Allocations of Government Funding for Public-owned Tourist Attractions in China: An Empirical Examination

Author Bios (50 Words for each Author)

Junya Liu is a doctoral candidate at the College of Business at Shanghai University of Finance and Economics. Her research focuses on organizational behavior and financial sustainability in tourism and leisure. Her Email Address is Liujunya613@hotmail.com.

Suiwen (Sharon) Zou, Ph.D. (szou@illinois.edu), is an assistant professor in the Department of Recreation, Sport and Tourism at the University of Illinois at Urbana-Champaign. Dr. Zou's research focuses on the pricing and financial issues of tourism and leisure services.

Jamie M. Chen, Ph.D., is an Associate Professor in the Norwegian School of Hotel Management at the University of Stavanger, Norway. Dr. Chen’s research focuses on tourism economics, service modeling, digital marketing, consumer behavior, social media analytics, and international business. Email: mei.chen@uis.no.

Abstract (150 Words)

For public tourist attractions, financial viability heavily depends upon sufficient government funding. However, research on government allocations has historically been quite rare. This study addressed this relevant gap by using a panel dataset of 171 public attractions in China from 2015 to 2018. Double-hurdle models and quantile regressions were employed to examine the determinants of government funding for public attractions. The findings suggested that attraction attributes played an influential role in the amount of government appropriations, but they were less impactful on the attractions’ likelihood of receiving government funding. Besides, it was revealed that attraction attributes exerted stronger impacts as attractions’ government funding level increased. The local economic condition was also a significant factor of both the possibility and the amount of government funding.

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Allocations of Government Funding for Public-owned Tourist Attractions in China: An Empirical Examination

For public tourist attractions, financial viability heavily depends upon sufficient government funding. However, research on government allocations has historically been quite rare. This study addressed this relevant gap by using a panel dataset of 171 public attractions in China from 2015 to 2018. Double-hurdle models and quantile regressions were employed to examine the determinants of government funding for public attractions. The findings suggested that attraction attributes played an influential role in the amount of government appropriations, but they were less impactful on the attractions’ likelihood of receiving government funding. Besides, it was revealed that attraction attributes exerted stronger impacts as attractions’ government funding level increased. The local economic condition was also a significant factor of both the possibility and the amount of government funding.