{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T02:47:27Z","timestamp":1769914047774,"version":"3.49.0"},"reference-count":36,"publisher":"Emerald","issue":"3","license":[{"start":{"date-parts":[[2013,9,2]],"date-time":"2013-09-02T00:00:00Z","timestamp":1378080000000},"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":[[2013,9,2]]},"abstract":"\n Purpose<\/jats:title>\n \u2013 This research aims to integrate the unified theory of acceptance and usage of technology (UTAUT) with task technology fit to explain users' behavioral intention of using library mobile applications in university libraries. <\/jats:p>\n <\/jats:sec>\n \n Design\/methodology\/approach<\/jats:title>\n \u2013 By integrating the unified theory of acceptance and usage of technology (UTAUT) and the moderator of task-technology fit, this research proposes a library mobile applications usage intention model. The study data come from a convenience sample of 363 undergraduate and graduate students. A structural equation modelling (SEM) technique was conducted to identify causal relationships. <\/jats:p>\n <\/jats:sec>\n \n Findings<\/jats:title>\n \u2013 Results showed that the UTAUT model fits the data well. The empirical data reveal that performance expectancy, effort expectancy, social influence, and facilitating conditions determine users' behavioral intention of using library mobile applications. As a determinant in the UTAUT model, the moderating effect of task-technology fit is also significant. Moreover, individuals with different levels of task-technology fit will strengthen or weaken the relationships of determinants in the intention to use library mobile applications in university libraries. <\/jats:p>\n <\/jats:sec>\n \n Research limitations\/implications<\/jats:title>\n \u2013 This study addresses self-reported behavioral intentions as part of the survey; as a result, the data may have introduced inaccuracies. The implications of the proposed library mobile applications success model are discussed. <\/jats:p>\n <\/jats:sec>\n \n Practical implications<\/jats:title>\n \u2013 University librarians should reinforce the efficiency of library mobile applications to influence users' willingness to use such applications. <\/jats:p>\n <\/jats:sec>\n \n Originality\/value<\/jats:title>\n \u2013 This study combines both the constructs of the UTAUT model and task-technology fit to consider intentions to use library mobile applications in university libraries.<\/jats:p>\n <\/jats:sec>","DOI":"10.1108\/lht-03-2013-0024","type":"journal-article","created":{"date-parts":[[2013,9,13]],"date-time":"2013-09-13T11:06:32Z","timestamp":1379070392000},"page":"478-492","source":"Crossref","is-referenced-by-count":79,"title":["Library mobile applications in university libraries"],"prefix":"10.1108","volume":"31","author":[{"given":"Chiao-Chen","family":"Chang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"140","reference":[{"key":"key2022020919561341000_b1","doi-asserted-by":"crossref","unstructured":"Ajzen, I.\n (1991), \u201cThe theory of planned behavior\u201d, Organizational Behavior and Human Decision Processes, Vol. 50 No. 2, pp. 179-211.","DOI":"10.1016\/0749-5978(91)90020-T"},{"key":"key2022020919561341000_b2","unstructured":"Ajzen, I.\n and \n Fishbein, M.\n (1980), Understanding Attitudes and Predicting Social Behavior, Prentice Hall, Englewood Cliffs, NJ."},{"key":"key2022020919561341000_b3","doi-asserted-by":"crossref","unstructured":"Anderson, J.C.\n and \n Gerbing, D.W.\n (1988), \u201cStructural equation modeling in practice: a review and recommended two-step approach\u201d, Psychological Bulletin, Vol. 103 No. 3, pp. 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