Zayat, WaelKilic, Huseyin SelcukYalcin, Ahmet SelcukZaim, SelimDelen, Dursun2024-05-192024-05-1920230360-83521879-0550https://doi.org10.1016/j.cie.2023.109075https://hdl.handle.net/20.500.12713/5378Industry 4.0 has received inordinate attention from the business as well as research communities. Along with the development of Industry 4.0 applications and the diversity of potential alternatives, Multi-Attribute Decision Making (MADM) techniques have been employed by researchers as systematic approaches to support the decision-making processes. However, as the adoption of Industry 4.0 technologies requires considerable capital, and as it is relatively difficult to identify the suitable MADM method for the decision-making process in certain conditions, it becomes necessary to determine which components of Industry 4.0 are most commonly in demand of MADM applications of decision making, and which MADM techniques are mostly preferred by researchers and businesses for varied directions of Industry 4.0. Therefore, this study aims to provide a comprehensive review of MADM methods and their applications for different components of Industry 4.0. A methodology, including a review framework, is provided for the related analyses. The proposed framework includes analyses concerning methods, subtopics, and bibliometry along with the related exploratory tables and figures. Finally, the trends and research gaps are clearly stated to shed light on the further research areas taking into consideration different challenges that can be encountered by researchers, along with a set of propositions to potentially overcome them.eninfo:eu-repo/semantics/closedAccessMulti-Criteria Decision Making (Mcdm)Multi-Attribute Decision-Making (Madm)Multi-Objective Decision-Making (Modm)Industry 40Prescriptive AnalyticsDecision SupportReview Article177WOS:0009447061000012-s2.0-85150784564N/A10.1016/j.cie.2023.109075Q1