From the standpoint of developing a transformative service to create improvements in collective wellbeing (Anderson & Ostrom, 2015), evidence of a sport–resilience relationship is gradually accumulating in the literature (Kim et al., 2022). Sport management and social science scholars are making considerable efforts to understand how sport entities with transformative services can contribute to consumer resilience—an intervention through a sport consumption experience that affects people’s abilities to cope with adversity (Inoue et al., 2022; MacIntosh et al., 2020). However, little is known about the sport industry and spatial consumer behavior in terms of consumer resilience. Although previous researchers have identified a macro-level association between sport industry and community resilience from a bird's eye view (Kim et al., 2021), it could not determine how and where sport industry at a macro level can be related to individual-level resilience through metaphors of Consumer Desire. Specifically, the spatial patterns of sport consumption (i.e., consumer spatial behavior) can be a result of sport consumer behavior affected by spatial context upon heterogeneous features of sport industry across regions (Kim et al., 2021) in the environment–behavior paradigm (Olsson & Gale, 1968). The macrolevel clustering of the sport industry in a region (environment) can be a community resource to provide individuals with the opportunity for sport consumption (behavior), which promotes the micro-level psychosocial factors for sport consumer resilience (Inoue et al., 2022). Furthermore, recent work illustrates heterogeneous spatial interaction at the regional level of the sport industry and individual-level sport consumption (Kim et al., 2022), suggesting the elaboration of cross-level spatial interaction models (Kim et al., 2021). Accordingly, in this study we aim to not only (a) determine spatially heterogeneous interactions in the association between sport industry and consumer spatial behavior in affecting consumer resilience, but also (b) identify what effect spatial interaction has on cross-level relationships. Using data focused on a multiscale-based nested geographic structure (e.g., individual-level consumption by zip code, county, state, and nation) that could elucidate the sport consumer spatial behavior, We collected multiple types of data from Florida, including the location quotient of the main seven sport industries (e.g., sport facilities) and socioeconomic factors (e.g., social vulnerability) at the county level from secondary sources. In addition, we acquired individual-level data from Qualtrics panels (1,107 Florida residents) to measure sport consumer spatial behavior (e.g., location-based sport consumption experience) and consumer resilience using the Connor-Davidson Resilience Scale. To address spatial interaction and heterogeneity, we used a comprehensive analytical model for global and local spatial analysis, including a spatial multilevel mediation (SMM) model and multiscale geographically weighted regression (MGWR) model. As a result of the SMM model, the county-level cluster of sport facilities affected individual-level participatory sport consumption, which enhanced consumer resilience (cross-level interaction effect). However, considerable spatial non-stationarity appeared in the spatial interaction, indicating interregional interactions in the cross-level effects within a county. The results of MGWR indicated significant spatially heterogeneous patterns in the association between the cluster of sport facilities and participatory sport consumption. That is, it was clarified that the spatial heterogeneous effects of the clustering of sport facilities on sport consumer spatial behavior are associated with consumer resilience. This empirical interdisciplinary work, including sport management, geography, and consumer psychology, advances knowledge of consumer spatial behavior and resilience by demonstrating heterogeneous spatial interactions. Practically, the current study calls for spatial management planning and strategy in sport industry for enhancing consumer resilience through spatial sport consumption, considering spatially varying patterns.

주5일 근무제가 확대되어 국민의 여가시간이 증가되고 소득수준이 향상됨에 따라 해양레저스포츠에 대한 국민들의 관심이 높아가고 있다. 지자체들도 전시회, 국제요트대회 등을 경쟁적으로 개최하고 대규모 투자를 추진하고 있다. 그러나 우리나라는 선진국의 수요패턴과 달리 수요가 크게 늘어나지 않고 있다. 그동안 해양레저스포츠의 활성화를 위하여 스포츠관점에서는 많은 연구가 이루어졌으나 산업적 관점에서 산업환경 요인에 대한 연구는 미미한 실정이다. 본 연구에서는 해양레저스포츠산업에 영향을 미치는 경제적, 사회적 환경 등 환경요인을 고찰한다. 이를 위해 해양레저스포츠산업을 둘러싸고 있는 산업환경 요인을 해양레저스포츠산업의 주요성장 지표인 인구 천명당 레저보트(요트 모타보트) 보유척수와의 상관관계로 분석하였다. 마지막으로 선진국과의 해양레저스포츠산업 환경요인을 비교분석하여 우리나라 해양레저스포츠산업의 발전을 위한 방향을 제시하고자 한다.

Prior literature has posited that the sport industry has been effective method to drive the economic growth. Given the rationale, this study sets China as a research object with a quarterly data from the first quarter of 2003 to the fourth quarter of 2017 to explore how the sport industry affects economic growth. This study employed Johansen cointegration test and dynamic ordinary least squares as methods for an empirical analysis. The input of sport industry, the labor input, the capital input, and the economic growth are used as research variables. The results show that there is a long-run relationship among them. Johansen cointegration test’s estimation indicated that 1% increase in the input of sport industry will lead to 0.064% increase in economic growth. Dynamic ordinary least squares’ estimation showed that whenever in the one lead, in the one lag and in the present period, the input of sport industry always poses a positive effect on economic growth. Labor input also has a positive effect on economic growth. The capital input has a negative effect on economic growth. Finally, even though the input of sport industry has a positive effect on economic growth, its impact on economic growth is relative weak.