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Stephen L. Shapiro, Tim DeSchriver, and Daniel A. Rascher

Luxury suites have become a key revenue source and an important element of sport facility design for professional sport organizations. There are a variety of factors influencing the pricing of luxury suites; however, the recent recession has impacted the premium seat sales market significantly. The current investigation was the first empirical examination of luxury suite pricing determinants for professional sport facilities. An economic model, utilizing multiple regression analysis, was constructed to examine the relationship between the current price of luxury suites for major North American professional sports facilities and selected demographic, economic, and team/facility/league-specific explanatory variables, in a uncertain economic climate. The final economic models were found to be significant, explaining 57% and 60% of the variability in luxury suite prices, respectively. Significant variables of interest included team performance and league affiliation, which had a positive influence and the number of competing venues, which had a negative influence on luxury suite prices. The current findings further the body of knowledge in the pricing of admissions to sporting events though the development of the first pricing determinants models for luxury suites, which take into consideration the tenuous economic environment.

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Gidon S. Jakar and Kiernan O. Gordon

and Planning B: Urban Analytics and City Science, 44 ( 4 ), 647 – 667 . https://doi.org/10.1177/0265813515624686 Feng , X. , & Humphreys , B. ( 2018 ). Assessing the economic impact of sports facilities on residential property values: A spatial hedonic approach . Journal of Sports Economics

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John L. Crompton

Many sports events, facilities, and franchises are subsidized either directly or indirectly by investments from public sector funds. The scarcity of tax dollars has led to growing public scrutiny of their allocation; in this environment there is likely to be an increased use of economic impact analysis to support public subsidy of these events. Many of these analyses report inaccurate results. In this paper, 11 major contributors to the inaccuracy are presented and discussed. They include the following: using sales instead of household income multipliers; misrepresenting employment multipliers; using incremental instead of normal multiplier coefficients; failing to accurately define the impacted-area; including local spectators; failing to exclude “time-switchers” and “casuals;” using “fudged” multiplier coefficients; claiming total instead of marginal economic benefits; confusing turnover and multiplier; omitting opportunity costs; and measuring only benefits while omitting costs.

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John Crompton

Government contributions to the funding of major league facilities ipso facto recognize that some portion of the benefits accruing from such facilities accrue to the public in general, rather than being captured exclusively by the franchise owner. The challenge for facility advocates is to demonstrate the return on investment to the taxpayer. This has been elusive. The canard that substantial returns accrue from the direct economic impact of visitors to games has been discredited. A taxonomy of four alternate sources of spillover benefits that are most frequently cited is proposed: increased community visibility; enhanced community image; stimulation of other development; and psychic income. Justifications using to the first three of these alternates are conceptualized as focusing on external audiences, with the intent of encouraging their investment of resources in the community. In some contexts, some economic benefits may accrue from these sources, but in most cases they cannot be demonstrated to be sufficient to justify the taxpayers’ investment. It is argued that psychic income, which focuses internally on the benefits received by existing residents in the community, is likely to be key to justifying public subsidy of major league facilities. It is suggested that the contingency valuation method is an appropriate approach for measuring the psychic income provided by a professional sport franchise.

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Chalida Svastisalee, Jasper Schipperijn, Bjørn E. Hostein, Lisa M. Powell, and Pernille Due

Background:

To investigate socioeconomic patterning of physical activity resources in Copenhagen.

Methods:

We used multivariate logistic regression analysis to examine the association between physical activity-supportive resources [public open space (POS), cycling and walking paths, sports facilities, and intersection density] and neighborhood sociodemographic indicators (low education, recent immigrants, children under 15 yr, and household income).

Results:

Neighborhoods with high proportions of residents with low education were most likely to have POS (OR = 2.63; CI: 2.10–3.29), paths (OR = 3.60; CI: 2.84–4.56) and sports facilities (OR = 5.96; CI: 4.31–8.24). Mid-to-low income areas were less likely to contain POS (OR = 67; CI: 0.49–0.90), paths (OR = 0.36; CI: 0.26–0.50), and sports facilities (OR = 0.48; CI: 0.30–0.77). Areas with children were less likely to have connected streets (OR = 0.51; CI: 0.31–0.83) but more likely to have POS (OR = 1.40; CI: 1.15–1.70) and paths (OR = 1.52; CI: 1.25–1.85).

Conclusions:

Residents living in areas with high proportions of low education or young children are likely to have high exposure to physical activity resources. Exposure to physical activity resources in Copenhagen may not explain the inequalities in physical activity behavior. Further examination of exposure to built environment resources is warranted.

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Burn-Jang Lim, Hee-Duk Rho, Tong-Jin Kim, Ung-Kun Chung, Sinbok Kang, and Jin-Kyung Park

The purpose of this study was to examine the financial investments factors in promoting mass sport in Korea and to determine their relative importance and investment priorities. This information would be a guideline for sports administrators' decision making in establishing investment policy. The Delphi technique (Dalkey, 1976) using 30 experts in mass sport administration and the Analytic Hierarchy Process method (Saaty, 1983) were used in this study. Six investment factors with 21 subfactors were derived. The top investment priority was given to the Sports Facilities factor, followed by the factors of Publicity, Leaders, Administrative Support, Voluntary Sports Clubs, and Programs. Investment priorities of subfactors in each factor were also discussed.

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Christina M. Thornton, Kelli L. Cain, Terry L. Conway, Jacqueline Kerr, Brian E. Saelens, Lawrence D. Frank, Karen Glanz, and James F. Sallis

Background:

The after-school period provides an opportune context for adolescent physical activity. This study examined how characteristics of after-school recreation environments related to adolescent physical activity.

Methods:

Participants were 889 adolescents aged 12 to 17 (mean = 14.1, SD = 1.4) from 2 US regions. Adolescents reported on whether their school offered after-school supervised physical activity, access to play areas/fields, and presence of sports facilities. Outcomes were accelerometer-measured after-school physical activity, reported physical activity on school grounds during nonschool hours, attainment of 60 minutes of daily physical activity excluding school physical education, and BMI-for-age z-score. Mixed regression models adjusted for study design, region, sex, age, ethnicity, vehicles/licensed drivers in household, and distance to school.

Results:

School environment variables were all significantly associated with self-reported physical activity on school grounds during non-school hours (P < .001) and attainment of 60 minutes of daily physical activity (P < .05). Adolescents’ accelerometer-measured after-school physical activity was most strongly associated with access to supervised physical activity (P = .008).

Conclusions:

Policies and programs that provide supervised after-school physical activity and access to play areas, fields, and sports facilities may help adolescents achieve daily physical activity recommendations.