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COVID-19 and Attendance Demand for Professional Sport in Japan: A Multilevel Analysis of Repeated Cross-Sectional National Data during the Pandemic

Author

Listed:
  • Hiroaki Funahashi

    (School of Health and Sport Sciences, Chukyo University, 101 Tokodachi, Kaizu-cho, Toyota 470-0393, Japan)

  • Shintaro Sato

    (Faculty of Sport Sciences, Waseda University, 3-4-1 Higashifushimi Nishi-Tokyo, Tokyo 202-0021, Japan)

  • Takuya Furukawa

    (Department of Sports Management, Faculty of Management, Osaka Seikei University, 3-10-62 Aikawa Higashiyodogawa-ku, Osaka 533-0007, Japan)

Abstract

In the current investigation, we assess the effect of COVID-19 on intention-based spectator demand for professional sports in Japan captured by eight, monthly repeated cross-sectional national surveys from May to December 2020 ( n = 20,121). We regress spectator demand on individual (e.g., gender), prefecture-wave (e.g., COVID-19 infection status), and prefecture-level factors (i.e., with or without quality professional teams). The results of multilevel logistic regression demonstrate that individual (i.e., male, younger, full-time employment, and with children status) and prefecture-level team factors (i.e., with teams) were associated with intention-based spectator demand. Nevertheless, COVID-19-related factors were found to be unrelated to spectator demand. The findings imply that sports fans are likely to return to the stadium once behavioral restrictions are lifted. The current research provided further evidence that individual factors and team quality serve as influential antecedents of spectator demand in the context of the COVID-19 epidemic.

Suggested Citation

  • Hiroaki Funahashi & Shintaro Sato & Takuya Furukawa, 2022. "COVID-19 and Attendance Demand for Professional Sport in Japan: A Multilevel Analysis of Repeated Cross-Sectional National Data during the Pandemic," IJERPH, MDPI, vol. 19(9), pages 1-10, April.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:9:p:5318-:d:803537
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    References listed on IDEAS

    as
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