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Antecedents and consequences of telework during the COVID-19 pandemic: a natural experiment in Japan

Author

Listed:
  • Hiina Domae

    (Kyoto University)

  • Masataka Nakayama

    (Kyoto University)

  • Kosuke Takemura

    (Shiga University)

  • Yasushi Watanabe

    (Kyoto University)

  • Matthias S. Gobel

    (University of Sussex)

  • Yukiko Uchida

    (Kyoto University)

Abstract

Amidst the global COVID-19 pandemic, telework (remote work) has become a widespread practice adopted by companies worldwide. However, Japan has notably maintained a low rate of telework implementation, suggesting cultural factors hindering its adoption. This study aimed to elucidate the antecedents and consequences of teleworking in Japan. Leveraging the natural experiment created by the COVID-19 pandemic, we addressed two key questions: (1) What socio-psychological factors in Japanese workplaces were important for implementing telework in the first place? and (2) How did the implementation of telework subsequently influence socio-psychological factors in these workplaces? Employees from various Japanese companies completed three waves of an online survey before and during the pandemic. Results showed that telework was more likely to be implemented in organizations characterized by a meritocracy. Results also showed that the implementation of telework demonstrated no measurable negative effects but instead increased levels of independence, organizational commitment, and perceived hierarchy mutability.

Suggested Citation

  • Hiina Domae & Masataka Nakayama & Kosuke Takemura & Yasushi Watanabe & Matthias S. Gobel & Yukiko Uchida, 2024. "Antecedents and consequences of telework during the COVID-19 pandemic: a natural experiment in Japan," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-13, December.
  • Handle: RePEc:pal:palcom:v:11:y:2024:i:1:d:10.1057_s41599-024-02770-7
    DOI: 10.1057/s41599-024-02770-7
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    References listed on IDEAS

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    1. Okubo, Toshihiro, 2022. "Telework in the spread of COVID-19," Information Economics and Policy, Elsevier, vol. 60(C).
    2. Robert Tibshirani, 2011. "Regression shrinkage and selection via the lasso: a retrospective," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 73(3), pages 273-282, June.
    3. Adamovic, Mladen, 2022. "How does employee cultural background influence the effects of telework on job stress? The roles of power distance, individualism, and beliefs about telework," International Journal of Information Management, Elsevier, vol. 62(C).
    4. Venkatesh, Viswanath, 2020. "Impacts of COVID-19: A research agenda to support people in their fight," International Journal of Information Management, Elsevier, vol. 55(C).
    5. Mansour Javidan & Robert J House & Peter W Dorfman & Paul J Hanges & Mary Sully de Luque, 2006. "Conceptualizing and measuring cultures and their consequences: a comparative review of GLOBE's and Hofstede's approaches," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 37(6), pages 897-914, November.
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