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Determinants of end-user acceptance of biometrics: Integrating the “Big 3” of technology acceptance with privacy context

Caroline Lancelot Miltgen (), Ales Popovic and Tiago Oliveira
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Caroline Lancelot Miltgen: GRANEM - Groupe de Recherche Angevin en Economie et Management - UA - Université d'Angers - AGROCAMPUS OUEST - Institut National de l'Horticulture et du Paysage
Ales Popovic: ULISBOA - Universidade de Lisboa = University of Lisbon = Université de Lisbonne
Tiago Oliveira: ULISBOA - Universidade de Lisboa = University of Lisbon = Université de Lisbonne

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Abstract: The information systems (IS) literature has long emphasized the importance of user acceptance of computer-based IS. Evaluating the determinants of acceptance of information technology (IT) is vital to address the problem of underutilization and leverage the benefits of IT investments, especially for more radical technologies. This study examines individual acceptance of biometric identification techniques in a voluntary environment, measuring the intention to accept and further recommend the technology resulting from a carefully selected set of variables. Drawing on elements of technology acceptance model (TAM), diffusion of innovations (DOI) and unified theory of acceptance and use of technology (UTAUT) along with the trust-privacy research field, we propose an integrated approach that is both theoretically and empirically grounded. By testing some of the most relevant and well-tested elements from previous models along with new antecedents to biometric system adoption, this study produces results which are both sturdy and innovative. We first confirm the influence of renowned technology acceptance variables such as compatibility, perceived usefulness, facilitating conditions on biometrics systems acceptance and further recommendation. Second, prior factors such as concern for privacy, trust in the technology, and innovativeness also prove to have an influence. Third, unless innovativeness, the most important drivers to explain biometrics acceptance and recommendation are not from the traditional adoption models (TAM, DOI, and UTAUT) but from the trust and privacy literature (trust in technology and perceived risk).

Keywords: Biometric system; Technology acceptance; Privacy; Risk; Trust; Personal data (search for similar items in EconPapers)
Date: 2013
Note: View the original document on HAL open archive server: https://audencia.hal.science/hal-01116141
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Citations: View citations in EconPapers (24)

Published in Decision Support Systems, 2013, 56, pp.103-114. ⟨10.1016/j.dss.2013.05.010⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-01116141

DOI: 10.1016/j.dss.2013.05.010

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