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This study aims to explore the most salient contributors to residents' support for tourism. As such, the authors measure residents' fear and risk of coronavirus disease 2019 (COVID-19) and residents' animosity towards tourists as predictors of attitudinal, intentional and behavioural support for tourism in China, Malaysia, Kazakhstan and Iran.

An online survey of 1,318 respondents across four countries was conducted, with data analysed using structural equation modelling.

This study shows that residents' perceptions about tourism development vary in different countries based on the impact of COVID-19, even though some factors, such as perceived risk and fear of COVID-19, have a similar effect on residents' attitudes and intentions to support tourism.

Only residents from four countries participated due to the collaborative effort of researchers from these specific countries.

Insight into residents' perceptions and responses to COVID-19 can aid policymakers and managers in developing effective crisis recovery strategies.

The data from this study can serve as a foundation for future research to examine residents' attitudes and support towards tourism during the post-COVID-19 period.

Unlocking the unrevealing of residents' perceptions and coping mechanisms towards tourists during the pandemic, this research shines a light on their crucial role in the revival of the tourism industry. With an exclusive focus on residents' attitudes and behaviours, this study stands out amongst the few that delve into this crucial aspect of post-pandemic recovery.

This study aims to investigate the relationships between the perceived neighborhood walkable environment (PNWE), neighborhood interaction (NI) and residents’ mental health, with a focus on examining differences among residents of different age groups.

Using an electronic survey questionnaire, data on PNWE, NI and mental health were collected from 1,159 residents across 205 communities in Shanghai, China. Our study utilized a structural equation modeling (SEM), employing the maximum likelihood estimation method. The structural equation model was fitted using the MPLUS software.

The mental health of young and middle-aged adults is generally poor, and they are at higher risk of depression than children and older adults. The effects of PNWE and NI on the mental health of residents varied among different age groups. As residents get older, their mental health is more affected by the PNWE. In addition, the influence of the PNWE on children and older adults’ mental health is direct and not mediated by NI. For young and middle-aged adults, the influence of the PNWE on their mental health needs to be mediated by NI.

This study marks the first examination of the relationship between PNWE, NI and mental health among different age groups of residents in China. The findings of this research can assist policymakers in gaining a deeper understanding of the underlying mechanisms by which PNWE affects mental health. Furthermore, it can contribute to the development of more targeted walkable environment designs aimed at enhancing mental health among various age groups.

This study aims to identify the attitudes of Chinese residents towards tourists and tourism development. Based on periods of observation, temporary residency and several visits for more than a decade, and supplemented by data collected from 478 residents, the study examines to what extent the rural villagers identify the tourism induced changes as being an outcome of official Chinese policies. The villages, Xidi, Hongcun and Nanping, are three heritage villages in Anhui Province and represent appropriate case studies for such an examination due to their differing histories of tourism administrative procedures. Findings contribute to scholarly knowledge by putting pro-poor tourism and community participation under scrutiny in Chinese context. A change of residents’ perceptions towards tourism could potentially be consequential for tourists’ experience and the sustainability of tourism development, particularly in emerging rural destinations.

This paper aims to investigate the relationship between tourism efficiency at the city level and the quality of life (QOL) of residents. It focuses on assessing whether more efficient tourism cities in China, from an economic standpoint, also offer a higher quality of life for their residents.

A sample of 40 Chinese cities from 2010 to 2019 is analyzed. The study first employs Data Envelopment Analysis to construct a production technology and estimate the technical tourism efficiency of each city. Subsequently, a nonparametric statistical test of independence is applied yearly to explore potential relationships between the cities’ tourism efficiency rankings and their residents’ QOL. This latter is measured by constructing an index for each city following the OECD framework.

The findings of the study are mixed, revealing no clear relationship between tourism efficiency and residents’ quality of life within the analyzed period. This suggests a complex interplay between economic efficiency in tourism and the broader social and environmental factors contributing to QOL.

This study enhances the literature on tourism efficiency by investigating the relationship between tourism efficiency and QOL, an aspect frequently overlooked in efficiency evaluations. Our approach offers a comprehensive understanding of the interplay between economic performance in the tourism sector and the social well-being of city populations. To the best of the authors’ knowledge, this is the first instance where such a relationship has been explored at the city level within the Chinese context.

This paper attempts to study the relationship between the level of urban innovation and subjective well-being (SWB). The following questions are discussed: (1) Does improving the level of innovation in cities affect the SWB of residents? (2) If urban innovation levels affect residents' SWB, can improving urban innovation level improve residents' SWB? (2) If urban innovation level improves residents' SWB, what is the possible mechanism? (3) Is there any difference in the effect of urban innovation level on the SWB of different groups?

This paper chooses the ordinary least squares (OLS) regression method for baseline regression with robust standard errors, and the regression results of Oprobit will be presented in detail in the robustness test section. The model is constructed by matching the micro data and the macro data. Meanwhile, the instrumental variable (IV) method is also used to deal with the possible endogeneity problem.

This paper finds that urban innovation has significantly improved the SWB of residents. This finding still holds after considering the endogeneity issue and conducting a series of robustness tests. Moreover, the level of innovation positively influences residents' SWB mainly through the paths of increasing income levels, improving environmental quality and promoting convenience in life. What's more, urban innovation has a more significant effect on the SWB of low-income groups and those with low education levels. Finally, based on the findings, this paper also proposes some policy recommendations to further improve the SWB of residents.

Given the limitations of the data, the above study deals with China. In the future, international data can be further used to further explore the impact of the innovation level of international cities on the SWB of residents and then the research conclusions can be applied to the international community to provide theoretical basis and empirical support for policy makers of various countries, which will help improve the SWB of residents of various countries and enrich the theoretical and empirical research on the impact of innovation on the SWB of residents.

Well-being is a goal constantly pursued by human beings. This paper shows that urban innovation has significantly improved the SWB of residents. The findings provide guides to improve the SWB of residents and provide a certain theoretical basis and empirical reference for policy makers.

The possible innovations or contributions of this paper include: (1) based on the China Household Income Survey (CHIP) and the “Report on Innovation of Chinese Cities and Industries”, this paper studies the impact of urban innovation levels on residents' SWB, supplementing the gaps in existing literature; (2) through group analysis, the heterogeneity of the impact of urban innovation level on groups with different incomes and education levels was discussed and (3) the mechanism of urban innovation level on residents' SWB was identified. These studies and discussions provide a basis for more effective improvement of residents' SWB and provide a valuable reference for promoting people's pursuit of a better life.

The purpose is to understand the factors affecting Chinese diet selections and propose strategies for revolutionizing Chinese diets toward healthy ones.

This study implemented an online discrete choice experiment to identify the factors affecting diet selections among urban Chinese consumers. Four different diet patterns were used to label each of the product alternatives in the experiment, which varied in taste and cost. Specifically, implying the healthiness and sustainability of a diet, the diet alternatives included the average diet, the Chinese Food Guide Pagoda diet, the EAT-Lancet diet and the Flexitarian diet. Using consumer data from six provincial capital cities, we used random parameter logit models to estimate their preferences.

Diet type and diet cost were found to be more important in urban Chinese consumers' diet selections than the ability to customize taste. The average diet, although not healthy and sustainable, was preferred most by respondents, signaling the challenges of shifting the consumer diet in China. Increasing the cost of the average diet can significantly promote sustainable healthy diet choices among urban Chinese residents. In other words, improving the affordability of sustainable healthy diets would have the potential to fuel the diet revolution in China.

Instead of choices of a single food item, this paper focused on the individual selection of a diet, where different food products can act as substitutes or as complements for one another. We also proposed a way to assess individual preferences and valuations for several different diets.

The research attempts to estimate how the use of WeChat, the most popular mobile social networking application in contemporary China, affects rural household income.

Our materials are 4,552 rural samples from the Chinese General Social Survey, and a treatment effect (TE) model is employed to address the endogeneity of WeChat usage.

The results prove that WeChat usage has a statistically significant and positive correlation with rural household income. This conclusion remains robust after using alternative variables to replace the explanatory and dependent variables. Our research provides two channels through which WeChat usage boosts rural household income, namely, it can promote their off-farm employment and participation in investment activities.

Theoretically, the study provides several micro-evidences for understanding the impact of mobile social networks on rural household welfare. Further, our findings may shed light on the importance of digital technology applications in rural poverty alleviation for developing countries.

Redistributive policies aim to reduce income disparities and improve social equity. This study investigates whether redistributive effects that successfully diminish objective income inequality also effectively alter people’s perceptions of inequality.

Utilizing data from the 2018 China Household Income Survey (CHIP), comprising 56,167 individuals, this study applies ordered probability regression (Oprobit) and ordinary least squares (OLS) for analysis. To address potential biases in estimates, we employed the generalized propensity score matching (GPSM) method to estimate the treatment effect of transfer income on perceptions of inequality.

The results indicate that while China’s redistribution policies effectively reduce income disparities, they do not improve perceptions of inequality. Individuals exhibit biased attitudes toward redistributive policies. Specifically, perceptions of inequality are insensitive to the overall redistributive effect; the relationship is negative among the poor but positive among the rich. This contradictory pattern may be attributed to perceived income losses among the rich and gains among the poor.

The findings have important implications for policy development. Redistribution policies should not only aim to mitigate income disparities but also address and improve people’s perceptions of inequality.

Existing literature has largely overlooked the impact of redistribution on perceived income inequality. This study represents an early effort to explore whether redistributive policies that reduce income inequality also influence people’s perceptions of inequality.

Smart community construction (SCC) and efficiency require resident participation. This paper aims to explore the determinants of residents’ participation intention (RPI) in the SCC.

Based on the theory of planned behavior (TPB), this study proposed an extended conceptual model to deeply analyze the RPI in the SCC. The relationship between all constructs was verified by processing and analyzing online survey data using confirmatory factor analysis (CFA), structural equation model (SEM), and bootstrapping method.

Participation attitude, perceived behavioral control, subjective norm, and perceived usefulness significantly and positively affected the RPI. Furthermore, intermediary effects in the extended conceptual model had been confirmed.

To fill the critical gap in the research on the determinants of the RPI in the SCC context, this study developed a novel conceptual model by extending the TPB to analyze the effects of self-driven and externally-driven factors on the RPI from the perspectives of residents’ psychology and external environment. The findings not only clarify the complex process of forming the RPI in the SCC but also provide a theoretical foundation for studying the RPI in similar community construction projects. Additionally, several strategies have been proposed to encourage residents’ participation in the SCC and promote the development of smart communities, such as clarifying residents’ participation obligations, improving the convenience services of smart communities, and diversifying residents’ participation approaches.

The purpose of this paper is to develop an index for measuring urban house price affordability that integrates spatial considerations and to explore the drivers of housing affordability using the post-least absolute shrinkage and selection operator (LASSO) approach and the ordinary least squares method of regression analysis.

The study is based on time-series data collected from 2005 to 2021 for 256 prefectural-level city districts in China. The new urban spatial house-to-price ratio introduced in this study adds the consideration of commuting costs due to spatial endowment compared to the traditional house-to-price ratio. And compared with the use of ordinary economic modelling methods, this study adopts the post-LASSO variable selection approach combined with the k-fold cross-test model to identify the most important drivers of housing affordability, thus better solving the problems of multicollinearity and overfitting.

Urban macroeconomics environment and government regulations have varying degrees of influence on housing affordability in cities. Among them, gross domestic product is the most important influence.

The paper provides important implications for policymakers, real estate professionals and researchers. For example, policymakers will be able to design policies that target the most influential factors of housing affordability in their region.

This study introduces a new urban spatial house price-to-income ratio, and it examines how macroeconomic indicators, government regulation, real estate market supply and urban infrastructure level have a significant impact on housing affordability. The problem of having too many variables in the decision-making process is minimized through the post-LASSO methodology, which varies the parameters of the model to allow for the ranking of the importance of the variables. As a result, this approach allows policymakers and stakeholders in the real estate market more flexibility in determining policy interventions. In addition, through the k-fold cross-validation methodology, the study ensures a high degree of accuracy and credibility when using drivers to predict housing affordability.