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Innovation diffusion in global contexts: determinants of post-adoption digital transformation of European companies

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  • Kevin Zhu
  • Shutao Dong
  • Sean Xin Xu
  • Kenneth L Kraemer

Abstract

Grounded in the diffusion of innovation theory and the technology–organization–environment framework, we develop an integrative model to study the determinants of post-adoption stages of innovation diffusion, using enterprise digital transformation as an example of technology-enabled innovations. We specify four innovation characteristics (relative advantage, compatibility, costs and security concern) and four contextual factors (technology competence, organization size, competitive pressure and partner readiness) as determinants of post-adoption usage, and postulate usage as an intermediate link to impact on firm performance. We test the proposed model using a dataset of 1415 companies from six European countries. We find that the innovation needs to be used extensively in value-chain activities before its impact can be realized. Among the innovation characteristics, we find that compatibility is the strongest driver, and security concern outweighs cost as a usage inhibitor. Among the contextual variables, technology competence, partner readiness and competitive pressure significantly drive e-business usage, and the structural inertia of large firms tends to slow down its penetration. Collectively, these results indicate that innovation diffusion can be better understood by including both innovation characteristics and contextual factors, whereas earlier literature has traditionally treated the two separately. Finally, we evaluate an international dimension among European countries and tease out important boundary conditions that would not have been evident in a single-country dataset. Our results show that careful attention must be paid to the economic and regulatory factors that may result in uneven innovation diffusion even among developed European countries.

Suggested Citation

  • Kevin Zhu & Shutao Dong & Sean Xin Xu & Kenneth L Kraemer, 2006. "Innovation diffusion in global contexts: determinants of post-adoption digital transformation of European companies," European Journal of Information Systems, Taylor & Francis Journals, vol. 15(6), pages 601-616, December.
  • Handle: RePEc:taf:tjisxx:v:15:y:2006:i:6:p:601-616
    DOI: 10.1057/palgrave.ejis.3000650
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    Cited by:

    1. Bazrkar Ardeshir & Moradzad Mehrdad & Shayegan Shady, 2024. "The Use of Artificial Intelligence in Employee Recruitment in the Furniture Industry of Iran According to the Role of Contextual Factors," Studia Universitatis „Vasile Goldis” Arad – Economics Series, Sciendo, vol. 34(2), pages 86-109, June.
    2. Ashraf Elsafty & Eslam Ramadan, 2023. "How User Acceptance Can Affect Government Website Efficiency," International Journal of Social Science Studies, Redfame publishing, vol. 11(2), pages 1329-1329, March.
    3. Marie-Anne Le-Dain & Lamiae Benhayoun & Judy Matthews & Marine Liard, 2023. "Barriers and opportunities of digital servitization for SMEs: the effect of smart Product-Service System business models," Service Business, Springer;Pan-Pacific Business Association, vol. 17(1), pages 359-393, March.
    4. Muhammad Zafar Yaqub & Abdullah Alsabban, 2023. "Industry-4.0-Enabled Digital Transformation: Prospects, Instruments, Challenges, and Implications for Business Strategies," Sustainability, MDPI, vol. 15(11), pages 1-33, May.
    5. Elisa Giampietri & Samuele Trestini, 2020. "Analysing farmers' intention to adopt web marketing under a technology-organisation-environment perspective: A case study in Italy," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 66(5), pages 226-233.
    6. Mahadi Bahari & Ibrahim Arpaci & Oguzhan Der & Fatih Akkoyun & Ali Ercetin, 2024. "Driving Agricultural Transformation: Unraveling Key Factors Shaping IoT Adoption in Smart Farming with Empirical Insights," Sustainability, MDPI, vol. 16(5), pages 1-22, March.
    7. Xuejun Jin & Xiao Pan, 2023. "Government Attention, Market Competition and Firm Digital Transformation," Sustainability, MDPI, vol. 15(11), pages 1-27, June.
    8. Wang, Lan, 2023. "Digital transformation and total factor productivity," Finance Research Letters, Elsevier, vol. 58(PA).
    9. Sadia Samar Ali & Rajbir Kaur & Shahbaz Khan, 2023. "Identification of innovative technology enablers and drone technology determinants adoption: a graph theory matrix analysis framework," Operations Management Research, Springer, vol. 16(2), pages 830-852, June.
    10. Ebrahim A. A. Ghaleb & P. D. D. Dominic & Narinderjit Singh Sawaran Singh & Gehad Mohammed Ahmed Naji, 2023. "Assessing the Big Data Adoption Readiness Role in Healthcare between Technology Impact Factors and Intention to Adopt Big Data," Sustainability, MDPI, vol. 15(15), pages 1-25, July.
    11. Mehreen Azam & Salman Bin Naeem & Maged N. Kamel Boulos & Anthony Faiola, 2023. "Modelling the Predictors of Mobile Health (mHealth) Adoption among Healthcare Professionals in Low-Resource Environments," IJERPH, MDPI, vol. 20(23), pages 1-17, November.

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