Technology readiness: a meta-analysis of conceptualizations of the construct and its impact on technology usage

Markus Blut*, Cheng Wang

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

246 Citations (Scopus)


The technology readiness (TR) index aims to better understand people’s propensity to embrace and use cutting-edge technologies. The initial TR construct considers four dimensions—innovativeness, optimism, insecurity, and discomfort—that collectively explain technology usage. The present meta-analysis advances understanding of TR by reexamining its dimensionality, and investigating mediating mechanisms and moderating influences in the TR–technology usage relationship. Using data from 193 independent samples extracted from 163 articles reported by 69,263 individuals, we find that TR is best conceptualized as a two-dimensional construct differentiating between motivators (innovativeness, optimism) and inhibitors (insecurity, discomfort). We observe strong indirect effects of these dimensions on technology usage through mediators proposed by the quality–value–satisfaction chain and technology acceptance model. The results suggest stronger relationships for motivators than for inhibitors, but also that these TR dimensions exert influence through different mediators. Further, the moderator results suggest that the strength of TR–technology usage relationships depends on the technology type (hedonic/utilitarian), examined firm characteristics (voluntary/mandatory use; firm support), and country context (gross domestic product; human development). Finally, customer age, education, and experience are related to TR. These findings enhance managers’ understanding of how TR influences technology usage.

Original languageEnglish
Pages (from-to)649-669
Number of pages21
JournalJournal of the Academy of Marketing Science
Issue number4
Publication statusPublished - 1 Jul 2020


  • Hierarchical linear meta-analysis
  • Meta-analysis
  • Quality–value–satisfaction chain
  • Structural equation modeling
  • Technology acceptance
  • Technology readiness


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