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Implications of the coronavirus (COVID-19) outbreak for innovation: Which technologies will improve our lives?

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  • Brem, Alexander
  • Viardot, Eric
  • Nylund, Petra A.

Abstract

In contrast to earlier coronavirus diseases such as SARS or MERS, whose impact was largely limited to specific regions of the world, the novel coronavirus, COVID-19, is affecting people across the globe. This article analyzes the effects of this worldwide phenomenon on certain technologies and how this may improve our lives. It presents technologies that relate directly to the treatment of the virus as well as those that have been used to adapt to living under this crisis. Given that such a pandemic will likely affect humanity again, this article also highlights how these technologies may prove helpful in the future. To this end, technological challenges, related innovation logics, and their social impacts are discussed.

Suggested Citation

  • Brem, Alexander & Viardot, Eric & Nylund, Petra A., 2021. "Implications of the coronavirus (COVID-19) outbreak for innovation: Which technologies will improve our lives?," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
  • Handle: RePEc:eee:tefoso:v:163:y:2021:i:c:s0040162520312774
    DOI: 10.1016/j.techfore.2020.120451
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    References listed on IDEAS

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    1. Tiejun, Zhu, 2021. "Implementation Status and Development Thinking on “Cloud National Examination” in China under the situation of “Online Anti-COVID-19 Epidemic”," Technological Forecasting and Social Change, Elsevier, vol. 162(C).
    2. Stoffregen, Julia & Pawlowski, Jan M., 2018. "Theorising about barriers to open e-learning systems in public administrations," Technological Forecasting and Social Change, Elsevier, vol. 132(C), pages 81-91.
    3. Alexander Bick & Adam Blandin & Karel Mertens, 2023. "Work from Home before and after the COVID-19 Outbreak," American Economic Journal: Macroeconomics, American Economic Association, vol. 15(4), pages 1-39, October.
    4. Sven Heidenreich & Katrin Talke, 2020. "Consequences of mandated usage of innovations in organizations: developing an innovation decision model of symbolic and forced adoption," AMS Review, Springer;Academy of Marketing Science, vol. 10(3), pages 279-298, December.
    5. Chen, Chih Ping & Weng, Ju-Yin & Yang, Chin-Sheng & Tseng, Fan-Mei, 2018. "Employing a data mining approach for identification of mobile opinion leaders and their content usage patterns in large telecommunications datasets," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 88-98.
    6. Alexander Brem & Éric Viardot (ed.), 2015. "Adoption of Innovation," Springer Books, Springer, edition 127, number 978-3-319-14523-5, January.
    7. Alexander Brem & Éric Viardot, 2015. "Adoption of Innovation: Balancing Internal and External Stakeholders in the Marketing of Innovation," Springer Books, in: Alexander Brem & Éric Viardot (ed.), Adoption of Innovation, edition 127, pages 1-10, Springer.
    8. Jiang, Ruth & Kleer, Robin & Piller, Frank T., 2017. "Predicting the future of additive manufacturing: A Delphi study on economic and societal implications of 3D printing for 2030," Technological Forecasting and Social Change, Elsevier, vol. 117(C), pages 84-97.
    9. Zec, Marin & Matthes, Florian, 2018. "Web-based software-support for collaborative morphological analysis in real-time," Technological Forecasting and Social Change, Elsevier, vol. 126(C), pages 168-181.
    10. Lee, Sang M. & Trimi, Silvana, 2021. "Convergence innovation in the digital age and in the COVID-19 pandemic crisis," Journal of Business Research, Elsevier, vol. 123(C), pages 14-22.
    11. Papa, Armando & Mital, Monika & Pisano, Paola & Del Giudice, Manlio, 2020. "E-health and wellbeing monitoring using smart healthcare devices: An empirical investigation," Technological Forecasting and Social Change, Elsevier, vol. 153(C).
    12. Shim, Yongwoon & Shin, Don, 2019. "Smartness in techno-nationalism? Combining actor-network theory and institutionalization to assess Chinese smart TV development," Technological Forecasting and Social Change, Elsevier, vol. 139(C), pages 87-98.
    13. Devezas, Tessaleno, 2020. "The struggle SARS-CoV-2 vs. homo sapiens–Why the earth stood still, and how will it keep moving on?," Technological Forecasting and Social Change, Elsevier, vol. 160(C).
    14. Barnes, Stuart J. & Mattsson, Jan, 2017. "Understanding collaborative consumption: Test of a theoretical model," Technological Forecasting and Social Change, Elsevier, vol. 118(C), pages 281-292.
    15. Lehoux, P. & Miller, F.A. & Daudelin, G., 2017. "Converting clinical risks into economic value: The role of expectations and institutions in health technology development," Technological Forecasting and Social Change, Elsevier, vol. 117(C), pages 206-216.
    16. Liébana-Cabanillas, Francisco & Marinkovic, Veljko & Ramos de Luna, Iviane & Kalinic, Zoran, 2018. "Predicting the determinants of mobile payment acceptance: A hybrid SEM-neural network approach," Technological Forecasting and Social Change, Elsevier, vol. 129(C), pages 117-130.
    17. Stoffregen, Julia Dorothée & Pawlowski, Jan M. & Ras, Eric & Tobias, Eric & Šćepanović, Snezana & Fitzpatrick, Dónal & Mehigan, Tracey & Steffens, Petra & Przygoda, Christiane & Schilling, Peter & Fri, 2016. "Barriers to open e-learning in public administrations," Technological Forecasting and Social Change, Elsevier, vol. 111(C), pages 198-208.
    18. Wang, Yichuan & Kung, LeeAnn & Byrd, Terry Anthony, 2018. "Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations," Technological Forecasting and Social Change, Elsevier, vol. 126(C), pages 3-13.
    19. Lee, Sang Yup & Lee, Keeheon, 2018. "Factors that influence an individual's intention to adopt a wearable healthcare device: The case of a wearable fitness tracker," Technological Forecasting and Social Change, Elsevier, vol. 129(C), pages 154-163.
    20. Shin, Hyungsup & Jung, Jiyeon & Koo, Yoonmo, 2020. "Forecasting the video data traffic of 5 G services in south korea," Technological Forecasting and Social Change, Elsevier, vol. 153(C).
    21. Giones, Ferran & Brem, Alexander & Pollack, Jeffrey M. & Michaelis, Timothy L. & Klyver, Kim & Brinckmann, Jan, 2020. "Revising entrepreneurial action in response to exogenous shocks: Considering the COVID-19 pandemic," Journal of Business Venturing Insights, Elsevier, vol. 14(C).
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