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This study investigates the determinants of Chief Executive Officer (CEO) cash compensation in relation to corporate governance and performance in China's listed firms. This article also aims at analyzing gender earning differentials among CEOs.

The empirical analysis is based on the panel data set which contains information on the CEOs of 1,701 firm-year observations over the period 2006-2010. A Oaxaca decomposition is also implemented to measure the gap between male and female CEO compensation.

The paper observes that CEO compensation relies more on firm accounting performance than on stock market performance. This relationship is especially evident when accounting performance is measured as the return-on-assets. Dominant shareholders such as the state and block holders have a distinct impact on the use of incentive pay. The presence of a compensation committee in a Chinese listed firm is correlated with an excessive pay package for the Chief Executive Officer (CEO), even though there is evidence that pay-for-performance is more likely in the presence of a compensation committee. Furthermore, this context extends the international body of evidence on CEO compensation by offering a novel accounting of the gender gap in pay among China's listed firms. Examination of the dataset reveals that women represent approximately 6.8 percent of CEOs. In keeping with international norms, female CEOs are more senior and better educated than their male counterparts, yet they receive less favorable compensation. The Oaxaca decomposition shows a larger unexplained part of the pay-gap and suggests that the gender statistically explains a great deal of the gap in pay between male and female CEOs across China's listed firms.

This article contributes to the international corporate governance literature and implications for the design of good corporate governance for China's listed firms. Moreover, this article also highlights the current gender gap among CEOs in compensation.

This paper aims to, under the framework of the pollution haven hypothesis (PHH), test the theory that foreign direct investment (FDI) creates an intra-host country pollution haven in developing nations by studying the contemporary case of China.

This empirical analysis has used a panel dataset of 30 provinces that was analyzed for the period of 1997-2011. An Oaxaca decomposition was also implemented to examine the effects of environmental stringency on regional pollution.

The estimates indicate that openness to FDI generally appears to be good for the environment. The results of estimation show that the western region of China has developed a potential “comparative advantage” in pollution-intensive industries, thanks to the strong incentive of economic expansion. However, further estimates concerning the location decisions of FDI suggest that the providers of FDI still prefer to locate in the coastal regions of China, where a tighter environmental regulation policy has been imposed. The findings suggest that the better infrastructure and technology spillover of environmental policy-making might be more attractive to FDI than comparatively weak environmental stringency.

This study applies a model advanced in previous theoretical literature which divides the effects of trade into the categories of scale, technique and composition. It also contributes to the understanding of the PHH in the context of intra-host country analysis.

The purpose of this paper is to study the effects of multidimensional friendship networks on economic outcomes in the domain of online people-to-people (P2P) lending markets.

The empirical analysis is based on the data set of transactions and friendship networks from PPDai.com market, the most prominent P2P lending market in China. A friendship hierarchy is proposed in this paper to conceptualize friendship network types. Furthermore, methodologies of t-test, logistic regression and ordinary least squares regression are implemented to measure the impact of multidimensional friendship network variables on the probability of successful funding, as well as the interest rates on funded loans.

The study demonstrates significant effects of structural, relational and cognitive friendship networks using PPDai.com data. The results indicate that structural friendship network measured in terms of the number of friendship ties is a significant factor of funding performance. Additionally, borrowers, who are involved in higher-quality friendship networks, are more likely to be funded and pay lower interest rates on funded loans. Also, the deeper the level of the relationship is in the friendship hierarchy, the more significant will be the effect of friendship on the final economic results. Furthermore, quality is more important than quantity in determining funding performance.

This paper is the first to study the effects of multidimensional friendship networks on economic outcome variables in the domain of online P2P lending, thus broadening the theory of multidimensional social capital, which can deepen our understanding about how social networks work and have significant implications practically and theoretically.

The aim of this study is to propose an efficient rule extraction and integration approach for identifying phishing websites. The proposed approach can elucidate patterns of phishing websites and identify them accurately.

Hyperlink indicators along with URL-based features are used to build the identification model. In the proposed approach, very simple rules are first extracted based on individual features to provide meaningful and easy-to-understand rules. Then, the F-measure score is used to select high-quality rules for identifying phishing websites. To construct a reliable and promising phishing website identification model, the selected rules are integrated using a simple neural network model.

Experiments conducted using self-collected and benchmark data sets show that the proposed approach outperforms 16 commonly used classifiers (including seven non–rule-based and four rule-based classifiers as well as five deep learning models) in terms of interpretability and identification performance.

Investigating patterns of phishing websites based on hyperlink indicators using the efficient rule-based approach is innovative. It is not only helpful for identifying phishing websites, but also beneficial for extracting simple and understandable rules.

The purpose of this paper is to review the criminal enforcement of insider dealing cases in People's Republic of China's (PRC) securities market and to provide feasible suggestions for improvement for a more coherent and streamlined insider dealing regulatory framework in the PRC during the enforcement of China's new Securities Law (SL 2020) in March 2020.

Through analysing the previous literature on public interest theories and economic theories of regulation, this paper examines the necessity to regulate insider dealing in China with criminal law to ensure fairness and avoid monopolies in its securities market. The paper reviews the criminalising of severe insider dealing cases in China from the Nanking National Government in the 1920s to the inception of the securities market of the PRC in the 1990s to the present day. The investigation, prosecution, enforcement and trial of criminal offences of insider dealing in China are thoroughly examined.

The paper finds a tendency for over reliance on the investigation and the administrative judgement of the China Securities Regulatory Commission in criminal investigation, prosecution and trial in the PRC.

To the best of the authors’ knowledge, this paper is one of the first papers to critically and thoroughly analyse the criminal enforcement of insider dealing in China following the recent enforcement of China’s new Securities Law in March 2020.