Linjia Zhang

Rural tourism has become a key instrument for promoting economic development in rural areas. In response, the central government of China launched the National Rural Tourism Key Villages (LRTV) policy in 2019, designating 320 villages with high tourism potential to receive financial support, talent training, and destination planning to boost rural revitalization. This study employs the synthetic control method from 2005 to 2021 to assess the policy’s economic effects. Results show that treated villages experienced, on average, a 12.45% increase in local GDP relative to their synthetic counterparts. This result suggests that state-led tourism policies can promote economic growth in rural areas with weak tourism market mechanisms. The policy’s effectiveness also varies by economic conditions, population density, and tourism type. This study fills a gap by providing evidence on rural tourism effectiveness in China with implications for other developing economies.

The purpose of this contribution is to compute the popular Malmquist productivity index while adding a component representing plant capacity utilisation. In particular, this is—to the best of our knowledge—the first empirical application estimating both input- and output-oriented Malmquist productivity indices in conjunction with the corresponding input- and output-oriented plant capacity utilisation measures. Our empirical application focuses on a provincial data set of tourism activities in China over the period 2008–2016. The results contain the output- and input-oriented Malmquist productivity indices, some Spearman rank correlations between both, a t-test whether these indices differ from unity, and some bootstrapping analysis.

Measuring productivity has been a hot topic in tourism research recently. This research note suggests a tailored productivity indicator capable of dealing with two important features of the tourism suppliers. First, it takes the economic objective of the tourism entities into account, which better reflects the targets of tourism entities. Second, the indicator provides a suitable tool for evaluating performance of tourism suppliers under multiple activity scenarios, which better matches the characteristics of tourism services. The empirical illustration to the Chinese star-rated hotel industry highlights the advantages of the suggested indicator for the tourism industry. In particular, we find that Chinese hotels present better performances over time, but not for every activity. This indicator can also be applied to other tourism-related industries.

This study aims to investigate the moderating effects of various distance measures on the relationship between relative pandemic severity and bilateral tourism demand. After confirming its validity using actual hotel and air demand measures, we leveraged data from Google Destination Insights to understand daily bilateral tourism demand between 148 origin countries and 109 destination countries. Specifically, we estimated a series of fixed-effects panel data gravity models based on the year-over-year change in daily demand. Results show that a 10% increase in seven-day smoothed COVID-19 cases led to a 0.0658% decline in year-over-year demand change. The moderating distance measures include geographic, cultural, economic, social, and political distance. Results show that long-haul tourism demand was less affected by a destination’s pandemic severity relative to tourists’ place of origin. The moderating effect of national cultural dimensions indulgence versus constraints was also confirmed. Lastly, a discussion and implications for international destination marketing are provided.

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.

This paper examines the nexus between inbound tourism and bilateral trade in the context of China. Within a gravity model framework, both the cointegration approach and fixed-effects panel technique is applied to conduct the research. The long-run equilibrium relationship between China’s inbound tourism and its bilateral trade flows is ascertained through cointegration tests. Results also show that foreign tourists are positively associated with trade flows between China and its tourism origin countries, while inbound leisure tourists to China have a larger effect on bilateral trade than business tourists. In addition, China’s export activity is more elastic to inbound tourism than is its import activity. These findings reveal important patterns that are useful for policymakers to promote international trade regarding the different influences of inbound tourism. Further, this study extends research on China’s inbound tourism and bilateral trade by providing new empirical developments.

This article investigates the role of technological change in the Chinese hotel sector over the period 2005 to 2015. The analysis is conducted at the provincial level and on the star-rating hotel basis. A three-step approach is adopted. First, the Malmquist productivity index and its decomposition into efficiency and technological change is estimated. Second, the significance of each component is statistically tested. Third, the technological change is decomposed to analyze the Hicks neutrality assumption. The findings show that the Chinese hotel sector experienced an overall productivity growth, which is mainly and significantly driven by a technological progress. In most of the cases, the technological change is not neutral, and input and output biases are characterized.