Zhang, Y. L., Xie, G. Y. & Chen, J. A Review on some Significant Methods in Operations Management. Appl. Mech. Mater. 278, 2137–2142 (2013).
Google Scholar
McFarlane, D. A. The challenges of operations management for business managers. Int. J. Operat. Logistics Manag. 3(1), 16–29 (2014).
Roth, A. & Rosenzweig, E. Advancing empirical science in operations management study: A clarion call to action. Manuf. Serv. Operat. Manag. 22(1), 179–190 (2020).
Google Scholar
Atasu, A., Corbett, C. J., Huang, X. & Toktay, L. B. Sustainable operations management through the perspective of manufacturing & service operations management. Manuf. Service Operat. Manag. 22(1), 146–157 (2020).
Google Scholar
Jankelová, N., Joniaková, Z., & Mišún, J., “Innovative Approaches in the Management of Healthcare Organisations,” Journal of Health Management, 09720634231216026, 2023.
Selvam, M., Ramachandran, M., Saravanan, V. & Nanjundan, P. Evaluation of Healthcare Operations Management using TOPSIS Method. J. Innov. Teach. Learn. 2(4), 19–27 (2023).
Ahmed, H., Al Bashar, M., Taher, M. A. & Rahman, M. A. Innovative Approaches To Sustainable Supply Chain Management In The Manufacturing Industry: A Systematic Literature Review. Global Mainstream J. Innov. Eng. Emerg. Technol. 3(02), 01–13 (2024).
Kuznetsov, P. M., Tsyrkov, G. A., & Yermokhin, Y. A. (2020, September). The integration platform for project and operational management of enterprise business processes. In 2020 International Conference Quality Management, Transport and Information Security, Information Technologies (IT &QM &IS) (pp. 249-252). IEEE.
Volik, M., Kovaleva, M., Btemirova, R., & Gagloeva, I., “Methodology of Improvement of Company Business Processes,” European Proceedings of Social and Behavioural Sciences, vol. 103, 2021.
Ibeh, C. V. et al. A review of agile methodologies in product lifecycle management: bridging theory and practice for enhanced digital technology integration. Eng. Sci. Technol. J. 5(2), 448–459 (2024).
Google Scholar
Zadeh, L. A. Fuzzy sets. Inf. Control 8, 338–353 (1965).
Google Scholar
Atanassov, K. T. Intuitionistic fuzzy sets. Fuzzy Sets Syst. 20(1), 87–96 (1986).
Google Scholar
B. C. Cuong, P.V. Hai, Some fuzzy logic operators for picture fuzzy sets, Seventh International Conference on Knowledge and Systems Engineering, (2015), 132-137.
Cuong, B. C. Picture fuzzy sets. J. Comput. Sci. Technol. 30, 409–420 (2014).
Wei, G. W., Alsaadi, F. E., Hayat, T. & Alsaedi, A. Projection models for multiple attribute decision-making with picture fuzzy information. Int. J. Mach. Learn. Cybern. 9(4), 713–719 (2018).
Google Scholar
Wei, G. W. & Gao, H. The generalized dice similarity measures for picture fuzzy sets and their applications. Informatica 29(1), 1–18 (2018).
Google Scholar
Wei, G. W. Some similarity measures for picture fuzzy sets and their applications. Iran. J. Fuzzy Syst 15(1), 77–89 (2018).
Google Scholar
Singh, P. Correlation coefficients for picture fuzzy sets. J. Intell. Fuzzy Syst 27, 2857–2868 (2014).
Son, L. H. DPFCM: a novel distributed picture fuzzy clustering method on picture fuzzy sets. Expert Syst. Appl. 2, 51–66 (2015).
Google Scholar
P. H. Phong, D.T. Hieu, R.T.H. Ngan, P.T. Them, Some compositions of picture fuzzy relations, in: proceedings of the 7th national conference on fundamental and applied information technology study, FAIR’7, Thai Nguyen, (2014), 19-20.
Ashraf, S., Abdullah, S. & Mahmood, T. M, Aslam, Cleaner production evaluation in gold mines using novel distance measure method with cubic picture fuzzy numbers. Int. J. Fuzzy Syst. 21, 2448–2461 (2019).
Google Scholar
Ashraf, S., Abdullah, S. & Mahmood, T. Aggregation operators of cubic picture fuzzy quantities and their application in decision support systems. Korean J. Math 28(2), 1976–8605 (2020).
Google Scholar
B. Li, J. Wang, L. Yang, X. Li Novel generalized simplified neutrosophic number einstein aggregation operator, Int. J. Appl. Math, 48(1)(2016), 1-6.
Ashraf, S., Abdullah, S., Mahmood, T., Ghani, F. & Mahmood, T. Spherical fuzzy sets and their applications in multi-attribute decision-making problems. J. Intell. Fuzzy Syst 36, 2829–2844 (2019).
Gundogdu, F. K. & Kahraman, C. Spherical fuzzy sets and spherical fuzzy TOPSIS method. J. Intell. Fuzzy Syst 36(1), 337–352 (2019).
Munir, M., Kalsoom, H., Ullah, K., Mahmood, T. & Chu, Y. M. T-spherical fuzzy Einstein hybrid aggregation operators and their applications in multi-attribute decision making problems. Symmetry 12, 365 (2020).
Google Scholar
Zeng, S., Munir, M., Mahmood, T. & Naeem, M. Some T-spherical fuzzy Einstein interactive aggregation operators and their application to selection of photovoltaic cells. Math. Probl. Eng. 2020, 1904362 (2020).
Google Scholar
Liu, P., Khan, Q., Mahmood, T. & Hassan, N. T-spherical fuzzy power Muirhead mean operator based on novel operational laws and their application in multi-attribute group decision making. IEEE Access 7, 22613–22632 (2019).
Google Scholar
Ullah, K., Mahmood, T. & Garg, H. Tvaluation of the performance of search and rescue robots using T-spherical fuzzy Hamacher aggregation operators. Int. J. Fuzzy Syst. 22(2), 570–582 (2020).
Google Scholar
Özdemirci, F., Yüksel, S., Dinçer, H. & Eti, S. An assessment of alternative social banking systems using T-Spherical fuzzy TOP-DEMATEL approach. Decision Anal. J. 6, 100184 (2023).
Google Scholar
Sarkar, A. et al. Sugeno-Weber Triangular Norm-Based Aggregation Operators Under T-Spherical Fuzzy Hypersoft Context. Inf. Sci. 645, 119305 (2023).
Google Scholar
Gurmani, S. H., Chen, H. & Bai, Y. Multi-attribute group decision-making model for selecting the most suitable construction company using the linguistic interval-valued T-spherical fuzzy TOPSIS method. Appl. Intell. 53(10), 11768–11785 (2023).
Google Scholar
Diakoulaki, D., Mavrotas, G. & Papayannakis, L. Determining objective weights in multiple criteria problems: The CRITIC method. Comput. Operat. Study 22(7), 763–777 (1995).
Google Scholar
Ali, J. A novel score function based CRITIC-MARCOS method with spherical fuzzy information. Comput. Appl. Math. 40(8), 280 (2021).
Google Scholar
Mukhametzyanov, I. Specific character of objective methods for determining weights of criteria in MCDM problems: Entropy, CRITIC and SD. Decision Making: Appl. Manage. Eng. 4(2), 76–105 (2021).
Zafar, S., Alamgir, Z. & Rehman, M. H. An effective blockchain evaluation system based on entropy-CRITIC weight method and MCDM techniques. Peer-to-Peer Netw. Appl. 14(5), 3110–3123 (2021).
Google Scholar
Peng, X., Zhang, X. & Luo, Z. Pythagorean fuzzy MCDM method based on CoCoSo and CRITIC with score function for 5G industry evaluation. Artif. Intell. Rev. 53(5), 3813–3847 (2020).
Google Scholar
Ranjan, R., Rajak, S. & Chatterjee, P. Material selection for sintered pulley in automobile: An integrated CRITIC-MARCOS model. Rep. Mech, Eng. 4(1), 225–240 (2023).
Google Scholar
Lakshmi, B. M. et al. An integrated CRITIC-TOPSIS-and Entropy-TOPSIS-based informative weighting and ranking approach for evaluating green energy sources and its experimental analysis on pyrolysis. Environ. Sci. Pollut. Res. 29(40), 61370–82 (2022).
Google Scholar
Silva, N. F., dos Santos, M., Gomes, C. F. S. & de Andrade, L. P. An integrated CRITIC and Grey Relational Analysis approach for investment portfolio selection. Decision Anal. J. 8, 100285 (2023).
Google Scholar
Sleem, A., Mostafa, N. & Elhenawy, I. Neutrosophic CRITIC MCDM Methodology for Ranking Factors and Needs of Customers in Product’s Target Demographic in Virtual Reality Metaverse. Neutrosophic Syst. Appl. 2, 55–65 (2023).
Google Scholar
Meena, A., Dhir, S. & Sushil, S. Coopetition, strategy, and business performance in the era of digital transformation using a multi-method approach: Some research implications for strategy and operations management. Int. J. Prod. Econ. 270, 109068 (2024).
Google Scholar
S. M. Vadivel, D. S. Shetty, A. H. Sequeira, E. Nagaraj, & V. Sakthivel (2022, December), A Sustainable Green Supplier Selection Using CRITIC Method. In International Conference on Intelligent Systems Design and Applications (pp. 308-315).
Kumari, A. & Acherjee, B. Selection of non-conventional machining process using CRITIC-CODAS method. Mater. Today: Proceedings 56, 66–71 (2022).
Google Scholar
Khargotra, R., Kumar, R., András, K., Fekete, G. & Singh, T. Thermo-hydraulic characterization and design optimization of delta-shaped obstacles in solar water heating system using CRITIC-COPRAS approach. Energy 261, 125236 (2022).
Google Scholar
Hafidy, I., Benghabrit, A., Zekhnini, K. & Benabdellah, A. C. Driving Supply Chain Resilience: Exploring the Potential of Operations Management and Industry 4.0. Procedia Comput. Sci. 232, 2458–2467 (2024).
Google Scholar
Büşra, B. A. Y. A. N. & Abacıoğlu, S. Bibliometric analysis of the MCDM methods in the last decade: WASPAS, MABAC, EDAS, CODAS, COCOSO, and MARCOS. Int. J. Bus. Economic Studies 4(2), 65–85 (2022).
Google Scholar
Vaid, S. K., Vaid, G., Kaur, S., Kumar, R. & Sidhu, M. S. Application of multi-criteria decision-making theory with VIKOR-WASPAS-Entropy methods: A case study of silent Genset. Mater. Today: Proceedings 50, 2416–2423 (2022).
Dehshiri, S. J. H., Amiri, M., Mostafaeipour, A. & Le, T. Integrating blockchain and strategic alliance in renewable energy supply chain toward sustainability: A comparative decision framework under uncertainty. Energy 304, 132136 (2024).
Google Scholar
Hosseini Dehshiri, S. J., Amiri, M., Mostafaeipour, A., Pamučar, D. & Le, T. Enhancing supply chain performance by integrating knowledge management and lean, agile, resilient, and green paradigms. J. Manage. Anal. 11(4), 738–769 (2024).
Eghbali-Zarch, M., Tavakkoli-Moghaddam, R., Dehghan-Sanej, K. & Kaboli, A. Prioritizing the effective strategies for construction and demolition waste management using fuzzy IDOCRIW and WASPAS methods. Eng. Constr. Archit. Manag. 29(3), 1109–1138 (2022).
Nguyen, P. H., Dang, T. T., Nguyen, K. A. & Pham, H. A. Spherical Fuzzy WASPAS-based Entropy Objective Weighting for International Payment Method Selection. Comput. Mater. Continua 72(1), 2055 (2022).
Google Scholar
Al-Barakati, A., Mishra, A. R., Mardani, A. & Rani, P. An extended interval-valued Pythagorean fuzzy WASPAS method based on new similarity measures to evaluate the renewable energy sources. Appl. Soft Comput. 120, 108689 (2022).
Google Scholar
Masoomi, B., Sahebi, I. G., Fathi, M., Yıldırım, F. & Ghorbani, S. Strategic supplier selection for renewable energy supply chain under green capabilities (fuzzy BWM-WASPAS-COPRAS approach). Energ. Strat. Rev. 40, 100815 (2022).
Google Scholar
Darzi, M. A. Evaluating e-waste mitigation strategies based on industry 5.0 enablers: An integrated scenario-based BWM and F-VIKOR approach. J. Environ. Manage. 373, 123999 (2025).
Google Scholar
Kumar, R. A Comprehensive Review of MCDM Methods, Applications, and Emerging Trends. Decision Making Adv. 3(1), 185–199 (2025).
Google Scholar
Bathrinath, S., Mohan, S., Koppiahraj, K., Bhalaji, R. K. A. & Santhi, B. Analysis of factors affecting sustainable performance in construction sites using fuzzy AHP-WASPAS methods. Mater. Today: Proceedings 62, 3118–3121 (2022).
Thanh, N. V. & Lan, N. T. K. Solar energy deployment for the sustainable future of Vietnam: Hybrid SWOC-FAHP-WASPAS analysis. Energies 15(8), 2798 (2022).
Google Scholar
Kshanh, I. & Tanaka, M. Comparative analysis of MCDM for energy efficiency projects evaluation towards sustainable industrial energy management: case study of a petrochemical complex. Expert Syst. Appl. 255, 124692 (2024).
Google Scholar
Yu, K., Wu, Q., Chen, X., Wang, W. & Mardani, A. An integrated MCDM framework for evaluating the environmental, social, and governance (ESG) sustainable business performance. Ann. Oper. Res. 342(1), 987–1018 (2024).
Google Scholar
N. Handayani, N. Heriyani, F. Septian, & A. D. Alexander (2023), Multi-criteria decision making using the WASPAS method for online English course selection.
Dehshiri, S. S. H., Dehshiri, S. J. H. & Firoozabadi, B. Evaluation of using solar energy in Iran’s textile industry towards cleaner production: Sustainable planning and feasibility analysis. J. Clean. Prod. 421, 138447 (2023).
Google Scholar
Hosseini Dehshiri, S. J. & Zanjirchi, S. M. Comparative analysis of multicriteria decision-making approaches for evaluation hydrogen projects development from wind energy. Int. J. Energy Res. 46(10), 13356–13376 (2022).
Google Scholar
Mahmood, T., Ullah, K., Khan, Q. & Jan, N. An approach towards decision-making and medical diagnosis problems using the concept of spherical fuzzy Sets. Neural Comput. Appl. 31, 7041–7053 (2018).
Google Scholar
Awan, U. et al. Big data analytics capability and decision-making: The role of data-driven insight on circular economy performance. Technol. Forecast. Soc. Chang. 168, 120766 (2021).
Google Scholar
Gong, X. (2023). Data-Driven Decision Making in Operations Management (Doctoral dissertation, Massachusetts Institute of Technology).
Oyetoro, A., “Operations Strategy: Developing an operations strategy aligned with business goals, including considerations such as capacity planning, facility location, and technology adoption,” 2024.
Qin, R., Nembhard, D. A. & Barnes, W. L. II. Workforce flexibility in operations management. Surv. Operat. Res. Manage. Sci. 20(1), 19–33 (2015).
Google Scholar
Sahoo, S. K. & Goswami, S. S. Green supplier selection using MCDM: A comprehensive review of recent studies. Spectrum Eng. Manage. Sci. 2(1), 1–16 (2024).
Google Scholar
Stratton, R., Zeng, M., Yeong, A., & Alsharief, T. (2023). Sustainable operations management. In Sustainable Management (pp. 362-390). Routledge.
Cuatrecasas, L. A lean management implementation method in service operations. Int. J. Serv. Technol. Manage. 5(5–6), 532–544 (2004).
Google Scholar
Zdęba-Mozoła, A., Kozłowski, R., Rybarczyk-Szwajkowska, A., Czapla, T. & Marczak, M. Implementation of lean management tools using an example of analysis of prolonged stays of patients in a multi-specialist hospital in Poland. Int. J. Environ. Study Public Health 20(2), 1067 (2023).
Google Scholar
Trofimov, I., Artykhov, A., Gostilovich, A. & Chizhov, S. Automation and digitalization of processes in the management of service organizations. Revista Gestão & Tecnologia 23, 112–125 (2023).
Google Scholar
Schumacher, A., Sihn, W., & Erol, S. (2016, October). Automation, digitization and digitalization and their implications for manufacturing processes. In Innovation and Sustainability Conference Bukarest (pp. 1-5). Amsterdam, The Netherlands: Elsevier.
Kumari, R. & Mishra, A. R. Multi-criteria COPRAS method based on parametric measures for intuitionistic fuzzy sets: application of green supplier selection. Iran. J. Sci. Technol. Trans. Electrical Eng. 44(4), 1645–1662 (2020).
Google Scholar
Chen, T. Y. An evolved VIKOR method for multiple-criteria compromise ranking modeling under T-spherical fuzzy uncertainty. Adv. Eng. Inform. 54, 101802 (2022).
Google Scholar
Rouyendegh, B. D. The intuitionistic fuzzy ELECTRE model. Int. J. Manage. Sci. Eng. Manage. 13(2), 139–145 (2018).
Ju, Y. et al. T-spherical fuzzy TODIM method for multi-criteria group decision-making problem with incomplete weight information. Soft. Comput. 25, 2981–3001 (2021).
Google Scholar
Stanujkić, D. & Karabašević, D. An extension of the WASPAS method for decision-making problems with intuitionistic fuzzy numbers: a case of website evaluation. Operat. Study Eng. Sci. Theory Appl. 1(1), 29–39 (2018).
Fan, J., Han, D. & Wu, M. T-spherical fuzzy COPRAS method for multi-criteria decision-making problem. J. Intell. Fuzzy Syst. 43(3), 2789–2801 (2022).
H. Camgoz Akdag, & A. Menekse (2023), Breast cancer treatment planning using a novel spherical fuzzy CRITIC-REGIME. Journal of Intelligent & Fuzzy Systems, (Preprint), 1-14.
Zhang, H. & Wei, G. Location selection of electric vehicle charging stations by using the spherical fuzzy CPT-CoCoSo and D-CRITIC method. Comput. Appl. Math. 42(1), 60 (2023).
Google Scholar
Yazdi, M. Risk assessment based on novel intuitionistic fuzzy-hybrid-modified TOPSIS approach. Saf. Sci. 110, 438–448 (2018).
Google Scholar
link