Archives For Technology acceptance

Mobile banking adoption

Wednesday, July 23, 2014

A study linking UTAUT, TTF and ITM in the context of mobile banking adoption, co-authored with T. Oliveira, M. Faria, and M. A. Thomas, is scheduled to appear in October 2014 issue of International Journal of Information Management. The work titled Extending the understanding of mobile banking adoption: When UTAUT meets TTF and ITM shows – through an empirical research conducted in Portugal – how utilizing and blending UTAUT, TTF, and ITM helps us understand mobile banking adoption. Abstract:

Mobile banking (mBanking) enables customers to carry out their banking tasks via mobile devices. We advance the extant body of knowledge about mBanking adoption by proposing a model for understanding the importance and relationship between the user perception of mBanking, initial trust in mBanking services, and the fit between the technology and mBanking task characteristics. We synergistically combine the strengths of three IS theories – task technology fit (TTF) model, unified theory of acceptance and usage of technology (UTAUT), and initial trust model (ITM). The model was tested in a study conducted in Portugal, one of the European Union (EU) countries with the highest mobile phone adoption. Based on the sample of 194 individuals we applied partial least squares (PLS) to test the conceptual model propose. The path significance levels were estimated using the bootstrapping method (500 resamples). The study found that facilitating conditions and behavioral intentions directly influence mBanking adoption. Initial trust, performance expectancy, technology characteristics, and task technology fit have total effect on behavioral intention. The paper offers valuable insights to decision-makers involved in the implementation and deployment of mBanking services. For researchers, the paper highlights the usefulness of integrating TTF, UTAUT and ITM in the development of a decision support framework to study the adoption of new technologies.

End-user acceptance of biometrics

Tuesday, December 3, 2013

A new publication is available on the topic of pervasive technology acceptance, co-authored with C. Lancelot Miltgen, and T. Oliveira (2013): Determinants of end-user acceptance of biometrics: Integrating the “Big 3” of technology acceptance with privacy context. The work significantly adds to our understanding of the determinants of end-user acceptance of biometric systems. 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).