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The purpose of this paper is to assess the influences of social trust and neighborhood cohesion on public trust in the police in China.

This study used survey data collected from roughly 5,600 respondents by the 2012 Chinese General Social Survey (CGSS). Multivariate regression was employed to analyze the effects of two forms of social trust, generalized trust and particularized trust, and three types of neighborhood cohesion, neighbor solidary, support and interaction, on public trust in the Chinese police, controlling for personal background characteristics.

Both generalized trust and particularized trust exerted a significant positive effect on trust in the Chinese police. Greater neighborhood cohesion also enhanced public trust in the police. Elderly, women, less educated and people with rural hukou and higher perceived social class were more likely to trust the police.

The CGSS data contained only a single item that could be used to measure public trust in the police. Future studies should consider using multiple survey items to reflect Chinese people’s trust from different conceptual dimensions, such as procedural- and outcome-based trust and police legitimacy. The CGSS data also did not contain information on some relevant predictors, such as victimization and fear of crime, personal and vicarious contact experiences with the police, and news and social media usage and exposure. Future studies, if possible, should incorporate these theoretically relevant and empirically proven variables into the analysis.

Improving neighborhood cohesion is a clear path to cultivate stronger public trust in the police. Policy-makers and officials must bring the neighborhood-centered approach back to local governance by working closely with police leaders and other private and parochial social institutions to launch programs that can effectively stabilize and strengthen local communities and actively promoting positive interactions and social bonds among residents. Policies and programs aimed at enhancing public trust in the police should target at younger, better educated and urban Chinese who are more likely to be critical of the police.

Despite their high relevance, social trust and neighborhood cohesion have received only limited attention in past research on Chinese attitudes toward the police. This study represents one of the first attempts to examine different forms of social trust and neighborhood cohesion on public trust in the police in China.

With the development of the economy, Chinese consumers increasingly seek and emphasise hedonic value over utility value when shopping. The purpose of this paper is to examine the relationship between shopping and consumers’ subjective well-being (SWB), the mediation effect of interpersonal relationship satisfaction and the moderation effects of tradition-directedness and trust in strangers on this relationship.

This research includes two studies. Study 1 tested hypotheses regarding the effects of general shopping behaviours based on data from the 2012 Survey of the Chinese General Social Survey (n=5,210). Study 2 tested hypotheses regarding the effects of mall shopping based on a questionnaire survey conducted in 2016 (n=251).

Results showed that shopping promoted SWB and interpersonal relationship satisfaction mediated this correlation. Findings also revealed that both the direct effect of mall shopping on SWB and the indirect effect through interpersonal relationship satisfaction were contingent on the level of tradition-directedness; the direct effect was significant only at a low level of tradition-directedness. Trust in strangers moderated the effect of mall shopping on interpersonal relationship satisfaction.

The economy and society in China are changing tremendously, affecting consumers’ values and behaviour. This study highlights one aspect of this change, provides a framework for the exploration of the relationship between shopping and SWB and extends a new understanding of how Chinese consumers’ behaviours and lifestyles are associated.

This paper aims to introduce the history and major achievement of the Chinese private enterprise survey (CPES), which is one of the most enduring large-scale nationwide sample surveys in China, providing important micro firm-level data for understanding and studying the development of Chinese enterprises and entrepreneurs over the past 26 years.

The main body of this paper is based on a bibliometric analysis of all literature using CPES until 2017.

This paper discusses problems that users may encounter during data mining. By doing so, it can assist other researchers to get a better understanding of what has been done (e.g. journals, topics, scholars and institutions) and do their research in a more targeted way.

As members of the survey project team, the authors also take a prospect of the future data design and use, as well as offer some suggestions about how to use the CPES data to improve high-quality development and business environment evaluation in China.

This paper is the first to provide an overall picture of academic papers in China and abroad that have used the CPES data.

This paper according to the logic of the “digital access divide--digital capability divide--digital outcome divide” aims to systematically discuss the impact of the digital divide on individual happiness in China, accounting for the variations that exist across different groups, as well as the corresponding mechanisms.

This paper presents cross-sectional analyses of the relationship between the digital divide and individual happiness in China. The analyses are based on data from the Chinese General Social Survey 2017, which academic institutions run on the Chinese Mainland. This database contains information on respondents' Internet access, skills and consequences of use, which can measure the digital divide of Chinese individuals at three levels.

First, individual happiness declined when they experienced the digital access divide in China. For the digital capability divide, the lower the usage skills, the more individual happiness declined. When analyzing the digital outcome divide, the greater the negative consequences, the more individual happiness declined. Second, the impacts of digital access, capability and outcome divide vary according to age, gender, education degrees, hukou, region and sub-dimensions. Third, the digital access and capability divide reduce individuals' happiness by lowering their self-rated social and economic status, whereas the digital outcome divide reduce individual happiness by lowering their fairness perception and social trust.

The authors believe that this is the first study to examine the impact and its variations among different groups of the three-level digital divide on individual happiness, as well as its mechanisms.

This chapter presents systematic evidence on the persistent power of guanxi, the Chinese phrase for informal social relations and networks, in transitional China. I draw heavily on my previous publications reporting findings from a series of probability sample surveys of the Job-Search Network (thereafter JSNET) project in Chinese cities, and job histories of the survey respondents combined cover a span of 37 years from 1978, the beginning year of China's market-oriented reforms, to 2014, the year of last JSNET survey completed.

The General Society Survey(GSS) is a kind of government-funded survey which aims at examining the Socio-economic status, quality of life, and structure of contemporary society. GSS data set is regarded as one of the authoritative source for the government and organization practitioners to make data-driven policies. The previous analytic approaches for GSS data set are designed by combining expert knowledges and simple statistics. By utilizing the emerging data mining algorithms, we proposed a comprehensive data management and data mining approach for GSS data sets.

The approach are designed to be operated in a two-phase manner: a data management phase which can improve the quality of GSS data by performing attribute pre-processing and filter-based attribute selection; a data mining phase which can extract hidden knowledge from the data set by performing data mining analysis including prediction analysis, classification analysis, association analysis and clustering analysis.

According to experimental evaluation results, the paper have the following findings: Performing attribute selection on GSS data set can increase the performance of both classification analysis and clustering analysis; all the data mining analysis can effectively extract hidden knowledge from the GSS data set; the knowledge generated by different data mining analysis can somehow cross-validate each other.

By leveraging the power of data mining techniques, the proposed approach can explore knowledge in a fine-grained manner with minimum human interference. Experiments on Chinese General Social Survey data set are conducted at the end to evaluate the performance of our approach.

This study aims to explore the effect of urban green space (UGS) on residents' subjective well-being (SWB) among different social groups.

Using national SWB and UGS data obtained from the China Urban Construction Statistical Yearbook and the Chinese General Social Survey, a multiple regression model was developed to estimate the effect of UGS on residents' SWB. Grouping regression for samples from distinct socioeconomic groups was performed to further discuss group-wise differences in SWB.

The green coverage rate of built-up areas and the number of parks accessed by every 10,000 individuals are significantly positively correlated with residents' SWB, whereas the green space area per capita and greening investment ratio are significantly negatively correlated with residents' SWB; the effect of UGS on residents' SWB varies among individuals with respect to gender, age, and income, with the most significant difference observed among groups with different incomes.

The empirical results of this study are expected to support the planning and construction of UGS by providing a reference for optimizing their service capabilities and highlighting their positive role in improving residents' SWB.

This paper examines the in-depth relationship between religious beliefs and individual social class mobility expectations in China.

The data used in this article are mainly from the China Comprehensive Social Survey in 2010 (CGSS2010). Compared with other years' CGSS data, CGSS2010 includes a module on religious topics, and the questionnaire information related to religion is more comprehensive and suitable for in-depth analysis.

The results show that religious beliefs have a significant positive impact on personal social class mobility expectations. Based on the principle of diminishing marginal returns on capital, the positive impact of religious belief on the expectation of individual social class mobility is more significant in groups with nonagricultural household registration, higher education level, older age and better family background conditions. However, with the further improvement of family background conditions, this positive impact begins to weaken. In addition, possible channels of action include prejudice effects, psychological effects, individual capital effects and social capital effects. The results of other effects are positive except for the prejudice effect. Overall, religious beliefs, as one of the important components of contemporary Chinese culture, have a positive significance for the “Chinese Dream”.

There is also little literature globally that provides an in-depth analysis of the relationship between religion and economic development. Studies have led to an understanding of the relationship between religious beliefs and individual social class mobility expectations. But it is unclear whether theories developed based on Western spiritual experience will be applicable to China or not. The authors have tested for China.

Purpose – This study develops a theoretical argument that social networks are embedded in the macro-level institutional environment. From the perspective of institutional embeddedness, I investigate the changing patterns and implications of social networks in job search and job earnings after China's overhaul of its employment system in the mid-1990s.Methodology/approach – The empirical evidence is drawn from 2003 Chinese General Social Survey data. I conduct statistical analyses to examine the roles of networks in job search and earning disparity by comparing two groups who obtained the job before and after the emerging labor market in urban China, respectively.Findings –Social networks have become much more popular in job search in the emerging labor market. Use of social networks in job search has also become more differentiated across job positions and employment organizations. While managerial status of the key helper and direct ties yield greater returns to employee earnings, strong indirect ties make less contribution to job earnings in the emerging labor market than that under the state-dominated employment system.Research implications – The findings suggest that we should analyze the concrete institutional environment to appreciate the roles of social networks in job search and social inequality.Originality/value – This study highlights that institutions are the key factor to shape the patterns and significance of social networks. As institutions evolve, network patterns and their significance can change accordingly.

Utilizing data from the 2017 Chinese General Social Survey (CGSS2017), the paper aims to investigate the impact of information and communication technology (ICT) adoption on residents' self-rated health and reveals the mechanisms behind ICT.

In the study, ICT adoption is defined as a dummy variable, which takes the value of one if respondents adopt the computers or mobile phone. Meanwhile, respondents' perceptions on five categories of self-rated health are used to construct the dependent variable. Then, based on a fixed-effects regression model, the ordinary least squares (OLS) and ordered probit approaches are applied to estimate their association. Moreover, the two-stage least squares (2SLS) and instrumental variable (IV)-oprobit methods are used to tackle the potential endogeneity of ICT adoption. Finally, the heterogeneity across individuals and regions as well as the underlying mechanisms are discussed.

The results indicate that ICT adoption significantly improves residents' self-rated health, which confirms the health utility model with ICT adoption. The conclusion is robust after overcoming the endogeneity issues with IV. In addition, heterogeneity analysis shows that ICT adoption is more beneficial to the health of residents who are male, young, better educated and those who live in the rural areas and in central and western China. Furthermore, the study demonstrates that ICT adoption for searching health-related information and improving social capital are two crucial mechanisms underlying its health effects.

The findings of this research can help Chinese Government improve population health by issuing corresponding digital and health policies at the regional and individual level.

First, the study provides fresh microscopic evidence on health outcomes of ICT adoption based on data from the latest wave of CGSS2017. Second, individual and regional heterogeneity is extensively discussed in contrast to most related macro studies that consider average effects. Third, the study addresses underlying mechanisms that have not been thoroughly tested or studied primarily on a theoretical level.