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In recent years, counterproductive knowledge behavior (CKB) and its types have received increasing interest in knowledge management as the degree of knowledge sharing and innovation in enterprises continues to increase. A rapidly growing number of studies have shed light on the important antecedents and consequences of employees’ CKB. However, the various labels, conceptualizations and operationalizations of CKB have fragmented this body of research. This study aims to systematically integrate the effects of the six types of organizational characteristics on CKB and further draws more general conclusions based on the results of previous studies.

Based on a survey of 103 effect values responsible for 52 CKB samples, the authors use the ABC theory to explore the effects of the six types of organizational characteristics on CKB. Moderator analysis were performed to resolve inconsistencies in empirical studies and understand the contexts under which CKB has the strongest or weakest effect.

The results showed that task interdependence and a positive organizational atmosphere, in general, negatively affect employees’ CKB in the moderation analysis. In contrast, workplace discomfort, negative organizational atmosphere, internal competition and time pressure positively and partly affect employees’ CKB. The direction and magnitude of these effects were affected by emotional factors, knowledge personnel types and sample sources. Discussing the theoretical, methodological and practical implications of these findings can offer a guiding framework for future research.

Better control of employees’ CKB is not achieved by adjusting organizational characteristics alone but by combining personal characteristics and mood changes with it to balance organizational characteristics and CKB. Furthermore, the large-sample joint study integrated the conceptual definition of CKB. The multivariate data study provided more reliable conclusions and a solid theoretical foundation for CKB research areas.

This study aims to investigate the effects of different dimensions of social capital on individual knowledge transfer to nurture the organization’s intellectual capital, as well as the interactions among these dimensions and explore the potential moderators.

This study conducted a meta-analysis with 108 independent empirical studies to examine the different dimensions of social capital–knowledge transfer relationships and the effects of moderators and used meta-analytic structural equation modeling (MASEM) to test the internal relationships among social capital dimensions.

The results show that structural, relational and cognitive social capitals are all positively related to knowledge transfer. In addition, different dimensions of social capital act as complements to one another. Further examinations reveal that the level of economic development has no significant moderating effect on the relationship between social capital and knowledge transfer. Then, the cultural context and profit climate characteristics moderate the relationship between social capital and knowledge transfer.

Leveraging the trilogy of signaling, learning and spillover effects, this meta-analytic study quantitatively integrates the relationships between different dimensions of social capital and knowledge transfer. It reconciles the present disparate findings, demonstrates the validity of different dimensional social capital interactions and obtains highly generalized conclusions. This study also introduces a dichotomy, saturation versus reinforcement, to explain the mixed results, which enriches social capital theory.

This paper aims to explore the underlying mechanisms and boundary conditions through which equipment manufacturing enterprises can capture market value from digital transformation, with a specific focus on the roles of knowledge search and knowledge recombination.

This study uses a double fixed-effects model to test the hypotheses, using a unique data set of “firm-year” observations from 739 publicly listed equipment manufacturing companies in China, spanning the period from 2018 to 2022.

Digital transformation drives market value creation in equipment manufacturing enterprises through both breakthrough knowledge recombination (BKR) and progressive knowledge recombination (PKR). In addition, the analysis of marginal conditions reveals that diversified knowledge search serves as a substitute for digital transformation in promoting BKR, while also positively moderating the relationship between digital transformation and PKR.

Grounded in the knowledge-based view theoretical framework, this study introduces the novel concepts of BKR and PKR and systematically examines how digital transformation impacts market value in equipment manufacturing enterprises.

The purpose of this study is to prepare trivalent chromium conversion (TCC) film on the Zn-Ni electrodeposited film on the surface of 2024 aluminum alloy and to ensure that the TCC film has good corrosion resistance and electrical conductivity.

The morphology of the TCC film was studied by scanning electron microscopy, and the elemental composition of the TCC film was characterized by X-ray energy dispersive spectroscopy. The TCC film was tested and the roughness was analyzed by 3D morphology (white light interference). The electrochemical behavior and corrosion resistance of TCC films were studied by the Tafel polarization curve and electrochemical impedance spectroscopy, and the conductivity was tested.

The TCC films were uniformly black and bright in appearance and were mainly compounds of Zn, Ni and Cr with O. The electrochemical impedance of the TCC film is larger than that of the Zn-Ni film, the corrosion current (I_corr) is smaller than that of the Zn-Ni film and the corrosion potential (E_corr) is larger than that of the Zn-Ni film, which has excellent corrosion resistance. TCCs were performed on the appropriate size of the shell sample, and the resistance of the shells was 1.5 mVDC, which meets the total resistance requirements of the test standard for composite connector accessories.

In this study, TCC film was successfully prepared on the Zn-Ni coating on the surface of 2024 aluminum alloy. The TCC film has good corrosion resistance and electrical conductivity.

This study aims to provide a new perspective and path to reduce the unsafe behavior of new generation of construction workers (NGCWs) in China. The purpose of this study is to explore the influencing mechanism of work-family balance on the unsafe behavior of NGCWs and test the mediating effect of job satisfaction and the moderating effect of group safety climate.

A theoretical model on the influencing mechanism of work-family balance on unsafe behavior of NGCWs was constructed through theoretical analysis. Research data were collected from 502 NGCWs via a questionnaire survey, and research hypotheses were testified with regression analysis.

The results show that work-family balance not only directly reduces NGCWs’ unsafe behavior but also indirectly reduces it through job satisfaction, which plays a partial mediating role. In addition to positively moderating the relationship between work-family balance and NGCWs’ unsafe behavior, group safety climate can also moderate the relationship between work-family balance and job satisfaction in a positive way.

This study provides practical implications for construction companies to reduce the unsafe behaviors of NGCWs from the perspective of work-family balance. Specifically, construction companies should adopt more flexible work rules, such as flexible organization and rotation systems, to increase their work autonomy. Meanwhile, construction companies need to improve the work environment and basic conditions for NGCWs, establish a reasonable salary system and provide attractive promotion opportunities to increase their job satisfaction. In addition, construction companies should provide active safety lectures and training, and supervisors should improve safety communication and interaction levels. Co-workers should remind workers about their safety attitudes and behaviors promptly. A good group safety climate will be created through the efforts of construction companies, supervisors and co-workers.

This study clarifies the influencing mechanism of work-family balance on the NGCWs’ unsafe behavior and further tests the partial mediating role of job satisfaction and the positively moderating effect of group safety climate on the influence relationship of work-family balance on job satisfaction and NGCWs’ unsafe behavior, which defines the boundary conditions of the relationship between work-family balance and NGCWs’ unsafe behavior, and promotes the effective integration of social exchange theory and theoretical system of influencing mechanism of construction workers’ unsafe behavior.

In recent years, personalized recommendations have facilitated easy access to users' personal information and historical interactions, thereby improving recommendation effectiveness. However, due to privacy risk concerns, it is essential to balance the accuracy of personalized recommendations with privacy protection. Accordingly, this paper aims to propose a neural graph collaborative filtering personalized recommendation framework based on federated transfer learning (FTL-NGCF), which achieves high-quality personalized recommendations with privacy protection.

FTL-NGCF uses a third-party server to coordinate local users to train the graph neural networks (GNN) model. Each user client integrates user–item interactions into the embedding and uploads the model parameters to a server. To prevent attacks during communication and thus promote privacy preservation, the authors introduce homomorphic encryption to ensure secure model aggregation between clients and the server.

Experiments on three real data sets (Gowalla, Yelp2018, Amazon-Book) show that FTL-NGCF improves the recommendation performance in terms of recall and NDCG, based on the increased consideration of privacy protection relative to original federated learning methods.

To the best of the authors’ knowledge, no previous research has considered federated transfer learning framework for GNN-based recommendation. It can be extended to other recommended applications while maintaining privacy protection.

This study aims to identify which types of information quality influence purchase intentions the most in live streaming commerce and to examine the role of network size in this context.

We propose a model to investigate the correlation among the quality of different information in live streaming commerce, consumer trust, network size and purchase intention. An empirical analysis of 505 questionnaires was conducted by constructing a structural equation model.

The empirical findings indicate that information quality can directly enhance purchase intention and exert an indirect influence through the mediating factors of trust in products and streamers. Perceived network size positively moderates the relationship between information quality and trust in products. Of the five types of information, the quality of bullet-screen comments information is most important to consumers.

This study represents the first systematic analysis of how the quality of multiple types of information in live streaming commerce influences consumer trust and purchase intention, integrated within a unified framework. It uniquely introduces network size as a moderating variable, offering both theoretical insights and practical guidance for balancing information quality with network size in live streaming commerce environments.

The purpose of this paper is to explore the correction mechanism of resilient safety culture on new generation of construction workers (NGCWs)' unsafe behavior and test the multiple mediation effects of job crafting and perceived work meaningfulness based on the context of Chinese construction industry in order to find a new way to effectively correct the NGCWs' unsafe behavior.

A theoretical model of correction mechanism was established based on literature research and theoretical deduction. An empirical study was employed based on confirmatory factor analysis and regression analysis with a sample of 404 NGCWs in China.

The results indicated that resilient safety culture can effectively correct NGCWs' unsafe behavior through job crafting and perceived work meaningfulness. Job crafting and perceived work meaningfulness can play independent and serial mediating roles between resilient safety culture and unsafe behavior.

Research results only represent a short-term law about the correction mechanism of NGCWs' unsafe behavior based on a questionnaire study from China's construction industry. It is necessary to continue to implement a longitudinal study to test it in a relatively long period in future research. The findings also need to be verified based on the young construction workers in other countries.

This study provides a theoretical basis and feasible management reference for construction enterprises in China to correct NGCWs' unsafe behavior from the perspective of resilient safety culture. Furthermore, the construction of resilient safety culture in construction enterprises can help NGCWs better carry out job crafting and perceive the meaning of work.

This paper clarifies the correction mechanism of resilient safety culture on unsafe behavior of NGCWs, and further tests the independent mediating roles and a serial mediating role of job crafting and perceived work meaningfulness between resilient safety culture and unsafe behavior, which fills the research gap about the influence mechanism of resilient safety culture on young construction workers' unsafe behavior and enriches the theoretical system of unsafe behavior correction of construction workers.

This study aims to examine the association between fair value accounting and the cost of corporate bonds, proxied by bond yield spread. In addition, this study explores the moderating role of auditor industry expertise at both the national and the city levels.

This study first examines the effect of the use of fair value on yield spread by estimating firm-level regression model, where fair value is the testing variable and yield spread is the dependent variable. To test the differential impact of the three levels of fair value inputs, this paper divides the fair value measures based on the three-level hierarchy, Level 1, Level 2 and Level 3, and replace them as the test variables in the regression model.

This study finds that the application of fair value accounting is generally associated with a higher bond yield spread, primarily driven by Level 3 estimates. The results also show that national-level auditor industry expertise is associated with lower bond yield spreads for Level 1 and Level 3 fair value inputs, whereas the impact of city-level auditor industry expertise on bondholders is mainly on Level 3 fair value inputs.

The paper innovates by exploring the impact of fair value accounting in a setting that extends beyond financial institutions, the traditional area of focus. Moreover, most prior research considers private debt, whereas this study examines public bonds, for which investors are more likely to rely on financial reporting for their information about a firm. Finally, the study differentiates between city- and national-level industry expertise in examining the role of auditors.

This research has several practical implications. First, firms seeking to raise debt capital should consider involving auditors, with either industry expertise or fair value expertise, due to the roles that auditors play in safeguarding the reliability of fair value measures, particularly for Level 3 measurements. Second, from standard-setting and regulatory perspectives, the study’s findings that fair value accounting is associated with higher bond yield spread cast further doubt on the net benefits of applying a full fair value accounting regime. Third, PCAOB may consider enhancing guidance to auditors on Level 2 fair value inputs, to further enhance audit quality. Finally, creditors can be more cautious in interpretating accounting information based on fair value while viewing the employment of auditor experts as a positive signal.

First, the paper extends research on the role of accounting information in public debt contracting. Second, this study adds to the auditing literature about the impact of industry expertise. Finally, and more generally, this study adds to the ongoing controversy on the application of fair value accounting.

Limited use of Internet of Things (IoT) technology on construction sites has restricted its value in the construction industry. To propel its widespread application, this paper explores the influencing factors and action paths of construction companies' IoT technology adoption behavior.

First, literature research, technology adoption theories, and semi-structured expert interviews were employed to build the adoption model. Second, a questionnaire survey was conducted among Chinese construction contractors to collect empirical data. Third, the structural equation model method and regression analysis were used to test the adoption model. Finally, the findings were further validated with interviews, case studies, and field observations.

External environmental pressure (EEP), perceived benefit (PB), top management support (TMS), company resource readiness (CRR), adoption intention (AI), and perceived compatibility (PCA) have a direct positive impact on adoption behavior (AB). In contrast, perceived cost (PC) and perceived complexity (PCL) exert a direct negative impact on AB. The EEP, PB, and PC are critical factors affecting AB, whereas AI is strongly affected by CRR and TMS. Besides, AI plays a part mediating role in the relationship between seven factors and AB. Company size and nature positively moderate AI's positive effect on AB.

This paper contributes to the knowledge of IoT technology adoption behavior in the construction sector by applying the technology adoption theories. Exploring the implementation barriers and drivers of IoT technology in construction sites from the perspective of organizational technology adoption behavior and introducing moderating variables to explain adoption behavior are innovations of this paper. The findings can help professionals better understand the IoT technology adoption barriers and enhance construction companies' adoption awareness, demand, and ability. This work also provides a reference for understanding the impact mechanism of the adoption behavior of other innovative technologies in construction.