Purdue University Graduate School
LaisMcCartneyMastersThesisFINAL.pdf (2.22 MB)

Using the UTAUT2 Model to Explain the Intention to Use Phone Biometrics

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posted on 2022-05-13, 18:56 authored by Lais A McCartneyLais A McCartney

Biometric technology is used in daily life, for authentication purposes. Perceptions about the privacy and security of biometrics are of great interest (Olorunsola et al., 2020). Ho et al. (2003) specifically added privacy to their biometric acceptance model as a potential influence on intention to use the technology since privacy about biometrics was found to be peoples’ primary concern. Surveys of perceptions and use of technology (Buckley & Nurse 2019; Carpenter et al. 2018; Olorunsola et al. 2020) have used many different models to predict people's willingness to use biometrics. Venkatesh, Thong, et al (2012) used the reliable and valid UTUAT2 (Unified Theory of Acceptance and Use of Technology), a consumer-based model, with phone biometrics. Could the UTAUT2 model explain variance in intention to use phone biometrics? Phone biometrics are defined as biometrics used on a mobile smartphone but are referred to as phone biometrics throughout this study. A survey using the UTAUT2 basic questions was posed to n = 329 people who owned a mobile phone, lived in the United States, and used phone biometrics, to see if the model explained the “intention to use” phone biometrics. An example application of phone biometrics was biometrics used on a personal phone. Example use cases included using biometrics to unlock a phone, using fingerprints or face, or opening or authenticating specific applications within the phone.

Venkatesh developed the UTAUT2 model to explain the intention to use in a consumer setting. His earlier model (UTAUT) examined intention to use in an organizational setting. The challenge was that these models are old (the UTAUT2 model is almost ten years old at the time of writing), and phone biometrics is a rapidly changing consumer technology. The overarching research question is whether the UTAUT2 model can explain the intention to use phone biometrics. The results showed that UTAUT2 constructs accounted for 79.1% of the variation in intention to use phone biometrics. 


Degree Type

  • Master of Science


  • Technology Leadership and Innovation

Campus location

  • West Lafayette

Advisor/Supervisor/Committee Chair

Stephen J. Elliott

Additional Committee Member 2

Kathryn Seigfried-Spellar

Additional Committee Member 3

Marcus Rogers

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