上海体育赛事与城市旅游互动融合研究
Interactive Fusion of Shanghai's Sport Events and Urban Tourism
Received:February 17, 2017  
DOI:
中文关键词:体育赛事  城市旅游  互动融合
英文关键词:sport event  urban tourism  interactive fusion
基金项目:2016年度国家体育总局体育哲学社会科学研究课题(2299SS16036);2016上海市哲学社会科学规划课题(2016BTY003);2016年上海体育社会科学研究课题(TYSKYJ2016042)。
Author NameAffiliationE-mail
HE Feng School of Economics Shanghai University hefeng@shu.edu.cn 
ZHANG Xiuping Physical Education College, Shanghai University  
WANG Guang Physical Education College, Shanghai University  
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中文摘要:
      通过模式比较,借鉴国际知名体育城市体育旅游互动融合经验,沿循“全球城市位序—省际效益规模组别—上海区位商和区县禀赋”的基准分析,剖析上海体育赛事与城市旅游互动融合的制度性瓶颈和现实困境。通过“市场牵引力—空间向心力—结构量子力”3个层面解析上海体育赛事与城市旅游互动融合机理。通过“两层三级四维”评估体系,即上海赛事旅游市场系统层和变量层两个层次,国际知名赛事、国家优势赛事、本地战略赛事3个级别,“需求结构—供给结构—产业结构—空间结构”4个维度,汇总需求特征。通过逐步多元回归,评估不同级别赛事规模变化率的影响因素,评价上海赛事旅游互动融合的经济效应。
英文摘要:
      Through model comparison and following the experience of the interactive fusion of sports and tourism in world-renowned sports cities, the article discusses the institutional bottleneck and practical difficulties of the interactive fusion of sport events and urban tourism in Shanghai in line with the benchmark analysis of "ranking of the world cities -- scale of the inter-provincial benefits -- local business and districts advantages of Shanghai". It tries to analyze the interactive fusion mechanism of Shanghai's sport events and urban tourism through the three levels of market traction, space centripetal force and structure quantum force. It summarizes the requirement characteristics with the evaluation system of "two levels, three grades and four dimensions", i.e., the levels of system and variables of Shanghai sport events and tourism market; the grades of world-renowned events, national priority events and local strategic events; the dimensions of requirement structure, supply structure, industry structure and space structure. It evaluates the influential factors of the size change rate of different-level events and the economic effects of the interactive fusion of Shanghai's sport events and tourism through multiple stepwise regressions.
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