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Dergiler / Tarım Ekonomisi Dergisi / 2026 / Cilt: 32 Sayı: 1

Tarım sigortasında firma seçimi için Bulanık Entropi ve CRADIS Tabanlı Çok Kriterli Karar Verme Modeli

A Fuzzy Entropy and CRADIS-Based Multi-Criteria Decision-Making Model for insurance company selection in agricultural insurance

Alkan Durmuş(DOKUZ EYLÜL ÜNİVERSİTESİ)0000-0002-5806-9962
Sayfa
81–96
Yayın Tarihi
2026-06-26
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

Bulgular: Analiz sonuçlarına göre, firmalar arasında özellikle hizmet kapsamı, prim bedeli, tazminat ödeme süresi ve müşteri memnuniyeti kriterleri açısından belirgin farklar gözlemlenmiştir.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:Amaç: Bu çalışmanın amacı, Türkiye'de faaliyet gösteren tarım sigortası firmalarının etkinliğini değerlendirmek ve karar vericilere uygun firma seçimi konusunda sistematik bir yaklaşım sunmaktır.
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Temel Bulgular & Veri:Bulanık mantık, karar vericilerin subjektif değerlendirmelerini daha gerçekçi bir biçimde modellemeye olanak tanımıştır.
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Sonuç & Katkı:Bulgular: Analiz sonuçlarına göre, firmalar arasında özellikle hizmet kapsamı, prim bedeli, tazminat ödeme süresi ve müşteri memnuniyeti kriterleri açısından belirgin farklar gözlemlenmiştir.
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Bulanık Cradis · Bulanık Entropi · çok kriterli karar verme

Özet

Amaç: Bu çalışmanın amacı, Türkiye'de faaliyet gösteren tarım sigortası firmalarının etkinliğini değerlendirmek ve karar vericilere uygun firma seçimi konusunda sistematik bir yaklaşım sunmaktır. Tarım sektörünün doğası gereği karşı karşıya kaldığı belirsizliklerin yönetiminde sigorta firmalarının performansı büyük önem taşımaktadır. Tasarım/Metodoloji/Yaklaşım: Çalışmada, çok kriterli karar verme (ÇKKV) yöntemlerinden Bulanık Entropi ve CRADIS yöntemleri bir arada kullanılmıştır. Öncelikle uzman görüşleriyle belirlenen kriterlerin önem ağırlıkları Bulanık Entropi yöntemiyle hesaplanmış, ardından firma alternatifleri CRADIS yöntemiyle sıralanmıştır. Bulanık mantık, karar vericilerin subjektif değerlendirmelerini daha gerçekçi bir biçimde modellemeye olanak tanımıştır. Bulgular: Analiz sonuçlarına göre, firmalar arasında özellikle hizmet kapsamı, prim bedeli, tazminat ödeme süresi ve müşteri memnuniyeti kriterleri açısından belirgin farklar gözlemlenmiştir. Elde edilen sıralama, karar vericilerin tercihlerini nesnel verilere dayandırmasına olanak tanımaktadır. Özgünlük/Değer: Bu çalışma, Türkiye’de tarım sigortası firmalarının değerlendirilmesine yönelik çok kriterli karar verme temelli nadir çalışmalardan biridir. Bulanık Entropi ve CRADIS yöntemlerinin birlikte kullanılması, sektördeki belirsizlikleri dikkate alan bütüncül bir değerlendirme sunmaktadır. Sonuçlar hem çiftçiler hem de politika yapıcılar için karar destek aracı niteliği taşımaktadır.

Abstract

Purpose: The aim of this study is to evaluate the performance of agricultural insurance companies operating in Türkiye and to provide a systematic approach for decision-makers in selecting the most appropriate firm. The performance of insurance providers plays a crucial role in managing the inherent uncertainties of the agricultural sector. Design/Methodology/Approach: This research integrates two multi-criteria decision-making (MCDM) techniques: Fuzzy Entropy and CRADIS. Initially, the importance weights of evaluation criteria—identified through expert opinions—were calculated using the Fuzzy Entropy method. Subsequently, the insurance firms were ranked via the CRADIS method. The fuzzy logic approach enabled the modeling of subjective judgments in a more realistic and reliable manner. Findings: The analysis revealed significant differences among firms, particularly in terms of service coverage, premium costs, compensation payment periods, and customer satisfaction. The resulting rankings provide decision-makers with an objective basis for evaluating and selecting insurance providers. Originality/Value: This study is one of the few applications of MCDM approaches in the context of agricultural insurance firm evaluation in Türkiye. The integration of Fuzzy Entropy and CRADIS offers a comprehensive framework that accounts for uncertainty in decision-making. The findings contribute to both practical decision support for farmers and strategic planning for policymakers.

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Bu Makaleye Atıf Yap

Durmuş, A. (2026). Tarım sigortasında firma seçimi için Bulanık Entropi ve CRADIS Tabanlı Çok Kriterli Karar Verme Modeli. Tarım Ekonomisi Dergisi, Cilt: 32 Sayı: 1, 81–96. https://doi.org/10.24181/tarekoder.1727881

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Kaynakça (97)

  1. Abdi, M. J., Raffar, N., Zulkafli, Z., Nurulhuda, K., Rehan, B. M., Muharam, F. M.,. & Tangang, F. (2022), Index-based insurance and hydroclimatic risk management in agriculture: A systematic review of index selection and yield-index modelling methods. International Journal of Disaster Risk Reduction, 67, 102653.
  2. Aikhuele, D. and Turan, F. (2016), An improved methodology for multi-criteria evaluations in the shipping industry. Brodogradnja, 67(3), 59-72.
  3. Ak, D., RD, W., HH, Y., Malekmohammadi, B., & Ar, Y. (2018), Environmental impact assessment (eia) of a gold mine tailing through the multi-criteria decision-making tool. Journal of Civil Engineering and Environmental Sciences, 061-066.
  4. Aktan HE, Samut PK (2013) Agricultural performance evaluation by integrating fuzzy AHP and VIKOR methods. Int J Appl Decis Sci 6(4):324–344.
  5. Alghamdi, M., Alshehri, N., & Akram, M. (2018), Multi-criteria decision-making methods in bipolar fuzzy environment. International Journal of Fuzzy Systems, 20(6), 2057-2064.
  6. Antón J (2008) Agricultural policies and risk management: a holistic approach. In: 108th EAAE seminar ‘income stabilisation in a changing agricultural world: policy and tools’, Warsaw, Poland.
  7. Aydın, B., Özkan, E., Hurma, H. ve Yılmaz, F. (2016), Kırklareli ve Edirne İllerinde Üreticilerin Ürün Sigortası Uygulamalarına Yaklaşımı, Derim, 33-2, 249-262.
  8. Aydın, B., Özkan, E., Kayalı, E., Atav, V., Gürbüz, M. A., Kurşun, İ., & Kayhan, İ. E. (2023), Examination of Soil Analysis Applications and Soil Analysis Subsidies in terms of Producers in Edirne and Tekirdağ Provinces. Tekirdağ Ziraat Fakültesi Dergisi, 20(1), 25-40.
  9. Baležentis, T., Morkūnas, M., Žičkienė, A., Volkov, A., Ribašauskienė, E., & Štreimikienė, D. (2021), Policies for rapid mitigation of the crisis’ effects on agricultural supply chains: a multi-criteria decision support system with monte carlo simulation. Sustainability, 13(21), 11899.
  10. Banihabib ME, Shabestari MH (2016) Fuzzy hybrid MCDM model for ranking the agricultural water demand management strategies in arid areas. Water Resour Manage 31(1):495–513.
  11. Başer, U., Bozoğlu, M., & Mennan, H. (2023), Çiftçilerin tarım sigortası yaptırmalarını etkileyen faktörler. Akademik Ziraat Dergisi, 12(1), 77-82. https://doi.org/10.29278/azd.1168328.
  12. Belissa, T., Bulte, E., Cecchi, F., Gangopadhyay, S., & Lensink, R. (2019), Liquidity constraints, informal institutions, and the adoption of weather insurance: A randomized controlled Trial in Ethiopia. Journal of Development Economics, 140, 269-278.
  13. Chen, T. Y., & Li, C. H. (2011), Objective weights with intuitionistic fuzzy entropy measures and computational experiment analysis. Applied Soft Computing, 11(8), 5411-5423.
  14. Çukur F, Saner G 2008. Malatya İli Kayısı Üretiminde Riskin Ölçülmesi ve Riske Karşı Oluşturulabilecek Stratejiler. Ege Üniversitesi Ziraat Fakültesi Dergisi, 46 (1): 33-42.
  15. Dass, B., Tomar, V. P., & Kumar, K. (2021), Generalized Parametric Exponential Entropy Measure of degree α and β on Fuzzy Set. Turkish Journal of Computer and Mathematics Education, 12(11), 459-468.
  16. Demeke M, Kiermeier M, Sow M (2016) Agriculture and food insecurity risk management in Africa. Food and Agriculture Organization of the United Nations, Rome.
  17. Du, X., Feng, H., & Hennessy, D. A. (2017), Rationality of choices in subsidized crop insurance markets. American Journal of Agricultural Economics, 99(3), 732-756.
  18. Enjolras, G., & Sentis, P. (2011), Crop insurance policies and purchases in France. Agricultural Economics, 42(4), 475-486.
  19. Ertan, A. ve Gök, M. (2012), Eğirdir İlçesi Tarım Üreticilerinin Tarım Sigortası Yaptırmaya Karar Verme Sürecinde Etkili Olan Faktörlerin Analizi, ODÜ Sosyal Bilimler Enstitüsü Sosyal Bilimler Araştırmaları Dergisi, 3-5, 66-76.
  20. Fang, L., Hu, R., Mao, H., & Chen, S. (2021), How crop insurance influences agricultural green total factor productivity: Evidence from Chinese farmers. Journal of Cleaner Production, 321, 128977.
  21. Farzaneh, M, Allahyari MS, Damalas CA, Seidavi A 2017. CropInsurance as a Risk Management Tool in Agriculture: The Case of Silk Farmer in Nothern Iran. Land Use Policy, 64: 225-232.
  22. Fleckenstein, M., Lythgoe, A., Lu, J., Thompson, N., Doering, O., Harden, S.,. & Prokopy, L. (2020), Crop insurance: A barrier to conservation adoption? Journal of Environmental Management, 276, 111223.
  23. Ghosh, R. K., Gupta, S., Singh, V., & Ward, P. S. (2021), Demand for crop insurance in developing countries: New evidence from India. Journal of agricultural economics, 72(1), 293-320.
  24. Gómez-Limón JA, Arriaza M, Riesgo L (2003) An MCDM analysis of agricultural risk aversion. Eur J Oper Res 151(3):569–585.
  25. Gu, H. Y., & Wang, C. W. (2020), Impacts of the COVID-19 pandemic on vegetable production and countermeasures from an agricultural insurance perspective. Journal of Integrative Agriculture, 19(12), 2866-2876.
  26. Hao, M., Lu, C., Zhou, X., & Xu, J. (2023), How agricultural farmers respond to risks during the COVID-19 Pandemic: an exploration through the dual social capitals approach. Agriculture, 13(2), 485.
  27. Hassanpour A, Pasha M, Susana L, Rahmanian N, Santomaso AC,Ghadiri M 2013. Analaysis of Seeded Granulation in High Shear Granulators by Discrete Element Method, Powder Technol. 238:5055.
  28. Hayran, S., Berk, A., & İMAMOĞLU, H. (2020), Yem bitkisi üreticilerinin tarım sigortası yaptırma kararlarına etki eden faktörler: balıkesir i̇li örneği. Ziraat Mühendisliği, 0(369), 22-29. https://doi.org/10.33724/zm.691105.
  29. İkikat Tümer, E., Ağır, H.B. ve Uslu, Z. (2019), Çiftçilerin Tarım Sigortası Yaptırma İstekliliği: Konya İli Ilgın İlçesi Örneği, KSÜ Tarım ve Doğa Dergisi, 22-4, 571-576.
  30. Jha, N., Prashar, D., Khalaf, O. I., Alotaibi, Y., Alsufyani, A., & Alghamdi, S. (2021), Blockchain based crop insurance: a decentralized insurance system for modernization of Indian farmers. Sustainability, 13(16), 8921.
  31. Joshi, D. and Kumar, S. (2014), Intuitionistic fuzzy entropy and distance measure based topsis method for multi-criteria decision making. Egyptian Informatics Journal, 15(2), 97-104.
  32. Jørgensen, S. L., Termansen, M., & Pascual, U. (2020), Natural insurance as condition for market insurance: Climate change adaptation in agriculture. Ecological Economics, 169, 106489.
  33. Kızılay, H. A. B. Ö. H. (2006), Antalya ilinde tarımsal üretimde risk yönetimi ve tarım sigortası uygulamaları. Tekirdağ Ziraat Fakültesi Dergisi, 3(2), 93-103.
  34. Kisaka-Lwayo M, Obi A (2012) Risk perceptions and management strategies by smallholder farmers in KwaZulu-Natal Province, South Africa. Int J Agric Manag 01(3):28–39.
  35. Kramer, B., Hazell, P., Alderman, H., Ceballos, F., Kumar, N., & Timu, A. G. (2022), Is agricultural insurance fulfilling its promise for the developing world? A review of recent evidence. Annual Review of Resource Economics, 14(1), 291-311.
  36. Krstić, B., Vasiljević, Z., & Nedeljković, M. (2017), Insurance contract as the basis for the safety of agricultural producers in the Republic of Srpska. Економика пољопривреде, 64(4), 1555-1570.
  37. Kurdyś-Kujawska, A., Sompolska-Rzechuła, A., Pawłowska-Tyszko, J., & Soliwoda, M. (2021), Crop insurance, land productivity and the environment: A way forward to a better understanding. Agriculture, 11(11), 1108.
  38. Lazarashouri, H. and Najafi, E. (2024), Enhancing emergency department efficiency through simulation and fuzzy multi-criteria decision-making integration. Journal of Operational and Strategic Analytics, 2(1), 56-71.
  39. Lee, S., & Ting, T. O. (2013), Uncertainty evaluation via fuzzy entropy for multiple facts. International Journal of Electronic Commerce Studies, 313-322.
  40. Lobell, D. B., & Gourdji, S. M. (2012), The influence of climate change on global crop productivity. Plant physiology, 160(4), 1686-1697.
  41. Lyu, K., & Barré, T. J. (2017), Risk aversion in crop insurance program purchase decisions: Evidence from maize production areas in China. China Agricultural Economic Review, 9(1), 62-80.
  42. Mahul, O., & Stutley, C. J. (2010), Government Support to Agricultural Insurance: Challenges and Options for Developing Countries. World Bank Publications.
  43. Mao, J., Zhao, Y., & Ma, C. (2016), A new type of compositive information entropy for ivifs and its applications. Mathematical Problems in Engineering, 2016, 1-13.
  44. Meuwissen MPM, Huirne RBM, Hardaker JB (2001) Risk and risk management: an empirical analysis of Dutch livestock farmers. Livest Prod Sci 69(1):43–53.
  45. Metin, E. (2021), Türkiye’de çiftçilerin gelir güvencesizliği riskine karşı “tarsi̇m”: manisa örneği. Adnan Menderes Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 8(1), 27-37. https://doi.org/10.30803/adusobed.878390.
  46. Morales C, Garrido A, Pálinkás P (2008) Risks perceptions and risk management instruments in the European Union: Do farmers have a clear idea of what they need ? In: 12th Congress of the European Association of Agricultural Economists, pp 1–8.
  47. Möhring, N., Ingold, K., Kudsk, P., Martin-Laurent, F., Niggli, U., Siegrist, M., Finger, R. (2020), Pathways for advancing pesticide policies. Nature food, 1(9), 535-540.
  48. Mukhametzyanov, I. (2021), Specific character of objective methods for determining weights of criteria in MCDM problems: Entropy, CRITIC and SD. Decision Making: Applications in Management and Engineering, 4(2), 76-105.
  49. Müller, B., Johnson, L., & Kreuer, D. (2017), Maladaptive outcomes of climate insurance in agriculture. Global Environmental Change, 46, 23-33.
  50. Nedeljković, M., Bajagić, M., & Dimitrijević, L. (2023), Selection of the location of the distribution center for agricultural products. Ekonomika Poljoprivrede, 70(4), 1075-1087.
  51. Nedeljković, M., Puška, A., Doljanica, S., Virijević Jovanović, S., Brzaković, P., Stević, Ž., & Marinkovic, D. (2021), Evaluation of rapeseed varieties using novel integrated fuzzy PIPRECIA–Fuzzy MABAC model. Plos one, 16(2), e0246857.
  52. Njegomir, V., & Rihter, J. D. (2018), The problem of the demand for crop insurance: The case of Serbia. Економика пољопривреде, 65(3), 995-1014.
  53. Orojloo M, Shahdany SMH, Roozbahani A (2018). Developing an integrated risk management framework for agricultural water conveyance and distribution systems within fuzzy decision making approaches. Sci Total Environ, 627:1363–1376.
  54. Pamučar, D., Tarle, S., & Parezanović, T. (2018), New hybrid multi-criteria decision-making dematel-mairca model: sustainable selection of a location for the development of multimodal logistics centre. Economic Research-Ekonomska Istraživanja, 31(1), 1641-1665.
  55. Pauly, M. V. (2000), Insurance reimbursement. In Handbook of health economics,Vol. 1, pp. 537-560.
  56. Pehlivan, E., & Akpınar, Ö. (2022), Çok kriterli karar verme teknikleri ile TARSİM özelinde bir uygulama. Başkent Üniversitesi Ticari Bilimler Fakültesi Dergisi, 6(2), 132-151.
  57. Pezikoğlu, F., Ergun, M. E., Öztürk, M., Altıntaş, A., & Uçar, M. (2012), Bursa İlinde bitkisel ürün sigortası uygulamalarına yönelik çiftçi yaklaşımı. 10. Ulusal Tarım Ekonomisi Kongresi, 1098-1102.
  58. Peter, R., & Ying, J. (2020), Do you trust your insurer? Ambiguity about contract nonperformance and optimal insurance demand. Journal of Economic Behavior & Organization, 180, 938-954.
  59. Piljan, I., Cogoljević, D., & Piljan, T. (2018), Insurance as a Factor for the Development of the Agricultural Sector in the Republic of Serbia. International Review, (3-4), 131-138.
  60. Priyadarshini, P., & Abhilash, P. C. (2020), Policy recommendations for enabling transition towards sustainable agriculture in India. Land use policy, 96, 104718.
  61. Puška, A., Lukić, M., Božanić, D., Nedeljković, M., & Hezam, I. (2023), Selection of an insurance company in agriculture through hybrid multi-criteria decision-making. Entropy, 25(6), 959.
  62. Puška, A., Nedeljković, M., Prodanović, R., Vladisavljević, R., & Suzić, R. (2022), Market assessment of pear varieties in serbia using fuzzy cradis and critic methods. Agriculture, 12(2), 139.
  63. Puška, A., Nedeljković, M., Stojanović, I., & Božanić, D. (2023), Application of fuzzy trust cradis method for selection of sustainable suppliers in agribusiness. Sustainability, 15(3), 2578.
  64. Puška, A., Stević, Ž., & Pamučar, D. (2022), Evaluation and selection of healthcare waste incinerators using extended sustainability criteria and multi-criteria analysis methods. Environment, Development and Sustainability, 1-31.
  65. Rajkumar, P., & Kannan, N. (2014), Factors Affecting Customer's Preferences for Selection of Life Insurance Companies: An Empirical Study with Reference to Tamilnadu. International Journal of Accounting and Business Management, 2(1), 87-95.
  66. Rezaei, J. (2015), Best-worst multi-criteria decision-making method. Omega, 53, 49-57.
  67. Siddiqui, M. H., & Sharma, T. G. (2010), Analyzing customer satisfaction with service quality in life insurance services. Journal of targeting, measurement and analysis for marketing, 18(3), 221-238.
  68. Sihem, E. (2017), Economic and socio-cultural determinants of agricultural insurance demand across countries. Journal of the Saudi Society of Agricultural Sciences, 18(2), 177-187.
  69. Soleimani, F., Meshkani, F., & Naami, A. (2013), An exploration study to detect important factors influencing insurance firms. Management Science Letters, 3(11), 2691-2698.
  70. Stojanović, Ž., Rakonjac-Antić, T., & Koprivica, M. (2019), Farmers’willingness To Purchase Crop Insurance: Evidence From Wheat And Raspberry Sectors in Serbia. Економика пољопривреде, 66(4), 1107-1125.
  71. Şahin, A. ve Miran, B. (2007), Çiftçi Algılarına Göre Bitkisel Ürünlerin Risk Haritası: Bayındır İlçesi Örneği, Ege Üniversitesi Ziraat Fakültesi Dergisi, 44-3, 59-74.
  72. Tahamipour, M., Zaker, M. R., & Abdollahi, M. (2021), Investigating the effect of insurance on the total productivity of agricultural production factors: Analysis based on index number approach. International Journal of New Political Economy, 2(1), 231-250.
  73. TARSIM. (2023), Annual Report 2023. https://www.tarsim.gov.tr/dergi/faaliyet-raporlari/en-2023 (Erişim Tarihi:05/05/2025).
  74. Tekin, A., & Karlı, B. (2021), Denizli ili Çivril ilçesinde elma üretimi yapan tarım işletmelerinde üreticilerin tarım sigortası yaptırma tercihleri. Mustafa Kemal Üniversitesi Tarım Bilimleri Dergisi, 26(1), 8-19.
  75. Tekin, A., Karli, B., & Gul, M. (2017), Development of implementation of agricultural insurance in Turkey. Scientific Papers: Management, Economic Engineering in Agriculture & Rural Development, 17(2), 355-364.
  76. Terin, M. ve Aksoy, A. (2015), Devlet Destekli Bitkisel Ürün Sigortası Uygulama Sonuçları Üzerine Bir Araştırma: Ortadoğu Anadolu (TRB) Bölgesi Örneği, ÇOMÜ Ziraat Fakültesi Dergisi, 3-2, 35–43.
  77. Tien, D., Trung, D., & Thien, N. (2022), Comparison of multi-criteria decision making methods using the same data standardization method. Strojnícky Časopis- Journal of Mechanical Engineering, 72(2), 57-72. https://doi.org/10.2478/scjme-2022-0016.
  78. Toledo R, Engler A, Ahumada V (2011) Evaluation of risk factors in agriculture: an application of the analytical hierarchical process (AHP) methodology. Chil J Agric Res 71(1):114–121.
  79. Valahzaghard, M. K., & Ferdousnejhad, M. (2013), Ranking insurance firms using AHP and Factor Analysis. Management Science Letters, 3(3), 937-942.
  80. Yazgı, F. E. and Olhan, E. (2018), Türkiye tarım sigortası sisteminde görülen sorunlar ve alternatif model arayışı. Adnan Menderes Üniversitesi Ziraat Fakültesi Dergisi, 15(1), 39-45. https://doi.org/10.25308/aduziraat.341134.
  81. Hayran, S., Berk, A., & İmamoğlu, H. (2020), Yem bitkisi üreticilerinin tarım sigortası yaptırma kararlarına etki eden faktörler: balıkesir i̇li örneği. Ziraat Mühendisliği, 0(369), 22-29. https://doi.org/10.33724/zm.691105.
  82. Wang YM, Yang JB, Xu DL, Chin KS (2006) On the centroids of fuzzy numbers. Fuzzy Sets Syst 157(7):919–926.
  83. Wei, C., Yan, F., & Rodríguez, R. (2016), Entropy measures for hesitant fuzzy sets and their application in multi-criteria decision-making. Journal of Intelligent & Fuzzy Systems, 31(1), 673-685.
  84. Xiao, Y., & Yao, J. (2019), Double trigger agricultural insurance products with weather index and yield index. China Agricultural Economic Review, 11(2), 299-316.
  85. Wu, X., Wu, B., Sun, J., & Yang, N. (2016), Classification of apple varieties using near infrared reflectance spectroscopy and fuzzy discriminant c‐means clustering model. Journal of Food Process Engineering, 40(2).
  86. Xu, M., Bai, C., Ши, Л., Puška, A., Štilić, A., & Stević, Ž. (2023), Assessment of mountain tourism sustainability using integrated fuzzy mcdm model. Sustainability, 15(19), 14358.
  87. Yazgı, F.E. ve Olhan, E. (2018), Türkiye Tarım Sigortası Sisteminde Görülen Sorunlar ve Alternatif Model Arayışı, ADÜ Ziraat Dergisi, 15-1, 39-45.
  88. Yazgı, F. E. and Olhan, E. (2017), Gelişmiş ülkeler ve türkiye'de tarım sigortası sistemlerinin karşılaştırılması. Tarım Ekonomisi Dergisi, 23(2), 231-239. https://doi.org/10.24181/tarekoder.369424.
  89. Yu, B., Zhao, X., Zheng, M., Yuan, X., & Hou, B. (2022), Entropy on intuitionistic fuzzy sets and hesitant fuzzy sets. Journal of Mathematics, 2022(1), 1585079.
  90. Yu, J., & Sumner, D. A. (2018), Effects of subsidized crop insurance on crop choices. Agricultural Economics, 49(4), 533-545.
  91. Yuan, J., Chen, Z., & Wu, M. (2023), A novel distance measure and cradis method in picture fuzzy environment. International Journal of Computational Intelligence Systems, 16(1).
  92. Zeleny, M. (Ed.). (2012), Multiple criteria decision making Kyoto 1975 (Vol. 123). Springer Science & Business Media.
  93. Zeng, W. and Guo, P. (2008), Normalized distance, similarity measure, inclusion measure and entropy of interval-valued fuzzy sets and their relationship. Information Sciences, 178(5), 1334-1342.
  94. Zhang, H., & Yang, S. (2016), Inclusion measure for typical hesitant fuzzy sets, the relative similarity measure and fuzzy entropy. Soft Computing, 20, 1277-1287.
  95. Abdi, M. J., Raffar, N., Zulkafli, Z., Nurulhuda, K., Rehan, B. M., Muharam, F. M.,. & Tangang, F. (2022), Index-based insurance and hydroclimatic risk management in agriculture: A systematic review of index selection and yield-index modelling methods. International Journal of Disaster Risk Reduction, 67, 102653.
  96. Fleckenstein, M., Lythgoe, A., Lu, J., Thompson, N., Doering, O., Harden, S.,. & Prokopy, L. (2020), Crop insurance: A barrier to conservation adoption? Journal of Environmental Management, 276, 111223.
  97. Pauly, M. V. (2000), Insurance reimbursement. In Handbook of health economics,Vol. 1, pp. 537-560.