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Despite recent organizational behavior studies have witnessed considerable progress in abusive supervision research; some demerits for both theory and methodology still remain in the past years. To clarify the current state of knowledge in the field, this study aims to analyze the current state of theories and methods on abusive supervision and provides a detailed future research agenda.

This paper conducted a literature review for both theory and methodology of the abusive supervision research using a content analysis of 134 publications.

For the theory part, this paper summarized the theories that had been applied to explain the relationship between abusive supervision and its consequences as well as antecedents. For the methodology part, this paper outlined some critical issues regarding country of origin, research design, measurement, analysis strategy and also summarized with a discussion of the relationship between methodological issues and article impact. Finally, this paper concluded by presenting an agenda for future abusive supervision research regarding both theory and methodology.

First, this paper summarizes the main theories, antecedents and consequences often used in abusive supervision research to allow scholars to carry out theoretically driven research investigating abusive supervision in the future. Second, through a content analysis of the methods sections of abusive supervision research in the samples (i.e. country of origin, research design, measurement and analytical procedures), this paper identified the potential reasons underlying the inconsistency in the conclusions of abusive supervision research and provide some guidance for future empirical studies. Third, based on the qualitative review, this paper provides an agenda for future research investigating abusive supervision by developing a content-specific theoretical framework to benchmark abusive supervision research against other research related to leadership and offers an accurate response to scholars’ criticisms of abusive supervision research.

Network embeddedness has been widely considered in enterprise innovation as an effective means of overcoming resource dilemmas. However, while focussing on acquiring external innovation resources, the existing research often ignores the vital role of internal routine updates. Therefore, this study explores the mechanism by which network embeddedness affects innovation performance of enterprises from the perspective of organisational routine updating.

This paper proposes a theoretical model based on social network theory and organisational routines–immune response theory. A total of 328 pieces of research data on high-tech enterprises in China were collected, and the hypotheses were verified using hierarchical regression analysis.

The results show that the two forms of network embeddedness – structural embeddedness and relational embeddedness, have a positive effect on enterprise innovation performance and a significant positive effect on organisational routine revision and organisational routine creation. Both organisational routine revision and organisational routine creation positively affect enterprise innovation performance and partially mediate the relationship between network embeddedness and enterprise innovation performance.

This conclusion provides a new perspective on the impact of network embeddedness on enterprise innovation performance and expands the related research on organisational routine updating. This study provides a theoretical reference for high-tech enterprises to improve their competitiveness and innovation performance through network embeddedness and organisational routine updating.

The deficiency of the mapping between fashion color (FoCo) value and linguistic color expression causes the difficulty of machine-based fashion understanding tasks that are heavily associated with color matching. The purpose of this paper is to propose the FoCo system and construct it with four steps, in order to bridge this gap.

The color distribution in HSB color space is analyzed to estimate the rough number of color categories. Similar color values are grouped to obtain the initial HSB value range for each color category. The intra-category color differences are calculated to determine their final HSB value ranges and Pantone color is used for fine-tuning.

With practical applications in mind, the FoCo system is designed as a hierarchical structure with three layers.

The FoCo system is designed as a hierarchical structure with three layers: color units for color matching-related tasks, color categories for style analysis tasks and color tones for color recognition tasks. Extensive experiments demonstrate the effectiveness of the FoCo system.

Efficient and high-accuracy intelligent color and material sorting systems are the main bottlenecks restricting the recycling of waste textiles. The mixing of waste textiles with different colors will make the reconstructed raw material of textile fiber useless or with low quality. In this study, some challenges about the automatic color sorting for waste textile recycling are discussed. A computer vision-based color sorting system for waste textile recycling is introduced, which can classify the required colors well and meet the efficiency requirements of an automatic recycling line.

There are four aspects, (1) two cameras with different exposure times and white-balance parameters are involved for establishing the computer vision system. (2) Two standard color databases with two cameras are constructed. (3) A statistical model to determine the colors of textile samples is presented in which uniform sampling of pixels and mid-tone enhancing techniques are exploited. (4) The experiments with a number of waste textile samples from a factory in Hong Kong are conducted to illustrate the efficiency of the developed system.

The experiments with a number of waste textile samples from a factory in Hong Kong are reported. The total classification accuracy performs good. The research methods and results reported in this study can provide an important reference for improving the intelligent level of color sorting for waste textile recycling.

It is the first time to introduce computer vision technology to a color sorting system for recycling waste textiles, especially in a real recycling factory in Hong Kong. The research methods and results reported in this study also deliver guidance for designing a computer vision-based color sorting system for other industrial scenarios.

The purpose of this study is to investigate the underlying characteristics that influence quality management implementation at manufacturing companies operating in China.

The data of this study were based on 199 manufacturing companies collected from a cross‐sectional survey in China. The cultural profiles of these companies were identified through cluster analysis. Multivariate analysis of variance was conducted to identify the effects of operating characteristics and cultural profile on the implementation level of quality management practices.

The results show that in general, there is no significant difference in implementing quality management practices among companies of different operating characteristics in terms of company size, industry, ownership, and production process. This study reveals that cultural profile is a distinguishing factor to explain the difference in quality management implementation among the companies.

As China is becoming an important supplier of products to the global market, it is necessary to understand how product quality is controlled and managed in China. This study examines the effects of operating and cultural characteristics of companies in China on their implementation of quality management practices. The results contribute to a deeper understanding of how to build an effective quality system at companies in China.

This review provides an overview of recent advances in electrochemical sensors for analyte detection in saliva, highlighting their potential applications in diagnostics and health care. The purpose of this paper is to summarize the current state of the field, identify challenges and limitations and discuss future prospects for the development of saliva-based electrochemical sensors.

The paper reviews relevant literature and research articles to examine the latest developments in electrochemical sensing technologies for saliva analysis. It explores the use of various electrode materials, including carbon nanomaterial, metal nanoparticles and conducting polymers, as well as the integration of microfluidics, lab-on-a-chip (LOC) devices and wearable/implantable technologies. The design and fabrication methodologies used in these sensors are discussed, along with sample preparation techniques and biorecognition elements for enhancing sensor performance.

Electrochemical sensors for salivary analyte detection have demonstrated excellent potential for noninvasive, rapid and cost-effective diagnostics. Recent advancements have resulted in improved sensor selectivity, stability, sensitivity and compatibility with complex saliva samples. Integration with microfluidics and LOC technologies has shown promise in enhancing sensor efficiency and accuracy. In addition, wearable and implantable sensors enable continuous, real-time monitoring of salivary analytes, opening new avenues for personalized health care and disease management.

This review presents an up-to-date overview of electrochemical sensors for analyte detection in saliva, offering insights into their design, fabrication and performance. It highlights the originality and value of integrating electrochemical sensing with microfluidics, wearable/implantable technologies and point-of-care testing platforms. The review also identifies challenges and limitations, such as interference from other saliva components and the need for improved stability and reproducibility. Future prospects include the development of novel microfluidic devices, advanced materials and user-friendly diagnostic devices to unlock the full potential of saliva-based electrochemical sensing in clinical practice.

To improve the efficiency and economy of electro-mechanical product's recycle process, this paper aims to propose a disassembly sequence planning (DSP) method to reduce additional efforts of removing extra parts in selectable disassembly.

The methodology has three parts, which includes a disassembly hybrid graphic model to describe the product disassembly information, an object inverse-directed method to optimize the disassembly design and a model reconstruction method to achieve a better DSP.

According to the disassembly cost criteria and the parameters of disassembly tools, the disassembly efficiency increases and the disassembly cost decreases due to the use of partial destructive mode compared with non-destructive mode. The proposed partial destructive DSP is more efficient and economical.

Partial destructive disassembly mode cannot be used for the flammable or explosive component in the procedure of the DSP optimization algorithm.

DSP of an electric corkscrew is analyzed to investigate the accuracy and efficiency of the proposed method.

This paper proposes a partial destructive disassembly based DSP method for product disassembly, which provides a new approach for the disposal of end-of-life products.

This study aims to analyze reform path for waste management policy implementation. With reference to the Bayesian theory, this study provides a dynamic policy conversion method through various context settings. Furthermore, this study attempts to present an empirical research paradigm.

Matland’s “ambiguity-conflict model” is applied to explain the problems and reform paths of China’s waste management policy implementation. Integrating structure discovery and bibliometrics into qualitative analysis, this study used search data from literature search engine with specific themes to achieve structure learning of Bayesian network with key factors refined in waste management policy.

The results show that China’s waste management policy implementation belongs to symbolic implementation with high ambiguity and high conflict. Four basic conversion paths for the waste management policy are proposed, which are classified by length and stability. Then, it is possible to locate the factors, paths and types of policy implementation through involvement analysis with features of each path and each district of policy implementation. Public education holds direct but unstable impact on waste management. Economic incentives hold continuous but gradually diminishing impact. Perceived policy effectiveness plays the crucial role like a central bridge. Resident conditions have a positive impact, which could be enhanced through economic development of China. The impact of subjective norm on waste management is not significant. But subjective norm has the potential breakthrough for solving stagnation of waste classification policy. However, the impacts from each factor may change along with economy growth and technology innovation.

This study uses the “ambiguity-conflict model” to position China’s waste classification policy and suggests that structure discovery methods help understand feasible reform paths for reform policy. The integration of theoretical analysis and quantitative simulation can achieve a comprehensive analysis of problems and solutions in waste management policy implementation of China. Promotion and education, economic incentives, perceived value, behavior control, subjective norm, perceived policy effectiveness, informal waste recycling system and residential conditions are explored as key factors for waste classification policy implementation as a representative in waste management policy. The role of each key factor and features of each conversion paths are integrated to position reform paths in the ambiguity-conflict model. This work helps to explain the stagnation of waste management policy implementation from the perspective of dynamic structure evolution, and some specific suggestions to get out of stagnation are proposed.

Given the emerging importance of the chief financial officer’s (CFO) role, this study aims to probe into the prevalence of corporate social responsibility (CSR) assurance practices in China and to examine whether or not CFO foreign, professional or academic experience affects the likelihood of CSR assurance decision.

All A-share listed Chinese companies during the year 2008–2017 with 5,144 firm-year observations have been investigated for this study.

This study finds a positive effect of CFO foreign and professional experience on CSR assurance. No significant association has been found between the CFO’s academic experience and CSR assurance. Additional analysis for Global Reporting Initiative (GRI) sampled firms shows that the academic and professional experience of CFOs has a significant positive association with CSR assurance. However, the main findings are replicated in the case of firms under mandatory CSR reporting.

The limitations of this study are its generalizability, unidimensional measure of CSR assurance which is unable to capture its quality and explore the other traits of CFOs.

It provides assurance practitioners with valuable longitudinal data on China’s CSR reporting and assurance services. Also, firms should recognize the importance of having competent CFOs to improve the credibility of their CSR reporting. The cross-sectional variation analysis (GRI and mandatory CSR) will help firms to assess the value of each CFO attribute for their nonfinancial reporting and auditing choices while considering internal and external stakeholder demands.

This study not only updates the existing understanding of CSR assurance methods in China but also explains the significance of CFO-specific experience in enhancing the credibility of nonfinancial reporting.

Rare earths are essential materials for many high-tech industries critical to both economic development and national defense. China, the world's dominant supplier of rare earths, has recently been imposing stricter controls over its production and export. The purpose of this paper is to examine the domestic roots of the changes in China's rare earth industry production and exports in its three-decade rise to the current global monopoly.

This paper adopts the historical institutionalism approach to analyze the trajectory of industry and trade development. The author analyzes data collected from government whitepapers and reputed scholarly and news sources.

This paper argues that the Chinese rare earth industry has gone through three periods of development, in which the state attempted to control the market and industry through reformulating rules and institutions to achieve state goals. Domestic state institutions, combined with macroeconomic environment and state governance strategy shaped the three-decade experience of rare earth industry and trade development in China.

This paper builds on existing findings about Chinese state regulations to provide a novel analytical framework to analyze the role of the state in industry and trade development in the rare earth industry. The focus on a single strategic industry seldom studied in the current literature also provides ample empirical value to further scholarly understanding about this industry.