Research Methodology for Tourism Destination Resilience and Analysis of Its Spatiotemporal Dynamics in the Post-epidemic Period

doi:10.5814/j.issn.1674-764x.2021.05.011

Abstract

Abstract:

As the COVID-19 pandemic continues to spread, the global tourism industry is facing enormous challenges. There is an urgent need to explore an effective path for tourism to recover and revitalize. With the normalization of the epidemic, tourism destinations will pay more attention to the prevention, warning, and coping strategies of the epidemic, and this focus will also be evident in the study of tourism destination resilience in the post-epidemic period. Some studies on the epidemic and the resilience of tourism are currently underway, but few of them are integrated with research on the resilience of tourism destinations in the post-epidemic period, although no systematic research ideas or methods have been found. Based on resilience theory, this paper summarizes the general research ideas and develops an epidemic resilience model suitable for urban tourism destinations. The present study also proposes a set of research methods based on the index system to analyze the resilience and its spatiotemporal dynamic characteristics of tourism destinations in the post-epidemic period. The methodology can be divided into three stages: Firstly, construct the conceptual model and evaluation system for tourism destination resilience; Secondly, select case sites for empirical analysis, measure the resilience of tourism destinations, and analyze the characteristics of spatiotemporal differences and subsequent factors of influence; And finally, establish an adaptive management mechanism for tourism destinations to use in response to the epidemic and in guiding the formulation of post-epidemic recovery policies.

Key words: epidemic, tourism destination, resilience, index system, spatiotemporal dynamics

FENG Ling, GUO Jiaxin, LIU Yi. Research Methodology for Tourism Destination Resilience and Analysis of Its Spatiotemporal Dynamics in the Post-epidemic Period[J]. Journal of Resources and Ecology, 2021, 12(5): 682-692.

Figures/Tables 7

References 59

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Models	The main content	Source
Destination Sustainability Framework (DSF)	Pointed out six elements of system resilience: Shock and stress; vulnerability; feedback loops; place; space; time	Calgaro et al. (2014)
Scale, Change and Resilience Model (SCRM)	Emphasized the different ways community members respond to chronic and sudden stress	Lew (2014)
Community Disasters Resilience Framework (CDRF)	Pointed out that the community capital related to the resilience of the community after disaster mainly includes social capital, economic capital, physical capital, human capital, and natural capital	Peacock et al. (2010)
Sphere of Tourism Resilience (STR)	Proposed the key elements of a resilient tourism system: harness market forces, stakeholder cohesion, leadership, flexibility, adaptability, and learning	Cochrane (2010)
Tourism Disaster Vulnerability Framework (TDVF)	Pointed out that public and private sector institutions, individuals, communities, infrastructure, and natural environment are all factors affecting the vulnerability of tourism destinations	Becken et al. (2014)

Models	The main content	Source
Destination Sustainability Framework (DSF)	Pointed out six elements of system resilience: Shock and stress; vulnerability; feedback loops; place; space; time	Calgaro et al. (2014)
Scale, Change and Resilience Model (SCRM)	Emphasized the different ways community members respond to chronic and sudden stress	Lew (2014)
Community Disasters Resilience Framework (CDRF)	Pointed out that the community capital related to the resilience of the community after disaster mainly includes social capital, economic capital, physical capital, human capital, and natural capital	Peacock et al. (2010)
Sphere of Tourism Resilience (STR)	Proposed the key elements of a resilient tourism system: harness market forces, stakeholder cohesion, leadership, flexibility, adaptability, and learning	Cochrane (2010)
Tourism Disaster Vulnerability Framework (TDVF)	Pointed out that public and private sector institutions, individuals, communities, infrastructure, and natural environment are all factors affecting the vulnerability of tourism destinations	Becken et al. (2014)

Dimensions	Primary indicators	Secondary indicators
Internal conditions of the tourism destination	Tourism economic system	Tourist arrivals, tourism revenue, tourism employment, the concentration of tourist market, etc.
	Tourism social system	Ratio of tourists to local residents, the structure of tourism talents, medical investment, internet penetration rate, etc.
	Tourism institution and cultural system	Tourism warning system, tourism policy publicity system, tourism organization cooperation system, etc.
Characteristics of the epidemic	Tourism infrastructure system	Abundance of tourism resources, the number of hotels, the density of traffic network, the number of medical institutions, etc.
Characteristics of the epidemic	Severity of the epidemic	Duration of the epidemic, the number of infections, death rate of the epidemic, distance from the epidemic center, etc.
Response capacity of the tourism destination	Losses caused by the epidemic	Direct loss of tourism revenue, loss of tourist arrivals, tourism unemployment rate, business operation, tourists’ willingness to travel, etc.
Response capacity of the tourism destination	Prevention and warning ability for epidemic	The response speed of tourism destination to epidemic, the number of tourism warning information sources, the number of tourism security institutions, etc.
Adaptive capacity of the tourism destination	Ability to recover from epidemic	The number of tourism support policies in the post-epidemic period, tourism emergency financial support, etc.
Adaptive capacity of the tourism destination	Potential for tourism development	Growth rate of tourism revenue, growth rate of tourist arrivals, growth rate of tourism investment, etc.

Dimensions	Primary indicators	Secondary indicators
Internal conditions of the tourism destination	Tourism economic system	Tourist arrivals, tourism revenue, tourism employment, the concentration of tourist market, etc.
	Tourism social system	Ratio of tourists to local residents, the structure of tourism talents, medical investment, internet penetration rate, etc.
	Tourism institution and cultural system	Tourism warning system, tourism policy publicity system, tourism organization cooperation system, etc.
Characteristics of the epidemic	Tourism infrastructure system	Abundance of tourism resources, the number of hotels, the density of traffic network, the number of medical institutions, etc.
Characteristics of the epidemic	Severity of the epidemic	Duration of the epidemic, the number of infections, death rate of the epidemic, distance from the epidemic center, etc.
Response capacity of the tourism destination	Losses caused by the epidemic	Direct loss of tourism revenue, loss of tourist arrivals, tourism unemployment rate, business operation, tourists’ willingness to travel, etc.
Response capacity of the tourism destination	Prevention and warning ability for epidemic	The response speed of tourism destination to epidemic, the number of tourism warning information sources, the number of tourism security institutions, etc.
Adaptive capacity of the tourism destination	Ability to recover from epidemic	The number of tourism support policies in the post-epidemic period, tourism emergency financial support, etc.
Adaptive capacity of the tourism destination	Potential for tourism development	Growth rate of tourism revenue, growth rate of tourist arrivals, growth rate of tourism investment, etc.

Data type	Access methods	Research applications
Basic data	Relevant management agencies and organizations	Map data, statistics, population data, etc.
Epidemic data	Relevant management agencies and organizations, WHO website	Number of infections, death rate, the duration of the epidemic, etc.
Service facility data	Relevant management agencies and organizations, network POI data	Number of medical institutions, tourist hotels, tourism resources, etc.
News and policy data	Web text analysis	Tourism early warning information, tourism development support policy, etc.
Visitors/business data	Questionnaires, telephone interviews, industry associations	Number of tourism enterprises, the operation of enterprises, the willingness of tourists to travel, etc.
Tourism traffic data	Network data, airlines, traffic-related administrative departments	Flight route data, high-speed train frequency data, etc.