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
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)
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)
Kao, C.: Efficiency decomposition in network data envelopment analysis: a relational model. Eur. J. Oper. Res. 192(3), 949–962 (2009)
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)
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)
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)
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)
Sheffi, Y., Rice, J.B., Jr.: A supply chain view of the resilient enterprise. MIT Sloan Manag. Rev. 47(1), 41 (2005)
**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
Sarkis, J., Talluri, S.: A model for strategic supplier selection. J. Supply Chain Manag. 38(4), 18–28 (2002)
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)
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)
Bai, C., Sarkis, J.: Green supplier development: analytical evaluation using rough set theory. J. Clean. Prod. 18(12), 1200–1210 (2010)
Rajesh, R., Ravi, V.: Supplier selection in resilient supply chains: a grey relational analysis approach. J. Clean. Prod. 86, 343–359 (2015)
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)
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)
Sawik, T.: Selection of resilient supply portfolio under disruption risks. Omega 41(2), 259–269 (2013)
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)
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)
Elleuch, H., Dafaoui, E., Elmhamedi, A., Chabchoub, H.: Resilience and vulnerability in supply chain: literature review. IFAC-PapersOnLine. 49(12), 1448–1453 (2016)
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)
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)
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)
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)
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
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)
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)
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)
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)
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)
Li, S., He, Y.: Compensation and information disclosure strategies of a green supply chain under production disruption. J. Clean. Prod. 281, 124851 (2021)
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)
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)
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)
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)
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)
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)
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)
Zhang, X., **ng, X.: Probabilistic linguistic VIKOR method to evaluate green supply chain initiatives. Sustainability. 9(7), 1231 (2017)
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)
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)
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)
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)
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)
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)
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)
**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)
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)
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)
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)
Hosseini, S., Khaled, A.A.: A hybrid ensemble and AHP approach for resilient supplier selection. J. Intell. Manuf. 30(1), 207–228 (2019)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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
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)
Zadeh, L.A.: Fuzzy sets. Inf. Control. 8(3), 338–353 (1965)
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)
Chen, Y.J.: Structured methodology for supplier selection and evaluation in a supply chain. Inf. Sci. 181(9), 1651–1670 (2011)
Sivanandam, S.N., Sumathi, S., Deepa, S.N.: Introduction to fuzzy logic using MATLAB. Springer, Berlin (2007)
Ordoobadi, S.M.: Development of a supplier selection model using fuzzy logic. Supply Chain Manag. Int. J. 14(4), 314–327 (2009)
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)
Zeydan, M., Çolpan, C., Çobanoğlu, C.: A combined methodology for supplier selection and performance evaluation. Expert Syst. Appl. 38(3), 2741–2751 (2011)
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)
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)
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)
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)
Hosseini, S., Barker, K.: Modeling infrastructure resilience using Bayesian networks: a case study of inland waterway ports. Comput. Ind. Eng. 93, 252–266 (2016)
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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 |
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 |
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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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DOI: https://doi.org/10.1007/s12597-024-00752-6