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Introducing alternatives ranking with elected nominee (ARWEN) method: a case study of supplier selection

    Shervin Zakeri Affiliation
    ; Prasenjit Chatterjee Affiliation
    ; Dimitri Konstantas Affiliation
    ; Ali Shojaei Farr Affiliation

Abstract

Supply chain management (SCM) has gradually evolved beyond the straightforward logic of benefits and economic viewpoints. Supplier selection and performance evaluation are the crucial strategic components of any SCM system with a substantial economic impact and risk reduction. Several conflicting factors make supplier selection a challenging multi-criteria decision-making problem. This paper introduces a method called alternative ranking with the elected nominee (ARWEN) to select suppliers in Iran’s dairy product chain store. The primary principle of ARWEN is to choose the best alternative based on the lowest change rate rather than the elected nominee. Four extensions of the ARWEN method are proposed depending upon the nature and level of information available to the decision-makers. A fifth extended version termed E-ARWEN is also recommended to consider the negative form of the elected nominee. Two novel statistical tools, the ranking performance index and the Zakeri-Konstantas distance product correlation coefficient, are also put forth to validate the ARWEN extensions’ outcomes. The results and verification of this new method are carried out through two supplier selection case examples. Comprehensive comparisons were carried out to explore the new methods’ behaviors, indicating ARWEN III and E-ARWEN have similar behavior to VIKOR, SAW, and EDAS in generating rankings.

Keyword : multi-criteria decision-making, ARWEN, ranking performance index, Zakeri-Konstantas distance product correlation coefficient, criteria performance index, supplier selection

How to Cite
Zakeri, S., Chatterjee, P., Konstantas, D., & Shojaei Farr, A. (2023). Introducing alternatives ranking with elected nominee (ARWEN) method: a case study of supplier selection. Technological and Economic Development of Economy, 29(3), 1080–1126. https://doi.org/10.3846/tede.2023.18789
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Jun 16, 2023
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References

Abdel-Baset, M., Chang, V., Gamal, A., & Smarandache, F. (2019). An integrated neutrosophic ANP and VIKOR method for achieving sustainable supplier selection: A case study in importing field. Computers in Industry, 106, 94–110. https://doi.org/10.1016/j.compind.2018.12.017

Alipour, M., Hafezi, R., Rani, P., Hafezi, M., & Mardani, A. (2021). A new Pythagorean fuzzy-based decision-making method through entropy measure for fuel cell and hydrogen components supplier selection. Energy, 234, 121208. https://doi.org/10.1016/j.energy.2021.121208

Aouadni, S., & Euchi, J. (2022). Using integrated MMD-TOPSIS to solve the supplier selection and fair order allocation problem: A Tunisian case study. Logistics, 6(1), 8. https://doi.org/10.3390/logistics6010008

Aouadni, S., Aouadni, I., & Rebaï, A. (2019). A systematic review on supplier selection and order allocation problems. Journal of Industrial Engineering International, 15(1), 267–289. https://doi.org/10.1007/s40092-019-00334-y

Badi, I., & Pamucar, D. (2020). Supplier selection for steelmaking company by using combined Grey-MARCOS methods. Decision Making: Applications in Management and Engineering, 3(2), 37–48. https://doi.org/10.31181/dmame2003037b

Badi, I., Abdulshahed, A. M., & Shetwan, A. (2018). A case study of supplier selection for a steelmaking company in Libya by using the Combinative Distance-based Assessment (CODAS) model. Decision Making: Applications in Management and Engineering, 1(1), 1–12.

Bolturk, E. (2018). Pythagorean fuzzy CODAS and its application to supplier selection in a manufacturing firm. Journal of Enterprise Information Management, 31(4), 550–564. https://doi.org/10.1108/JEIM-01-2018-0020

Çalık, A. (2021). A novel Pythagorean fuzzy AHP and fuzzy TOPSIS methodology for green supplier selection in the Industry 4.0 era. Soft Computing, 25(3), 2253–2265. https://doi.org/10.1007/s00500-020-05294-9

Chai, J., & Ngai, E. W. (2020). Decision-making techniques in supplier selection: Recent accomplishments and what lies ahead. Expert Systems with Applications, 140, 112903. https://doi.org/10.1016/j.eswa.2019.112903

Chatterjee, K., & Kar, S. (2018). Supplier selection in Telecom supply chain management: A Fuzzy-Rasch based COPRAS-G method. Technological and Economic Development of Economy, 24(2), 765–791. https://doi.org/10.3846/20294913.2017.1295289

Chatterjee, P., Athawale, V. M., & Chakraborty, S. (2011). Materials selection using complex proportional assessment and evaluation of mixed data methods. Materials & Design, 32(2), 851–860. https://doi.org/10.1016/j.matdes.2010.07.010

Chen, C. H. (2021). A hybrid multi-criteria decision-making approach based on ANP-entropy TOPSIS for building materials supplier selection. Entropy, 23(12), 1597. https://doi.org/10.3390/e23121597

Dutta, P., Jaikumar, B., & Arora, M. S. (2022). Applications of data envelopment analysis in supplier selection between 2000 and 2020: A literature review. Annals of Operations Research, 315, 1399–1454. https://doi.org/10.1007/s10479-021-03931-6

Ecer, F. (2021). Sustainable supplier selection: FUCOM subjective weighting method based MAIRCA approach. Journal of Economics and Administrative Sciences Faculty, 8(1), 26–47.

Ecer, F., & Pamucar, D. (2022). A novel LOPCOW-DOBI multi-criteria sustainability performance assessment methodology: An application in developing country banking sector. Omega, 112, 102690. https://doi.org/10.1016/j.omega.2022.102690

Ecer, F., & Torkayesh, A. E. (2022). A stratified fuzzy decision-making approach for sustainable circular supplier selection. IEEE Transactions on Engineering Management, 1–15. https://doi.org/10.1109/TEM.2022.3151491

Elhassouny, A., & Smarandache, F. (2016). Multi-criteria decision making method for n-wise criteria comparisons and inconsistent problems. Critical Review, 12, 81–112.

Fei, L., Deng, Y., & Hu, Y. (2019). DS-VIKOR: A new multi-criteria decision-making method for supplier selection. International Journal of Fuzzy Systems, 21(1), 157–175. https://doi.org/10.1007/s40815-018-0543-y

Formisano, A., & Mazzolani, F. M. (2015). On the selection by MCDM methods of the optimal system for seismic retrofitting and vertical addition of existing buildings. Computers & Structures, 159, 1–13. https://doi.org/10.1016/j.compstruc.2015.06.016

Gao, H., Ran, L., Wei, G., Wei, C., & Wu, J. (2020). VIKOR method for MAGDM based on q-rung interval-valued orthopair fuzzy information and its application to supplier selection of medical consumption products. International Journal of Environmental Research and Public Health, 17(2), 525. https://doi.org/10.3390/ijerph17020525

Ghadikolaei, A. S., Parkouhi, S. V., & Saloukolaei, D. D. (2022). Extension of a hybrid MABAC–DANP method under gray environment for green supplier selection. International Journal of Information Technology & Decision Making, 21(2), 755–788. https://doi.org/10.1142/S021962202150070X

Göçer, F. (2022). Limestone supplier selection for coal thermal power plant by applying integrated PF-SAW and PF-EDAS approach. Soft Computing, 26, 6393–6414. https://doi.org/10.1007/s00500-022-07157-x

Gore, C., Murray, K., & Richardson, B. (1992). Strategic decision-making. Cassell Press.

Gupta, S. M., & Ilgin, M. A. (2017). Multiple criteria decision making applications in environmentally conscious manufacturing and product recovery. CRC Press. https://doi.org/10.1201/9781315119304

Haddad, A. N., da Costa, B. B., de Andrade, L. S., Hammad, A., & Soares, C. A. (2021). Application of fuzzy-TOPSIS method in supporting supplier selection with focus on HSE criteria: A case study in the oil and gas industry. Infrastructures, 6(8), 105. https://doi.org/10.3390/infrastructures6080105

Haddad, M., Sanders, D., & Tewkesbury, G. (2020). Selecting a discrete multiple criteria decision making method for Boeing to rank four global market regions. Transportation Research Part A: Policy and Practice, 134, 1–15. https://doi.org/10.1016/j.tra.2020.01.026

Huang, Y., Lin, R., & Chen, X. (2021). An enhancement EDAS method based on Prospect Theory. Technological and Economic Development of Economy, 27(5), 1019–1038. https://doi.org/10.3846/tede.2021.15038

Hwang, C. L., & Yoon, K. (1981). Methods for multiple attribute decision making. In Lecture notes in economics and mathematical systems: Vol. 186. Multiple attribute decision making (pp. 58–191). Springer Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-48318-9_3

Ishizaka, A., & Nemery, P. (2013). Multi-criteria decision analysis: Methods and software. John Wiley & Sons. https://www.wiley.com/en-us/Multi+criteria+Decision+Analysis:+Methods+and+Software-p-9781119974079

Kahraman, C., & Alkan, N. (2021). Circular intuitionistic fuzzy TOPSIS method with vague membership functions: Supplier selection application context. Notes on Intuitionistic Fuzzy Sets, 27(1), 24–52. https://doi.org/10.7546/nifs.2021.27.1.24-52

Karami, S., Ghasemy Yaghin, R., & Mousazadegan, F. (2021). Supplier selection and evaluation in the garment supply chain: An integrated DEA–PCA–VIKOR approach. The Journal of the Textile Institute, 112(4), 578–595. https://doi.org/10.1080/00405000.2020.1768771

Keshavarz Ghorabaee, M., Zavadskas, E. K., Turskis, Z., & Antucheviciene, J. (2016). A new combinative distance-based assessment (CODAS) method for multi-criteria decision-making. Economic Computation & Economic Cybernetics Studies & Research, 50(3), 25–44.

Konys, A. (2019). Green supplier selection criteria: From a literature review to a comprehensive knowledge base. Sustainability, 11(15), 4208. https://doi.org/10.3390/su11154208

Kou, G., Lu, Y., Peng, Y., & Shi, Y. (2012). Evaluation of classification algorithms using MCDM and rank correlation. International Journal of Information Technology & Decision Making, 11(01), 197–225. https://doi.org/10.1142/S0219622012500095

Li, J., Fang, H., & Song, W. (2019). Sustainable supplier selection based on SSCM practices: A rough cloud TOPSIS approach. Journal of Cleaner Production, 222, 606–621. https://doi.org/10.1016/j.jclepro.2019.03.070

Liao, H., Wen, Z., & Liu, L. (2019). Integrating BWM and ARAS under hesitant linguistic environment for digital supply chain finance supplier section. Technological and Economic Development of Economy, 25(6), 1188–1212. https://doi.org/10.3846/tede.2019.10716

Liaqait, R. A., Warsi, S. S., Agha, M. H., Zahid, T., & Becker, T. (2022). A multi-criteria decision framework for sustainable supplier selection and order allocation using multi-objective optimization and fuzzy approach. Engineering Optimization, 54(6), 928–948. https://doi.org/10.1080/0305215X.2021.1901898

Liu, C., Rani, P., & Pachori, K. (2021). Sustainable circular supplier selection and evaluation in the manufacturing sector using Pythagorean fuzzy EDAS approach. Journal of Enterprise Information Management. https://doi.org/10.1108/JEIM-04-2021-0187

Liu, P., Wang, X., Wang, P., Wang, F., & Teng, F. (2022). Sustainable medical supplier selection based on multi-granularity probabilistic linguistic term sets. Technological and Economic Development of Economy, 28(2), 381–418. https://doi.org/10.3846/tede.2022.15940

Lu, J., Zhang, S., Wu, J., & Wei, Y. (2021). COPRAS method for multiple attribute group decision making under picture fuzzy environment and their application to green supplier selection. Technological and Economic Development of Economy, 27(2), 369–385. https://doi.org/10.3846/tede.2021.14211

MacCrimmon, K. R. (1968). Decision making among multiple-attribute alternatives: A survey and consolidated approach. RAND Corporation.

Madi, E. N., Garibaldi, J. M., & Wagner, C. (2016, July). An exploration of issues and limitations in current methods of TOPSIS and fuzzy TOPSIS. In 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (pp. 2098–2105). Vancouver. IEEE. https://doi.org/10.1109/FUZZ-IEEE.2016.7737950

Matić, B., Jovanović, S., Das, D. K., Zavadskas, E. K., Stević, Ž., Sremac, S., & Marinković, M. (2019). A new hybrid MCDM model: Sustainable supplier selection in a construction company. Symmetry, 11(3), 353. https://doi.org/10.3390/sym11030353

Menon, R. R., & Ravi, V. (2022). Using AHP-TOPSIS methodologies in the selection of sustainable suppliers in an electronics supply chain. Cleaner Materials, 5, 100130. https://doi.org/10.1016/j.clema.2022.100130

Mishra, A. R., Saha, A., Rani, P., Pamucar, D., Dutta, D., & Hezam, I. M. (2022). Sustainable supplier selection using HF-DEA-FOCUM-MABAC technique: A case study in the Auto-making industry. Soft Computing, 26, 8821–8840. https://doi.org/10.1007/s00500-022-07192-8

Mukhametzyanov, I., & Pamucar, D. (2018). A sensitivity analysis in MCDM problems: A statistical approach. Decision Making: Applications in Management and Engineering, 1(2), 51–80.

Opricovic, S. (1998). Multicriteria optimization of civil engineering systems [PhD Thesis]. Faculty of Civil Engineering, Belgrade.

Opricovic, S., & Tzeng, G. H. (2002). Multicriteria planning of post‐earthquake sustainable reconstruction. Computer-Aided Civil and Infrastructure Engineering, 17(3), 211–220. https://doi.org/10.1111/1467-8667.00269

Opricovic, S., & Tzeng, G. H. (2004). Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European Journal of Operational Research, 156(2), 445–455. https://doi.org/10.1016/S0377-2217(03)00020-1

Paldrak, M., Erdem, G., Tan Tacoğlu, M., Güçlükol, S., & Staiou, E. (2022). A literature review on supplier selection problem and fuzzy logic. In International Conference on Intelligent and Fuzzy Systems (pp. 339–351). Springer, Cham. https://doi.org/10.1007/978-3-031-09173-5_42

Pamučar, D., Stević, Ž., & Sremac, S. (2018). A new model for determining weight coefficients of criteria in MCDM models: Full consistency method (FUCOM). Symmetry, 10(9), 393. https://doi.org/10.3390/sym10090393

Pamucar, D., Torkayesh, A. E., & Biswas, S. (2022). Supplier selection in healthcare supply chain management during the COVID-19 pandemic: A novel fuzzy rough decision-making approach. Annals of Operations Research, 1–43. https://doi.org/10.1007/s10479-022-04529-2

Peng, J. J., Tian, C., Zhang, W. Y., Zhang, S., & Wang, J. Q. (2020). An integrated multi-criteria decision-making framework for sustainable supplier selection under picture fuzzy environment. Technological and Economic Development of Economy, 26(3), 573–598. https://doi.org/10.3846/tede.2020.12110

Qaradaghi, M., & Deason, J. P. (2018). Analysis of MCDM methods output coherence in oil and gas portfolio prioritization. Journal of Petroleum Exploration and Production Technology, 8(2), 617–640. https://doi.org/10.1007/s13202-017-0344-0

Ramírez-Ochoa, D. D., Pérez-Domínguez, L., Martínez-Gómez, E. A., Torres-Argüelles, V., Garg, H., & Sansabas-Villapando, V. (2022). Supplier selection process based on CODAS method using q-rung orthopair fuzzy information. In Garg, H. (Ed.), q-rung orthopair fuzzy sets (pp. 219–240). Springer. https://doi.org/10.1007/978-981-19-1449-2_9

Resende, C. H., Geraldes, C. A., & Junior, F. R. L. (2021). Decision models for supplier selection in industry 4.0 era: A systematic literature review. Procedia Manufacturing, 55, 492–499. https://doi.org/10.1016/j.promfg.2021.10.067

Ricci, F., Rokach, L., Shapira, B., & Kantor, P. B. (2011). Recommender systems handbook. Springer. https://doi.org/10.1007/978-0-387-85820-3

Rouyendegh, B. D., Yildizbasi, A., & Üstünyer, P. (2020). Intuitionistic fuzzy TOPSIS method for green supplier selection problem. Soft Computing, 24(3), 2215–2228. https://doi.org/10.1007/s00500-019-04054-8

Saaty, T. L. (1971). On polynomials and crossing numbers of complete graphs. Journal of Combinatorial Theory, Series A, 10(2), 183–184. https://doi.org/10.1016/0097-3165(71)90024-0

Saaty, T. L. (1988). What is the analytic hierarchy process? In Mathematical models for decision support (pp. 109–121). Springer. https://doi.org/10.1007/978-3-642-83555-1_5

Sałabun, W. (2015). The characteristic objects method: A new distance‐based approach to multicriteria decision‐making problems. Journal of Multi‐Criteria Decision Analysis, 22(1–2), 37–50. https://doi.org/10.1002/mcda.1525

Sałabun, W., & Urbaniak, K. (2020, June). A new coefficient of rankings similarity in decision-making problems. In International Conference on Computational Science (pp. 632–645). Amsterdam. Springer, Cham. https://doi.org/10.1007/978-3-030-50417-5_47

Salimian, S., Mousavi, S. M., & Antucheviciene, J. (2022). An interval-valued intuitionistic fuzzy model based on extended VIKOR and MARCOS for sustainable supplier selection in organ transplantation networks for healthcare devices. Sustainability, 14(7), 3795. https://doi.org/10.3390/su14073795

Saltelli, A., Aleksankina, K., Becker, W., Fennell, P., Ferretti, F., Holst, N., Li, S., & Wu, Q. (2019). Why so many published sensitivity analyses are false: A systematic review of sensitivity analysis practices. Environmental Modelling & Software, 114, 29–39. https://doi.org/10.1016/j.envsoft.2019.01.012

Schramm, V. B., Cabral, L. P. B., & Schramm, F. (2020). Approaches for supporting sustainable supplier selection – A literature review. Journal of Cleaner Production, 273, 123089. https://doi.org/10.1016/j.jclepro.2020.123089

Shang, Z., Yang, X., Barnes, D., & Wu, C. (2022). Supplier selection in sustainable supply chains: Using the integrated BWM, fuzzy Shannon entropy, and fuzzy MULTIMOORA methods. Expert Systems with Applications, 195, 116567. https://doi.org/10.1016/j.eswa.2022.116567

Smarandache, F. (2016). -discounting method for multi-criteria decision making. https://doi.org/10.2139/ssrn.2720888

Stević, Ž., Pamučar, D., Puška, A., & Chatterjee, P. (2020). Sustainable supplier selection in healthcare industries using a new MCDM method: Measurement of alternatives and ranking according to COmpromise solution (MARCOS). Computers & Industrial Engineering, 140, 106231. https://doi.org/10.1016/j.cie.2019.106231

Stević, Ž., Pamučar, D., Vasiljević, M., Stojić, G., & Korica, S. (2017). Novel integrated multi-criteria model for supplier selection: Case study construction company. Symmetry, 9(11), 279. https://doi.org/10.3390/sym9110279

Sun, Y., & Cai, Y. (2021). A flexible decision-making method for green supplier selection integrating TOPSIS and GRA under the single-valued neutrosophic environment. IEEE Access, 9, 83025–83040. https://doi.org/10.1109/ACCESS.2021.3085772

Suraraksa, J., & Shin, K. S. (2019). Comparative analysis of factors for supplier selection and monitoring: The case of the automotive industry in Thailand. Sustainability, 11(4), 981. https://doi.org/10.3390/su11040981

Tavana, M., Shaabani, A., Mansouri Mohammadabadi, S., & Varzgani, N. (2021). An integrated fuzzy AHP-fuzzy MULTIMOORA model for supply chain risk-benefit assessment and supplier selection. International Journal of Systems Science: Operations & Logistics, 8(3), 238–261. https://doi.org/10.1080/23302674.2020.1737754

Tong, L. Z., Wang, J., & Pu, Z. (2022). Sustainable supplier selection for SMEs based on an extended PROMETHEE II approach. Journal of Cleaner Production, 330, 129830. https://doi.org/10.1016/j.jclepro.2021.129830

Velasquez, M., & Hester, P. T. (2013). An analysis of multi-criteria decision-making methods. International Journal of Operations Research, 10(2), 56–66.

Wang, D., & Zhao, J. (2016). Design optimization of mechanical properties of ceramic tool material during turning of ultra-high-strength steel 300M with AHP and CRITIC method. The International Journal of Advanced Manufacturing Technology, 84(9–12), 2381–2390. https://doi.org/10.1007/s00170-015-7903-7

Wang, J., Wang, J. Q., Zhang, H. Y., & Chen, X. H. (2017). Distance-based multi-criteria group decision-making approaches with multi-hesitant fuzzy linguistic information. International Journal of Information Technology & Decision Making, 16(04), 1069–1099. https://doi.org/10.1142/S0219622017500213

Wei, C., Wu, J., Guo, Y., & Wei, G. (2021a). Green supplier selection based on CODAS method in probabilistic uncertain linguistic environment. Technological and Economic Development of Economy, 27(3), 530–549. https://doi.org/10.3846/tede.2021.14078

Wei, G., He, Y., Lei, F., Wu, J., Wei, C., & Guo, Y. (2020). Green supplier selection with an uncertain probabilistic linguistic MABAC method. Journal of Intelligent & Fuzzy Systems, 39(3), 3125–3136. https://doi.org/10.3233/JIFS-191584

Wei, G., Wei, C., & Guo, Y. (2021b). EDAS method for probabilistic linguistic multiple attribute group decision making and their application to green supplier selection. Soft Computing, 25(14), 9045–9053. https://doi.org/10.1007/s00500-021-05842-x

Wetzstein, A., Hartmann, E., Benton Jr, W. C., & Hohenstein, N. O. (2016). A systematic assessment of supplier selection literature – State-of-the-art and future scope. International Journal of Production Economics, 182, 304–323. https://doi.org/10.1016/j.ijpe.2016.06.022

Yazdani, M., Chatterjee, P., Pamucar, D., & Abad, M. D. (2020). A risk-based integrated decision-making model for green supplier selection: A case study of a construction company in Spain. Kybernetes, 49(4), 1229–1252. https://doi.org/10.1108/K-09-2018-0509

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

Zakeri, S. (2019). Ranking based on optimal points multi-criteria decision-making method. Grey Systems: Theory and Application, 9(1), 45–69. https://doi.org/10.1108/GS-09-2018-0040

Zakeri, S., & Konstantas, D. (2022). Solving decision-making problems using a measure for Information Values Connected to the Equilibrium Points (IVEP) MCDM method and Zakeri–Konstantas performance correlation coefficient. Information, 13(11), 512. https://doi.org/10.3390/info13110512

Zakeri, S., Chatterjee, P., Cheikhrouhou, N., & Konstantas, D. (2022a). Ranking based on optimal points and win-loss-draw multi-criteria decision-making with application to supplier evaluation problem. Expert Systems with Applications, 191, 116258. https://doi.org/10.1016/j.eswa.2021.116258

Zakeri, S., Ecer, F., Konstantas, D., & Cheikhrouhou, N. (2021). The vital-immaterial-mediocre multi-criteria decision-making method. Kybernetes. https://doi.org/10.1108/K-05-2021-0403

Zakeri, S., Yang, Y., & Hashemi, M. (2019). Grey strategies interaction model. Journal of Strategy and Management, 12(1), 30–60. https://doi.org/10.1108/JSMA-06-2018-0055

Zakeri, S., Yang, Y., & Konstantas, D. (2022b). A supplier selection model using alternative ranking process by alternatives’ stability scores and the grey equilibrium product. Processes, 10(5), 917. https://doi.org/10.3390/pr10050917

Zanakis, S. H., Solomon, A., Wishart, N., & Dublish, S. (1998). Multi-attribute decision making: A simulation comparison of select methods. European Journal of Operational Research, 107(3), 507–529. https://doi.org/10.1016.S0377-2217(97)00147-1

Zhang, H., Wei, G., & Chen, X. (2022). SF-GRA method based on cumulative prospect theory for multiple attribute group decision making and its application to emergency supplies supplier selection. Engineering Applications of Artificial Intelligence, 110, 104679. https://doi.org/10.1016/j.engappai.2022.104679

Zhou, H., Wang, J. Q., & Zhang, H. Y. (2018). Multi-criteria decision-making approaches based on distance measures for linguistic hesitant fuzzy sets. Journal of the Operational Research Society, 69(5), 661–675. https://doi.org/10.1080/01605682.2017.1400780

Žižović, M., & Pamucar, D. (2019). New model for determining criteria weights: Level Based Weight Assessment (LBWA) model. Decision Making: Applications in Management and Engineering, 2(2), 126–137.