A Structured Decision-Making Approach for Supplier Performance Evaluation in the Restaurant Sector

Sirawadee Arunyanart

doi:10.31181/dmame8220251493

Authors

Sirawadee Arunyanart Supply Chain and Logistics System Research Unit, Department of Industrial Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen 40002, Thailand

DOI:

https://doi.org/10.31181/dmame8220251493

Keywords:

Restaurant Industry; Food Raw Material; Supplier Selection; Multi-Criteria Decision-Making, Fuzzy TOPSIS, Rank-Based Weighting

Abstract

In the contemporary, highly competitive restaurant sector, securing high-quality food raw materials is pivotal to achieving sustained business success. An organised and systematic supplier selection process is fundamental for ensuring operational efficiency, cost control, and consistent service standards. The present study introduces a structured framework designed to assess and rank restaurant raw material suppliers by integrating subjective evaluations across multiple criteria. The proposed methodology follows a two-phase process. The first phase entails the identification of essential supplier evaluation criteria, utilising rank-based weighting methods to determine their relative significance from the perspective of restaurateurs in Thailand. In the second phase, the fuzzy technique for order preference by similarity to the ideal solution (fuzzy TOPSIS) is applied to assess and rank potential suppliers based on their aggregate performance. A practical case study is presented involving an independent full-service restaurant in Thailand that was required to select from four candidate suppliers. This case is used to demonstrate the effectiveness of the framework. Furthermore, a sensitivity analysis is conducted to examine the impact of different weighting approaches on the final supplier rankings. The results highlight eight key evaluation criteria: quality level, product cost, responsiveness speed, communication systems, delivery performance, lead time, fill rate, and process flexibility. Findings from the sensitivity analysis indicate that supplier rankings vary according to the weighting methodology applied, underscoring the necessity for adaptable decision-making models. Such flexibility is crucial as the relative importance of these criteria can shift in response to market dynamics or specific operational priorities. For restaurant operators, adopting a systematic approach is vital to address the inherent complexity and uncertainty of supplier assessments. Incorporating multiple weighting techniques can strengthen the robustness of selection processes. This study offers practical guidance for enhancing procurement strategies and competitive advantage, while also providing suppliers with valuable insights into industry requirements and expectations.

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References

[1] Abdullah, L., Chan, W., & Afshari, A. (2019). Application of PROMETHEE method for green supplier selection: A comparative result based on preference functions. Journal of Industrial Engineering International, 15(2), 271-285. https://doi.org/10.1007/s40092-018-0289-z

[2] Ahn, B. S. (2011). Compatible weighting method with rank order centroid: Maximum entropy ordered weighted averaging approach. European Journal of Operational Research, 212(3), 552-559. https://doi.org/10.1016/j.ejor.2011.02.017

[3] Ahuja, K., Chandra, V., Lord, V., & Peens, C. (2021). Ordering in: The rapid evolution of food delivery. McKinsey & Company, 22, 1-13. https://www.mckinsey.com/industries/technology-media-and-telecommunications/our-insights/ordering-in-the-rapid-evolution-of-food-delivery

[4] Alfares, H. K., & Duffuaa, S. O. (2016). Simulation-based evaluation of criteria rank-weighting methods in multi-criteria decision-making. International Journal of Information Technology & Decision Making, 15(01), 43-61. https://doi.org/10.1142/S0219622015500315

[5] Ali, S., Khalid, N., Javed, H. M. U., & Islam, D. M. Z. (2020). Consumer adoption of online food delivery ordering (OFDO) services in Pakistan: The impact of the COVID-19 pandemic situation. Journal of Open Innovation: Technology, Market, and Complexity, 7(1), 10. https://doi.org/10.3390/joitmc7010010

[6] Allaoui, H., Guo, Y., Choudhary, A., & Bloemhof, J. (2018). Sustainable agro-food supply chain design using two-stage hybrid multi-objective decision-making approach. Computers & Operations Research, 89, 369-384. https://doi.org/10.1016/j.cor.2016.10.012

[7] Alshehri, K. A., & Albukhari, A. A. (2021). Critical factors of supplier selection in the food and beverage industry of Saudi Arabia: A FUZZY-TOPSIS approach. Proceedings of the International Conference on Industrial Engineering and Operations Management, 211-219. https://ieomsociety.org/singapore2021/papers/44.pdf

[8] Amorim, P., Curcio, E., Almada-Lobo, B., Barbosa-Póvoa, A. P., & Grossmann, I. E. (2016). Supplier selection in the processed food industry under uncertainty. European Journal of Operational Research, 252(3), 801-814. https://doi.org/10.1016/j.ejor.2016.02.005

[9] Annosi, M. C., Brunetta, F., Appio, F. P., Watcharakomenkul, N., & Platania, F. (2024). Integrating intuition and rationality in strategic decision-making processes: Insights from product development in multinational corporations. IEEE Transactions on Engineering Management, 71, 8402-8416. https://doi.org/10.1109/TEM.2024.3395014

[10] Ayough, A., Shargh, S. B., & Khorshidvand, B. (2023). A new integrated approach based on base-criterion and utility additive methods and its application to supplier selection problem. Expert Systems with Applications, 221, 119740. https://doi.org/10.1016/j.eswa.2023.119740

[11] Banaeian, N., Mobli, H., Fahimnia, B., Nielsen, I. E., & Omid, M. (2018). Green supplier selection using fuzzy group decision making methods: A case study from the agri-food industry. Computers & Operations Research, 89, 337-347. https://doi.org/10.1016/j.cor.2016.02.015

[12] Banaeian, N., Mobli, H., Nielsen, I. E., & Omid, M. (2015). Criteria definition and approaches in green supplier selection–a case study for raw material and packaging of food industry. Production & Manufacturing Research, 3(1), 149-168. https://doi.org/10.1080/21693277.2015.1016632

[13] Barron, F. H., & Barrett, B. E. (1996). Decision quality using ranked attribute weights. Management science, 42(11), 1515-1523. https://doi.org/10.1287/mnsc.42.11.1515

[14] Bharucha, J. (2018). Tackling the challenges of reducing and managing food waste in Mumbai restaurants. British Food Journal, 120(3), 639-649. https://www.researchgate.net/publication/322668654

[15] Braglia, M., & Petroni, A. (2000). A quality assurance‐oriented methodology for handling trade‐offs in supplier selection. International Journal of Physical Distribution & Logistics Management, 30(2), 96-112. https://doi.org/10.1108/09600030010318829

[16] Brouwer, I. D., van Liere, M. J., de Brauw, A., Dominguez-Salas, P., Herforth, A., Kennedy, G., Lachat, C., Omosa, E. B., Talsma, E. F., & Vandevijvere, S. (2021). Reverse thinking: Taking a healthy diet perspective towards food systems transformations. Food Security, 13(6), 1497-1523. https://doi.org/10.1007/s12571-021-01204-5

[17] Cakar, T., & Çavuş, B. (2021). Supplier selection process in dairy industry using fuzzy TOPSIS method. Operational Research in Engineering Sciences: Theory and Applications, 4(1), 82-98. https://doi.org/10.31181/oresta2040182c

[18] Chai, J., Liu, J. N., & Ngai, E. W. (2013). Application of decision-making techniques in supplier selection: A systematic review of literature. Expert Systems with Applications, 40(10), 3872-3885. https://doi.org/10.1016/j.eswa.2012.12.040

[19] Chattopadhyay, A., & Bose, U. (2018). An assessment of objectivity convergence of fuzzy TOPSIS method extended with rank order weights in group decision making. Asian Journal of Managerial Science, 7(3), 26-33. https://doi.org/10.51983/ajms-2018.7.3.1347

[20] Cho, M., Bonn, M. A., Giunipero, L., & Jaggi, J. S. (2021). Supplier selection and partnerships: Effects upon restaurant operational and strategic benefits and performance. International Journal of Hospitality Management, 94, 102781. https://doi.org/10.1016/j.ijhm.2020.102781

[21] Chung, K.-C. (2015). Applying analytical hierarchy process to supplier selection and evaluation in the hospitality industry: A multiobjective approach. Acta Oeconomica, 65(s2), 309-323. https://doi.org/10.1556/032.65.2015.s2.23

[22] Cousins, J., Foskett, D., & Gillespie, C. (2002). Food and Beverage Management (2nd ed.). https://www.scribd.com/document/478959814/FOOD-AND-BEVERAGE-MANAGEMENT-2nd-Edition-1-pdf

[23] Danielson, M., & Ekenberg, L. (2014). Rank ordering methods for multi-criteria decisions. Joint International Conference on Group Decision and Negotiation, 128-135. https://doi.org/10.1007/978-3-319-07179-4_14

[24] Danielson, M., & Ekenberg, L. (2017). A robustness study of state-of-the-art surrogate weights for MCDM. Group Decision and Negotiation, 26(4), 677-691. https://doi.org/10.1007/s10726-016-9494-6

[25] Ding, Y., & Keh, H. T. (2016). A re-examination of service standardization versus customization from the consumer’s perspective. Journal of services marketing, 30(1), 16-28. https://doi.org/10.1108/JSM-02-2015-0088

[26] Dou, Z., Stefanovski, D., Galligan, D., Lindem, M., Rozin, P., Chen, T., & Chao, A. M. (2021). Household food dynamics and food system resilience amid the COVID-19 pandemic: A cross-national comparison of China and the United States. Frontiers in Sustainable Food Systems, 4, 577153. https://doi.org/10.3389/fsufs.2020.577153

[27] Elshaer, A. M. (2022). Restaurants’ response to COVID-19 pandemic: The realm of Egyptian independent restaurants. Journal of Quality Assurance in Hospitality & Tourism, 23(3), 716-747. https://doi.org/10.1080/1528008X.2021.1911732

[28] Floess, E., Grieshop, A., Puzzolo, E., Pope, D., Leach, N., Smith, C. J., Gill-Wiehl, A., Landesman, K., & Bailis, R. (2023). Scaling up gas and electric cooking in low-and middle-income countries: climate threat or mitigation strategy with co-benefits? Environmental Research Letters, 18(3), 034010. https://doi.org/10.1088/1748-9326/acb501

[29] Francis, G., Gallone, A., Nychas, G., Sofos, J., Colelli, G., Amodio, M., & Spano, G. (2012). Factors affecting quality and safety of fresh-cut produce. Critical reviews in food science and nutrition, 52(7), 595-610. https://doi.org/10.1080/10408398.2010.503685

[30] Fu, Y.-K. (2019). An integrated approach to catering supplier selection using AHP-ARAS-MCGP methodology. Journal of Air Transport Management, 75, 164-169. https://doi.org/10.1016/j.jairtraman.2019.01.011

[31] Gama, N., Alves, C. A., & Oliveira, P. S. (2020). Suppliers selection in restaurants: Application of Delphi and fuzzy AHP methods. Journal of Hospitality, 2(3-4), 94-106. http://htmjournals.com/jh/index.php/jh/article/view/25

[32] Gergin, R. E., Peker, İ., & Kısa, A. C. G. (2022). Supplier selection by integrated IFDEMATEL-IFTOPSIS Method: A case study of automotive supply industry. . Decision Making: Applications in Management and Engineering, 5(1), 169-193. https://doi.org/10.31181/dmame211221075g

[33] Gkoumas, A. (2022). Developing an indicative model for preserving restaurant viability during the COVID-19 crisis. Tourism and Hospitality Research, 22(1), 18-31. https://doi.org/10.1177/1467358421998057

[34] Govindan, K., Kadziński, M., & Sivakumar, R. (2017). Application of a novel PROMETHEE-based method for construction of a group compromise ranking to prioritization of green suppliers in food supply chain. Omega, 71, 129-145. https://doi.org/10.1016/j.omega.2016.10.004

[35] Gu, Q., Li, M., & Huang, S. (2023). An exploratory investigation of technology-assisted dining experiences from the consumer perspective. International Journal of Contemporary Hospitality Management, 35(3), 1010-1029. https://doi.org/10.1108/IJCHM-02-2022-0214

[36] Huang, S.-L., & Siao, H.-R. (2023). Factors affecting the implementation of online food delivery and its impact on restaurant performance during the covid-19 pandemic. Sustainability, 15(16), 12147. https://doi.org/10.3390/su151612147

[37] Ikinci, M., & Tipi, T. (2021). Food supplier selection in the catering industry using the analytic hierarchy process. Food Science and Technology, 42, e48420. https://doi.org/10.1590/fst.48420

[38] Ishizaka, A., Pereira, V., & Siraj, S. (2021). AHPSort-GAIA: a visualisation tool for the sorting of alternative in AHP portrayed through a case in the food and drink industry. Annals of Operations Research, 1-16. https://doi.org/10.1007/s10479-021-04082-4

[39] Javad, M. O. M., Darvishi, M., & Javad, A. O. M. (2020). Green supplier selection for the steel industry using BWM and fuzzy TOPSIS: A case study of Khouzestan steel company. Sustainable Futures, 2, 100012. https://doi.org/10.1016/j.sftr.2020.100012

[40] Kahraman, C., Cebeci, U., & Ulukan, Z. (2003). Multi‐criteria supplier selection using fuzzy AHP. Logistics information management, 16(6), 382-394. https://doi.org/10.1108/09576050310503367

[41] Kamble, S. S., & Raut, R. D. (2019). Evaluating the factors considered for procurement of raw material in food supply chain using Delphi-AHP methodology-a case study of potato chips processing company in India. International Journal of Productivity and Quality Management, 26(2), 176-189. https://doi.org/10.1504/IJPQM.2019.097765

[42] Kim, B., & Velthuis, O. (2021). From reactivity to reputation management: online consumer review systems in the restaurant industry. Journal of Cultural Economy, 14(6), 675-693. https://doi.org/10.1080/17530350.2021.1895280

[43] Lau, H., Shum, P. K., Nakandala, D., Fan, Y., & Lee, C. (2020). A game theoretic decision model for organic food supplier evaluation in the global supply chains. Journal of Cleaner Production, 242, 118536. https://doi.org/10.1016/j.jclepro.2019.118536

[44] Lima-Junior, F. R., & Carpinetti, L. C. R. (2016). Combining SCOR® model and fuzzy TOPSIS for supplier evaluation and management. International journal of production economics, 174, 128-141. https://doi.org/10.1016/j.ijpe.2016.01.023

[45] Lo, S.-K. J., Tavitiyaman, P., & Tsang, W.-S. L. (2024). Impact of customers' needs on online information search of upscale restaurant attributes and customer satisfaction. British Food Journal, 126(3), 941-964. https://doi.org/10.1108/BFJ-06-2023-0471

[46] Ma, L., Chen, H., Yan, H., Yang, L., & Wu, L. (2017). Multiple attribute decision making model and application to food safety risk evaluation. PloS one, 12(12), e0189835. https://doi.org/10.1371/journal.pone.0189835

[47] Marusak, A., Sadeghiamirshahidi, N., Krejci, C. C., Mittal, A., Beckwith, S., Cantu, J., Morris, M., & Grimm, J. (2021). Resilient regional food supply chains and rethinking the way forward: Key takeaways from the COVID-19 pandemic. Agricultural Systems, 190, 103101. https://doi.org/10.1016/j.agsy.2021.103101

[48] Menéndez Molist, A., Kallas, Z., Puig De Morales, M., Boughamoura, O., Noutfia, Y., & Ouabouch, H. (2022). Preferences analysis of restaurants, industry and retailers for selecting fruits and vegetables suppliers in Spain, France and Morocco. https://doi.org/10.13033/isahp.y2022.053.

[49] Miranda-Ackerman, M. A., Azzaro-Pantel, C., & Aguilar-Lasserre, A. A. (2017). A green supply chain network design framework for the processed food industry: Application to the orange juice agrofood cluster. Computers & Industrial Engineering, 109, 369-389. https://doi.org/10.1016/j.cie.2017.04.031

[50] Modibbo, U. M., Hassan, M., Ahmed, A., & Ali, I. (2022). Multi-criteria decision analysis for pharmaceutical supplier selection problem using fuzzy TOPSIS. Management Decision, 60(3), 806-836. https://doi.org/10.1108/MD-10-2020-1335

[51] Mohammed, H. J., Kasim, M. M., & Shaharanee, I. N. M. (2017). Selection of suitable e-learning approach using TOPSIS technique with best ranked criteria weights. AIP Conference Proceedings, 0735415951. https://doi.org/10.1063/1.5012207

[52] Moreno-Gené, J., Daries, N., & Cristobal-Fransi, E. (2023). Effects of restaurant expenses on enhanced profitability: Do Michelin-starred restaurants perform differently? International Journal of Gastronomy and Food Science, 34, 100811. https://doi.org/10.1016/j.ijgfs.2023.100811

[53] Moskowitz, H. R. (1995). Food quality: conceptual and sensory aspects. Food Quality and Preference, 6(3), 157-162. https://doi.org/10.1016/0950-3293(94)00030-Y

[54] Mun, S. G., & Jang, S. S. (2018). Restaurant operating expenses and their effects on profitability enhancement. International Journal of Hospitality Management, 71, 68-76. https://doi.org/10.1016/j.ijhm.2017.12.002

[55] Nurhayati, N., & Zulfikar, M. (2023). Supplier assessment for supply chain performance and effective food safety implementation: a framework. Media Bina Ilmiah, 18(1), 211-220. https://doi.org/10.33758/mbi.v18i1.563

[56] Pouyakian, M., Azimi, H. R., Patriarca, R., Keighobadi, E., Fardafshari, M., & Hanifi, S. M. (2024). Application of Functional Resonance Analysis and fuzzy TOPSIS to identify and prioritize factors affecting newly emerging risks. Journal of Loss Prevention in the Process Industries, 91, 105400. https://doi.org/10.1016/j.jlp.2024.105400

[57] Pramanik, D., Mondal, S. C., & Haldar, A. (2022). A framework for managing uncertainty in information system project selection: An intelligent fuzzy approach. In Big Data and Information Theory, 103-112. Routledge. https://doi.org/10.1080/17509653.2019.1604191

[58] Puška, A., & Stojanović, I. (2022). Fuzzy multi-criteria analyses on green supplier selection in an agri-food company. Journal of Intelligent Management Decision, 1(1), 2-16. https://doi.org/10.56578/jimd010102

[59] Qu, G., Zhang, Z., Qu, W., & Xu, Z. (2020). Green supplier selection based on green practices evaluated using fuzzy approaches of TOPSIS and ELECTRE with a case study in a Chinese internet company. International journal of environmental research and public health, 17(9), 3268. https://doi.org/10.3390/ijerph17093268

[60] Ramlan, R., Bakar, E. M. N. E. A., Mahmud, F., & Ng, H. K. (2016). The ideal criteria of supplier selection for SMEs food processing industry. MATEC Web of Conferences, 2261-236X. https://doi.org/10.1051/matecconf/20167005006

[61] Roszkowska, E. (2013). Rank ordering criteria weighting methods–a comparative overview. Optimum. Studia Ekonomiczne(5 (65)), 14-33. http://hdl.handle.net/11320/2189

[62] Saad Andaleeb, S., & Conway, C. (2006). Customer satisfaction in the restaurant industry: an examination of the transaction‐specific model. Journal of services marketing, 20(1), 3-11. https://doi.org/10.1108/08876040610646536

[63] Sarwar, M., & Bashir, F. (2024). Design concept evaluation based on cloud rough model and modified AHP-VIKOR: An application to lithography tool manufacturing process. Advanced engineering informatics, 60, 102369. https://doi.org/10.1016/j.aei.2024.102369

[64] Setiawansyah, Aldino, A. A., Palupiningsih, P., Laxmi, G. F., Mega, E. D., & Septiana, I. (2023). Determining best graduates using TOPSIS with surrogate weighting procedures approach. In 2023 International Conference on Networking, Electrical Engineering, Computer Science, and Technology (IConNECT), 60-64. IEEE. https://doi.org/10.1109/IConNECT56593.2023.10327119

[65] Sharma, J., & Tripathy, B. B. (2023). An integrated QFD and fuzzy TOPSIS approach for supplier evaluation and selection. The TQM Journal, 35(8), 2387-2412. https://doi.org/10.1108/TQM-09-2022-0295

[66] Shi, H., Quan, M.-Y., Liu, H.-C., & Duan, C.-Y. (2018). A novel integrated approach for green supplier selection with interval-valued intuitionistic uncertain linguistic information: A case study in the agri-food industry. Sustainability, 10(3), 733. https://doi.org/10.3390/su10030733

[67] Shroff, A., Shah, B. J., & Gajjar, H. (2022). Online food delivery research: A systematic literature review. International Journal of Contemporary Hospitality Management, 34(8), 2852-2883. https://doi.org/10.1108/IJCHM-10-2021-1273

[68] Silalahi, A., Sukwadi, R., Le, M.-T., & Thu, N. T. B. (2023). A hybrid model of analytical network process and mixed-integer programming for selecting restaurant food supplier. Mathematica Applicanda, 51(1). http://dx.doi.org/10.14708/ma.v51i1.7105

[69] Sokhanvar, A., & Bouri, E. (2023). Commodity price shocks related to the war in Ukraine and exchange rates of commodity exporters and importers. Borsa Istanbul Review, 23(1), 44-54. https://doi.org/10.1016/j.bir.2022.09.001

[70] Sutoyo, M. N., & Mangkona, A. T. S. (2021). The selection of SNMPTN applicants using the TOPSIS and rank order centroid (ROC) methods. ILKOM Jurnal Ilmiah, 13(3), 272-284. https://doi.org/10.33096/ilkom.v13i3.936.272-284

[71] Swink, M., Hu, K., & Zhao, X. (2022). Analytics applications, limitations, and opportunities in restaurant supply chains. Production and Operations Management, 31(10), 3710-3726. https://doi.org/10.1111/poms.13704

[72] Tang, Y., Chin, T. A., & Abdullah, M. (2024). Supplier selection criteria of restaurant: A cross-industry literature review. Journal of Tourism, Hospitality and Environment Management, 9(36), 159-172. http://dx.doi.org/10.35631/JTHEM.936013

[73] Tavana, M., Yazdani, M., & Di Caprio, D. (2017). An application of an integrated ANP–QFD framework for sustainable supplier selection. International Journal of Logistics Research and Applications, 20(3), 254-275. https://doi.org/10.1080/13675567.2016.1219702

[74] Thanaraksakul, W., & Phruksaphanrat, B. (2009). Supplier evaluation framework based on balanced scorecard with integrated corporate social responsibility perspective. In Proceedings of the International MultiConference of Engineers and Computer Scientists 2, 18-20. https://www.researchgate.net/publication/44259868

[75] Thanh, N. V., & Lan, N. T. K. (2022). A new hybrid triple bottom line metrics and fuzzy MCDM model: Sustainable supplier selection in the food-processing industry. Axioms, 11(2), 57. https://doi.org/10.3390/axioms11020057

[76] Tjindana, B. O., & Irawan, Y. B. (2024). Supplier selection using AHP-TOPSIS: Case study in Taigersprung restaurant. Bina Ekonomi, 28(2), 165-177. https://core.ac.uk/download/pdf/629994696.pdf

[77] Trienekens, J., & Zuurbier, P. (2008). Quality and safety standards in the food industry, developments and challenges. International journal of production economics, 113(1), 107-122. https://doi.org/10.1016/j.ijpe.2007.02.050

[78] Türkeș, M. C., Stăncioiu, A. F., Băltescu, C. A., & Marinescu, R.-C. (2021). Resilience innovations and the use of food order & delivery platforms by the Romanian restaurants during the COVID-19 pandemic. Journal of Theoretical and Applied Electronic Commerce Research, 16(7), 3218-3247. https://doi.org/10.3390/jtaer16070175

[79] Vasilakakis, K., & Sdrali, D. (2023). Supplier selection criteria in the Greek hotel food and beverage divisions. Journal of Hospitality and Tourism Insights, 6(2), 447-463. https://doi.org/10.1108/JHTI-07-2021-0169

[80] Walker, J. R. (2021). The restaurant: from concept to operation. John Wiley & Sons. https://books.google.com.pk/books?id=-_1GEAAAQBAJ&dq=%5B1%5D+Walker,+J.+R.+(2021)

[81] Wang, J., & Zionts, S. (2015). Using ordinal data to estimate cardinal values. Journal of Multi‐Criteria Decision Analysis, 22(3-4), 185-196. https://doi.org/10.1002/mcda.1528

[82] Wang, Y., Wang, W., Wang, Z., Deveci, M., Roy, S. K., & Kadry, S. (2024). Selection of sustainable food suppliers using the Pythagorean fuzzy CRITIC-MARCOS method. Information sciences, 664, 120326. https://doi.org/10.1016/j.ins.2024.120326

[83] Wood, D. A. (2016). Supplier selection for development of petroleum industry facilities, applying multi-criteria decision making techniques including fuzzy and intuitionistic fuzzy TOPSIS with flexible entropy weighting. Journal of Natural Gas Science and Engineering, 28, 594-612. https://doi.org/10.1016/j.jngse.2015.12.021

[84] Wu, S.-H., & Ku, E. C. (2024). Aligning restaurants and artificial intelligence computing of food delivery service with product development. Journal of Hospitality and Tourism Technology, 15(3), 379-396. https://doi.org/10.1108/JHTT-10-2023-0322

[85] Wu, X., Huang, Z., & Shen, S. (2019). Comprehensive evaluation of medical service capability in TCM hospitals by using the fuzzy combined method of TOPSIS and rank sum ratio. 2019 3rd International Conference on Data Science and Business Analytics (ICDSBA), 1728146445. https://doi.org/10.1109/ICDSBA48748.2019.00058

[86] Xia, W., & Wu, Z. (2007). Supplier selection with multiple criteria in volume discount environments. Omega, 35(5), 494-504. https://doi.org/10.1016/j.omega.2005.09.002

[87] Yazdani, M., Pamucar, D., Chatterjee, P., & Torkayesh, A. E. (2022). A multi-tier sustainable food supplier selection model under uncertainty. Operations Management Research, 15(1), 116-145. https://doi.org/10.1007/s12063-021-00186-z

[88] Zhou, B., & Wen, T. (2024). Research on supplier evaluation of chain restaurant companies based on analytic hierarchy process. 2024 5th International Conference on Management Science and Engineering Management (ICMSEM 2024), 9464635703. https://doi.org/10.2991/978-94-6463-570-6_49