Measuring sustainability and competitiveness of tourism destinations with data envelopment analysis

Abstract

This study analyses sustainability and competitiveness through measurements of efficiency, using data envelopment analysis. It constructs a meta-frontier non-radial directional distance function (meta-frontier NDDF) approach, which is then used to define a tourism development index and a tourism sustainability index. Using these indexes, the paper evaluates the efficiency of the tourism sector and its dynamic evolution for 27 cities in the Yangtze River Delta, China, (YRD) from 2010 to 2019. Considering regional heterogeneity, this paper analyzes the meta-frontier, group-frontier efficiency and technology gap ratio of urban tourism in the YRD, and explores the competitiveness of the cities. The results show that the more traditional measure of tourism efficiency, namely the tourism development index, which does not take account of the sector’s undesirable output (i.e., the negative impacts of carbon emissions from travel), produces overestimates. This study highlights the following practical implications: The increasing competition among tourism destinations requires tourism industry managers to determine the appropriate allocation of resources to promote the sustainable development of urban tourism. In the context of the need for global ‘carbon neutrality’, more consideration should be given to the negative impact of tourism on the natural environment to enhance the competitiveness of tourist destinations.

Keywords:

• Tourism destination
• sustainable development
• competitive analysis
• meta-frontier NDDF
• data envelopment analysis
• Yangtze River Delta

Acknowledgment

The authors would like to thank editors and anonymous reviewers for their helpful comments and suggestions.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

The research was partially supported by the National Natural Science Foundation of China (Nos. 71971124; 71932005); the Liberal Arts Development Fund of Nankai University (No. ZB21BZ0106); the One Hundred Talents Program of Nankai University (No. 63213023).

Notes on contributors

Dongdong Wu

Dongdong Wu is a PhD candidate at College of Tourism and Service Management, Nankai University, China. His research focuses on sustainable tourism, tourism firm management, text mining, and decision science. His research has been published in journals such as: JCLP, CAIE, ITOR, TASM, GS, etc. Email: [email protected].

Hui Li

Hui Li, PhD, is a Young Chang-Jiang professor and Associate Dean at College of Tourism and Service Management, Nankai University, China. His research focuses on tourism big data mining and prediction, tourism firm management and governance. He has published over 80 papers on tourism, management and information science, such as: ATR, TM, JTR, IJHM, IJCHM, CIT, JHTM, APJTR; EJOR, COR, JORS, FOR; IEEE TSMCA, IAM, INFFUS, INS, etc. Email: [email protected].

Yuhong Wang

Yuhong Wang, PhD, is a full professor majoring in Management Science and Engineering at School of Business, Jiangnan University, China. His research focuses on grey system theory, systems prediction and decision making. His research has been published in journals such as: OMEGA, JORS, CAIE, ESWA, ITOR, TASM, JCLP, GS, etc. Email: [email protected].