The effects of perceived risk and technology type on users’ acceptance of technologies☆
Introduction
Venkatesh et al. [26] compared and tested the variables in eight different models about users’ technology acceptance including the technology acceptance model (TAM) [6] and diffusion of innovation (DOI) [22]. Subsequently, they proposed a unified theory of acceptance and use of technology (UTAUT), which consisted of four core determinants of acceptance/use and four moderating factors.
Although such models explain much of the variance, there seem to be two critical factors that are overlooked or have received inadequate attention—perceived risk (PR) and technology type. PR has been recognized as an important factor and was modeled as an antecedent of perceived usefulness (PU), and a sub-construct of others, such as trust (or as its antecedent [21]). However, PR was not considered in UTAUT.
When people decide whether or not to use a technology, the technology type affects their decision. In marketing, for example, it is widely acknowledged that consumers’ decision-making criteria vary across different types of products [20], [23]. It is not reasonable to assume that the effects of PU and perceived ease of use (PEU) on behavioral intension (BI) would be similar for different technologies.
The main object of our study was therefore to refine UTAUT, by considering the effect of PR and technology type on it. We also re-evaluated the effect of two moderating variables: gender and experience.
Section snippets
Prior research and theoretical background
Davis’ original TAM had three key constructs—PU, PEU, and system usage (SU). Hong et al. [12] added two categories of external variables – individual differences and system characteristics – and Chau [4] modified it by using only four constructs—PEU, perceived long-term usefulness, perceived short-term usefulness, and behavioral intention to use. Gefen et al. [11] combined ‘trust’ in explaining users’ acceptance of online shopping.
The UTAUT had four core constructs – performance expectancy,
Empirical study
We tested our hypotheses using data collected from subjects who participated in a group task experiment. For each subject, two identical questionnaires were used to measure the variables of interest before and after the experiment.
Limitations
Our study had several limitations due to the sampling methods and measurement instruments. First, the sample was a student group in a university; the sample was relatively homogeneous and does not represent the real world population. However, the subjects were diverse in terms of ethnic background, job experience, and age. Also, though the sample size of 161 was not too small for a model with 3 or 4 constructs, a bigger sample size would have been better. Second, the technologies examined in
Conclusions
In a practical sense, managers may introduce a new technology successfully by emphasizing different factors based on the degree of perceived risk and technology type. We considered two moderating variables, PR and technology type, in addition to the moderating variables in UTAUT. We tested how they moderate the effects of PU and PEU on users’ intention to use a technology. It was shown the PR and technology type were moderating variables.
While analyzing the effects of the variables, this study
Il Im is an Assistant Professor of Information Systems at School of Business, Yonsei University. He received his PhD from Marshall School of Business, University of Southern California. Prior to joining Yonsei University, Dr. Im was an Assistant Professor in the Information Systems Department at New Jersey Institute of Technology. His research articles have been published in various journals including Information & Management, ACM Transactions on Information Systems, Journal of Organizational
References (29)
- et al.
Technology acceptance model for internet banking: an invariance analysis
Information & Management
(2005) - et al.
What drives mobile commerce? An empirical evaluation of the revised technology acceptance model
Information & Management
(2005) - et al.
Understanding information technology acceptance by individual professionals: toward an integrated view
Information & Management
(2006) - et al.
Perceived usefulness, ease of use, and usage of information technology: a replication
MIS Quarterly
(1992) - et al.
The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations
Journal of Personality and Social Psychology
(1986) - et al.
The moderating effect of perceived risk on consumer's evaluations of product incongruity: preference for the norm
Journal of Consumer Research
(2001) An empirical assessment of a modified technology acceptance model
Journal of Management Information Systems
(1996)- et al.
An attitudinal model of technology-based self-service: moderating effects of consumer traits and situational factors
Journal of Academy of Marketing Science
(2002) Perceived usefulness, perceived ease of use and user acceptance of information technology
MIS Quarterly
(1989)- et al.
User acceptance of computer technology: a comparison of two theoretical models
Management Science
(1989)
Extending the technology acceptance model by inclusion of perceived risk
The relative importance of perceived ease-of-use in IS adoption: a study of e-commerce adoption
JAIS
Structural equation modeling and regression: guidelines for research practice
Communications of the AIS
Trust and TAM in online shopping: an integrated model
MIS Quarterly
Cited by (359)
Modelling public attitude towards air taxis in Germany
2024, Transportation Research Interdisciplinary PerspectivesDriving the dual learning process of management knowledge: A social cognitive theory perspective
2024, International Journal of Management EducationWhat drives managers towards algorithm aversion and how to overcome it? Mitigating the impact of innovation resistance through technology readiness
2023, Technological Forecasting and Social Change
Il Im is an Assistant Professor of Information Systems at School of Business, Yonsei University. He received his PhD from Marshall School of Business, University of Southern California. Prior to joining Yonsei University, Dr. Im was an Assistant Professor in the Information Systems Department at New Jersey Institute of Technology. His research articles have been published in various journals including Information & Management, ACM Transactions on Information Systems, Journal of Organizational Computing and Electronic Commerce, and Advances in Consumer Research, His current research focuses on personalization technologies and their impacts, technology acceptance, and electronic commerce.
Yongbeom Kim is an Associate Professor of Information Systems at Fairleigh Dickinson University. He received his BS and MS in electrical engineering from Seoul National University, and MPhil and PhD in information systems from the Stern School of Business of New York University. His research interests include performance evaluation of interactive computer systems, enterprise systems, and IS education. He has published in such journals as the Journal of Management Information Systems, Information Processing & Management, Information Resources Management Journal, Business Process Management Journal, and Journal of Information Systems Education.
Hyo-Joo Han is an assistant professor of Information Systems at Georgia Southern University. She holds a PhD from the New Jersey Institute of Technology, an MBA and an MS in IS from the Pensylvania State University, a BS in Animal Science and Bio-Technology from Kyungpook National University in South Korea. Her research interests include Pervasive Computing, Computer-Mediated Communication, Computer-Supported Cooperative Work, Education in IT, and E-Commerce. Her recent research is focused on working towards a greater understanding of Older Adults Technology Acceptace Model especially with the Internet.
- ☆
This research was partially supported by NSF Grants, DUE-0434998 and DUE-0434581.