{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,8]],"date-time":"2025-11-08T12:16:41Z","timestamp":1762604201355,"version":"3.41.2"},"reference-count":71,"publisher":"Emerald","issue":"6","license":[{"start":{"date-parts":[[2020,4,9]],"date-time":"2020-04-09T00:00:00Z","timestamp":1586390400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JD"],"published-print":{"date-parts":[[2020,4,9]]},"abstract":"<jats:sec><jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title><jats:p>Theory is a kind of condensed human knowledge. This paper is to examine the mechanism of interdisciplinary diffusion of theoretical knowledge by tracing the diffusion of a representative theory, the Technology Acceptance Model (TAM).<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title><jats:p>Based on the full-scale dataset of Web of Science (WoS), the citations of Davis's original work about TAM were analysed and the interdisciplinary diffusion paths of TAM were delineated, a supervised machine learning method was used to extract theory incidents, and a content analysis was used to categorize the patterns of theory evolution.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Findings<\/jats:title><jats:p>It is found that the diffusion of a theory is intertwined with its evolution. In the process, the role that a participating discipline play is related to its knowledge distance from the original disciplines of TAM. With the distance increases, the capacity to support theory development and innovation weakens, while that to assume analytical tools for practical problems increases. During the diffusion, a theory evolves into new extensions in four theoretical construction patterns, elaboration, proliferation, competition and integration.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Research limitations\/implications<\/jats:title><jats:p>The study does not only deepen the understanding of the trajectory of a theory but also enriches the research of knowledge diffusion and innovation.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title><jats:p>The study elaborates the relationship between theory diffusion and theory development, reveals the roles of the participating disciplines played in theory diffusion and vice versa, interprets four patterns of theory evolution and uses text mining technique to extract theory incidents, which makes up for the shortcomings of citation analysis and content analysis used in previous studies.<\/jats:p><\/jats:sec>","DOI":"10.1108\/jd-02-2020-0023","type":"journal-article","created":{"date-parts":[[2020,4,17]],"date-time":"2020-04-17T06:43:33Z","timestamp":1587105813000},"page":"1109-1134","source":"Crossref","is-referenced-by-count":10,"title":["Tracing theory diffusion: a text mining and citation-based analysis of TAM"],"prefix":"10.1108","volume":"76","author":[{"given":"Fang","family":"Wang","sequence":"first","affiliation":[]},{"given":"Xiaoyu","family":"Wang","sequence":"additional","affiliation":[]}],"member":"140","reference":[{"issue":"2","key":"key2020092114360266200_ref001","doi-asserted-by":"crossref","first-page":"361","DOI":"10.1111\/j.1540-5915.1999.tb01614.x","article-title":"Are individual differences germane to the acceptance of new information technologies?","volume":"30","year":"1999","journal-title":"Decision Sciences"},{"issue":"2","key":"key2020092114360266200_ref002","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1007\/s10961-007-9070-y","article-title":"Knowledge diffusion from university and public research. 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