Testing Convergence of Tourism Development and Exploring Its Influencing Factors: Empirical Evidence from the Greater Bay Area in China

Hui Chen, Tianyi Chen, Long Li, Xiaoliang Chen and Jian Huang
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Hui Chen: School of Geography and Planning, Sun Yat-Sen University, Guangzhou 510006, China
Tianyi Chen: Faculty of Health and Sports Science, Juntendo University, Inzai 2701695, Chiba, Japan
Long Li: School of Information Technology in Education, South China Normal University, Guangzhou 510631, China
Xiaoliang Chen: School of Geography and Remote Sensing, Guangdong Provincial Center for Urban and Migration Studies, Guangzhou University, Higher Education Mega Center, Guangzhou 510006, China
Jian Huang: School of Geography and Remote Sensing, Guangdong Provincial Center for Urban and Migration Studies, Guangzhou University, Higher Education Mega Center, Guangzhou 510006, China

Sustainability, 2022, vol. 14, issue 11, 1-12

Abstract: Inverse globalization and the spread of epidemics have affected the world economy. Promoting the convergence and resilience of the tourism industry is an important means of boosting regional economic recovery and high-quality development. Taking the nine cities in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) as cases, this study measures the state of development in each city from 2010 to 2019, and it constructs a coupled coordinated model to evaluate the integration of culture and tourism development. The entropy method and the coupling-coordination-degree model are evaluated through this empirical analysis. The results demonstrate that most cities in the GBA show an upward trend in the development and integration of the tourism industry. The development and integration of the tourism industry in Guangzhou and Shenzhen has always been in a leading position. The main factors that affect the level of tourism-industry convergence in the GBA cities include the level of economic development, the scale of government spending, the level of urbanization, and the level of technological innovation.

Keywords: cultural tourism; influencing factors; Guangdong–Hong Kong–Macao Greater Bay Area (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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