Research Article
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Year 2021, Volume: 25 Issue: 4, 885 - 897, 30.08.2021
https://doi.org/10.16984/saufenbilder.877919

Abstract

Supporting Institution

Galatasaray Üniversitesi

References

  • [1] A. L. Radu, M. A. Scrieciu and D. M. Caracota, "Carbon Footprint Analysis: Towards a Projects Evaluation Model for Promoting Sustainable Development,” Procedia Economics and Finance, vol. 6, pp. 353-363, Jan. 2013.
  • [2] H. O. Arslan, C. Cigdemoglu, and C. Moseley, “A three-tier diagnostic test to assess pre-service teachers’ misconceptions about global warming, greenhouse effect, ozone layer depletion, and acid rain,” International Journal of Science Education, vol. 34, no. 11, pp. 1667-1686, 2012.
  • [3] J. Houghton, “Global warming,” Reports on Progress in Physics, vol. 68, no. 6, pp. 1343–1403, Jun. 2005.
  • [4] Intergovernmental panel on climate change (IPCC) Global warming of 1.5 °C [Data accessed: Jul. 2020]. Available: https://www.ipcc.ch/sr15/chapter/spm/
  • [5] J. A. Dearing, R. W. Battarbee, R. Dikau, I. Larocque, and F. Oldfield, “Human–environment interactions: learning from the past,” Regional Environmental Change, vol. 6, pp. 1-16, 2006.
  • [6] A. Zakeri, F. Dehghanian, B. Fahimnia, and J. Sarkis, “Carbon pricing versus emissions trading: A supply chain planning perspective,” International Journal of Production Economics, vol. 164, pp. 197–205, 2015.
  • [7] S. Onut, S. S. Kara, E. Isik, "Long term supplier selection using a combined fuzzy MCDM approach: A case study for a telecommunication company," Expert Systems with Applications, vol. 36, 2009, pp. 3887-3895.
  • [8] M. Stojčić, E. K. Zavadskas, D. Pamučar, Ž. Stević, and A. Mardani, “Application of MCDM methods in sustainability engineering: A literature review 2008–2018,” Symmetry, vol. 11, no. 3, pp. 350, 2019.
  • [9] M. A. M. A. Kermani, H. Navidi, and F. Alborzi, “A novel method for supplier selection by two competitors, including multiple criteria,” International Journal of Computer Integrated Manufacturing, vol. 25, no. 6, pp. 527-535, 2012.
  • [10] R. K. Mavi, M. Goh, and N. Zarbakhshnia, “Sustainable third-party reverse logistic provider selection with fuzzy SWARA and fuzzy MOORA in plastic industry,” The International Journal of Advanced Manufacturing Technology, vol. 91, no. 5, pp. 2401-2418, 2017.
  • [11] S. Tadić, S. Zečević, and M. Krstić, “Assessment of the political city logistics initiatives sustainability,” Transportation research procedia, vol. 30, pp. 285-294, 2018.
  • [12] N. Zarbakhshnia, H. Soleimani, and H. Ghaderi, “Sustainable third-party reverse logistics provider evaluation and selection using fuzzy SWARA and developed fuzzy COPRAS in the presence of risk criteria,” Applied Soft Computing, vol. 65, pp. 307-319, 2018.
  • [13] S. Perçin, “An Integrated Fuzzy SWARA and Fuzzy AD Approach for Outsourcing Provider Selection,” Journal of Manufacturing Technology Management, vol. 30, no. 2, pp. 531-552, 2019.
  • [14] D. Sumrit, “Supplier Selection for Vendor-Managed Inventory in Healthcare Using Fuzzy Multi-Criteria Decision-Making Approach,” Decision Science Letters, vol. 9, no. 2, pp. 233-256, 2020.
  • [15] A. Ulutas, “Using of Fuzzy SWARA and Fuzzy ARAS Methods to Solve Supplier Selection Problem,” Theoretical and Applied Mathematics in International Business, pp. 136-148, 2020.
  • [16] P. Rani, A. R. Mishra, A. Mardani, F. Cavallaro, D. Štreimikienė, and S. A. R. Khan, “Pythagorean Fuzzy SWARA–VIKOR Framework for Performance Evaluation of Solar Panel Selection,” Sustainability, vol. 12, no. 10, pp. 4278, 2020.
  • [17] M. R. Moniri, A. A. Tabriz, A. Ayough, and M. Zandieh, “Turnaround project risk assessment using hybrid fuzzy SWARA and EDAS method: case of upstream oil process industries in Iran,” Journal of Engineering, Design and Technology, 2020.
  • [18] Y. Hu and S. S. Rao, “Game-theory approach for multi-objective optimal design of stationary flat-plate solar collectors,” Engineering Optimization, vol. 41, no. 11, pp. 1017-1035, 2009.
  • [19] C. H. Tan, X. Yang, and H. Xu, “An investigation of the word-processing software market war in South Korea: A game-theoretic approach,” Information & Management, vol. 47, no. 2, pp. 96-101, 2010.
  • [20] F. Peldschus, E. K. Zavadskas, Z. Turskis, and J. Tamosaitiene, “Sustainable Assessment of Construction Site by Applying Game Theory,” Engineering Economics, vol. 21, no. 3, pp. 223-237, 2010.
  • [21] K. Madani and J. R. Lund, “A Monte-Carlo game theoretic approach for multi-criteria decision making under uncertainty,” Advances in water resources, vol. 34, no. 5, pp. 607-616, 2011.
  • [22] M. Medineckiene, E. K. Zavadskas, and Z. Turskis, “Dwelling selection by applying fuzzy game theory,” Archives of civil and mechanical engineering, vol. 11, no. 3, pp. 681-697, 2011.
  • [23] S. H. Zolfani and S. S. A. Banihashemi, “Personnel selection based on a novel model of game theory and MCDM approaches,” Proceeding of 8th International Scientific Conference" Business and Management, pp. 15-16, 2014.
  • [24] M. N. Hindia, A. W. Reza, and K. A. Noordin, “A novel scheduling algorithm based on game theory and multicriteria decision making in LTE network,” International Journal of Distributed Sensor Networks, vol. 11, no. 3, 604752, 2015.
  • [25] S. Hashemkhani Zolfani, R. Maknoon, and E. K. Zavadskas, “Multiple nash equilibriums and evaluation of strategies. New application of MCDM methods,” Journal of Business Economics and Management, vol. 16, no. 2, pp. 290-306, 2015.
  • [26] M. Moradi, M. R. Delavar, and B. Moshiri, “A GIS-based multi-criteria analysis model for earthquake vulnerability assessment using Choquet integral and game theory,” Natural hazards, vol. 87, no. 3, pp. 1377-1398, 2017.
  • [27] A. Debnath, A. Bandyopadhyay, J. Roy, and S. Kar, “Game theory based multi criteria decision making problem under uncertainty: a case study on Indian tea industry,” Journal of Business Economics and Management, vol. 19, no. 1, pp. 154-175, 2018.
  • [28] T. Liu, Y. Deng, and F. Chan, “Evidential supplier selection based on DEMATEL and game theory,” International Journal of Fuzzy Systems, vol. 20, no. 4, pp. 1321-1333, 2018.
  • [29] N. V. Najafi, A. A. Khamseh, and A. Mirzazadeh, “An integrated sustainable and flexible supplier evaluation model under uncertainty by game theory and subjective/objective data: Iranian casting industry,” Global Journal of Flexible Systems Management, vol. 21, no. 4, pp. 309-322, 2020.
  • [30] V. Keršuliene, E. K. Zavadskas, and Z. Turskis, “Selection of Rational Dispute Resolution Method by Applying New Step‐Wise Weight Assessment Ratio Analysis (SWARA),” Journal of Business Economics and Management, vol. 11, no. 2, pp. 243-258, 2010.
  • [31] S. H. Zolfani and J. Saparauskas, “New application of SWARA method in prioritizing sustainability assessment indicators of energy system,” Engineering Economics, vol. 24, no. 5, pp. 408-414, 2013.
  • [32] C. Kahraman, U. Cebeci, and Z. Ulukan, “Multi‐criteria supplier selection using fuzzy AHP,” Logistics information management, vol. 16, no. 6, pp. 382-394, 2003. [33] H. Y. Wu, G. H. Tzeng, Y. H. Chen, “A fuzzy MCDM approach for evaluating banking performance based on Balanced Scorecard,” Expert systems with applications, vol. 36, no. 6, pp. 10135-10147, 2009.
  • [34] J. F. Nash, “Equilibrium points in n-person games,” Proceedings of the national academy of sciences, vol. 36, no. 1, pp. 48-49, 1950.
  • [35] R. Li, H. Ma, F. Wang, Y. Wang, Y. Liu, and Z. Li, “Game optimization theory and application in distribution system expansion planning, including distributed generation,” Energies, vol. 6, no. 2, pp. 1101-1124, 2013.
  • [36] D. Velegol, P. Suhey, J. Connolly, N. Morrissey, and L. Cook, “Chemical game theory,” Industrial & Engineering Chemistry Research, vol. 57, no. 41, pp. 13593-13607, 2018.
  • [37] G. P. Cachon and S. Netessine, “Game theory in supply chain analysis,” Models, methods, and applications for innovative decision making, pp. 200-233, 2006.
  • [38] S. P. H. Heap and Y. Varoufakis, Game Theory: A Critical Text. Routledge, London; New York, 2004. [39] T. Börgers, “Iterated elimination of dominated strategies in a Bertrand-Edgeworth model,” The Review of Economic Studies, vol. 59, no. 1, pp. 163-176, 1992.
  • [40] R. Gibbons, A primer in game theory. Harvester Wheatsheaf New York, 1992.
  • [41] A. Fallahpour, E. U. Olugu, S. N. Musa, K. Y. Wong, and S. Noori, “A decision support model for sustainable supplier selection in sustainable supply chain management,” Computers & Industrial Engineering, vol. 105, pp. 391-410, 2017.
  • [42] S. B. Tsai, Y. M. Wei, K. Y. Chen, L. Xu, P. Du, and H. C. Lee, “Evaluating green suppliers from a green environmental perspective,” Environment and Planning B: Planning and Design, vol. 43, no. 5, pp. 941-959, 2016.
  • [43] A. Liu, Y. Xiao, H. Lu, S. B. Tsai, and W. Song, “A fuzzy three-stage multi-attribute decision-making approach based on customer needs for sustainable supplier selection,” Journal of Cleaner Production, vol. 239, 118043, 2019.
  • [44] A. Ulutaş, A. Topal, A., and R. Bakhat, “An application of fuzzy integrated model in green supplier selection,” Mathematical Problems in Engineering, 2019, 2019.
  • [45] J. Qin, X. Liu, X., and W. Pedrycz, “An extended TODIM multi-criteria group decision making method for green supplier selection in interval type-2 fuzzy environment,” European Journal of Operational Research, vol. 258, no. 2, pp. 626-638, 2017.
  • [46] C. Bai and J. Sarkis, “Integrating sustainability into supplier selection with grey system and rough set methodologies,” International Journal of Production Economics, vol. 124, no. 1, pp. 252-264, 2010.
  • [47] K. Govindan, R. Khodaverdi, and A. Jafarian, “A fuzzy multi criteria approach for measuring sustainability performance of a supplier based on triple bottom line approach,” Journal of Cleaner Production, vol. 47, pp. 345-354, 2013.
  • [48] F. Vahidi, S. A. Torabi, and M. J. Ramezankhani, “Sustainable supplier selection and order allocation under operational and disruption risks,” Journal of Cleaner Production, vol. 174, pp. 1351-1365, 2018.
  • [49] S. A. S. and J. Rezaei, “A grey-based green supplier selection model for uncertain environments,” Journal of cleaner production, vol. 221, pp. 768-784, 2019.
  • [50] A. Awasthi, S. S. Chauhan, and S. K. Goyal, “A fuzzy multicriteria approach for evaluating environmental performance of suppliers,” International Journal of Production Economics, vol. 126, no. 2, pp. 370-378, 2010.
  • [51] L. Shen, L. Olfat, K. Govindan, R. Khodaverdi, and A. Diabat, “A fuzzy multi criteria approach for evaluating green supplier's performance in green supply chain with linguistic preferences,” Resources, Conservation and Recycling, vol. 74, pp. 170-179, 2013.
  • [52] R. Liang and H. Y. Chong, “A hybrid group decision model for green supplier selection: A case study of megaprojects,” Engineering, Construction and Architectural Management, vol. 26, no. 8, pp. 1712-1734, 2019.
  • [53] A. H. Lee, H. Y. Kang, C. F. Hsu, and H. C. Hung, “A green supplier selection model for high-tech industry,” Expert systems with applications, vol. 36, no. 4, pp. 7917-7927, 2009.
  • [54] T. Lee, T. P. N. Le, A. Genovese, and L. S. Koh, “Using FAHP to determine the criteria for partner's selection within a green supply chain,” Journal of Manufacturing Technology Management, vol. 23, no. 1, 25-55,2012.
  • [55] D. Y. Chang, “Applications of the extent analysis method on fuzzy AHP,” European journal of operational research, vol. 95, no. 3, pp. 649-655, 1996.

Green Supplier Selection Using Game Theory Based on Fuzzy SWARA

Year 2021, Volume: 25 Issue: 4, 885 - 897, 30.08.2021
https://doi.org/10.16984/saufenbilder.877919

Abstract

Green supplier selection involves a difficult and complex decision-making process because the criteria have a relationship with each other. Due to conflicts, the selection becomes crucial. Likewise, strategies among alternatives are critical to decide the best one. To overcome these difficulties, multi-criteria decision making methods and game theory approaches are appropriate. In this study, fuzzy SWARA, which is a multicriteria decision making method using fuzzy numbers to express uncertainty, and game theory are integrated to select the best alternative according to the vague opinion of decision makers. As a case study, an application is handled for a chemical company which produces cleaning products in Turkey. The selection occurs between two alternative green suppliers. The strategies of alternative suppliers are evaluated using the fuzzy SWARA method, then game theory aid to evaluate competition of the alternatives.

References

  • [1] A. L. Radu, M. A. Scrieciu and D. M. Caracota, "Carbon Footprint Analysis: Towards a Projects Evaluation Model for Promoting Sustainable Development,” Procedia Economics and Finance, vol. 6, pp. 353-363, Jan. 2013.
  • [2] H. O. Arslan, C. Cigdemoglu, and C. Moseley, “A three-tier diagnostic test to assess pre-service teachers’ misconceptions about global warming, greenhouse effect, ozone layer depletion, and acid rain,” International Journal of Science Education, vol. 34, no. 11, pp. 1667-1686, 2012.
  • [3] J. Houghton, “Global warming,” Reports on Progress in Physics, vol. 68, no. 6, pp. 1343–1403, Jun. 2005.
  • [4] Intergovernmental panel on climate change (IPCC) Global warming of 1.5 °C [Data accessed: Jul. 2020]. Available: https://www.ipcc.ch/sr15/chapter/spm/
  • [5] J. A. Dearing, R. W. Battarbee, R. Dikau, I. Larocque, and F. Oldfield, “Human–environment interactions: learning from the past,” Regional Environmental Change, vol. 6, pp. 1-16, 2006.
  • [6] A. Zakeri, F. Dehghanian, B. Fahimnia, and J. Sarkis, “Carbon pricing versus emissions trading: A supply chain planning perspective,” International Journal of Production Economics, vol. 164, pp. 197–205, 2015.
  • [7] S. Onut, S. S. Kara, E. Isik, "Long term supplier selection using a combined fuzzy MCDM approach: A case study for a telecommunication company," Expert Systems with Applications, vol. 36, 2009, pp. 3887-3895.
  • [8] M. Stojčić, E. K. Zavadskas, D. Pamučar, Ž. Stević, and A. Mardani, “Application of MCDM methods in sustainability engineering: A literature review 2008–2018,” Symmetry, vol. 11, no. 3, pp. 350, 2019.
  • [9] M. A. M. A. Kermani, H. Navidi, and F. Alborzi, “A novel method for supplier selection by two competitors, including multiple criteria,” International Journal of Computer Integrated Manufacturing, vol. 25, no. 6, pp. 527-535, 2012.
  • [10] R. K. Mavi, M. Goh, and N. Zarbakhshnia, “Sustainable third-party reverse logistic provider selection with fuzzy SWARA and fuzzy MOORA in plastic industry,” The International Journal of Advanced Manufacturing Technology, vol. 91, no. 5, pp. 2401-2418, 2017.
  • [11] S. Tadić, S. Zečević, and M. Krstić, “Assessment of the political city logistics initiatives sustainability,” Transportation research procedia, vol. 30, pp. 285-294, 2018.
  • [12] N. Zarbakhshnia, H. Soleimani, and H. Ghaderi, “Sustainable third-party reverse logistics provider evaluation and selection using fuzzy SWARA and developed fuzzy COPRAS in the presence of risk criteria,” Applied Soft Computing, vol. 65, pp. 307-319, 2018.
  • [13] S. Perçin, “An Integrated Fuzzy SWARA and Fuzzy AD Approach for Outsourcing Provider Selection,” Journal of Manufacturing Technology Management, vol. 30, no. 2, pp. 531-552, 2019.
  • [14] D. Sumrit, “Supplier Selection for Vendor-Managed Inventory in Healthcare Using Fuzzy Multi-Criteria Decision-Making Approach,” Decision Science Letters, vol. 9, no. 2, pp. 233-256, 2020.
  • [15] A. Ulutas, “Using of Fuzzy SWARA and Fuzzy ARAS Methods to Solve Supplier Selection Problem,” Theoretical and Applied Mathematics in International Business, pp. 136-148, 2020.
  • [16] P. Rani, A. R. Mishra, A. Mardani, F. Cavallaro, D. Štreimikienė, and S. A. R. Khan, “Pythagorean Fuzzy SWARA–VIKOR Framework for Performance Evaluation of Solar Panel Selection,” Sustainability, vol. 12, no. 10, pp. 4278, 2020.
  • [17] M. R. Moniri, A. A. Tabriz, A. Ayough, and M. Zandieh, “Turnaround project risk assessment using hybrid fuzzy SWARA and EDAS method: case of upstream oil process industries in Iran,” Journal of Engineering, Design and Technology, 2020.
  • [18] Y. Hu and S. S. Rao, “Game-theory approach for multi-objective optimal design of stationary flat-plate solar collectors,” Engineering Optimization, vol. 41, no. 11, pp. 1017-1035, 2009.
  • [19] C. H. Tan, X. Yang, and H. Xu, “An investigation of the word-processing software market war in South Korea: A game-theoretic approach,” Information & Management, vol. 47, no. 2, pp. 96-101, 2010.
  • [20] F. Peldschus, E. K. Zavadskas, Z. Turskis, and J. Tamosaitiene, “Sustainable Assessment of Construction Site by Applying Game Theory,” Engineering Economics, vol. 21, no. 3, pp. 223-237, 2010.
  • [21] K. Madani and J. R. Lund, “A Monte-Carlo game theoretic approach for multi-criteria decision making under uncertainty,” Advances in water resources, vol. 34, no. 5, pp. 607-616, 2011.
  • [22] M. Medineckiene, E. K. Zavadskas, and Z. Turskis, “Dwelling selection by applying fuzzy game theory,” Archives of civil and mechanical engineering, vol. 11, no. 3, pp. 681-697, 2011.
  • [23] S. H. Zolfani and S. S. A. Banihashemi, “Personnel selection based on a novel model of game theory and MCDM approaches,” Proceeding of 8th International Scientific Conference" Business and Management, pp. 15-16, 2014.
  • [24] M. N. Hindia, A. W. Reza, and K. A. Noordin, “A novel scheduling algorithm based on game theory and multicriteria decision making in LTE network,” International Journal of Distributed Sensor Networks, vol. 11, no. 3, 604752, 2015.
  • [25] S. Hashemkhani Zolfani, R. Maknoon, and E. K. Zavadskas, “Multiple nash equilibriums and evaluation of strategies. New application of MCDM methods,” Journal of Business Economics and Management, vol. 16, no. 2, pp. 290-306, 2015.
  • [26] M. Moradi, M. R. Delavar, and B. Moshiri, “A GIS-based multi-criteria analysis model for earthquake vulnerability assessment using Choquet integral and game theory,” Natural hazards, vol. 87, no. 3, pp. 1377-1398, 2017.
  • [27] A. Debnath, A. Bandyopadhyay, J. Roy, and S. Kar, “Game theory based multi criteria decision making problem under uncertainty: a case study on Indian tea industry,” Journal of Business Economics and Management, vol. 19, no. 1, pp. 154-175, 2018.
  • [28] T. Liu, Y. Deng, and F. Chan, “Evidential supplier selection based on DEMATEL and game theory,” International Journal of Fuzzy Systems, vol. 20, no. 4, pp. 1321-1333, 2018.
  • [29] N. V. Najafi, A. A. Khamseh, and A. Mirzazadeh, “An integrated sustainable and flexible supplier evaluation model under uncertainty by game theory and subjective/objective data: Iranian casting industry,” Global Journal of Flexible Systems Management, vol. 21, no. 4, pp. 309-322, 2020.
  • [30] V. Keršuliene, E. K. Zavadskas, and Z. Turskis, “Selection of Rational Dispute Resolution Method by Applying New Step‐Wise Weight Assessment Ratio Analysis (SWARA),” Journal of Business Economics and Management, vol. 11, no. 2, pp. 243-258, 2010.
  • [31] S. H. Zolfani and J. Saparauskas, “New application of SWARA method in prioritizing sustainability assessment indicators of energy system,” Engineering Economics, vol. 24, no. 5, pp. 408-414, 2013.
  • [32] C. Kahraman, U. Cebeci, and Z. Ulukan, “Multi‐criteria supplier selection using fuzzy AHP,” Logistics information management, vol. 16, no. 6, pp. 382-394, 2003. [33] H. Y. Wu, G. H. Tzeng, Y. H. Chen, “A fuzzy MCDM approach for evaluating banking performance based on Balanced Scorecard,” Expert systems with applications, vol. 36, no. 6, pp. 10135-10147, 2009.
  • [34] J. F. Nash, “Equilibrium points in n-person games,” Proceedings of the national academy of sciences, vol. 36, no. 1, pp. 48-49, 1950.
  • [35] R. Li, H. Ma, F. Wang, Y. Wang, Y. Liu, and Z. Li, “Game optimization theory and application in distribution system expansion planning, including distributed generation,” Energies, vol. 6, no. 2, pp. 1101-1124, 2013.
  • [36] D. Velegol, P. Suhey, J. Connolly, N. Morrissey, and L. Cook, “Chemical game theory,” Industrial & Engineering Chemistry Research, vol. 57, no. 41, pp. 13593-13607, 2018.
  • [37] G. P. Cachon and S. Netessine, “Game theory in supply chain analysis,” Models, methods, and applications for innovative decision making, pp. 200-233, 2006.
  • [38] S. P. H. Heap and Y. Varoufakis, Game Theory: A Critical Text. Routledge, London; New York, 2004. [39] T. Börgers, “Iterated elimination of dominated strategies in a Bertrand-Edgeworth model,” The Review of Economic Studies, vol. 59, no. 1, pp. 163-176, 1992.
  • [40] R. Gibbons, A primer in game theory. Harvester Wheatsheaf New York, 1992.
  • [41] A. Fallahpour, E. U. Olugu, S. N. Musa, K. Y. Wong, and S. Noori, “A decision support model for sustainable supplier selection in sustainable supply chain management,” Computers & Industrial Engineering, vol. 105, pp. 391-410, 2017.
  • [42] S. B. Tsai, Y. M. Wei, K. Y. Chen, L. Xu, P. Du, and H. C. Lee, “Evaluating green suppliers from a green environmental perspective,” Environment and Planning B: Planning and Design, vol. 43, no. 5, pp. 941-959, 2016.
  • [43] A. Liu, Y. Xiao, H. Lu, S. B. Tsai, and W. Song, “A fuzzy three-stage multi-attribute decision-making approach based on customer needs for sustainable supplier selection,” Journal of Cleaner Production, vol. 239, 118043, 2019.
  • [44] A. Ulutaş, A. Topal, A., and R. Bakhat, “An application of fuzzy integrated model in green supplier selection,” Mathematical Problems in Engineering, 2019, 2019.
  • [45] J. Qin, X. Liu, X., and W. Pedrycz, “An extended TODIM multi-criteria group decision making method for green supplier selection in interval type-2 fuzzy environment,” European Journal of Operational Research, vol. 258, no. 2, pp. 626-638, 2017.
  • [46] C. Bai and J. Sarkis, “Integrating sustainability into supplier selection with grey system and rough set methodologies,” International Journal of Production Economics, vol. 124, no. 1, pp. 252-264, 2010.
  • [47] K. Govindan, R. Khodaverdi, and A. Jafarian, “A fuzzy multi criteria approach for measuring sustainability performance of a supplier based on triple bottom line approach,” Journal of Cleaner Production, vol. 47, pp. 345-354, 2013.
  • [48] F. Vahidi, S. A. Torabi, and M. J. Ramezankhani, “Sustainable supplier selection and order allocation under operational and disruption risks,” Journal of Cleaner Production, vol. 174, pp. 1351-1365, 2018.
  • [49] S. A. S. and J. Rezaei, “A grey-based green supplier selection model for uncertain environments,” Journal of cleaner production, vol. 221, pp. 768-784, 2019.
  • [50] A. Awasthi, S. S. Chauhan, and S. K. Goyal, “A fuzzy multicriteria approach for evaluating environmental performance of suppliers,” International Journal of Production Economics, vol. 126, no. 2, pp. 370-378, 2010.
  • [51] L. Shen, L. Olfat, K. Govindan, R. Khodaverdi, and A. Diabat, “A fuzzy multi criteria approach for evaluating green supplier's performance in green supply chain with linguistic preferences,” Resources, Conservation and Recycling, vol. 74, pp. 170-179, 2013.
  • [52] R. Liang and H. Y. Chong, “A hybrid group decision model for green supplier selection: A case study of megaprojects,” Engineering, Construction and Architectural Management, vol. 26, no. 8, pp. 1712-1734, 2019.
  • [53] A. H. Lee, H. Y. Kang, C. F. Hsu, and H. C. Hung, “A green supplier selection model for high-tech industry,” Expert systems with applications, vol. 36, no. 4, pp. 7917-7927, 2009.
  • [54] T. Lee, T. P. N. Le, A. Genovese, and L. S. Koh, “Using FAHP to determine the criteria for partner's selection within a green supply chain,” Journal of Manufacturing Technology Management, vol. 23, no. 1, 25-55,2012.
  • [55] D. Y. Chang, “Applications of the extent analysis method on fuzzy AHP,” European journal of operational research, vol. 95, no. 3, pp. 649-655, 1996.
There are 53 citations in total.

Details

Primary Language English
Subjects Engineering, Industrial Engineering
Journal Section Research Articles
Authors

Mehmet Ali Taş 0000-0003-3333-7972

Esra Çakır 0000-0003-4134-7679

Publication Date August 30, 2021
Submission Date February 10, 2021
Acceptance Date June 8, 2021
Published in Issue Year 2021 Volume: 25 Issue: 4

Cite

APA Taş, M. A., & Çakır, E. (2021). Green Supplier Selection Using Game Theory Based on Fuzzy SWARA. Sakarya University Journal of Science, 25(4), 885-897. https://doi.org/10.16984/saufenbilder.877919
AMA Taş MA, Çakır E. Green Supplier Selection Using Game Theory Based on Fuzzy SWARA. SAUJS. August 2021;25(4):885-897. doi:10.16984/saufenbilder.877919
Chicago Taş, Mehmet Ali, and Esra Çakır. “Green Supplier Selection Using Game Theory Based on Fuzzy SWARA”. Sakarya University Journal of Science 25, no. 4 (August 2021): 885-97. https://doi.org/10.16984/saufenbilder.877919.
EndNote Taş MA, Çakır E (August 1, 2021) Green Supplier Selection Using Game Theory Based on Fuzzy SWARA. Sakarya University Journal of Science 25 4 885–897.
IEEE M. A. Taş and E. Çakır, “Green Supplier Selection Using Game Theory Based on Fuzzy SWARA”, SAUJS, vol. 25, no. 4, pp. 885–897, 2021, doi: 10.16984/saufenbilder.877919.
ISNAD Taş, Mehmet Ali - Çakır, Esra. “Green Supplier Selection Using Game Theory Based on Fuzzy SWARA”. Sakarya University Journal of Science 25/4 (August 2021), 885-897. https://doi.org/10.16984/saufenbilder.877919.
JAMA Taş MA, Çakır E. Green Supplier Selection Using Game Theory Based on Fuzzy SWARA. SAUJS. 2021;25:885–897.
MLA Taş, Mehmet Ali and Esra Çakır. “Green Supplier Selection Using Game Theory Based on Fuzzy SWARA”. Sakarya University Journal of Science, vol. 25, no. 4, 2021, pp. 885-97, doi:10.16984/saufenbilder.877919.
Vancouver Taş MA, Çakır E. Green Supplier Selection Using Game Theory Based on Fuzzy SWARA. SAUJS. 2021;25(4):885-97.