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Impact of personality on technology adoption: An empirical model

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  • Arun Vishwanath

Abstract

An innovator's personality along with the perceived attributes of an innovation predicts the rate of diffusion. The current study focuses on the personality factors that determine the likelihood of adoption of a technological innovation. To that end, the study distinguishes between global innovativeness and context‐specific innovativeness. An information processing model was tested where technological innovativeness was purported to be indirectly influenced by an individual's global innovativeness, through its impact on communication and media use behaviors. The structural model was tested on two separate technology clusters, and partial support was found for linking sophistication in information search, and prior technology ownership to technological innovativeness.

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  • Arun Vishwanath, 2005. "Impact of personality on technology adoption: An empirical model," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 56(8), pages 803-811, June.
    • Handle: RePEc:bla:jamist:v:56:y:2005:i:8:p:803-811
    DOI: 10.1002/asi.20169
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    Cited by:

    1. Cunningham, Mitchell L. & Regan, Michael A. & Horberry, Timothy & Weeratunga, Kamal & Dixit, Vinayak, 2019. "Public opinion about automated vehicles in Australia: Results from a large-scale national survey," Transportation Research Part A: Policy and Practice, Elsevier, vol. 129(C), pages 1-18.
    2. van Rijnsoever & Marius Meeus & Roger Donders, 2012. "The effects of economic status and recent experience on innovative behavior under environmental variability: an experimental approach," Innovation Studies Utrecht (ISU) working paper series 12-01, Utrecht University, Department of Innovation Studies, revised Jan 2012.
    3. Soyoung An & Thomas Eck & Huirang Yim, 2023. "Understanding Consumers’ Acceptance Intention to Use Mobile Food Delivery Applications through an Extended Technology Acceptance Model," Sustainability, MDPI, vol. 15(1), pages 1-14, January.
    4. van Rijnsoever, Frank J. & Meeus, Marius T.H. & Donders, A. Rogier T., 2012. "The effects of economic status and recent experience on innovative behavior under environmental variability: An experimental approach," Research Policy, Elsevier, vol. 41(5), pages 833-847.
    5. Joost Rietveld & J. P. Eggers, 2018. "Demand Heterogeneity in Platform Markets: Implications for Complementors," Organization Science, INFORMS, vol. 29(2), pages 304-322, April.
    6. Iaia, Lea & Leonelli, Simona & Masciarelli, Francesca & Christofi, Michael & Cooper, Sir Cary, 2022. "The malevolent side of masstige consumers’ behavior: The role of dark triad and technology propensity," Journal of Business Research, Elsevier, vol. 149(C), pages 954-966.
    7. Kwon, Wi-Suk & Woo, Hongjoo & Sadachar, Amrut & Huang, Xiao, 2021. "External pressure or internal culture? An innovation diffusion theory account of small retail businesses’ social media use," Journal of Retailing and Consumer Services, Elsevier, vol. 62(C).

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