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The complexity of different types of attitudes in initial and continued ICT use

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  • Ping Zhang
  • Heshan Sun

Abstract

In the information systems (IS) field, research interest in attitude has fluctuated over the past decades given the inconsistent and inconclusive findings on attitude's effects on behavioral intention (BI) to use information and communication technology (ICT). This study addresses the conceptual, operational, and temporal dynamics of attitude that may have caused the inconsistent and inconclusive results. A longitudinal study was conducted to validate our hypotheses. The results show that: (a) The attitude that significantly influences BI needs to be at a particular specificity with BI on two aspects, the same evaluation target and the same evaluation time, where the time specificity can supersede the target specificity; (b) the relationships among attitudes and intention remain the same if they are measured at the same time, regardless of use stages; (c) the two types of attitudes show different long‐lasting effects over time; (d) omitting important mediating factors in a research model may generate misleading messages; and (e) attitudes alone can explain a large amount of variances in BI. The results can help explain the reasons behind inconsistent findings in the literature, inspire additional research efforts, and suggest bringing attitudes back to information systems research due to their theoretical and practical importance.

Suggested Citation

  • Ping Zhang & Heshan Sun, 2009. "The complexity of different types of attitudes in initial and continued ICT use," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(10), pages 2048-2063, October.
  • Handle: RePEc:bla:jamist:v:60:y:2009:i:10:p:2048-2063
    DOI: 10.1002/asi.21116
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    Cited by:

    1. Damon E. Campbell & John D. Wells & Joseph S. Valacich, 2013. "Breaking the Ice in B2C Relationships: Understanding Pre-Adoption E-Commerce Attraction," Information Systems Research, INFORMS, vol. 24(2), pages 219-238, June.
    2. Kim, Youngseek & Adler, Melissa, 2015. "Social scientists’ data sharing behaviors: Investigating the roles of individual motivations, institutional pressures, and data repositories," International Journal of Information Management, Elsevier, vol. 35(4), pages 408-418.
    3. Weiquan Wang & Jingjun (David) Xu & May Wang, 2018. "Effects of Recommendation Neutrality and Sponsorship Disclosure on Trust vs. Distrust in Online Recommendation Agents: Moderating Role of Explanations for Organic Recommendations," Management Science, INFORMS, vol. 64(11), pages 5198-5219, November.

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