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China's increasing income inequality might cause a series of problems, such as the slowdown of economic growth, social and economic tension, the decline of the ecological environment quality and the threat to citizens' health. Consequently, income inequality will inevitably affect the ecological well-being performance (EWP) level of China's provinces through the above aspects. Analyzing the impact of income inequality on EWP and its spatial spillover effects are conducive to improving the level of EWP in China. Therefore, the research purpose of this paper is to use China's provincial data from 2001 to 2017 to analyze the impact of income inequality on EWP and the spatial spillover effect based on the evaluation of the EWP value of each province.

At first, this study utilizes the super efficiency slacks-based measure model (Super-SBM model) to calculate the EWP values of 30 provinces in China, which can evaluate and rank the effective decision units in the SBM model and make up for the defect that the effective decision units cannot be distinguished. Then this study applies the spatial Durbin model and Tobit regression model (SDM-Tobit model) to explore the impact of income inequality and other influencing factors on EWP and the spatial spillover effects in adjacent areas.

Firstly, the average EWP in China fluctuated slightly and showed a downward trend from 2001 to 2017. In addition, the EWP values of the provinces in the western region are usually weaker than those in the eastern and central regions. Moreover, income inequality is negatively correlated with EWP, and the EWP has a spatial spillover effect, which means the EWP level in a region is affected by EWP values in the adjacent regions. Furthermore, the industrial structure and urbanization level are both negatively related to EWP, while technology level, investment openness, trade openness and education level are positively related to EWP.

Compared with the existing research, the possible contribution of this research is that it takes income inequality as one of the important influencing factors of EWP and adopts the SDM-Tobit model to analyze the impact mechanism of income inequality on EWP from the perspective of time and space, providing new ideas for improving the EWP of various provinces in China.

Using the industrial data between 2000 and 2016, this study analysed the process of coupling and coordinated development of technological innovation and standardisation. Accordingly, the study considered the high-tech industry (five sub-sectors) in China as the research object.

Based on the summary of innovation and standardisation literature review, this study constructed a theoretical model of the influence of technological innovation and standardisation on industrial development from the perspective of the coupling system. Furthermore, the study employed multivariate linear regression analysis to explore coupling coordination relationships.

The study results revealed that high coupling coordination between technological innovation and standardisation is highly conducive to industrial development. Moreover, requirements for standardisation levels differ owing to different stages and characteristics in each segmented industry.

This study primarily contributes to the literature by using a bibliometrics tool to summarise related literature on innovation and standardisation and provides a new perspective of reviewing, and it also offers new evidence on the coupling coordination relationship between innovation and standardisation in the high-tech industry.

AI is an emerging tool in HRM practices that has drawn increasing attention from HRM researchers and HRM practitioners. While there is little doubt that AI-enabled HRM exerts positive effects, it also triggers negative influences. Gaining a better understanding of the dark side of AI-enabled HRM holds great significance for managerial implementation and for enriching related theoretical research.

In this study, the authors conducted a systematic review of the published literature in the field of AI-enabled HRM. The systematic literature review enabled the authors to critically analyze, synthesize and profile existing research on the covered topics using transparent and easily reproducible procedures.

In this study, the authors used AI algorithmic features (comprehensiveness, instantaneity and opacity) as the main focus to elaborate on the negative effects of AI-enabled HRM. Drawing from inconsistent literature, the authors distinguished between two concepts of AI algorithmic comprehensiveness: comprehensive analysis and comprehensive data collection. The authors also differentiated instantaneity into instantaneous intervention and instantaneous interaction. Opacity was also delineated: hard-to-understand and hard-to-observe. For each algorithmic feature, this study connected organizational behavior theory to AI-enabled HRM research and elaborated on the potential theoretical mechanism of AI-enabled HRM's negative effects on employees.

Building upon the identified secondary dimensions of AI algorithmic features, the authors elaborate on the potential theoretical mechanism behind the negative effects of AI-enabled HRM on employees. This elaboration establishes a robust theoretical foundation for advancing research in AI-enable HRM. Furthermore, the authors discuss future research directions.

This paper aims to understand the magnetohydrodynamics (MHD) mechanism in the molten pool under different modes of magnetic field. The comparison focuses on the Lorenz force excitation and its effect on the melt flow and solidification parameters, intending to obtain practical references for the design of magnetic field-assisted laser directed energy deposition (L-DED) equipment.

A three-dimensional transient multi-physical model, coupled with MHD and thermodynamic, was established. The dimension and microstructure of the molten pool under a 0T magnetic field was used as a benchmark for accuracy verification. The interaction between the melt flow and the Lorenz force is compared under a static magnetic field in the X-, Y- and Z-directions, and also an oscillating and alternating magnetic field.

The numerical results indicate that the chaotic fluctuation of melt flow trends to stable under the magnetostatic field, while a periodically oscillating melt flow could be obtained by applying a nonstatic magnetic field. The Y and Z directional applied magnetostatic field shows the effective damping effect, while the two nonstatic magnetic fields discussed in this paper have almost the same effect on melt flow. Since the heat transfer inside the molten pool is dominated by convection, the application of a magnetic field has a limited effect on the temperature gradient and solidification rate at the solidification interface due to the convection mode of melt flow is still Marangoni convection.

This work provided a deeper understanding of the interaction mechanism between the magnetic field and melt flow inside the molten pool, and provided practical references for magnetic field-assisted L-DED equipment design.

The purpose of this paper is to draw attention to the significant lower completion rate of mergers and acquisitions (M&As) by firms from emerging economies (EEs) (China in particular) compared with firms from advanced economies, and identify the country- and industry-level factors that affect the completion of cross-border M&As by Chinese firms.

This study explores the effects of economic, cultural and institutional distances and target firms in technology- and knowledge-intensive industries on the completion of cross-border M&As by Chinese firms. It also examines the interplay between distance factors and technology- and knowledge-intensive industries on cross-border M&A completion. This study adopts a quantitative approach and is based on a sample of 768 announced cross-border M&A deals by firms in China between 2000 and 2015.

The results indicate that economic distance increases the likelihood of the completion of cross-border M&As when the target is in a more developed economy than China, but decreases when the target is in a less developed economy. Cultural and institutional distances have a significant, negative impact on the completion of cross-border M&As. In addition, target technology-intensive industries have a significant direct negative effect on cross-border M&A completion and moderate the relationship between the distance factors and the likelihood of cross-border M&A completion.

The results reveal factors that affect the completion of cross-border M&As by emerging market firms (EMFs). Further research, however, is needed to discover how distance factors affect how EMFs find, evaluate and negotiate international bids. To broaden the scope of the research, data for firms from other EEs would also be required.

The study expands the literature that considers the effects of major distances on cross-border M&A completion. In addition, the importance of defining and measuring distances in the context of cross-border M&As is highlighted. Finally, the study expands knowledge on how cross-border M&As affect the internationalization strategies of EMFs by conceptualizing and testing how target industries affect cross-border M&A completion.

The emergence of social media as a corporate disclosure channel has caused significant changes in the production and dissemination of corporate information. This review identifies important themes in recent research on the impact of social media on the corporate information environment and provides suggestions for further explorations of this new but fast-growing area of research. Specifically, we first review the evolution of Internet-based corporate disclosure and related regulations, and then focus on three recent streams of research: 1) companies’ use of social media; 2) information produced by non-corporate users and its impact on capital markets; and 3) the credibility of corporate information on social media platforms.

This paper proposes a recommendation method that mines the semantic relationship between resources and combine it with collaborative filtering (CF) algorithm for crowdsourcing knowledge-sharing communities.

First, structured tag trees are constructed based on tag co-occurrence to overcome the tags' lack of semantic structure. Then, the semantic similarity between tags is determined based on tag co-occurrence and the tag-tree structure, and the semantic similarity between resources is calculated based on the semantic similarity of the tags. Finally, the user-resource evaluation matrix is filled based on the resource semantic similarity, and the user-based CF is used to predict the user's evaluation of the resources.

Folksonomy is a knowledge classification method that is suitable for crowdsourcing knowledge-sharing communities. The semantic similarity between resources can be obtained according to the tags in the folksonomy system, which can be used to alleviate the data sparsity and cold-start problems of CF. Experimental results show that compared with other algorithms, the algorithm in this paper performs better in mean absolute error (MAE) and F1, which indicates that the proposed algorithm yields better performance.

The proposed folksonomy-based CF method can help users in crowdsourcing knowledge-sharing communities to better find the resources they need.

Studies of the antecedents of daily abusive supervision have mainly focused on work stressors and family stressors, ignoring the potential importance of commuting stressors that are encountered enroute to work. Based in affective events theory, the authors propose a daily, within-person model to examine how the commuting stressors faced by supervisors affect their propensity to engage in abusive supervision behavior and the mechanisms underlying this effect.

Using experience-sampling methodology, the authors collected data from 49 supervisors in China who responded to two daily surveys for 10 working days.

The authors found that daily morning commuting anger mediates the link between daily morning commuting stressors and subsequent abusive supervision. The authors also found that trait-displaced aggression moderates this relationship, such that the mediating effect occurs only when supervisors' trait-displaced aggression is high rather than low.

This study enriches the antecedents of daily abusive supervision and extends the commuting literature to the leadership context.

Tourists’ destination image is crucial for visiting intentions. An ancient capital with diverse characteristics is an important component of China’s urban tourism. The purpose of this paper is to address the following questions: what are the differences and commonalities of the perceived destination image of ancient capitals? What makes the difference of the perceived destination image in these cities? Aside from the exterior factors, are there internal factors of cities that influence tourists’ cognition and perception of destination image?

The comment text data of Baidu tourism website were used to determine the differences in the destination images of China’s four great ancient capitals: Beijing, Xi’an, Nanjing and Luoyang. ROST content mining and semantic network analysis were for differences and commonalities of the perceived destination image, and correlation analysis was used to explore the internal factors of cities that influence tourists’ cognition and perception of destination image.

Though the same as ancient capital, the four ancient capitals’ images are far apart; historical interests are the core of tourism experience in ancient capital city; image perception is from physical carrier, history and culture, and human cognition; tourist’ destination affect of ancient capital is most from its history and culture; protecting identity and maintaining daily life are crucial for ancient city tourism.

Previous studies on ancient capitals have focused on the invariable identity of ancient capitals’ destination images, and left a gap on determining from where the invariable identity comes in general and how much it influences destination image. This gap was addressed in this study, by analyzing the destination images of four ancient capitals in China as cases. In this way, this study provided reference to the other ancient cities worldwide.