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Examining the Effects of Computer Self-Efficacy and System Complexity on Technology Acceptance

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  • Bassam Hasan

    (The University of Toledo, USA)

Abstract

Despite the prevalence of computing in all aspects of society, some computer systems may not be fully accepted by their intended users or become underutilized. Thus, acceptance and use of information technologies remain a paramount issue in information systems (IS) research and practice. Extending previous research by integrating computer self-efficacy and perceived system complexity as external variables to the technology acceptance model (TAM), this study examines the direct and indirect effects of these two factors on system acceptance and use. The results indicated that computer self-efficacy and system complexity had significant direct effects on perceived usefulness and perceived ease of use as well as indirect effects on attitude and behavioral intention. However, the effect of perceived ease of use on attitude was stronger than that of perceived usefulness. In turn, attitude demonstrated a non-significant impact on behavioral intention. These findings highlight several implications for research and practice.

Suggested Citation

  • Bassam Hasan, 2007. "Examining the Effects of Computer Self-Efficacy and System Complexity on Technology Acceptance," Information Resources Management Journal (IRMJ), IGI Global, vol. 20(3), pages 76-88, July.
    • Handle: RePEc:igg:rmj000:v:20:y:2007:i:3:p:76-88
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    Cited by:

    1. Jacob Peng & Ira Abdullah, 2018. "Building a market simulation to teach business process analysis: effects of realism on engaged learning," Accounting Education, Taylor & Francis Journals, vol. 27(2), pages 208-222, March.
    2. Alireza Tamjidyamcholo & Sameer Kumar & Ainin Sulaiman & Rahmatollah Gholipour, 2016. "Willingness of members to participate in professional virtual communities," Quality & Quantity: International Journal of Methodology, Springer, vol. 50(6), pages 2515-2534, November.
    3. Mohammadbashir Sedighi & Hamideh Parsaeiyan & Yashar Araghi, 2021. "An Empirical Study of Intention to Continue Using of Digital Ride-hailing Platforms," The Review of Socionetwork Strategies, Springer, vol. 15(2), pages 489-515, November.
    4. Marie-E. Godefroid & Vincent Borghoff & Ralf Plattfaut & Björn Niehaves, 2024. "Teleworking antecedents: an exploration into availability bias as an impediment," Information Systems and e-Business Management, Springer, vol. 22(2), pages 247-284, June.
    5. Thilini Chathurika Gamage, 2019. "Determinants of Cloud Computing Adoption among SMEs in Sri Lanka: A Meta Theoretical Framework," International Journal of Asian Social Science, Asian Economic and Social Society, vol. 9(2), pages 189-203, February.
    6. Eleanor Eytam & Oded Lowengart & Noam Tractinsky, 2021. "Effects of visual simplicity in product design and individual differences in preference of interactive products," Review of Managerial Science, Springer, vol. 15(5), pages 1347-1389, July.
    7. Chung-Hung Tsai, 2014. "Integrating Social Capital Theory, Social Cognitive Theory, and the Technology Acceptance Model to Explore a Behavioral Model of Telehealth Systems," IJERPH, MDPI, vol. 11(5), pages 1-21, May.
    8. Kim, Changsu & Oh, Eunhae & Shin, Namchul & Chae, Myungsin, 2009. "An empirical investigation of factors affecting ubiquitous computing use and U-business value," International Journal of Information Management, Elsevier, vol. 29(6), pages 436-448.

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