What is feminist philosophy? A difficult question for feminist scholars in China. Women's studies in the Chinese mainland are characteristically policy‐oriented, geared to practical concerns and moral urgency. Empirical research projects engage many pressing social issues related to the changing situation of women in a rapid marketification of society and commercialization of culture since the post‐1978 reform movement. Here are some examples: migrant female workers and their working conditions in the urban centers; the impact of rural industrialization on women in (...) the countryside: discrimination against women in employment as well as in other aspects of social life; marriage and sexual relations. What follows in this article however, represents an effort to identify and categorize trends in emerging feminist theories. The main questions that might be seen as in one way or another philosophical are located in the historical context of the transformation of Chinese socialism. As we have only very limited access to publications in Hong Kong and Taiwan, to avoid mispresentation we regret that we cannot discuss the feminist work developed in these areas. (shrink)

Although the trickle-down effect of ethical leadership has been documented in the literature, its underlying mechanism still remains largely unclear. To address this gap, we develop a cross-level dual-process model to explain how the effect occurs. Drawing on social learning theory, we hypothesize that the ethical leadership of high-level managers could cascade to middle-level supervisors via its impact on middle-level supervisors’ two ethical expectations. Using a sample of 69 middle-level supervisors and 381 subordinates across 69 sub-branches from a large banking (...) firm in China, we found that middle-level supervisors’ ethical efficacy expectation and unethical behavior–punishment expectation accounted for the trickle-down effect. The explanatory role of middle-level supervisors’ ethical behavior–reward expectation, however, was not supported. The theoretical and practical implications are discussed. (shrink)

This study examines the relation of ethical leadership with loyalty to supervisor, as well as mediating and moderating variables of this relation by proposing a moderated mediation model. Specifically, we employed time-lagged research design to collect two waves of data from 395 supervisor-subordinate dyads in 74 teams, and used multilevel structural equation modeling to test the moderated mediation model. Results indicated that ethical leadership was positively related to loyalty to supervisor, interactional justice mediated the relationship between ethical leadership and loyalty (...) to supervisor, and collectivistic orientation moderated the relationship between ethical leadership and interactional justice. Moreover, collectivistic orientation moderated the strength of the indirect effect of ethical leadership on loyalty to supervisor, and the mediated relationship was stronger for high collectivistic subordinates than for low collectivistic subordinates. Theoretical and practical implications and future research directions were discussed. (shrink)

This paper studies the state of charge estimation of supercapacitors and lithium batteries in the hybrid energy storage system of electric vehicles. According to the energy storage principle of the electric vehicle composite energy storage system, the circuit models of supercapacitors and lithium batteries were established, respectively, and the model parameters were identified online using the recursive least square method and Kalman filtering algorithm. Then, the online estimation of SOC was completed based on the Kalman filtering algorithm and unscented Kalman (...) filtering algorithm. Finally, the experimental platform for SOC estimation was built and Matlab was used for calculation and analysis. The experimental results showed that the SOC estimation results reached a high accuracy, and the variation range of estimation error was [−0.94%, 0.34%]. For lithium batteries, the recursive least square method is combined with the 2RC model to obtain the optimal result, and the estimation error is within the range of [−1.16%, 0.85%] in the case of comprehensive weighing accuracy and calculation amount. Moreover, the system has excellent robustness and high reliability. (shrink)

The question whether corporate social responsibility (CSR) initiatives can be transferred to firm performance to achieve sustainable development goals (SDGs) prompted this study to investigate how CSR strategies influence both SDGs and financial performance. A mediated moderating model based on the organizational alignment theory was developed to examine the mediating and moderating roles of organizational structure and corporate governance, respectively. By analyzing the three-year panel data of 1,480 firm-year observations from publicly listed companies in Taiwan, we find that organizational structure (...) mediates the relationship between a firm’s CSR strategy and firm performance consisting of SDG disclosures, sales revenue, net profit, and return on equity. Corporate governance plays a moderating role in the relationship between organizational structure and firm performance. Our objective financial data provide evidence supporting “doing well by doing good.” The proposed organizational alignment model and empirical results enhance the theoretical understanding of the CSR research field. The research findings have several practical implications for business executives to improve a firm’s social and financial performance. (shrink)

One Road One Belt has made a drastic change not only to the lives of people but also to their minds and future prospective. This initiative has connected not only countries but has consolidated trading patterns. It has not only impacted physical trade but has also boosted the e-commerce of China. Therefore, this study has tried to find the major patterns of trading across the globe and digital commerce considering the factors of production. China, being the cheapest country for manufacturing, (...) has excelled in the e-commerce as well. The targeted population for this study was contractors, marketers, logistic service providers, and engineers. The sample size in this study was 329. Data collection was done through a survey developed on the Likert scale. The software used for the data analysis was Smart-PLS for structural equation modeling. Findings of the study show that factors of production and international trade have an impact on e-commerce. Moreover, the foreign policy and international relations have also been found to have a significant role in e-commerce. (shrink)

Teaching seeks to enhance learners’ well-being as well as their educational motivation since both constructs cause advancement in the process of learning and they increase the level of success in the educational cycle. Well-being is a critical requirement inside the academic environment that is considered as the main dimension of individuals’ tendency in the topic of positive psychology research, which is crucial for learning. Besides, as a significant idea in language domain and in order to consider the relation between well-being (...) and motivation, the other concept is arisen in PP, namely resilience that seems to be effective for learners as it deals with the capability to effectively manage difficulties in the past and present time in the learning process. As a result, this study considers the relationship between well-being and motivation; however, it also inspects the mediating role of resilience in this regard. Consequently, this review of literature holds suggestions for researchers, philosophers, and experts searching for better exploration and attention to the functions of resilience as a mediator in the relationship between learners’ motivation and well-being. (shrink)

This study examined the relationships between the role of the instructor and university students’ learning outcomes in cloud-based classrooms during the COVID-19 pandemic. The results of an online survey of 7,210 university students in mainland China revealed that the students’ perceived learning outcomes and learning satisfaction were positively related to instructor innovation and negatively related to instructor performance. Instructional support was positively related to the students’ perceived learning outcomes but not directly related to their learning satisfaction. The students’ academic self-efficacy (...) mediated the influence of instructional support and instructor innovation on their perceived learning outcomes and learning satisfaction. The results contribute to knowledge of the role instructors play in facilitating students’ learning outcomes in higher education and suggest ways to improve the learning environment and learning outcomes, especially in cloud-based virtual classrooms. (shrink)

While competition has become increasingly fierce in organizations and in the broader market, the research on competition at an individual level is limited. Most existing research focuses on trait competitiveness. We argue that employee competitiveness can be state-like and can be demonstrated as an attitude toward and behavior representative of competition. We therefore propose a dynamic model with two separate components: competitive attitude and competitive behavior. Drawing upon self-determination theory and the person-environment interaction perspective, we examine how employee competitive attitude (...) and competitive behavior can be influenced by both personal characteristics and team climate, which in turn leads to different work outcomes, as demonstrated in two studies. Study 1 developed measures for competitive attitude and competitive behavior. Study 2 collected data from salespeople in a large insurance company in three waves. The results showed that employee competitive attitude and behavior could be predicted by personality. Moreover, employee competitive attitude and behavior were related to sales performance in differential ways via job crafting, and these mediated relationships could be moderated by team climate. These findings support the two-component dynamic model combining competitive attitude and behavior, which helps promote understanding of the dynamics of competition and its consequences at the individual level. Theoretical and practical implications are also discussed. (shrink)

The current study proposes a moderated mediation model to explain the relationship between humble leadership and team innovation. Our hypothesis integrates social information processing theory with the existing literature on humble leadership. As a result, we theorize that when a humble individual leads a team, the team members are more likely to reconsider strategies, review events with self-awareness, share diverse information, and adapt to new ideas, which in turn promotes innovative team activities. Moreover, consistent with the research that emphasizes the (...) inclusion of team culture in exploring leader–innovation relationships, we investigate the moderating role of a team’s expertise diversity in the above positive, indirect relationship. We test our model by using both archival and survey data collected from 135 teams within 18 medium-to-large internet technology firms in China. The findings largely support our theoretical assertions, suggesting that humble leadership has important implications for team processes and innovation. (shrink)

Rheumatoid arthritis is a progressive systemic autoimmune disease characterized by inflammation of the joints and surrounding tissues, which seriously affects the life of patients. The Sharp/van der Heijde method has been widely used in clinical evaluation for the RA disease. However, this manual method is time-consuming and laborious. Even if two radiologists evaluate a specific location, their subjective evaluation may lead to low inter-rater reliability. Here, we developed an efficient model powered by deep convolutional neural networks to solve these problems (...) and automated the overall scoring on hand X-rays. The depthwise separable convolution technique is used based on ResNet-50 due to the high resolution of hand X-rays. An inverted residual block is introduced to devise a ResNet-Dwise50 model to enhance the efficiency of the model. The model was trained and tested using bilateral posteroanterior images of 3818 patients. The experiment results show the ResNet-Dwise50 model achieved an MAE of 14.90 and RMSE of 22.01 while ensuring high efficiency. There was no statistical difference between the average scores given by two experienced radiologists and predicted scores from our model. (shrink)

Many scholars have focused on understanding ways of how to suppress knowledge hiding by employees. Existing studies have demonstrated that mindfulness could effectively inhibit employees’ knowledge hiding. This study aims to investigate the impact of leader–subordinate mindfulness congruence on subordinate knowledge hiding and its internal mechanisms. Based on the role theory, we collected 169 leadership data and 368 employee data at three time-points through collecting questionnaire of matching leaders and subordinates. In addition, we used polynomial regression and response surface analysis (...) to validate our research hypotheses. The results demonstrated that: Compared with the “high leader–high subordinate” mindfulness congruence condition, subordinates in the “low leader–low subordinate” mindfulness congruence condition were more likely to exhibit knowledge hiding. Compared with the “low leader–high subordinate” mindfulness incongruence, subordinates under the “high leader–low subordinate” mindfulness incongruence are more likely to exhibit knowledge hiding. The more incongruent the mindfulness between the leader and the subordinate is, the more likely an employee is to exhibit knowledge hiding. Emotional exhaustion mediated the correlation between leader–subordinate mindfulness congruence and knowledge hiding. When the gender of the leader and the subordinate is different, the impact of mindfulness congruence on the inhibition of emotional exhaustion is stronger. This study provides a new perspective for researching the impact of mindfulness on individual behavior and provides a new idea for the research related to inhibiting knowledge hiding. (shrink)

Engagement, a psychological individual difference variable with three facets, has recently attracted scholarly attention. Through a large-scale survey, we examined what we call ‘L2 engagement’ among 21,370 secondary school students in China, with an L2 engagement scale adapted from the Utrecht Work Engagement Scale -student version. Factor analysis showed this scale to be empirically unidimensional with three highly intercorrelated facets and very high internal consistency; this contributes to our understanding of the conceptual challenges surrounding the construct of engagement and the (...) broader issue concerning the correspondence between empirical constructs and theoretical terms. Hierarchical regression revealed that the selected sociobiographical variables were linked to L2 engagement to varying degrees; adopting a more refined approach to gauge the unique contribution of a predictor to L2 engagement in hierarchical regression, we identified L2 proficiency, parental attention, study time and frequency of parental coaching as important predictors for L2 engagement. We call for more studies to adopt our L2 engagement scale, a sufficiently valid and reliable instrument developed based on a large sample. We also propose a few future research directions. (shrink)

Numerous studies have focused on the understanding of rapid automatized naming, which can be applied to predict reading abilities and developmental dyslexia in children. Eye tracking technique, characterizing the essential ocular activities, might have the feasibility to reveal the visual and cognitive features of RAN. However, traditional measures of eye movements ignore many dynamical details about the visual and cognitive processing of RAN, and are usually associated with the duration of time spent on some particular areas of interest, fixation counts, (...) revisited fixation counts, saccadic velocities, or saccadic amplitudes. To cope with this drawback, we suggested an entropy-based method to measure eye movements for the first time, which first mapped eye movements during RAN in a time-series and then analyzed the time-series by a proper definition of entropy from the perspective of information theory. Our findings showed that the entropy was more sensitive to reflect small perturbation of eye movements, and thus gained better performance than traditional measures. We also verified that the entropy of eye movements significantly deceased with the age and the task complexity of RAN, and significantly correlated with traditional eye-movement measures [e.g., total time of naming ] and the RAN-related skills [e.g., selective attention, cognitive speed, and visual-motor integration]. Our findings may bring some new insights into the understanding of both RAN and eye tracking technique itself. (shrink)

Experts play a crucial role in underpinning decision-making in most management situations. While recent studies have disclosed the impacts of individuals’ inherent cognition and the external environment on expert performance, these two-dimensional mechanisms remain poorly understood. In this study, we identified 14 factors that influence expert performance in a bid evaluation and applied cross-impact matrix multiplication to examine the interdependence of the factors. The results indicate that the two dimension-related factors affect each other within a person–environment system, and a poor (...) situation perception gives rise to the deviation of expert performance. Expert performance can be improved if external supervision and expertise are strengthened through deliberate practices. The study proposes a new expert performance research tool, elucidates its mechanism in bid evaluation from a cognitive psychology perspective, and provides guidelines for its improvement in workplace contexts. (shrink)

With environmental issues increasingly becoming prominent in today’s business world, firms may need to pay extra attention to developing their environmental strategies and capabilities in response to environmental concerns and achieving sustainable growth. While a broad consensus exists on the value of green innovation, current empirical research on how different types of green innovation strategies may account for the international performance of a firm remains scant. Addressing this gap is important because determining how to better manage a firm’s green innovation (...) strategies nowadays has become increasingly important for firms hoping to achieve and maintain their sustainable performance advantages. This study aims to bridge this gap by systematically examining how various types of green innovation strategies can be beneficial to firms in an emerging market economy. This study also examined the important role that potential risks of supply chain play in shaping the relationships between various types of green innovation strategies and firm performance. This study proposes that the effective management of supply chain risks may be important to the successful implementation of green innovation strategies because green innovation has increasingly become a collaborative effort. This study empirically tested the hypotheses by gathering survey data from a sample of 337 firms in China’s manufacturing industries. Results demonstrate that the green innovation strategies of firms are positively related to their firm performance. Additionally, the potential risks faced by the firms in efficiently and effectively managing their supply chain significantly moderate the impact of green product innovation and green process innovation strategies on their firm performance. This study not only offers useful theoretical implications for the green innovation strategy research and for better and effective supply chain risk management. It also provides important practical guidelines and managerial actions that practicing managers can implement to accelerate their green innovation strategy, assess the effect of supply chain risks, and thus improve firm performance in the post-pandemic era. (shrink)

In this article, we propose a new method to learn the underlying acyclic mixed graph of a linear non-Gaussian structural equation model with given observational data. We build on an algorithm proposed by Wang and Drton, and we show that one can augment the hidden variable structure of the recovered model by learning multidirected edges rather than only directed and bidirected ones. Multidirected edges appear when more than two of the observed variables have a hidden common cause. We detect the (...) presence of such hidden causes by looking at higher order cumulants and exploiting the multi-trek rule. Our method recovers the correct structure when the underlying graph is a bow-free acyclic mixed graph with potential multidirected edges. (shrink)

Based on the existing financial system risk models, a set of time-lag financial system risk models is established considering the influence brought by time-lag factors on the financial risk system, and the dynamical behavior of this system is analyzed by using chaos theory. Through Matlab simulation, the bifurcation diagram and phase diagram of time-lag risk intensity and control intensity are plotted. The analysis shows that this kind of time-lag financial system risk model has complex dynamic behavior, different motion states will (...) appear when different parameter values are selected, and the time-lag risk intensity parameter also has a very strong influence on the system motion. To ensure the operation of the financial system in a stable state, measures with certain delay effects must be taken to control the risk and to choose the appropriate time-lag control intensity, and too much or too little time-lag control intensity is not conducive to the benign operation of the system. (shrink)

Fraud can cause severe financial losses and affect the physical and mental health of victims. This study aimed to explore the manipulative characteristics of fraudsters and their relationship with other psychological variables. Thirty-four fraudsters were selected from a medium-security prison in China, and thirty-one healthy participants were recruited online. Both groups completed an emotional face-recognition task and self-report measures assaying emotional manipulation, psychopathy, emotion recognition, and empathy. Results showed that imprisoned fraudsters had higher accuracy in identifying fear and surprise faces (...) but lower accuracy in identifying happiness than controls. Significantly lower scores on non-prosocial factors on the Managing the Emotions of Others scale were found for imprisoned fraudsters, relative to controls. Imprisoned fraudsters had low scores in the assessment of psychopathy than the control group, especially Factor 1. For empathy, imprisoned fraudsters had significantly higher scores in perspective-taking than controls. Correlation analyses revealed that psychopathic traits were positively correlated with non-prosocial factors in both groups. However, the relationships between emotional manipulation and emotional recognition and empathy were not consistent across the groups. The results suggest that fraudsters may pretend to be as prosocial as healthy controls, who had lower antisocial tendencies, normal empathy ability, and would like to manipulate others’ emotions positively during social interaction. (shrink)

In this article, we use the two-sided market theory as a support and take the operating data of eight Chinese third-party payment platform companies as samples, based on pricing models and multiple regression analysis, to build a price feature model for a third-party payment platform. The results show that under the two-sided market environment, the scale of consumer and the same-side network externality of the merchant have a negative significant effect on the pricing of the third-party payment platform to the (...) seller; The market share of the platform and the bank fee cost of the platform have a positive significant effect on the pricing of a third-party payment platform to the merchant. At the same time, the same-side network externality of the seller, the scale of a merchant, and the selection of the business model of the platform have no significant effect on the pricing of the third-party payment platform to the merchant. These conclusions provide a scientific basis for a third-party payment platform enterprise to develop an appropriate pricing strategy and operating model. (shrink)

Rebate has long been a crucial tool that has attracted researchers from a diverse range of fields including marketing and supply chain management. When a manufacturer uses a retailer for reaching end customers, the rebate strategy undertakes an additional dimension. Here we show whether the two rebate strategies, manufacturer rebate and channel rebate, can be the optimal choice for the manufacturer and the retailer. And we aim at full coordination with rebate. Game theory is exploited to identify the equilibrium rebate (...) decisions, which are fully characterized with two rebate strategies considering rebate sensitivity. Furthermore, we demonstrate how the decisions depend on parameters, such as market size, rebate redemption rate, and competition intensity in monopoly and duopoly supply chain systems. Our work also coordinates the supply chain with two coordination policies and examines if they can achieve full coordination. Counterintuitive findings suggest that the channel rebate with sensitivity and discrimination is not effective and the manufacturer rebate is the unique optimal option. Besides, the coordination can be realized with a centralized rebate in monopoly setting when the manufacturer forgoes her own interest. Then full coordination can be achieved in duopoly setting with a new coordination policy, rebate combination, given the redemption rate for the channel rebate is lower compared with the manufacturer rebate. Managerial insights are suggested that offering rebates with discrimination can have significant inventory and coordination policy implications and can lead to a double win under a well-controlled redemption rate. (shrink)

To identify the common and specific structural basis of bipolar depression and unipolar depression is crucial for clinical diagnosis. In this study, a total of 85 participants, including 22 BD patients, 36 UD patients, and 27 healthy controls, were enrolled. A voxel-based morphology method was used to identify the common and specific changes of the gray matter volume to determine the structural basis. Significant differences in GMV were found among the three groups. Compared with healthy controls, UD patients showed decreased (...) GMV in the orbital part of the left inferior frontal gyrus, whereas BD patients showed decreased GMV in the orbital part of the left middle frontal gyrus. Compared with BD, UD patients have increased GMV in the left supramarginal gyrus and middle temporal gyrus. Our results revealed different structural changes in UD and BD patients suggesting BD and UD have different neurophysiological underpinnings. Our study contributes toward the biological determination of morphometric changes, which could help to discriminate between UD and BD. (shrink)

The rapid development of digital technologies has transformed the world but can be a double-edged sword. We study the interaction of important variables that affect individual news reporters’ performance in which digital technology is the dominant feature. A multilevel model illustrates how transactive memory and job competence affect individual performance. The empirical study includes data from 19 teams of news reporters and 211 valid survey responses, applying hierarchical linear modeling to analyze the data. The results indicate that transactive memory and (...) technology competence help to improve a reporter’s job performance. More importantly, teamwork competence fully mediates the relationships. Our findings thus suggest that teamwork competence is the core skill. Neither technology competence nor transactive memory alone translates directly into enhanced individual performance. (shrink)

This study investigated the characteristics and development of peer support networks in an effort to unravel the role of friendship in this developmental process. The relationships between friendship networks and peer support networks were explored, and the influence of dyadic and triadic friendships on the development of peer support relationships was examined. Two waves of data were collected among a sample of adolescents in six Chinese junior high schools (n= 913 students from 28 classrooms; mean age = 14.13 years; 50.49% (...) boys), and classroom friendship networks and peer support networks were analyzed. The results showed that peer support networks were sparse, hierarchical, and sex-segregated. Furthermore, peer support networks and friendship networks partially overlapped. Friends tended to have similar support-seeking and support-providing ties. Longitudinal multiplex social network analysis revealed that peer support networks changed moderately over time, and friendships played various roles in the development of peer support networks. Dyadic friendships improved the formation of peer support ties. A mutual friend improved the formation of support relationships between two students when the mutual friend chose the two students as friends, but a mutual friend also hindered or had no effects on the formation of support relationships in other cases. The implications for educators to improve peer support networks are presented, and directions for future research are discussed. (shrink)

The logic of the hide and seek game $$\textbf{LHS}$$ was proposed to capture interactions between agents in pursuit-evasion environments. In this paper, we explore a hybrid extension of $$\textbf{LHS}$$ and show that such an extension is beneficial in several aspects. We will show that it improves the technical properties of the resulting logical system, and expands the potential applications of the system. Specifically, we will investigate the expressive power of the hybrid logic of the hide and seek game $${\mathcal {H}}(\textbf{LHS})$$ (...) and its crucial fragment $${\mathcal {H}}(\textbf{LHS}^{-})$$, at both model and frame levels. We will present complete Hilbert-style proof systems for both the logics $${\mathcal {H}}(\textbf{LHS}^{-})$$ and $${\mathcal {H}}(\textbf{LHS})$$, which in fact provides a solution to a known open problem. (shrink)

Clinical ethics consultations (CECs) play an important role in resolving ethical issues in clinical practice worldwide. The government has encouraged the development of CECs in China to address the ethical challenges arising in prenatal diagnosis. So far, the current state and challenges facing CEC remain understudied. This study aimed to explore the perspectives of employees on ethics committees for prenatal diagnosis in 13 medical institutions in Hunan Province, China. Twenty-eight employees participated in interviews. Our qualitative approach employed content analysis to (...) identify major themes in interviewees’ responses, which covered the composition and vision of their prenatal diagnosis ethics committee, as well as the challenges they faced. The results show that CEC in China is in an exploratory stage, with models for CEC composition, and workflow varying significantly. Therefore, we propose the future direction of efforts to improve CECs, including improving CEC working mechanisms and operating procedures, strengthening ethical training for healthcare workers and ethics committee employees, and developing more specific ethical guidance based on the accumulated experiences of ethics committee employees in the early development of CEC for prenatal diagnosis. (shrink)

The integration of machine learning algorithms into the legal recommendation system marks a burgeoning area of research, with a particular focus on enhancing the accuracy and efficiency of judicial decision-making processes. The application of Bayesian Network (BN) emerges as a potent tool in this context, promising to address the inherent complexities and unique nuances of legal texts and individual case subtleties. However, the challenge of achieving high accuracy in BN parameter learning, especially under conditions of limited data, remains a significant (...) hurdle. This study proposes an Enhanced Maximum Parameter Learning (EMPL) algorithm, tailored for BN parameter optimization in scenarios characterized by small sample sizes. The EMPL algorithm, innovatively incorporating the Synthetic Minority Over-sampling Technique (SMOTE), begins with the formulation of inequality constraints derived from domain expertise. It establishes a minimal dataset threshold necessary for effective parameter learning. Through the introduction of an index weighting factor function that dynamically adjusts according to the sample size, the algorithm facilitates the derivation of refined BN parameters. The core innovation of the EMPL algorithm lies in its use of an exponentially weighted factor function, designed to be responsive to variations in sample size, and its capacity to expand the parameter space using SMOTE to align with qualitative constraints from expert insights. This approach enables the integration of data-derived parameters with those obtained through expert experience in an exponentially weighted manner, culminating in the optimization of BN parameters. Comparative analysis reveals that the EMPL algorithm achieves superior learning accuracy over traditional Maximum Likelihood Estimation (MLE) and qualitative maximum a posteriori (QMAP) approach, particularly in contexts of sparse data. Furthermore, it demonstrates enhanced performance relative to variable weight learning algorithms, underscoring its potential to significantly improve decision-making processes in the legal domain through advanced BN parameter learning. (shrink)

Literary exchanges between China and Korea have played a pivotal role in the formation and development of the East Asian Han cultural circle. This paper explains the advantages of cultural exchange in ancient literary works of China and Korea from the perspective of common cultural background and diplomatic relations between the two countries, and puts forward the necessity of studying cultural exchange and mutual influence in literary works of the two countries from the perspective of the importance of cultural exchange (...) and its influence on political relations and economic development. Finally, the cultural exchanges and mutual influences in the ancient literature of China and Korea are analyzed in depth. The results of the study show that 29 and 53 works of Chinese and Korean ancient literature respectively involve elements of the other country's culture, and that there are obvious cultural exchanges and mutual influences in the literary works. It is also found that Chinese and Korean readers are highly receptive to this kind of ancient literature, and are able to understand the cultural elements and images of each other's countries through this kind of works. The study found that the mutual exchange of Chinese and Korean cultures in ancient China has a long history, and in the future, through the communication and reference platform of literary exchange, it will be able to promote the further development of the comprehensive partnership between China and Korea. (shrink)

Based on upper echelon theory, we employ machine learning to explore how CEO characteristics influence corporate violations using a large-scale dataset of listed firms in China for the period 2010–2020. Comparing ten machine learning methods, we find that eXtreme Gradient Boosting (XGBoost) outperforms the other models in predicting corporate violations. An interpretable model combining XGBoost and SHapley Additive exPlanations (SHAP) indicates that CEO characteristics play a central role in predicting corporate violations. Tenure has the strongest predictive power and is negatively (...) associated with corporate violations, followed by marketing experience, education, duality (i.e., simultaneously holding the position of chairperson), and research and development experience. In contrast, shareholdings, age, and pay are positively related to corporate violations. We also analyze violation severity and violation type, confirming the role of tenure in predicting more severe and intentional violations. Overall, our findings contribute to preventing corporate violations, improving corporate governance, and maintaining order in the financial market. (shrink)