Examining Determinants of Sport Event Attendance: A Multilevel Analysis of a Major League Baseball Season. Issue 1 (2nd January 2022)

• Record Type: Journal Article
• Authors: Lim, Namhun; Pedersen, Paul M.
• Is Part Of: Journal of global sport management. Volume 7:Issue 1(2022)
• Page Start: 181
• Page End: 198
• Publication Date: 2022-01-02
• Subjects: Attendance -- attendance determinants -- MLB -- multilevel modeling -- hierarchical linear regression modeling; 考勤 -- 考勤决定因素 -- 大联盟 -- 多级建模 -- 分层线性回归建模; Sports administration -- Periodicals; Sports administration; Periodicals; 796.06
• DOI: 10.1080/24704067.2018.1537675
• Languages: English
• ISSNs: 2470-4067

Abstract

Abstract: Attendance data in sports leagues are organized at more than one level and thus are nested data with factors varying by individual games (e.g. single game attendance figure), which are nested within the factors varying by teams (e.g. local population and income level, stadium). Such a nested data structure requires a multilevel modeling approach for an accurate examination of attendance. Also, although the previous application of multilevel modeling to sport attendance research has been limited to the data aggregated and averaged by seasons or by teams, no multilevel modeling of attendance data at the individual game level is available. The uniqueness of the current study is its extension of the multilevel modeling approach by analyzing the audience data at the individual game level. Thus, this study examined the relationship between attendance determinants and single game attendance in a Major League Baseball (MLB) season by using multilevel modeling with 14 game level variables and 12 team level variables. Twelve predictors (e.g. home/visiting team playoff appearances, day of game, season progress, ticket price, stadium capacity, game uncertainty) significantly ( p < .05) influenced attendance.