Abstract
As one of the world’s largest and fastest growing industries, tourism is facing the challenge of balancing growth and eco-environmental protection. Taking tourism CO2 emissions as undesirable outputs, this research employs the bootstrapping data envelopment analysis (DEA) approach to measure the eco-efficiency of China’s hotel industry. Using a dataset consisting of 31 provinces in the period 2016–2019, the bootstrapping-based test validates that the technology exhibits variable returns to scale. The partitioning around medoids (PAM) algorithm, based on the bootstrap samples of eco-efficiency, clusters China’s hotel industry into two groups: Cluster 1 with Shandong as the representative medoid consists of half of the superior coastal provinces and half of the competitive inland provinces, while Cluster 2 is less efficient with Jiangsu as the representative medoid. Therefore, it is suggested that the China government conduct a survey of only Shandong and Jiangsu to approximately capture the key characteristics of the domestic hotel industry’s eco-efficiency in order to formulate appropriate sustainable development policies. Lastly, biased upward eco-efficiencies may provide incorrect information and misguide managerial and/or policy implications.
Highlights
Accepted: 1 March 2022The tourism sector is one of the largest and fastest growing industries in the world.According to the Report on World Tourism Economy Trends [1], global tourism revenues were only USD 2 billion in 1950, but hit USD 5.8 trillion in 2019, which is equivalent to6.7% of global gross domestic product (GDP)
This section discusses the test for returns to scale, the eco-efficiencies of China’s hotel industry, coastal versus inland hotels, and the cluster analysis
If the production possibility set exhibits variable returns to scale (VRS) at some locations, βvrs still remains consistent, but βcrs turns out to be inconsistent [28]. This situation suggests that the BCC model is more suitable for measuring eco-efficiency than the CCR model
Summary
Accepted: 1 March 2022The tourism sector is one of the largest and fastest growing industries in the world.According to the Report on World Tourism Economy Trends [1], global tourism revenues were only USD 2 billion in 1950, but hit USD 5.8 trillion in 2019, which is equivalent to6.7% of global gross domestic product (GDP). The tourism sector is one of the largest and fastest growing industries in the world. According to the Report on World Tourism Economy Trends [1], global tourism revenues were only USD 2 billion in 1950, but hit USD 5.8 trillion in 2019, which is equivalent to. 6.7% of global gross domestic product (GDP). 1950, but reached 12.31 billion in 2019 for an increase of 4.6% over 2018. As their demand highly correlates with the number of tourists seeking to stay overnight, hotels are one of the fastest-growing segments of the tourism sector. The hotel industry provides similar products and services that are visible and imitated by competitors; it is highly competitive. The measurement of hotel efficiency is a vital theme in tourism research
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