Structural Modeling in Green Supply Chain Management Practices under Chains of Qualitative Indices

  • Atul Kumar Sahu Department of Mechanical Engineering, National Institute of Technology, Raipur, India
  • Harendra Kumar Narang Department of Mechanical Engineering, National Institute of Technology, Raipur, India
  • Mridul Singh Rajput Department of Mechanical Engineering, National Institute of Technology, Raipur, India
Keywords: Supply Chain Management (SCM), Modeling, Fuzzy Theory, Green Practices, Qualitative Framework

Abstract

The successfully execution of any business is today's dynamic era is possible by integrating the zone of environmental thinking in the business activities. Green Supply Chain Management (GSCM) is a significant view, which needs to be integrated with core business proceedings for the sake of executing sustainable business in today's market life. GSCM is the incorporation of environmental thinking into diverse arena of the Supply Chain Management (SCM). Thus, in this study, the authors presented a framework for modeling GSCM practices by considering the chains of qualitative Indices. The implication of fuzzy sets theory along with DEMATEL (Decision-Making Trial and Evaluation Laboratory) technique under the domain of GSCM is presented in this work. Modeling based on momentous decisive factor responsible for driving the GSCM network is presented in this study. The authors shaped an approach for addressing the green practices under uncertainty and impreciseness for the manufacturing firms. The major intension of the proposed work is to enlarge the views of the researchers and readers towards developing a mathematical framework for implementing GSCM by the concerned firms. An index based on fuzzy information is presented and the computational effort for modeling the green practices is presented, so that the managers can easily understand the proposed work and can model green practices in their decision making.

Downloads

Download data is not yet available.

References

Fallahpour, A., Udoncy Olugu, E., Nurmaya Musa, S., Yew Wong, K.,& Noori, S. (2017). A decision support model for sustainable supplier selection in sustainable supply chain management. Journal ofComputers & Industrial Engineering, 105, 391-410.

Fontela, E., & Gabus, A. (1976). The DEMATEL Observer, DEMATEL 1976 Report. Switzerland, Geneva, Battelle Geneva Research Center.

Hamdan, S.,& Cheaitou, A. (2017). Supplier selection and order allocation with green criteria: An MCDM and multi-objective optimization approach.Computers & Operations Research, 81, 282-304.

Kannan, D., Khodaverdi, R., Olfat, L., Jafarian, A.,& Diabat, A. (2013). Integrated fuzzy multi criteria decision making method and multi-objective programming approach for supplier selection and order allocation in a green supply chain.Journal of Cleaner Production, 47, 355-367.

Keshavarz, G. M., Amiri, M., Zavadskas, E. K., Turskis, Z.,& Antucheviciene, J. (2017). A new multi-criteria model based on interval type-2 fuzzy sets and EDAS method for supplier evaluation and order allocation with environmental considerations. Journal of Computers & Industrial Engineering, 112, 156-174.

Klir, G. J., & Yuan, B. (1995). Fuzzy sets and fuzzylogic: theory and applications.4, Prentice-Hall, Englewood Cliffs.

Kusi-Sarpong, S., Bai, C., Sarkis, J., & Wang, X. (2015). Green supply chain practices evaluation in the mining industry using a joint rough sets and fuzzy TOPSIS methodology.Resources Policy, 46(1), 86-100.

Lee, H. S, Tzeng, G. H, Yeih, W., Wang, Y. J.,& Yang, S. C (2013). Revised DEMATEL: resolving the infeasibility ofDEMATEL.Applied Mathematical Modelling, 37(10-11), 6746–6757.

Leekwijck, V., & Kerre, E. E. (1999). Defuzzification: criteria and classification, Journal of Fuzzy Sets and Systems, 108(2), 159-178.

Malviya, R. K.,& Kant, R., (2016). Hybrid decision making approach to predict and measure the success possibility of green supply chain management implementation.Journal of Cleaner Production, 135, 387-409.

Sahu, A. K., Sahu, A. K., & Sahu, N. K. (2017). Benchmarking of advanced manufacturing machines based on fuzzy-TOPSIS method. In Theoretical and Practical Advancements for Fuzzy System Integration (pp. 309-350). IGI Global.

Sahu A. K., Sahu, N. K.,& Sahu, A. K. (2016a). Application of integrated TOPSIS in ASC index: partners benchmarking perspective.Benchmarking: An International Journal, 23(3), 540-563.

Sahu A. K., Sahu, N. K.,& Sahu, A. K. (2016b). Appraisal of partner enterprises under GTFNS environment in agile SC.International Journal of Decision Support System Technology, 8(3), 1-19.

Sahu A. K., Sahu, N. K.,& Sahu, A. K. (2016c). Application of modified MULTI-MOORA for CNC machine tool evaluation in IVGTFNS environment: an empirical study.International Journal of Computer Aided Engineering and Technology, 8(3), 234–259.

Sahu A. K.,Narang, H. K.,& Rajput, M.S. (2018). A Grey-DEMATEL approach for implicating e-waste management practice: modeling in context of Indian scenario.Grey Systems: Theory and Application,8(1), 84-99.

Sahu, S. K., Datta, S., Patel, S. K.,& Mahapatra. S. S. (2013). Industrial supply chain performance benchmarking using fuzzy grey relation method.Global Journal of Management and Business Studies,3(7), 775-784.

Sari, K. (2017). A novel multi-criteria decision framework for evaluating green supply chain management practices.Computers & Industrial Engineering, 105,338-347.

Tseng, M. L., Lin, R.. J., Lin, Y. H., Chen, R. H.,& Tan, K. (2014). Close-loop or open hierarchical structures in green supply chain management under uncertainty.Expert Systems with Applications, 41(7),3250-3260.

Tzeng, G. H., Chiang, C. H.,& Li, C.W (2007). Evaluating intertwined effects in e-learning programs: a novel hybrid MCDM model based on factor analysis and DEMATEL. Expert Systems with Applications, 32(4),1028–1044.

Wu, W. W.,& Lee, Y. T (2007). Developing global manager’scompetenciesusing the fuzzy DEMATEL method.Expert Systems with Applications, 32(2),499–507.

Yang, J. L., & Tzeng, G. H (2011). An integrated MCDM technique combined with DEMATEL for a novel cluster-weighted with ANP method.Expert Systems with Applications, 38(3), 1417–1424.

Zadeh, L. A. (1965). Fuzzy sets,Information and Control, 8, 338-353.

Zadeh, L. A. (1975). The concept of a linguistic variable and its application to approximate reasoning. Information Sciences, 8(3), 199-249.

Published
2019-03-15
Section
Articles