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Employing fuzzy DEA for Green-resilient supplier selection in an electronic industry of household appliances: a case study (Snowa)

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Abstract

The choice of green-resilient supplier selection as a complex multi-criterion decision-making problem that often involves some uncertain situations, has become a key issue in the development of electronics manufacturing. Decision-making models supporting the assessment of supply chain performance must consider comprehensive elements in the supply network, covering not only cost and technical capabilities, but also greenness and resilience aspects. Therefore, in order to fill the research gap, the present study proposed an integrated decision-making method based on the fuzzy set theory and data envelopment analysis (DEA) approach for supplier selection in a supply chain network to handle uncertainties caused by decision makers ‘subjective judgments which could reduce the supply chain costs and environmental impact and, moreover, extend the value of resilience. A case study was used to validate the applicability of the proposed model. The sensitivity analysis was employed to examine the impact of the proposed model. Furthermore, the proposed DEA-based model has been compared with a supplier selection Fuzzy inference system based method in the literature to show its validation. The results indicated the proposed fuzzy DEA method can provide a reliable and consensus decision-making framework for enterprises to select green-resilient suppliers in the electronic industry of household appliances.

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References

  1. Zeng, X., Yang, C., Chiang, J.F., Li, J.: Innovating e-waste management: from macroscopic to microscopic scales. Sci. Total. Environ. 575, 1–5 (2017)

    Article  Google Scholar 

  2. Bosch, A.C., O’Neill, B., Sigge, G.O., Kerwath, S.E., Hoffman, L.C.: Heavy metals in marine fish meat and consumer health: a review. J. Sci. Food Agric. 96(1), 32–48 (2016)

    Article  Google Scholar 

  3. Kao, C.: Efficiency decomposition in network data envelopment analysis: a relational model. Eur. J. Oper. Res. 192(3), 949–962 (2009)

    Article  Google Scholar 

  4. Moon, H., Min, D.: Assessing energy efficiency and the related policy implications for energy-intensive firms in Korea: DEA approach. Energy 133, 23–34 (2017)

    Article  Google Scholar 

  5. Haldar, M., Kohyama, M., So, A.Y., Wumesh, K.C., Wu, X., Briseño, C.G., Satpathy, A.T., Kretzer, N.M., Arase, H., Rajasekaran, N.S., Wang, L.: Heme-mediated SPI-C induction promotes monocyte differentiation into iron-recycling macrophages. Cell 156(6), 1223–1234 (2014)

    Article  Google Scholar 

  6. Melnyk, S.A., Bititci, U., Platts, K., Tobias, J., Andersen, B.: Is performance measurement and management fit for the future? Manag. Account. Res. 25(2), 173–186 (2014)

    Article  Google Scholar 

  7. Brandon-Jones, E., Squire, B., Autry, C.W., Petersen, K.J.: A contingent resource-based perspective of supply chain resilience and robustness. J. Supply Chain Manag. 50(3), 55–73 (2014)

    Article  Google Scholar 

  8. Sheffi, Y., Rice, J.B., Jr.: A supply chain view of the resilient enterprise. MIT Sloan Manag. Rev. 47(1), 41 (2005)

    Google Scholar 

  9. **ong, L., Zhong, S., Liu, S., Zhang, X., Li, Y.: An approach for resilient-green supplier selection based on WASPAS, BWM, and TOPSIS under intuitionistic fuzzy sets. Math. Probl. Eng. (2020). https://doi.org/10.1155/2020/1761893

    Article  Google Scholar 

  10. Sarkis, J., Talluri, S.: A model for strategic supplier selection. J. Supply Chain Manag. 38(4), 18–28 (2002)

    Article  Google Scholar 

  11. Chai, X.J., Castañón, A.N., Öngür, D., Whitfield-Gabrieli, S.: Anticorrelations in resting state networks without global signal regression. Neuroimage 59(2), 1420–1428 (2012)

    Article  Google Scholar 

  12. Ho, W., Xu, X., Dey, P.K.: Multi-criterion decision making approaches for supplier evaluation and selection: a literature review. Eur. J. Operational Res. 202(1), 16–24 (2010)

    Article  Google Scholar 

  13. Bai, C., Sarkis, J.: Green supplier development: analytical evaluation using rough set theory. J. Clean. Prod. 18(12), 1200–1210 (2010)

    Article  Google Scholar 

  14. Rajesh, R., Ravi, V.: Supplier selection in resilient supply chains: a grey relational analysis approach. J. Clean. Prod. 86, 343–359 (2015)

    Article  Google Scholar 

  15. Wang, T.K., Zhang, Q., Chong, H.Y., Wang, X.: Integrated supplier selection framework in a resilient construction supply chain: An approach via analytic hierarchy process (AHP) and grey relational analysis (GRA). Sustainability. 9(2), 289 (2017)

    Article  Google Scholar 

  16. Torabi, S.A., Baghersad, M., Mansouri, S.A.: Resilient supplier selection and order allocation under operational and disruption risks. Transp. Res. Part E. Logist. Transp. Rev. 79, 22–48 (2015)

    Article  Google Scholar 

  17. Sawik, T.: Selection of resilient supply portfolio under disruption risks. Omega 41(2), 259–269 (2013)

    Article  Google Scholar 

  18. Foroozesh, N., Tavakkoli-Moghaddam, R., Mousavi, S.M., Vahdani, B.: A new comprehensive possibilistic group decision approach for resilient supplier selection with mean–variance–skewness–kurtosis and asymmetric information under interval-valued fuzzy uncertainty. Neural Comput. Appl. 31(11), 6959–6979 (2019)

    Article  Google Scholar 

  19. Abedian, M., Saghafinia, A., Hejazi, M.: A fuzzy analysis approach to green-resilient supplier selection in electronic manufacturing systems. Cybern. Syst. 19, 1–27 (2022)

    Google Scholar 

  20. Elleuch, H., Dafaoui, E., Elmhamedi, A., Chabchoub, H.: Resilience and vulnerability in supply chain: literature review. IFAC-PapersOnLine. 49(12), 1448–1453 (2016)

    Article  Google Scholar 

  21. Louzada, F., Ara, A., Fernandes, G.B.: Classification methods applied to credit scoring: Systematic review and overall comparison. Surv. Operations Res. Manag. Sci. 21(2), 117–134 (2016)

    Article  Google Scholar 

  22. Banasik, A., Bloemhof-Ruwaard, J.M., Kanellopoulos, A., Claassen, G.D., van der Vorst, J.G.: Multi-criterion decision making approaches for green supply chains: a review. Flex. Serv. Manuf. J. 30(3), 366–396 (2018)

    Article  Google Scholar 

  23. Khoshnava, S.M., Rostami, R., Valipour, A., Ismail, M., Rahmat, A.R.: Rank of green building material criteria based on the three pillars of sustainability using the hybrid multi criteria decision making method. J. Clean. Prod. 173, 82–99 (2018)

    Article  Google Scholar 

  24. Fallahpour, A., Olugu, E.U., Musa, S.N., Khezrimotlagh, D., Wong, K.Y.: An integrated model for green supplier selection under fuzzy environment: application of data envelopment analysis and genetic programming approach. Neural Comput. Appl. 27(3), 707–725 (2016)

    Article  Google Scholar 

  25. Azadeh, A., Abdollahi, M., Farahani, M.H., Soufi, H.R.: Green-resilient supplier selection: an integrated approach. InInternational IEEE Conference, (Vol. 26). Istanbul july 2014

  26. Mohammed, A., Harris, I., Soroka, A., Naim, M.M., Ramjaun, T.: Evaluating green and resilient supplier performance: AHP-fuzzy topsis decision-making approach. InICORES, pp. 209–216 (2018)

  27. Gupta, R., Biswas, I., Mohanty, B.K., Kumar, S.: Performance of three-echelon supply chain under uncertainty: influence of contract sequence and individual rationality. Benchmarking: an International Journal. (2022)

  28. Tsai, C.K., Phumchusri, N.: Fuzzy analytical hierarchy process for supplier selection: a case study in an electronic component manufacturer. Eng. J. 25(8), 73–86 (2021)

    Article  Google Scholar 

  29. Chen, A., Hsieh, C.Y., Wee, H.M.: A resilient global supplier selection strategy—a case study of an automotive company. Int. J. of Adv. Manuf. Technol. 87(5), 1475–1490 (2016)

    Article  Google Scholar 

  30. Song, M., Fisher, R., Kwoh, Y.: Technological challenges of green innovation and sustainable resource management with large scale data. Technol. Forecast. Soc. Chang. 144, 361–368 (2019)

    Article  Google Scholar 

  31. Li, S., He, Y.: Compensation and information disclosure strategies of a green supply chain under production disruption. J. Clean. Prod. 281, 124851 (2021)

    Article  Google Scholar 

  32. Li, W., **, Y., Liu, S.Q., Li, M., Chen, L., Wu, X., Zhu, S., Masoud, M.: An improved evaluation framework for industrial green development: considering the underlying conditions. Ecol. Ind. 112, 106044 (2020)

    Article  Google Scholar 

  33. Raeesi, R., Ghasemi Varnamkhasti, E., Saeidi, S.N., Kouhbor, M.A.: Green productivity in Iran’s thermal power plants: the Malmquist–Luenberger approach. Environ. Energy Econ. Res. 4(1), 1–3 (2020)

    Google Scholar 

  34. Khan, S.A., Sharif, A., Golpîra, H., Kumar, A.: A green ideology in Asian emerging economies: from environmental policy and sustainable development. Sustain. Dev. 27(6), 1063–1075 (2019)

    Article  Google Scholar 

  35. Chiou, C.Y., Hsu, C.W., Hwang, W.Y.: Comparative investigation on green supplier selection of the American, Japanese and Taiwanese electronics industry in China. In2008 IEEE international conference on industrial engineering and engineering management. pp. 1909–1914. IEEE (2008)

  36. Geng, Z., Zeng, R., Han, Y., Zhong, Y., Fu, H.: Energy efficiency evaluation and energy saving based on DEA integrated affinity propagation clustering: Case study of complex petrochemical industries. Energy 179, 863–875 (2019)

    Article  Google Scholar 

  37. Li, X., Bi, F., Han, Z., Qin, Y., Wang, H., Wu, W.: Garbage source classification performance, impact factor, and management strategy in rural areas of China: a case study in Hangzhou. Waste Manage. 89, 313–321 (2019)

    Article  Google Scholar 

  38. Feng, L., Cheng, L., Dong, Z., Tao, D., Barnhart, T.E., Cai, W., Chen, M., Liu, Z.: Theranostic liposomes with hypoxia-activated prodrug to effectively destruct hypoxic tumors post-photodynamic therapy. ACS Nano 11(1), 927–937 (2017)

    Article  Google Scholar 

  39. Zhang, X., **ng, X.: Probabilistic linguistic VIKOR method to evaluate green supply chain initiatives. Sustainability. 9(7), 1231 (2017)

    Article  Google Scholar 

  40. Hoejmose, S.U., Grosvold, J., Millington, A.: The effect of institutional pressure on cooperative and coercive ‘green’supply chain practices. J. Purch. Supply Manag. 20(4), 215–224 (2014)

    Article  Google Scholar 

  41. Zhou, W., Su, D., Yang, J., Tao, D., Sohn, D.: When do strategic orientations matter to innovation performance of green-tech ventures? The moderating effects of network positions. J. Clean. Prod. 279, 123743 (2021)

    Article  Google Scholar 

  42. Gupta, R., Biswas, I., Kumar, S.: Pricing decisions for three-echelon supply chain with advertising and quality effort-dependent fuzzy demand. Int. J. Prod. Res. 57(9), 2715–2731 (2019)

    Article  Google Scholar 

  43. Zhou, W., Su, D., Yang, J., Tao, D., Sohn, D.: When do strategic orientations matter to innovation performance of green-tech ventures? The moderating effects of network positions. J. Clean. Prod. 10(279), 123743 (2021)

    Article  Google Scholar 

  44. Park, Y.S., Egilmez, G., Kucukvar, M.: Emergy and end-point impact assessment of agricultural and food production in the United States: A supply chain-linked Ecologically-based Life Cycle Assessment. Ecol. Ind. 62, 117–137 (2016)

    Article  Google Scholar 

  45. HakimiAsl, M., Amalnick, M.S., Zorriassatine, F., HakimiAsl, A.: Green supplier evaluation by using an integrated fuzzy AHP-VIKOR approach. Int. J. Supply Operations Manag. 3(2), 1284–1300 (2016)

    Google Scholar 

  46. Han, Y., Geng, Z., Zhu, Q., Qu, Y.: Energy efficiency analysis method based on fuzzy DEA cross-model for ethylene production systems in chemical industry. Energy 83, 685–695 (2015)

    Article  Google Scholar 

  47. **e, L., Chen, C., Yu, Y.: Dynamic assessment of environmental efficiency in Chinese industry: A multiple DEA model with a Gini criterion approach. Sustainability. 11(8), 2294 (2019)

    Article  Google Scholar 

  48. Hu, A.H., Hsu, C.W.: Critical factors for implementing green supply chain management practice: an empirical study of electrical and electronics industries in Taiwan. Management research review. (2010)

  49. Sureeyatanapas, P., Waleekhajornlert, N., Arunyanart, S., Niyamosoth, T.: Resilient supplier selection in electronic components procurement: An integration of evidence theory and rule-based transformation into TOPSIS to tackle uncertain and incomplete information. Symmetry. 12(7), 1109 (2020)

    Article  Google Scholar 

  50. Gao, H., Ju, Y., Gonzalez, E.D., Zhang, W.: Green supplier selection in electronics manufacturing: an approach based on consensus decision making. J. Clean. Prod. 245, 118781 (2020)

    Article  Google Scholar 

  51. Hosseini, S., Khaled, A.A.: A hybrid ensemble and AHP approach for resilient supplier selection. J. Intell. Manuf. 30(1), 207–228 (2019)

    Article  Google Scholar 

  52. Banaeian, N., Mobli, H., Fahimnia, B., Nielsen, I.E., Omid, M.: Green supplier selection using fuzzy group decision making methods: a case study from the agri-food industry. Comput. Oper. Res. 89, 337–347 (2018)

    Article  Google Scholar 

  53. Haldar, S., Karmaker, C.L., Hossain, S.R.: A framework to evaluate and improve supply chain: FAHP based case study on a supermarket. Int. J. Res. Ind. Eng. 8(3), 225–242 (2019)

    Google Scholar 

  54. Haldar, A., Ray, A., Banerjee, D., Ghosh, S.: Resilient supplier selection under a fuzzy environment. Int. J. Manag. Sci. Eng. Manag. 9(2), 147–156 (2014)

    Google Scholar 

  55. Ahmady, N., Azadi, M., Sadeghi, S.A., Saen, R.F.: A novel fuzzy data envelopment analysis model with double frontiers for supplier selection. Int J Log Res Appl 16(2), 87–98 (2013)

    Article  Google Scholar 

  56. Chan, F.T., Kumar, N., Tiwari, M.K., Lau, H.C., Choy, K.: Global supplier selection: a fuzzy-AHP approach. Int. J. Prod. Res. 46(14), 3825–3857 (2008)

    Article  Google Scholar 

  57. Zahiri, B., Zhuang, J., Mohammadi, M.: Toward an integrated sustainable-resilient supply chain: A pharmaceutical case study. Transp. Res. Part E. Logist. Transp. Rev. 103, 109–142 (2017)

    Article  Google Scholar 

  58. Bonab, S.R., Haseli, G., Rajabzadeh, H., Ghoushchi, S.J., Hajiaghaei-Keshteli, M., Tomaskova, H.: Sustainable resilient supplier selection for IoT implementation based on the integrated BWM and TRUST under spherical fuzzy sets. Decis. Mak. Appl. Manag. Eng. 6(1), 153–185 (2023)

    Article  Google Scholar 

  59. Haseli, G., Ranjbarzadeh, R., Hajiaghaei-Keshteli, M., Ghoushchi, S.J., Hasani, A., Deveci, M., Ding, W.: HECON: Weight assessment of the product loyalty criteria considering the customer decision’s halo effect using the convolutional neural networks. Inform. Sci. 623, 184–205 (2023)

    Article  Google Scholar 

  60. Haseli, G., Torkayesh, A.E., Hajiaghaei-Keshteli, M., Venghaus, S.: Sustainable resilient recycling partner selection for urban waste management: Consolidating perspectives of decision-makers and experts. Appl. Soft Comput. 137, 110120 (2023)

    Article  Google Scholar 

  61. Saghafinia, A., Fallahpour, A., Asadpour, M., Abedian, M.: Green supplier selection in a fuzzy environment: FIS and FPP approaches. Cybern. Syst. (2022). https://doi.org/10.1080/01969722.2022.2138118

    Article  Google Scholar 

  62. Abedian, M., Amindoust, A., Maddahi, R., Jouzdani, J.: A game theory approach to selecting marketing-mix strategies. J. Adv. Manag. Res. 19(1), 139–158 (2021)

    Article  Google Scholar 

  63. Zadeh, L.A.: Fuzzy sets. Inf. Control. 8(3), 338–353 (1965)

    Article  Google Scholar 

  64. Abedian, M., Saghafinia, A., Hejazi, M.: A fuzzy analysis approach to green-resilient supplier selection in electronic manufacturing systems. Cybern. Syst. 54(5), 577–603 (2023)

    Article  Google Scholar 

  65. Chen, Y.J.: Structured methodology for supplier selection and evaluation in a supply chain. Inf. Sci. 181(9), 1651–1670 (2011)

    Article  Google Scholar 

  66. Sivanandam, S.N., Sumathi, S., Deepa, S.N.: Introduction to fuzzy logic using MATLAB. Springer, Berlin (2007)

    Book  Google Scholar 

  67. Ordoobadi, S.M.: Development of a supplier selection model using fuzzy logic. Supply Chain Manag. Int. J. 14(4), 314–327 (2009)

    Article  Google Scholar 

  68. Banker, R.D., Charnes, A., Cooper, W.W.: Some models for estimating technical and scale inefficiencies in data envelopment analysis. Manag. Sci. 30(9), 1078–1092 (1984)

    Article  Google Scholar 

  69. Zeydan, M., Çolpan, C., Çobanoğlu, C.: A combined methodology for supplier selection and performance evaluation. Expert Syst. Appl. 38(3), 2741–2751 (2011)

    Article  Google Scholar 

  70. Takamura, Y., Tone, K.: A comparative site evaluation study for relocating Japanese government agencies out of Tokyo. Socioecon. Plann. Sci. 37(2), 85–102 (2003)

    Article  Google Scholar 

  71. Demir, L., Akpınar, M.E., Araz, C., Ilgın, M.A.: A green supplier evaluation system based on a new multi-criterion sorting method: VIKORSORT. Expert Syst. Appl. 114, 479–487 (2018)

    Article  Google Scholar 

  72. Ghadikolaei, A.S., Parkouhi, S.V., Saloukolaei, D.D.: Extension of a hybrid MABAC–DANP method under gray environment for green supplier selection. Int. J. Inf. Technol. Decis. Mak. 21(02), 755–788 (2022)

    Article  Google Scholar 

  73. Sahu, A.K., Datta, S., Mahapatra, S.S.:Evaluation and selection of resilient suppliers in fuzzy environment: exploration of fuzzy-VIKOR. Benchmarking: An International Journal. (2016)

  74. Hosseini, S., Barker, K.: Modeling infrastructure resilience using Bayesian networks: a case study of inland waterway ports. Comput. Ind. Eng. 93, 252–266 (2016)

    Article  Google Scholar 

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Acknowledgements

The authors would like to acknowledge the editor and reviewers of OPSEARCH for their valuable comments and suggestion.

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A.S, M.A and M.H have contributed towards writing and finalizing the article.

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Correspondence to Ali Saghafinia.

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Appendices

Appendix A

Supplier selection indicators defined from literatures:

A

Cost

The unit price of the product

B

Quality

Quality of product, Defect rate at the customer’s plant, or the supplier’s process capability

C

Delivery performance

The supplier’s order cycle time, on-time delivery performance, and ship** accuracy

D

Innovation and technology

The supplier’s innovation and technological advances

E

Service and support

The supplier’s ability and willingness to assist with the design process and ability to provide technical assistance and support for post-sales services

F

Firm’s image and reputation

The supplier’s profile, image, market share, and brand recognition

G

Customer satisfaction

A measurement that determines how products or services provided by a company meet customer expectations

H

Production capacity

The volume of products that can be produced and delivered by the supplier using their current resources

I

Eco-design

Product materials that are easy to recycle and reuse, using as little material and energy as possible, thus reducing the impact on the environment

J

Training programs on environmental issues

Environmental staff training and involvement

K

Environmental competencies (EC)

Green product, Green warehousing, Green transportation, Use of green material in the production process, Measure of carbon management, Usage of toxic substances Environment production

L

Pollutant emission

control level

Controlling of ecological impacts, Availability use of clean technologies, Pollution production, Air emission level

M

Energy efficiency

Recourse consumption, Waste water energy consumption, Effluence and waste, Amount of solid waste

N

Eco-design recycling

Percentage of recycle waste, Reuse air emissions, Green use, reduce the energy consumption in an environmentally sound manner

O

Level of disposal of

hazardous chemicals

disposal of hazardous chemicals in accordance with green principles

P

Life cycle management

Management of the green products life cycle including design, material selection, manufacturing, marketing, and logistics

Q

Environment-conscious production

Producing products in accordance with green principles and with mimimal negative impact on environment

R

Fuel structure change

Increasing the share of new ane pure energies, hydroelectric and nuclear power

S

Responsiveness

The supplier’s ability and availability to quickly react or respond to customer requirements

T

Safety stock inventory

The supplier’s capacity to hold adequate amounts of essential materials and goods to support customers during disruptive events

U

Backup supplier contracts (BSC)

The supplier’s outsourcing contracts which enable customers to overcome shortages of supply capacity in the case of disruption

V

Invulnerable location

The supplier’s location which should be in a safe area with low risk of natural disasters to minimise impacts on supply chain processes

W

Delivery rerouting

Rerouting options (based on the supplier’s location) or the supplier’s ability to adjust transportation routes during disruptive events

X

Risk of production shutdown

The possibility of production shutdown, which may be caused by failure of facilities, machine breakdown, labour strikes, natural disasters, and technological problems

Y

Restoration

The supplier’s ability to restore damaged facilities and equipment or to resume production to a normal state of operation

Z

Robustness

Physical protection infrastructure and safety system of the supplier’s building and facilities to minimise negative impacts of disruption, especially in the case of natural disasters

Appendix B

Indicator’s weights.

Please encircle on the box you find appropriate.

Main Criteria (indicators)

Importance being attached by the company

Sub-criteria (indicators)

 

General aspects

      

Product price: The unit price of the product

0

1

2

3

4

5

      

Product quality: Quality of product, Defect rate at the customer’s plant, or the supplier’s process capability

0

1

2

3

4

5

      

Delivery performance: The supplier’s order cycle time, on-time delivery performance, and ship** accuracy

0

1

2

3

4

5

      

Innovation and technology: The supplier’s innovation and technological advances

0

1

2

3

4

5

 

1

2

3

4

5

Service and support: The supplier’s ability and willingness to assist with the design process and ability to provide technical assistance and support for post-sales services

0

1

2

3

4

5

      

Firm’s image and reputation: The supplier’s profile, image, market share, and brand recognition

0

1

2

3

4

5

      

Production capacity: The volume of products that can be produced and delivered by the supplier using their current resources

0

1

2

3

4

5

      

Customer satisfaction: A measurement that determines how products or services provided by a company meet customer expectations

0

1

2

3

4

5

      

Any other indicator you consider: please specify ……………………………….

0

1

2

3

4

5

Resilient aspects

      

Concern about preservation of resiliency

      

Responsiveness: The supplier’s ability and availability to quickly react or respond to customer requirements

0

1

2

3

4

5

      

Safety stock inventory: The supplier’s capacity to hold adequate amounts of essential materials and goods to support customers during disruptive events

0

1

2

3

4

5

      

Backup Supplier Contracts (BSC): The supplier’s outsourcing contracts which enable customers to overcome shortages of supply capacity in the case of disruption

0

1

2

3

4

5

      

Invulnerable location: The supplier’s location which should be in a safe area with low risk of natural disasters to minimise impacts on supply chain processes

0

1

2

3

4

5

      

Delivery rerouting: Rerouting options (based on the supplier’s location) or the supplier’s ability to adjust transportation routes during disruptive events

0

1

2

3

4

5

      

Risk of production shutdown: The possibility of production shutdown, which may be caused by failure of facilities, machine breakdown, labour strikes, natural disasters, and technological problems

0

1

2

3

4

5

 

1

2

3

4

5

Restoration: The supplier’s ability to restore damaged facilities and equipment or to resume production to a normal state of operation

0

1

2

3

4

5

      

Robustness: Physical protection infrastructure and safety system of the supplier’s building and facilities to minimise negative impacts of disruption, especially in the case of natural disasters

0

1

2

3

4

5

      

Any other indicator you consider: please specify ……………………………….

0

1

2

3

4

5

Green aspects

      

Ability to develop long-term relationships with customer

0

1

2

3

4

5

      

Eco-design: Product materials that are easy to recycle and reuse, using as little material and energy as possible, thus reducing the impact on the environment

0

1

2

3

4

5

      

Training programs on environmental issues: Environmental staff training and involvement

0

1

2

3

4

5

      

Environmental Competencies (EC): Green product, Green warehousing, Green transportation, Use of green material in the production process, Measure of carbon management, Usage of toxic substances Environment production

0

1

2

3

4

5

      

Pollutant emission control level: Controlling of ecological impacts, Availability use of clean technologies, Pollution production, Air emission level

0

1

2

3

4

5

      

Energy Efficiency: Recourse consumption, Waste water energy consumption, Effluence and waste, Amount of solid waste

      
      

Eco-Design Recycling: Percentage of recycle waste, Reuse air emissions, Green use, reduce the energy consumption in an environmentally sound manner

0

1

2

3

4

5

      

Level of disposal of hazardous chemicals: disposal of hazardous chemicals in accordance with green principles

0

1

2

3

4

5

      

Life cycle management: Management of the green products life cycle including design, material selection, manufacturing, marketing, and logistics

      
 

1

2

3

4

5

Environment-conscious production: Producing products in accordance with green principles and with mimimal negative impact on environment

0

1

2

3

4

5

      

Fuel structure change: Increasing the share of new ane pure energies, hydroelectric and nuclear power

0

1

2

3

4

5

      

Any other indicator you consider: please specify ……………………………….

0

1

2

3

4

5

  1. Not Considered = (0); Weak Importance = (1); Low Moderate Importance = (2); Moderate Importance = (3); Strong Importance = (4); Extreme Importance = (5)

Appendix C

Suppliers’ performances.

Please encircle on the box you find appropriate.

Sub-criteria (indicators)

Supplier’s performance with respect to sub-criteria

Cost: The unit price of the product

1

2

3

4

5

Quality: Quality of product, Defect rate at the customer’s plant, or the supplier’s process capability

1

2

3

4

5

Innovation and technology: The supplier’s innovation and technological advances

1

2

3

4

5

Production capacity: The volume of products that can be produced and delivered by the supplier using their current resources

1

2

3

4

5

Responsiveness: The supplier’s ability and availability to quickly react or respond to customer requirements

1

2

3

4

5

Safety stock inventory: The supplier’s capacity to hold adequate amounts of essential materials and goods to support customers during disruptive events

1

2

3

4

5

Robustness: Physical protection infrastructure and safety system of the supplier’s building and facilities to minimize negative impacts of disruption, especially in the case of natural disasters

1

2

3

4

5

Restoration: The supplier’s ability to restore damaged facilities and equipment or to resume production to a normal state of operation

1

2

3

4

5

Environmental Competencies (EC): Green product, Green warehousing, Green transportation, Use of green material in the production process, Measure of carbon management, Usage of toxic substances Environment production

1

2

3

4

5

Pollutant emission control level: Controlling of ecological impacts, Availability use of clean technologies, Pollution production, Air emission level

1

2

3

4

5

Energy Efficiency: Recourse consumption, Waste water energy consumption, Effluence and waste, Amount of solid waste

1

2

3

4

5

Fuel structure change: Increasing the share of new ane pure energies, hydroelectric and nuclear power

1

2

3

4

5

  1. Weakly performed = (1); Low moderately performed = (2); Moderately performed = (3); Strongly performed = (4); Extremely performed = (5)

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Saghafinia, A., Abedian, M. & Hejazi, M. Employing fuzzy DEA for Green-resilient supplier selection in an electronic industry of household appliances: a case study (Snowa). OPSEARCH (2024). https://doi.org/10.1007/s12597-024-00752-6

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