Abstract
Rural tourism plays an important role in advancing the rural economy but faces unexpected risks and challenges such as the deterioration of operational performance. Information and communications technologies (ICT) – such as digital payment platforms, online booking systems, social media marketing, and virtual reality tours – become pervasive in the tourism industry during the current digital era. However, little empirical evidence has been presented about how such technologies impact rural tourism and if rural tourism resilience gets enhanced with the support of ICT in China. This study addresses this research gap by analyzing a sample of 20,716 rural tourism operators from the Third National Agricultural Census of 2016 in Beijing, which is a major urban center in China with a substantial market for rural tourism products and services. With the aid of a treatment effect model (TEM), the research results show that ICT can be an effective way to promote the rural tourism industry through mitigating business difficulties and risks and therefore to enhance the resilience of rural tourism. Our study shows that ICT plays an important and positive role in promoting tourism sales externally and enhancing management internally. The heterogeneity of the operator’s organization type and human capital also makes a difference. The sample data robustly show that ICT can effectively alleviate “scale discrimination” and support “low education level bias”, which is conducive to small-scaled business households and has also increased the resilience of those operators who are at a disadvantaged position in the industry.
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Notes
Quoted from Why two Indexes of Folk Tourism in the Suburbs of Beijing Decline Steeply-A Survey of Structural Reform on the Supply Side of Rural Tourism, Beijing Daily, Page 8, April 10, 2018, http://bjrb.bjd.com.cn/html/2018-04/10/content_237447.html.
This document was deemed the “No. 1 Central Document” of the CPC Central Committee of that year. Generally, the No. 1 Central Document is considered by policymakers one of the most important documents issued that year.
Quoted from the 45th Statistical Report on the Development of China’s Internet, issued by the China Internet Network Information Center, http://www.cac.gov.cn/2020-04/27/c_1589535470378587.htm. The “traveling reservation” to which this document refers includes online booking of air tickets, hotels, train tickets, tourism products, and vacation packages.
Due to space constraints, we do not report on the process to control for the control variables. Please, contact the author to obtain the detailed report.
Since there are samples of negative profit, 647 samples will be lost by taking the logarithm, but the proportion is very low and does not affect the results.
Owing to the difference between arithmetic average and geometric average, if operating income and operating profit in their logarithmic forms are converted to their original value, there will be deviation (Ma & Abdulai, 2016). Therefore, unless otherwise specified, the following estimates of the average treatment effect are expressed in the logarithmic forms of operating income and profit.
Operating organizations include legal entities, unregistered entities, and industrial establishments of multi-industry legal entities. The definition of legal entity, unregistered entity, and industrial establishment of multi-industry legal entity can be found in the Third National Agricultural Census Plan of Beijing City.
In the Third National Agricultural Census Plan of Beijing City, registered capital was the only indicator that was close to the investment scale. Moreover, owing to the fact that most rural tourism operators are self-employed and that market authorities supervise them with relative flexibility, registered capital is already low or null (including lack of data), resulting in a large difference between registered capital and the actual investment scale. Additionally, despite the fact that the number of tourists received can reflect operation scale (at least to a certain extent), there are also many rural tourism business projects that have large investment scales and cannot be directly measured by the number of tourists. This is related to market positioning (e.g., “being private” and “being peaceful and quiet”). Even so, we still compared the average treatment effect of ICT use in the groups based on the quartile of registered capital and the number of tourists received. The results showed that most of the average treatment effects of ICT1, ICT2, and ICT4 on operating income and profits decreased with the increase of registered capital and the number of tourists received. Still, there was no significant change for the effects of ICT3 in each quantile group. This corroborates the results of the classification by organization type. Please contact the author to obtain the relevant results.
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The authors gratefully acknowledge financial support from the National Natural Science Foundation of China (No.72073135), the special developing and guiding fund for building world-class universities (disciplines) of Renmin University of China (No.23XNO002) and Social Science Foundation of Beijing (No.23JJA003).
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Zhong, Z., Zhang, Y., Zhang, J. et al. How information and communication technologies contribute to rural tourism resilience: evidence from China. Electron Commer Res (2024). https://doi.org/10.1007/s10660-024-09854-1
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DOI: https://doi.org/10.1007/s10660-024-09854-1