{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,25]],"date-time":"2026-06-25T21:59:06Z","timestamp":1782424746147,"version":"3.54.5"},"reference-count":58,"publisher":"Emerald","issue":"4","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,10,31]]},"abstract":"<jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>This study aimed to identify and rank the barriers faced by disabled elderly people in China regarding the adoption of artificial intelligence (AI) in their lives using dynamic grey relational analysis (DGRA) and technique for order performance by similarity to ideal solution (TOPSIS). DGRA was employed to assess the strength of relationships between barriers dynamically, while TOPSIS ranked them based on proximity to ideal solutions.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Design\/methodology\/approach<\/jats:title>\n                    <jats:p>Using a cross-sectional study design, primary data were collected from 253 elderly individuals with disabilities in Jiangsu, China. Along with DGRA and TOPSIS, the Kruskal\u2013Wallis test was also conducted to evaluate the differences of identified barriers across age groups.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Findings<\/jats:title>\n                    <jats:p>We found that the top three most significant barriers were (1) awareness and training, (2) trust and (3) transparency and explainability in both DGRA and TOPSIS cases. Additionally, the Kruskal\u2013Wallis test revealed that age (=60\u00a0years) did not significantly influence these barriers, as the study population consisted of disabled elderly with similar perceptions across age groups. This study is timely because the country\u2019s demographic shift is expected to begin in 2027, and 26% of its population will be 65\u00a0years or older by 2050.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Originality\/value<\/jats:title>\n                    <jats:p>This study is the first of its kind to apply the DGRA, TOPSIS and Kruskal\u2013Wallis tests to identify and rank the barriers to AI adoption for the disabled elderly in China.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1108\/gs-12-2024-0147","type":"journal-article","created":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T15:49:09Z","timestamp":1757605749000},"page":"732-754","source":"Crossref","is-referenced-by-count":6,"title":["Evaluation of barriers to artificial intelligence adoption: grey multi-criteria decision-making"],"prefix":"10.1108","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3719-7914","authenticated-orcid":true,"given":"Muhammad","family":"Nawaz","sequence":"first","affiliation":[{"name":"School of Business Administration, Hunan University , ,","place":["Changsha, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sifeng","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Management, Northwestern Polytechnical University , ,","place":["Xi\u2019an, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Naiming","family":"Xie","sequence":"additional","affiliation":[{"name":"College of Economics and Management, Nanjing University of Aeronautics and Astronautics , ,","place":["Nanjing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Beenish","family":"Ramzan","sequence":"additional","affiliation":[{"name":"Institute for Grey Systems and Decision Sciences, GreySys Foundation , ,","place":["Lahore, Pakistan"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"140","published-online":{"date-parts":[[2025,8,6]]},"reference":[{"issue":"1","key":"2025103102413935900_ref001","doi-asserted-by":"publisher","first-page":"67","DOI":"10.1108\/FS-10-2021-0199","article-title":"AI adoption by human resource management: a study of its antecedents and impact on HR system effectiveness","volume":"25","author":"Agarwal","year":"2022","journal-title":"Foresight"},{"issue":"2","key":"2025103102413935900_ref002","doi-asserted-by":"publisher","first-page":"42","DOI":"10.52812\/ijgs.19","article-title":"Grey relational evaluation of the supplier selection criteria in the Indonesian hospitality industry","volume":"1","author":"Angela","year":"2021","journal-title":"International Journal of Grey Systems"},{"key":"2025103102413935900_ref003","doi-asserted-by":"publisher","DOI":"10.1007\/s12597-025-00905-1","article-title":"Some models of grey \u03b2 coverings and their topological properties","author":"Atef","year":"2025","journal-title":"Opsearch"},{"issue":"1","key":"2025103102413935900_ref004","doi-asserted-by":"publisher","first-page":"5","DOI":"10.52812\/msbd.37","article-title":"Evaluation of automotive parts suppliers through ordinal priority approach and TOPSIS","volume":"2","author":"Bah","year":"2022","journal-title":"Management Science and Business Decisions"},{"issue":"2","key":"2025103102413935900_ref005","doi-asserted-by":"publisher","first-page":"530","DOI":"10.1108\/JEIM-06-2020-0233","article-title":"Can we trust AI? 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