{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,6]],"date-time":"2026-04-06T10:19:07Z","timestamp":1775470747921,"version":"3.50.1"},"reference-count":54,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2023,6,20]],"date-time":"2023-06-20T00:00:00Z","timestamp":1687219200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>Crop insurance is used to reduce risk in agriculture. This research is focused on selecting an insurance company that provides the best policy conditions for crop insurance. A total of five insurance companies that provide crop insurance services in the Republic of Serbia were selected. To choose the insurance company that provides the best policy conditions for farmers, expert opinions were solicited. In addition, fuzzy methods were used to assess the weights of the various criteria and to evaluate insurance companies. The weight of each criterion was determined using a combined approach based on fuzzy LMAW (the logarithm methodology of additive weights) and entropy methods. Fuzzy LMAW was used to determine the weights subjectively through expert ratings, while fuzzy entropy was used to determine the weights objectively. The results of these methods showed that the price criterion received the highest weight. The selection of the insurance company was made using the fuzzy CRADIS (compromise ranking of alternatives, from distance to ideal solution) method. The results of this method showed that the insurance company DDOR offers the best conditions for crop insurance for farmers. These results were confirmed by a validation of the results and sensitivity analysis. Based on all of this, it was shown that fuzzy methods can be used in the selection of insurance companies.<\/jats:p>","DOI":"10.3390\/e25060959","type":"journal-article","created":{"date-parts":[[2023,6,20]],"date-time":"2023-06-20T02:26:56Z","timestamp":1687228016000},"page":"959","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Selection of an Insurance Company in Agriculture through Hybrid Multi-Criteria Decision-Making"],"prefix":"10.3390","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3274-0188","authenticated-orcid":false,"given":"Adis","family":"Pu\u0161ka","sequence":"first","affiliation":[{"name":"Government of Br\u010dko District of Bosnia and Herzegovina, Department of Public Safety, Bulevara Mira 1, 76100 Br\u010dko, Bosnia and Herzegovina"}]},{"given":"Marija","family":"Luki\u0107","sequence":"additional","affiliation":[{"name":"Faculty of Business Economics and Entrepreneurship, Economics, Finance and Banking, Mitropolita Petra 8, 11000 Belgrade, Serbia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9657-0889","authenticated-orcid":false,"given":"Darko","family":"Bo\u017eani\u0107","sequence":"additional","affiliation":[{"name":"Military Academy, University of Defence in Belgrade, Veljka Lukica Kurjaka 33, 11000 Belgrade, Serbia"}]},{"given":"Miroslav","family":"Nedeljkovi\u0107","sequence":"additional","affiliation":[{"name":"Institute of Agricultural Economics, Volgina 15, 11060 Belgrade, Serbia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2747-6722","authenticated-orcid":false,"given":"Ibrahim M.","family":"Hezam","sequence":"additional","affiliation":[{"name":"Statistics & Operations Research Department, College of Sciences, King Saud University, Riyadh 11451, Saudi Arabia"}]}],"member":"1968","published-online":{"date-parts":[[2023,6,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1108\/CAER-04-2015-0036","article-title":"Risk aversion in crop insurance program purchase decisions","volume":"9","author":"Lyu","year":"2017","journal-title":"China Agric. 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