The Nature of Technological Change in the Chinese Hotel Sector

Peypoch, Nicolás; Song, Yuegang; Zhang, Linjia

doi:10.1177/1096348020944459

Cited by 7 publications

(2 citation statements)

References 52 publications

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“…Inspired by the potential usefulness of this method, MPI has been used extensively for the tourism sector. We refer to Peypoch et al, (2021) and Walheer and Zhang, (2022) for their literature reviews.…”

Section: Methodsmentioning

confidence: 99%

Dynamic Technical Performance Measurement in Rural Tourism

Zhu

Liu

Luo

et al. 2022

Journal of Global Information Management

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With the characteristic of low carbon emission and sustainability, the development of rural tourism becomes one of the key parts to achieve mutual carbon target in Chinese tourism industry. However, previous research on China's rural tourism has largely ignored the quantitative examination of rural tourism initiatives. This paper aims to quantify and measure the efficiency as well as efficiency variation of rural tourism in 25 provinces of China using data envelopment analysis (DEA) and Malmquist productivity index (MPI). The results reveal that the overall efficiency of rural tourism in China is still low, and there exists an obvious regional difference in rural tourism in China. The result not only identify the leading and following regions in Chinese rural tourism, but also reveal how their position in the group changes over time. This is valuable information for managers having to take strategic and tactical decisions to better achieve the low-carbon and sustainable development of China's tourism industry.

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Section: Methodsmentioning

confidence: 99%

Dynamic Technical Performance Measurement in Rural Tourism

Zhu

Liu

Luo

et al. 2022

Journal of Global Information Management

Self Cite

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“…Regarding research content, previous studies focused on quantitative evaluation of the TTFP of tourism enterprises (Reynolds and Biel, 2007), industries (Walheer and Zhang, 2018), and tourism destinations (Goncalves, 2013; Sun et al, 2015). Some scholars also discussed the internal composition, regional differences, spatial correlations, and driving factors of TTFP (Peypoch et al, 2021; Li et al, 2014; Yi and Liang, 2015; Xia et al, 2018).…”

Section: Literature Reviewmentioning

confidence: 99%

Evaluating the tourism green productivity and its driving factors in the context of climate change

Zheng

Luo

2023

Tourism Economics

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In the context of global climate changes, the green transformation of tourism industry has become a general trend. This study constructed a comprehensive evaluation model (Super SBM-GML) to measure the tourism green productivity (TGP) and used methods including kernel density estimation, spatiotemporal transition, and quantile regression to analyze the evolutionary characteristics and driving factors of province-level TGP in China between 2009 and 2019. The results showed the following: (1) China’s TGP exhibited a two-stage growth trend, maintaining steady growth before 2014 and accelerating thereafter. (2) Regarding the dynamic evolutionary characteristics, the local spatial structure of provincial TGP remains unstable, and the provinces themselves can change their relative positions relatively easily, showing certain characteristics of spatial agglomeration and dynamic interaction. (3) The spatiotemporal network pattern of provincial tourism green productivity was dominated by positive correlations, indicating that the overall collaborative dynamics between provinces were stronger than the competition. However, a certain degree of spatiotemporal competition could be found between some neighboring provinces. (4) The TGP is affected by various driving factors such as tourism economic scale, industrial structure, scientific and technological innovation and environmental regulations, but the driving intensity and direction of each factor differ significantly across the TGP developmental stages.

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