{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,6]],"date-time":"2026-01-06T02:06:20Z","timestamp":1767665180908,"version":"3.41.2"},"reference-count":44,"publisher":"Emerald","issue":"4","license":[{"start":{"date-parts":[[2015,4,7]],"date-time":"2015-04-07T00:00:00Z","timestamp":1428364800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2015,4,7]]},"abstract":"<jats:sec>\n               <jats:title content-type=\"abstract-heading\">Purpose<\/jats:title>\n               <jats:p> \u2013 Proposing a fuzzy multi-criteria decision making (MCDM) algorithm that is able to incorporate the heterogeneousness effect of DM group into the decision process, in order to determine the best remotely operated vehicle (ROV) design alternative to manufacture and developing a practical decision aid tool based on this algorithm. The paper aims to discuss these issues. <\/jats:p>\n            <\/jats:sec>\n            <jats:sec>\n               <jats:title content-type=\"abstract-heading\">Design\/methodology\/approach<\/jats:title>\n               <jats:p> \u2013 An algorithm utilizes fuzzy AHP Buckley\u2019s approach for modeling heterogeneousness of the DM group, fuzzy AHP Chang\u2019s extent analysis to calculate the priority values of criteria and Chen\u2019s fuzzy TOPSIS for ranking the alternatives and finally group working technique for initiation issues is developed. MATLAB is used to implement the algorithm and generate a decision aid tool. Real life application and sensitivity analysis is performed by the help of generated tool. Literature and background explanations are also provided. <\/jats:p>\n            <\/jats:sec>\n            <jats:sec>\n               <jats:title content-type=\"abstract-heading\">Findings<\/jats:title>\n               <jats:p> \u2013 A MCDM algorithm that incorporates the heterogeneousness effect of the DM group into the decision process is introduced. Sensitivity analysis suggested the independence of the final result from DM group and criteria set. A practical decision aid tool is generated for ROV manufacturing companies. <\/jats:p>\n            <\/jats:sec>\n            <jats:sec>\n               <jats:title content-type=\"abstract-heading\">Practical implications<\/jats:title>\n               <jats:p> \u2013 A computerized MCDM aid tool that incorporates heterogeneousness of the DM group into the decision process is generated. Tool let ROV manufacturing companies to evaluate ROV design alternatives with respect to qualitative and quantitative criteria and determine proper choice. <\/jats:p>\n            <\/jats:sec>\n            <jats:sec>\n               <jats:title content-type=\"abstract-heading\">Originality\/value<\/jats:title>\n               <jats:p> \u2013 Determination of the proper ROV design alternative to manufacture gap within the literature filled with an algorithm that provides more reliable results due to its incorporation the heterogeneousness of the DM group into the decision process characteristic. A practical decision aid tool is generated.<\/jats:p>\n            <\/jats:sec>","DOI":"10.1108\/k-10-2014-0222","type":"journal-article","created":{"date-parts":[[2015,6,8]],"date-time":"2015-06-08T08:55:27Z","timestamp":1433753727000},"page":"623-645","source":"Crossref","is-referenced-by-count":5,"title":["A fuzzy MCDM algorithm and practical decision aid tool to determine the best ROV design alternative"],"prefix":"10.1108","volume":"44","author":[{"given":"Birol","family":"\u00dclker","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"140","reference":[{"key":"key2020122501453987000_b1","doi-asserted-by":"crossref","unstructured":"Aktan, H.E.\n                and \n                  Tosun, O.\n                (2013), \u201cAn integrated fuzzy AHP-fuzzy TOPSIS approach for AS\/RS selection\u201d, \n                  International Journal of Productivity and Quality Management\n               , Vol. 11 No. 2, pp. 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