n iyi ve en kötünün tek olmadığı durumlarda en iyi-en kötü yöntemi ile grup kararı verme: bursiyer seçimine ilişkin vaka çalışması

Öz

Öğrencilere yönelik burslar, devlet veya kurumlar tarafından sağlanan mali desteklerdir. Sağlanan bursun gerekliliklerini başarıyla yerine getirmek için gerekli olan bilgi, beceri ve yeteneklere sahip çok sayıda rakip öğrenci olabilir. Bu nedenle, burs sağlayıcılar için birden fazla başvuru arasından en uygun öğrencileri seçmek zordur. Bu çalışmada, burs seçimi karmaşık bir karar verme problemi olarak ele alınmış ve bu problem, Çok Kriterli Karar Verme (ÇKKV) yönteminlerinden olan En İyi-En Kötü Yöntemi (BWM) ve Birleşik Uzlaşma Çözümü (CoCoSo yöntemi) birlikte kullanılarak çözülmüştür. Bu yöntemlerin burslu öğrenci seçme problemine uygulanabilirliği, gerçek bir problemin çözümü ile gösterilmiştir. Problem, grup karar verme problemi olarak tasarlanmıştır. Problemde kriterlerin ağırlıkları, Analitik Hiyerarşi Süreci yönteminin geliştirilmiş bir hali olan BWM ile hesaplanmıştır. Aynı zamanda, karar vericilerin en iyi ve en kötü kriterlerinin ortak ve tek olmadığı probleme bir çözüm önerilmiştir. Öte yandan, başvuran adayların sıralamaları için CoCoSo yöntemi kullanılmıştır. Bu çalışma ile bursiyer seçim problem, ilk kez BWM ve CoCoSo yöntemleri ile çözülmüştür. Çalışmadan elde edilen tatmin edici sonuçlar, bir dizi aday veya alternatif arasından en iyi adayı veya alternatifi sıralamak ya da seçmek için BWM ve CoCoSo yöntemlerinin birlikte kullanımının uygun ve etkili bir yaklaşım olacağını göstermektedir.

Anahtar Kelimeler

• Bursiyer öğrenci seçimi
• ÇKKV
• BWM
• CoCoSo

Group decision making in best-worst method when the best and worst are not unique: case study of scholar selection

Abstract

Scholarships for the students are the financial supports provided by the government or institutions. There may be a great number of competing applicants with the knowledge, skills and abilities to successfully fulfill the scholarship needs. So, it is difficult to select the most suitable students among multiple applicants for these providers. In this study, scholarship students’ selection is handled as a complex decision making problem, and this problem is solved by integration of two Multi Criteria Decision Making (MCDM) methods, Best-Worst Method (BWM) and COmbined COmpromise SOlution (CoCoSo). In order to demonstrate the applicability of these methods to the scholarship student selection problem, a real problem is solved. This problem is designed as a group decision making problem, and BWM, the improved Analytic Hierarchy Process method, is employed to derive the criteria weights. A solution to the problem where decision makers’ best and worst criteria are not common and unique is suggested. On the other hand, CoCoSo method is used for the ranking purposes of the applicants. The novelty of this study is that scholarship selection problem is solved with BWM and CoCoSo methods for the first time. The integrated usage of BWM and CoCoSo methods is thought as suitable and effective methods to rank or select the best candidate or alternative among a number of candidates or alternatives because of satisfactory results.

Keywords

• Scholarship student selection
• MCDM
• BWM
• CoCoSo

References

1. [1] Indriyanti AD, Prehanto DR, Prismana IGLEP, Sujatmiko B, Fikandda J. “Simple additive weighting algorithm to aid administrator decision making of the underprivileged scholarship”. Journal of Physics: Conference Series, 1402(6), 1-7, 2019.
2. [2] Mardhiyyah R, Sejati RHP, Ratnasari D. “A decision support system of scholarship grantee selection using Moora”. International Journal of Applied Business and Information Systems, 3(1), 21-27, 2019.
3. [3] Hasan P, Utami E, Yunita S, Pawan E. “Selection of scholarship acceptance using AHP and TOPSIS methods”. IEEE 2019 International Conference on Information and Communications Technology, Yogyakarta, Indonesia, 24-25 July 2019.
4. [4] Marfuah, Widiantoro S. “The implementation of Analytical Hierarchy Process method for outstanding achievement scholarship reception selection at Universal University of Batam”. IOP Conference Series: Earth and Environmental Science, 97(1), 1-9, 2017.
5. [5] Yeh CH. “A problem‐based selection of multi‐attribute decision‐making methods”. International Transactions in Operational Research, 9(2), 169-181, 2002.
6. [6] Yeh CH. “The selection of multiattribute decision making methods for scholarship student selection”. International Journal of Selection and Assessment, 11(4), 289-296, 2003.
7. [7] Uyun S, Riadi I. “A fuzzy TOPSIS multiple-attribute decision making for scholarship selection”. Telkomnika, 9(1), 37-46, 2011.
8. [8] Wimatsari GAN, Putra KGD, Buana PW. “Multi-attribute decision making scholarship selection using a modified fuzzy TOPSIS”. International Journal of Computer Sciences, 10(2), 309-317, 2013.

9. [9] Saptarini NGAPH, Prihatini PM. “Decision support system for scholarship in Bali state polytechnic using AHP and TOPSIS”. International Conference on Information Technology and Business (ICITB), Bandar Lampung, Indonesia, 20-21 August 2015.
10. [10]Purba RA, Sembiring J. “Selection of scholarship recipients by using promethee method in Polytechnic Unggul LP3M Medan”. International Seminar on Application for Technology of Information and Communication (ISemantic), Semarang, Indonesia, 5-6 August 2016.
11. [11] Mesran KT, Sianturi RD, Waruwu FT, Siahaan AP. “Determination of education scholarship recipients using preference selection index”. International Journal of Scientific Research in Science and Technology, 3(6), 230-234, 2017.
12. [12] Puspitasari TD, Sari EO, Destarianto P, Riskiawan HY. “Decision support system for determining scholarship selection using an analytical hierarchy process”. Journal of Physics: Conference Series, 953 (1), 1-5, 2018.
13. [13] Rizana AF, Soesanto RP. “Design of decision support system application for determining scholarship grantee using Analytical Hierarchy Process and Factor Rating”. International Conference on Industrial Enterprise and System Engineering, Yogyakarta, Indonesia, 21-22 November 2018.
14. [14] Mahmud N, Muhammat Pazil NS, Mazlan UH, Jamaluddin SH, Che Hasan NN. Scholarship Eligibility and Selection: A Fuzzy Analytic Hierarchy Process Approach. Editors: Saian R, Abbas M. Proceedings of the Second International Conference on the Future of ASEAN (ICoFA), 175-183, Singapore, Springer, 2018.
15. [15] Anamisa DR, Rachmad A, Putro SS, Jauhari A, Khozaimi A, Pujiastutik R, Rahmanita E. “The selection system of student scholarship based on simple additive weighting and technique for order preference by similarity to ıdeal solution method”. 1st International Conference on Computer Science and Engineering Technology, Kudus, Indonesia, 25 October 2018.
16. [16] Mufizar T, Mulyani EDS, Wiyono RA, Arifiana W. “A combination of Multi Factor Evaluation Process (MFEP) and the Distance to the Ideal Alternative (DIA) methods for majors selection and scholarship recipients in SMAN 2 Tasikmalaya”. 6th International Conference on Cyber and IT Service Management (CITSM), Indonesia, 7-9 August 2018.
17. [17] Utami A, Ruskan EL. “Development of decision support system for selection of Yayasan alumni scholarship using MOORA method”. Advances in Intelligent Systems Research, 172, 706-710, 2020.
18. [18] Oktaviani O, Triayudi A, Solihati ID. “Comparison of weighted product method and simple additive weighting in scholarship recipient selection: comparison of weighted product method and simple additive weighting in scholarship recipient selection”. Jurnal Mantik, 3(4), 337-347, 2020.
19. [19] Rafida V, Widiyatni W, Harpad B, Yulsilviana E. “Implementation of multi-attribute rating technique simple in selection of acceptance scholarship of PMDK (Case Study: STMIK Widya Cipta Dharma)”. International Journal of Modern Education & Computer Science, 13(1), 22-33, 2021.
20. [20] Rezaei J. “Best-worst multi-criteria decision-making method”. Omega, 53, 49-57, 2015.
21. [21] Saaty T. The Analytic Hierarchy Process: Planning, Priority Setting, Resources Allocation. 1st ed. London, England, McGraw-Hill, 1980.
22. [22] Bozbura FT, Beskese A. “Prioritization of organizational capital measurement indicators using fuzzy AHP”. International Journal of Approximate Reasoning, 44(2), 124-147, 2007.
23. [23] Oğuztimur S. “Why fuzzy analytic hierarchy process approach for transport problems?”. 51st European Regional Science Association Conference, Barcelona, Spain, 30 August-2 September 2011.
24. [24] Yazdani M, Zarate P, Zavadskas EK, Turskis Z. “A Combined Compromise Solution (CoCoSo) method for multi-criteria decision-making problems”. Management Decision, 57(9), 2501-2519, 2018.
25. [25] Peng X, Huang H. “Fuzzy decision making method based on CoCoSo with CRITIC for financial risk evaluation”. Technological and Economic Development of Economy, 26(4), 695-724, 2020.
26. [26] Mou Q, Xu Z, Liao H. “An intuitionistic fuzzy multiplicative best-worst method for multi-criteria group decision making”. Information Sciences, 374, 224-239, 2016.
27. [27] Ghaffari S, Arab A, Nafari J, Manteghi M. “Investigation and evaluation of key success factors in technological innovation development based on BWM”. Decision Science Letters, 6(3), 295-306, 2017.
28. [28] Bezerianos G. Market Choice Opportunities For Gas Sweetening Technologies. Ph.D Dissertation, Delft University of Technology, Delft, Netherlands, 2016.
29. [29] Rezaei J, Wang J, Tavasszy L. “Linking supplier development to supplier segmentation using Best Worst Method”. Expert Systems with Applications, 42(23), 9152-9164, 2015.
30. [30] Koçak H, Çağlar A, Öztaş GZ. “Euclidean Best–Worst method and its application”, International Journal of Information Technology & Decision Making, 17(5), 1587-1605, 2018.
31. [31] Rezaei J, Nispeling T, Sarkis J, Tavasszy L. “A supplier selection life cycle approach integrating traditional and environmental criteria using the best worst method”. Journal of Cleaner Production, 135, 577-588, 2016.
32. [32] Ren J, Liang H, Chan FT. “Urban sewage sludge, sustainability, and transition for Eco-City: Multi-Criteria sustainability assessment of technologies based on bestworst method”. Technological Forecasting and Social Change, 116, 29-39, 2016.
33. [33] Bakker SW. Improving The Performance of the Trolley Supply Chain With a Focus On Visibility Using Best-Worst Multi-Criteria Decision Making Method. MSc Thesis, Delft University of Technology, Amsterdam, Holland, 2014.
34. [34] Sadaghiani S, Ahmad KW, Rezaei J, Lóránt Tavasszy L. “Evaluation of external forces affecting supply chain sustainability in oil and gas ındustry using Best Worst Method”. International Mediterranean Gas and Oil Conference (MedGO), Mechref, Lebanon, 16-18 April 2015.
35. [35] Rezaei J, Hemmes A, Tavasszy L. “Multi-criteria decisionmaking for complex bundling configurations in surface transportation of air freight”. Journal of Air Transport Management, 61, 95-105, 2016.
36. [36] Gupta H, Barua MK. “Identifying enablers of technological innovation for Indian MSMEs using best–worst multi criteria decision making method”. Technological Forecasting and Social Change, 107, 69-79, 2016.
37. [37] Abadi F, Sahebi I, Arab A, Alavi A, Karachi H. “Application of best-worst method in evaluation of medical tourism development strategy”. Decision Science Letters, 7(1), 77-86, 2018.
38. [38] Ecer F. “Sustainability assessment of existing onshore wind plants in the context of triple bottom line: a BestWorst Method (BWM) based MCDM framework”. Environmental Science and Pollution Research, 28, 19677-19693, 2021.
39. [39] Ulutaş A. “The analysis of the importance of the criteria used in the selection of transport vehicle according to cargo companies by BWM”. Equinox Journal of Economics Business and Political Studies, 7(2), 127-140, 2020.
40. [40] Bilgiç S, Torğul B, Paksoy T. "Sürdürülebilir enerji yönetimi için BWM yöntemi ile yenilenebilir enerji kaynaklarının değerlendirilmesi". Verimlilik Dergisi, 2, 95-110, 2021.
41. [41] Arsu T, Uğuz Arsu Ş. “Personel seçim sürecinde kullanılan kriterlerin Best-Worst Metodu (BWM) ile değerlendirilmesi”. Üçüncü Sektör Sosyal Ekonomi Dergisi, 56(3), 1949-1967, 2021.
42. [42] Öz İ. "Decision making in evaluation and selection of launch site with the best and worst method". Gazi University Journal of Science, 35(4), 1521-1533, 2022.
43. [43] Akyüz G, Tosun Ö, Aka S. “Performance evaluation of nonlife insurance companies with Best-Worst Method and TOPSIS”. Uluslararası Yönetim İktisat ve İşletme Dergisi, 16(1), 108-125, 2020.
44. [44] You X, Chen T, Yang Q. “Approach to multi-criteria group decision-making problems based on the Best-WorstMethod and ELECTRE method”. Symmetry, 8(9), 1-16, 2016.
45. [45] Serrai W, Abdelli A, Mokdad L, Hammal Y. “An efficient approach for Web service selection”. Computers and Communication (ISCC), Messina, Italy, 27-30 June 2016.
46. [46] Abdulkareem KH, Arbaiy N, Zaidan AA, Zaidan BB, Albahri OS, Alsalem MA, Salih MM. “A novel multi-perspective benchmarking framework for selecting image dehazing intelligent algorithms based on BWM and group VIKOR techniques”. International Journal of Information Technology & Decision Making, 19, 1-49, 2020.
47. [47] Chitsaz N, Azarnivand A. “Water scarcity management in arid regions based on an extended multiple criteria technique”. Water Resource Management, 31, 233-250, 2017.
48. [48] Guo S, Zhao H. “Fuzzy best-worst multi-criteria decisionmaking method and its applications”. Knowledge-Based Systems, 121, 23-31, 2017.
49. [49] Ketabchi R, Ghaeli M. “An application of fuzzy BWM for risk assessment in offshore oil projects”. Journal of Project Management, 4(3), 233-240, 2019.
50. [50] Xu Y, Zhu X, Wen X, Herrera-Viedma E. “Fuzzy Best-Worst Method and its application in initial water rights allocation”. Applied Soft Computing, 101, 1-15, 2021.
51. [51] Aboutorab H, Saberi M, Asadabadi MR, Hussain O, Chang E. “ZBWM: The Z-number extension of Best Worst Method and its application for supplier development”. Expert Systems with Applications, 107, 115-125, 2018.
52. [52] Amoozad Mahdiraji H, Arzaghi S, Stauskis G, Zavadskas EK. “A hybrid fuzzy BWM-COPRAS method for analyzing key factors of sustainable architecture”. Sustainability 10(5), 1-26, 2018.
53. [53] Parhizgarsharif A, Lork A, Telvari A. “A hybrid approach based on the BWM-VIKOR and GRA for ranking facility location in construction site layout for Mehr project in Tehran”. Decision Science Letters, 8(3), 233-248, 2019.
54. [54] Kolagar M. “Adherence to urban agriculture in order to reach sustainable cities; a BWM– WASPAS approach”. Smart Cities, 2(1), 31-45, 2019.
55. [55] Arslanhan H, Tosun Ö. “Ulaştırma modu seçimi probleminin bütünleşik en iyi-en kötü ve WASPAS yöntemleriyle çözülmesi”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, 27(1), 13-23, 2021.
56. [56] Bahrami Y, Hassani H, Maghsoudi A. “BWM-ARAS: A new hybrid MCDM method for Cu prospectivity mapping in the Abhar area, NW Iran”. Spatial Statistics, 33, 1-23, 2019.
57. [57] Çakır E, Can M. “Best-worst yöntemine dayalı ARAS yöntemi ile dış kaynak kullanım tercihinin belirlenmesi: turizm sektöründe bir uygulama”. Atatürk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 23(3), 1273-1300, 2019.
58. [58] Çalık A. “Hedef pazar seçimi için hibrit BWM-ARAS karar verme modeli”. Manisa Celal Bayar Üniversitesi Sosyal Bilimler Dergisi, 18(3), 196-210, 2020.
59. [59] Kolagar M, Hosseini SMH, Felegari R, Fattahi P. “Policymaking for renewable energy sources in search of sustainable development: a hybrid DEA-FBWM approach”. Environment Systems and Decisions, 40, 485-509, 2019.
60. [60] Wu Q, Zhou L, Chen Y, Chen H. “An integrated approach to green supplier selection based on the interval type-2 fuzzy best-worst and extended VIKOR methods”. Information Sciences, 502, 394-417, 2019.
61. [61] Liu A, Ji X, Lu H, Liu H. “The selection of 3PRLs on selfservice mobile recycling machine: Interval-valued pythagorean hesitant fuzzy best-worst multi-criteria group decision-making”. Journal of Cleaner Production, 230, 734-750, 2019.
62. [62] Behzad M, Zolfani SH, Pamucar D, Behzad M. “A comparative assessment of solid waste management performance in the Nordic countries based on BWMEDAS”. Journal of Cleaner Production, 266, 1-11, 2020.
63. [63] Muravev D, Mijic N. “A novel integrated provider selection multicriteria model: the BWM MABAC model”. Decision Making: Applications in Management and Engineering, 3(1), 60-78, 2020.
64. [64] Telli G, Ayçin E. "Öğretmen seçim sürecinde en iyi-en kötü ve Mabac yöntemlerinin bütünleşik olarak kullanılması". TroyAcademy, 6, 733-750, 2021.
65. [65] Özdağoğlu A, Keleş MK, Işıldak B. “Isparta Süleyman Demirel havalimanını kullanan havayolu firmaları performanslarının BWM, MAIRCA VE MABAC ile değerlendirilmesi”. Uluslararası İktisadi ve İdari İncelemeler Dergisi, 29, 175-194, 2020.
66. [66] Nabeeh NA, Abdel-Monem A, Abdelmouty A. “A novel methodology for assessment of hospital service according to BWM, MABAC, PROMETHEE II”. Neutrosophic Sets and Systems, 31(1), 63-79, 2020.
67. [67] Mohammadi M, Rezaei J. “Bayesian best-worst method: A probabilistic group decision making model”. Omega, 96, 1-8, 2020.
68. [68] Akbari R, Dabbagh R, Ghoushchi SJ. “HSE risk prioritization of molybdenum operation process using extended FMEA approach based on Fuzzy BWM and Z-WASPAS”. Journal of Intelligent & Fuzzy Systems, 38(4), 5157-5173, 2020.
69. [69] Ishizaka A, Resce G. “Best-Worst PROMETHEE method for evaluating school performance in the OECD's PISA project”. Socio-Economic Planning Sciences, 73, 1-7, 2021.
70. [70] Karakış E. “BWM ve bulanık TODIM yöntemleri ile perakende sektöründe tedarikçi seçiminin gerçekleştirilmesi”. Uluslararası İktisadi ve İdari İncelemeler Dergisi, 34, 37-60, 2022.
71. [71] Yucesan M, Gul M, Celik E. “A holistic FMEA approach by fuzzy-based Bayesian network and best–worst method”. Complex and Intelligent Systems, 7, 1547-1564, 2021.
72. [72] Zolfani SH, Chatterjee P, Yazdani M. “A structured framework for sustainable supplier selection using a combined BWM-CoCoSo model”. International Scientific Conference in Business, Management and Economics Engineering, Vilnius, Lithuania, 9-10 May 2019.
73. [73] Alrasheedi M, Mardani A, Mishra AR, Streimikiene D, Liao H, Al‐nefaie AH. “Evaluating the green growth indicators to achieve sustainable development: A novel extended interval‐valued intuitionistic fuzzy‐combined compromise solution approach”. Sustainable Development, 29(1), 120-142, 2021.
74. [74] Torkayesh AE, Pamucar D, Ecer F, Chatterjee P. “An integrated BWM-LBWA-CoCoSo framework for evaluation of healthcare sectors in Eastern Europe”. Socio-Economic Planning Sciences, 78, 1-12, 2021.
75. [75] Ecer F, Pamucar D. “Sustainable supplier selection: A novel integrated fuzzy best worst method (F-BWM) and fuzzy CoCoSo with Bonferroni (CoCoSo’B) multi-criteria model”. Journal of Cleaner Production, 266, 1-18, 2020.
76. [76] Zavadskas EK, Turskis Z, Antucheviciene J, Zakarevicius A. “Optimization of weighted aggregated sum product assessment”. Elektronika ir elektrotechnika, 122(6), 3-6, 2012.
77. [77] Aytekin A, Gündoğdu HG. “OECD ve AB üyesi ülkelerin sürdürülebilir yönetişim düzeylerine göre SWARA tabanlı TOPSIS-SORT-B ve WASPAS yöntemleriyle incelenmesi”. Öneri Dergisi, 16(56), 943-971, 2021.
78. [78] Ozdagoglu A, Ulutas A, Keles MK. “The ranking of Turkish universities with CoCoSo and MARCOS”. Journal of Economics, Business and Organization Research, 374-392, 2020.
79. [79] Khan S, Haleem A. “Investigation of circular economy practices in the context of emerging economies: a CoCoSo approach”. International Journal of Sustainable Engineering, 14(3), 357-367, 2021.
80. [80] Erceg Ž, Starcevic V, Pamucar D, Mitrovic G, Stevi´c Ž, Žiki´c S. “A new model for stock management in order to rationalize costs: ABC-FUCOM-interval rough CoCoSo model”. Symmetry, 11, 1-29, 2019.
81. [81] Barua A, Jeet S, Kumar Bagal D, Satapathy P, Kumar Agrawal P. “Evaluation of mechanical behavior of hybrid natural fiber reinforced nano sic particles composite using hybrid Taguchi-Cocoso method”. International Journal of Innovative Technology and Exploring Engineering (IJITEE), 8(10), 3341-3345, 2019.
82. [82] Wen Z, Liao H, Mardani A, Al-Barakati A. “A hesitant fuzzy linguistic Combined Compromise Solution method for multiple criteria decision making”. International Conference on Management Science and Engineering Management, Ontario, Canada, 5-8 August 2019.
83. [83] Ecer F, Pamucar D. “Sustainable supplier selection: A novel integrated fuzzy best worst method (F-BWM) and fuzzy CoCoSo with Bonferroni (CoCoSo’B) multi-criteria model”. Journal of Cleaner Production, 266, 1-18, 2020.
84. [84] Akgül Y. “Borsa İstanbul’da işlem gören ticari bankaların finansal performansının bütünleşik CRITIC CoCoSo modeliyle analizi”. Ekonomi ve Finansal Araştırmalar Dergisi, 3(2), 71-90, 2022.
85. [85] Peng X, Zhang X, Luo Z. “Pythagorean fuzzy MCDM method based on CoCoSo and CRITIC with score function for 5G industry evaluation”. Artificial Intelligence Review, 53, 3813–3847, 2020.
86. [86] Peng X, Smarandache F. “A decision-making framework for China’s rare earth industry security evaluation by neutrosophic soft CoCoSo method”. Journal of Intelligent & Fuzzy Systems, 39(5), 7571-7585, 2020.
87. [87] Ulutaş A, Karakuş CB, Topal A. “Location selection for logistics center with fuzzy SWARA and CoCoSo methods”. Journal of Intelligent & Fuzzy Systems, 38(4), 4693-4709, 2020.
88. [88] Stanujkic D, Popovic G, Zavadskas EK, Karabasevic D, Binkyte-Veliene A. “Assessment of progress towards achieving sustainable development goals of the “Agenda 2030” by using the CoCoSo and the Shannon Entropy methods: the case of the EU Countries”. Sustainability, 12(14), 1-16, 2020.
89. [89] Topal A. “Çok kriterli karar verme analizi ile elektrik üretim şirketlerinin finansal performans analizi: Entropi tabanlı CoCoSo yöntemi”. Business and Management Studies: An International Journal, 9(2), 532-546, 2021.
90. [90] Lai H, Liao H, Wen Z, Zavadskas EK, Al-Barakati A. “An improved CoCoSo Method with a maximum variance optimization model for cloud service provider selection”. Engineering Economics, 31(4), 411-424, 2020.
91. [91] Pala O. “BIST inşaat endeksinde bütünleşik CCSD-COCOSO tabanlı finansal performans analizi”. Afyon Kocatepe Üniversitesi Sosyal Bilimler Dergisi, 23(4), 1500-1513, 2021.
92. [92] Liao H, Qin R, Wu D, Yazdani M, Zavadskas E.K. “Pythagorean fuzzy combined compromise solution method integrating the cumulative prospect theory and combined weights for cold chain logistics distribution center selection”. International Journal of Intelligent Systems, 35(12), 2009-2031, 2020.
93. [93] Luo Y, Zhang X, Qin Y, Yang Z, Liang Y. “Tourism attraction selection with sentiment analysis of online reviews based on probabilistic linguistic term sets and the IDOCRIWCOCOSO model”. International Journal of Fuzzy Systems, 23(1), 295-308, 2021.
94. [94] Vikas C, Mishra A. “Analyzing the critical success enablers of industry 4.0 using hybrid fuzzy AHP-CoCoSo method”. Journal of Industrial Integration and Management, 7(4), 493-514, 2022.
95. [95] Gençkaya Ö, Gündoğdu HG, Aytekin A. “Büyükşehir belediyeleri web sitelerinin yönetişim ilkeleri açısından değerlendirilmesi”. Eskişehir Osmangazi Üniversitesi İktisadi ve İdari Bilimler Dergisi, 16(3), 705-726, 2021.
96. [96] Peng X, Krishankumar R, Ravichandran KS. “A novel interval-valued fuzzy soft decision-making method based on CoCoSo and CRITIC for intelligent healthcare management evaluation”. Soft Computing, 25, 4213-4241, 2021.
97. [97] Akıllı K, İpekçi Çetin E. “Selection of scholarship students in higher education with VIKOR method”. International Journal of Assessment Tools in Education, 7(3), 379-391, 2020.