. & Hum, S.H. (2009). Performance measurement in supply chain entities: balanced scorecard perspective. Benchmarking An International Journal.
Pasaribu, S. W., Rajagukguk, E., Sitanggang, M., Rahim, R., & Abdillah, L. A. (2018). Implementasi multi-objective optimization On the basis of ratio analysis (MOORA) Untuk Menentukan Kualitas Buah Mangga Terbaik. JURIKOM (jurnal Riset Komputer), 5(1), 50–55.
Petrillo, A., De Felice, F., & Zomparelli, F. (2019). Performance measurement for world-class manufacturing: A model for the Italian automotive industry. Total Quality Management & Business Excellence, 30(7–8), 908–935.
Sainaghi, R., Phillips, P., & Zavarrone, E. (2017). Performance measurement in tourism firms: A content analytical meta-approach. Tourism Management, 59, 36–56.
Sangwa, N.R. & Sangwan, K.S. (2018). Development of an integrated performance measurement framework for lean organizations. Journal of Manufacturing Technology Management.
Sarkis, J., Shaw, S., Grant, D.B. & Mangan, J. (2010). Developing environmental supply chain performance measures. Benchmarking. An International Journal.
Uysal, F. (2012). An integrated model for sustainable performance measurement in supply chain. Procedia-Social and Behavioral Sciences, 62, 689–694.
Van Horenbeek, A., & Pintelon, L. (2014). Development of a maintenance performance measurement framework—using the analytic network process (ANP) for maintenance performance indicator selection. Omega, 42(1), 33–46.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Goli, A., Mohammadi, H. Developing a sustainable operational management system using hybrid Shapley value and Multimoora method: case study petrochemical supply chain. Environ Dev Sustain 24, 10540–10569 (2022). https://doi.org/10.1007/s10668-021-01844-9
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10668-021-01844-9