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An Extension of the Technology Acceptance Model to Determine the Intention to Use Biometric Devices
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Author(s): Tabitha James (Virginia Polytechnic Institute and State University, USA), Taner Pirim (Mississippi Center for Supercomputing Research, USA), Katherine Boswell (University of Louisiana - Monroe, USA), Brian Reithel (University of Mississippi, USA) and Reza Barkhi (Virginia Polytechnic Institute and State University, USA)
Copyright: 2008
Pages: 22
Source title:
End User Computing Challenges and Technologies: Emerging Tools and Applications
Source Author(s)/Editor(s): Steve Clarke (University of Hull Business School, UK)
DOI: 10.4018/978-1-59904-295-4.ch005
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Abstract
Protection of physical assets and digital information is of growing importance to society. The need for development and use of security technologies is ever increasing. As with any new technology, user acceptance of new software and hardware devices is often hard to gauge, and policies to introduce and ensure adequate and correct usage of such technologies are often lacking. Security technologies have widespread applicability to different organizational contexts that may present unusual and varied adoption considerations. This study adapts the technology acceptance model and extends it to study the intention to use security devices, more specifically biometrics, across a wide variety of organizational contexts. Due to the use of physiological characteristics, biometrics present unique adoption concerns. The extension of the technology acceptance model for biometrics is useful, as biometrics encompass many of the same adoption concerns as traditional security devices, but include a level of invasiveness that is obvious to the user. Through the use of vignettes, this study encompasses a systematically varied set of usage contexts for biometric devices to provide a generalizable view of the factors impacting intention to use over all categories of situational contexts of the device’s use. The technology acceptance model is extended in this study to include constructs for perceived need for privacy, perceived need for security, and perceived physical invasiveness of biometric devices as factors that influence intention to use. The model is shown to be a good predictor of intention to use biometric devices and implications of the results for biometric and security technology acceptance is discussed.
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