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Bibliometric analysis of technology adoption literature published from 1997 to 2020

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  • Xu, Zeshui
  • Ge, Zijing
  • Wang, Xinxin
  • Skare, Marinko

Abstract

With the rapid development of emerging technologies, research on technology adoption is valuable for improving the reception efficiency of new technologies. This paper uses bibliometric analysis methods and visualization software to explore the research stages, the hot issues, the limitations of the research and the future fronts. A total of 11,706 documents were collected as the original data using the retrieval formulas. Sorted by the numbers of citations, the top 10% of the documents are extracted as the top-cited documents. First, combining software and bibliometric analysis, we obtain the annual development trends and identify the productive countries/regions, the influential institutions and the high-yielding authors. In addition, we overview the representative authors and their works in the development of technology adoption. Then, we conduct keyword analysis and burstiness analysis to identify the academic hotspots, research fronts and limitations in this field. The results show that increasingly more researches have shifted from theories to applications. Technology adoption has multiple applications in the fields of online shopping, mobile learning, mobile banking, e-learning and health care delivery. Finally, we draw conclusions on the bibliometric findings and forecast the future research trends of technology adoption. In the future, more researches will focus on the impacts of age, gender, culture, and the environment on technology adoption.

Suggested Citation

  • Xu, Zeshui & Ge, Zijing & Wang, Xinxin & Skare, Marinko, 2021. "Bibliometric analysis of technology adoption literature published from 1997 to 2020," Technological Forecasting and Social Change, Elsevier, vol. 170(C).
    • Handle: RePEc:eee:tefoso:v:170:y:2021:i:c:s0040162521003280
    DOI: 10.1016/j.techfore.2021.120896
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    Cited by:

    1. Wang, Xinxin & Qin, Yong & Xu, Zeshui & Škare, Marinko, 2022. "A look at the focus shift in innovation literature due to Covid-19 pandemic," Journal of Business Research, Elsevier, vol. 145(C), pages 1-20.
    2. Xinxin Wang & Zeshui Xu & Yong Qin & Marinko Skare, 2023. "The global impact of financial development on renewable energy in a panel structural vector autoregression analysis," Sustainable Development, John Wiley & Sons, Ltd., vol. 31(3), pages 1364-1383, June.
    3. Bratanova, Alexandra, 2023. "Analysis of Australian business and research specialisation in antimicrobial resistance technology," MPRA Paper 118699, University Library of Munich, Germany.
    4. Wang, Xinxin & Xu, Zeshui & Qin, Yong & Skare, Marinko, 2022. "Innovation, the knowledge economy, and green growth: Is knowledge-intensive growth really environmentally friendly?," Energy Economics, Elsevier, vol. 115(C).
    5. Mauricio Marrone & Sascha Lemke & Lutz M. Kolbe, 2022. "Entity linking systems for literature reviews," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(7), pages 3857-3878, July.
    6. Laura Grassi & Nicolas Figini & Lorenzo Fedeli, 2022. "How does a data strategy enable customer value? The case of FinTechs and traditional banks under the open finance framework," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-34, December.
    7. Capestro, Mauro & Rizzo, Cristian & Kliestik, Tomas & Peluso, Alessandro M. & Pino, Giovanni, 2024. "Enabling digital technologies adoption in industrial districts: The key role of trust and knowledge sharing," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    8. Ben Jabeur, Sami & Ballouk, Hossein & Ben Arfi, Wissal & Sahut, Jean-Michel, 2023. "Artificial intelligence applications in fake review detection: Bibliometric analysis and future avenues for research," Journal of Business Research, Elsevier, vol. 158(C).
    9. Wang, Bo & Yang, Zihan & Le Hoa Pham, Thi & Deng, Nana & Du, Heran, 2023. "Can social impacts promote residents’ pro-environmental intentions and behaviour: Evidence from large-scale demand response experiment in China," Applied Energy, Elsevier, vol. 340(C).
    10. Cheikh-Ammar, Mustapha, 2024. "Toward a theory of technology desirability: Blending task and feature fit with mutual values," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    11. Nick Vink, 2022. "African agricultural development: How are we contributing?," Agricultural Economics, International Association of Agricultural Economists, vol. 53(4), pages 540-562, July.

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