{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,11]],"date-time":"2025-03-11T04:11:52Z","timestamp":1741666312668,"version":"3.38.0"},"reference-count":85,"publisher":"SAGE Publications","issue":"2","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IDT"],"published-print":{"date-parts":[[2024,6,7]]},"abstract":"<jats:p>Adoption of \u201cIndustry 4.0\u201d technologies in construction is rising in recent years due to intervention of government and non government bodies for combating environmental challenges. In order to understand various enablers that influence \u201cadoption of Industry 4.0\u201d \u2013 technologies, this study is conducted for assessing degree of enablers in Indian construction. A hybrid MCDM approach using \u2013 Fuzzy SWARA and Fuzzy COPRAS named as ARank-FSC is proposed. Fuzzy \u201cSWARA\u201d aids in obtaining relative weights of enablers while COPRAS helps in ranking and selecting most efficient amongst them. The proposed approach is applied on a case organization engaged in construction. Results indicate that profitability acts as top ranked enabler that would significantly affect \u201cIndustry 4.0\u201d acceptance in Indian construction. Stakeholders coordination, Governmental regulations, strategic planning, building information modeling and risk taking behavior are also critical enablers that significantly affect acceptance of \u201cIndustry 4.0\u201d technologies in construction industry of developing countries like India. The present study aims to analyze-the-rank of enablers-in \u201cadoption-of-Industry-4.0\u201d. The proposed approach is put through a sensitivity analysis to determine its robustness. This research\u2019s conclusions and ramifications-will-be-useful-to-practitioners-and-researchers-in-understanding degree of enablers for implementation-of-Industry 4.0-in-construction-industries of developing countries like India.<\/jats:p>","DOI":"10.3233\/idt-240459","type":"journal-article","created":{"date-parts":[[2024,5,17]],"date-time":"2024-05-17T17:27:48Z","timestamp":1715966868000},"page":"663-683","source":"Crossref","is-referenced-by-count":0,"title":["ARank-FSC: Assessment and ranking of Industry 4.0 enablers using fuzzy SWARA and fuzzy COPRAS in Indian 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