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A cross-category analysis of dispositional drivers of technology adoption

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  • Ratchford, Mark
  • Ratchford, Brian T.

Abstract

Using the Technology Adoption Propensity (TAP) index, a psychometric scale that measures four dimensions of consumers’ technological predispositions, we examine the relative influence of contributing (optimism and proficiency) and inhibiting (dependence and vulnerability) dispositional attitudes on the adoption of a varied range of 19 technologies. Our results indicate considerable differences in the relation between technology usage and the attitudes of respondents across the technologies. We show that individuals can be grouped into three technology clusters based on technological dispositions: high proficiency/low vulnerability; low proficiency & optimism/high vulnerability; high optimism/low vulnerability. Each cluster may indicate a need for a particular sales strategy given differences in consumer attitudes.

Suggested Citation

  • Ratchford, Mark & Ratchford, Brian T., 2021. "A cross-category analysis of dispositional drivers of technology adoption," Journal of Business Research, Elsevier, vol. 127(C), pages 300-311.
    • Handle: RePEc:eee:jbrese:v:127:y:2021:i:c:p:300-311
    DOI: 10.1016/j.jbusres.2021.01.037
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    1. Bhatnagar, Amit & Ghose, Sanjoy, 2004. "A latent class segmentation analysis of e-shoppers," Journal of Business Research, Elsevier, vol. 57(7), pages 758-767, July.
    2. Mick, David Glen & Fournier, Susan, 1998. "Paradoxes of Technology: Consumer Cognizance, Emotions, and Coping Strategies," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 25(2), pages 123-143, September.
    3. Zhu, Zhen & Nakata, Cheryl & Sivakumar, K. & Grewal, Dhruv, 2013. "Fix It or Leave It? Customer Recovery from Self-service Technology Failures," Journal of Retailing, Elsevier, vol. 89(1), pages 15-29.
    4. Markus Blut & Cheng Wang, 2020. "Technology readiness: a meta-analysis of conceptualizations of the construct and its impact on technology usage," Journal of the Academy of Marketing Science, Springer, vol. 48(4), pages 649-669, July.
    5. Alsajjan, Bander & Dennis, Charles, 2010. "Internet banking acceptance model: Cross-market examination," Journal of Business Research, Elsevier, vol. 63(9-10), pages 957-963, September.
    6. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    7. Porter, Constance Elise & Donthu, Naveen, 2006. "Using the technology acceptance model to explain how attitudes determine Internet usage: The role of perceived access barriers and demographics," Journal of Business Research, Elsevier, vol. 59(9), pages 999-1007, September.
    8. Alba, Joseph W & Hutchinson, J Wesley, 1987. "Dimensions of Consumer Expertise," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 13(4), pages 411-454, March.
    9. Viswanath Venkatesh & Fred D. Davis, 2000. "A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies," Management Science, INFORMS, vol. 46(2), pages 186-204, February.
    10. Bruner, Gordon II & Kumar, Anand, 2005. "Explaining consumer acceptance of handheld Internet devices," Journal of Business Research, Elsevier, vol. 58(5), pages 553-558, May.
    11. Lam, Shun Yin & Chiang, Jeongwen & Parasuraman, A., 2008. "The effects of the dimensions of technology readiness on technology acceptance: An empirical analysis," Journal of Interactive Marketing, Elsevier, vol. 22(4), pages 19-39.
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