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The metaverse is a virtual world where users can communicate with each other in a computer-generated environment. The use of metaverse technology has the potential to revolutionize the way businesses operate, interact with customers, and collaborate with employees. However, several obstacles must be addressed and overcome to ensure the successful implementation of metaverse technology. This study aims to examine the implementation of metaverse technology in the management of an organization's supply chain, with a focus on predicting potential barriers to provide suitable strategies.

Covariance-based structural equation modeling (CB-SEM) was used to test the model. In addition, artificial neural network modeling (ANN) was also performed.

The CB-SEM results revealed that a firm's technological limitations are among the most significant barriers to implementing metaverse technology in the supply chain management (SCM). The ANN results further highlighted that the firm's technological limitations are the most crucial input factors, followed by a lack of governance and standardization, integration challenges, poor diffusion through the network, traditional organizational culture, lack of stakeholder commitment, lack of collaboration and low perception of value by customers.

Because metaverse technology has the potential to provide organizations with a competitive advantage, increase productivity, improve customer experience and stimulate creativity, it is crucial to discuss and develop solutions to implementation challenges in the business world. Companies can position themselves for success in this fascinating and quickly changing technological landscape by conquering these challenges.

This study provides insights to metaverse technology developers and supply chain practitioners for successful implementation in SCM, as well as theoretical contributions for supply chain managers aiming to implement such environments.

This study aims to address workplace cyber incivility in digital environments by proposing human resource (HR) management strategies derived from a systematic review of the literature. It seeks to clarify the concept of cyber incivility, identify its antecedents and outcomes and provide practical recommendations for HR practices to mitigate its effects.

A systematic review following PRISMA guidelines analyzed 31 empirical studies (2006–2024) using Google Scholar, PsycINFO, Business Source Complete and Web of Science databases with keywords, including “cyber incivility,” “digital workplace” and “employee well-being.” Studies were included if they focused on workplace cyber incivility, provided primary data and were published in English, while those on cyber aggression or bullying were excluded. Two authors independently screened studies, resolving discrepancies through discussion. Thematic analysis synthesized findings on definitions, antecedents, outcomes and moderators.

The review identifies gaps in the literature, including inconsistent measurement approaches, limited understanding of cyber incivility’s multidimensional nature, insufficient examination of dyadic perspectives between perpetrators and targets and fragmented research across different digital platforms. The included studies (n = 31) examined diverse professional contexts, with sample sizes ranging from 69 to 830 participants. Cyber incivility is shaped by individual factors (e.g. personality traits, demographic characteristics), situational factors (e.g. workload, stress) and technology-driven factors (e.g. misinterpretation in digital communication). Its negative impacts include reduced job satisfaction, heightened stress, burnout and increased turnover intentions. Evidence-based HR recommendations include developing digital communication guidelines, implementing resilience-building programs and offering training on digital etiquette and conflict resolution.

This study provides a comprehensive framework for understanding cyber incivility in digital work environments and offers evidence-based HR interventions to foster respectful communication and improve employee well-being. It bridges existing research gaps by synthesizing fragmented studies and highlighting actionable strategies for HR professionals.

The purpose of this paper is to empirically analyze the impact of directors’ and officers’ (D&O) liability insurance on enterprise strategic change. It also explores the mediating role of litigation risk, the moderating roles of enterprise science and technology level and precipitation organizational slack between them. In addition, it examines the joint moderating roles of the top management team (TMT) external social network and enterprise science and technology level, and enterprise scale and precipitation organizational slack.

Using the unbalanced panel data of A-share listed companies in the Shanghai and Shenzhen stock exchanges of China from 2002 to 2020 as the research sample, this paper uses the ordinary least square method and fixed-effect model to study the relationship between D&O liability insurance and enterprise strategic change. The study also focuses on the mediating mechanism and moderating mechanisms between them.

The authors find that D&O liability insurance has an “incentive effect,” which can significantly promote enterprise strategic change. Litigation risk plays a partial mediating role between D&O liability insurance and enterprise strategic change. Enterprise science and technology level and precipitation organizational slack negatively moderate the relationship between D&O liability insurance and enterprise strategic change. TMT external social network and enterprise science and technology level, and enterprise-scale and precipitation organizational slack have joint moderating effects on the relationship between D&O liability insurance and enterprise strategic change.

This paper confirms the “incentive effect hypothesis” of the impact of D&O liability insurance on enterprise strategic change, which not only broadens the research perspective of enterprise strategic management but also further expands the research scope of D&O liability insurance. Besides, this paper thoroughly explores the influencing mechanisms between D&O liability insurance and enterprise strategic change, providing incremental contributions to the research literature in the field of enterprise risk management and corporate governance. The findings have practical guiding significance for expanding the coverage of D&O liability insurance, promoting the implementation of strategic changes and improving the level of corporate governance of Chinese enterprises.

The effects of gendered views on employee voice are of great importance for knowledge sharing within public universities. Yet, they are still neglected by current human resource management and entrepreneurship literature. While strengthening themselves by reinforcing the strengths and opportunities, public universities can generate entrepreneurial opportunities through various knowledge-sharing mechanisms, including social networks and employee voice. This became a crucial lever for public universities to leverage competitive advantages and to support entrepreneurial activities through network knowledge-based sharing. For this purpose, this study aims to examine the various aspects of entrepreneurship via the voice of employees, emphasizing the moderating effect of gender and the mediating role of social networks on the link between employee voice and the entrepreneurial atmosphere of universities.

The authors collected survey data from a cross-sectional sample of 335 employees engaged in entrepreneurship activities within public universities in an emerging economy context and analyzed the data using partial least squares structural equation modeling (PLS-SEM) with the Smart-PLS software.

The PLS-SEM analysis found that different dimensions of the university entrepreneurial climate (communication, knowledge sharing and innovative climate) positively impact members’ voices within public universities. This effect is amplified by social networks, which are crucial for spreading knowledge among faculty, thereby fostering a more open and collaborative academic environment.

When acting, the university top management team should encourage the generation and dissemination of entrepreneurial ideas to nurture a dynamic entrepreneurial atmosphere and social involvement, ultimately supporting sustainable competitive advantages through a culture of strategic knowledge sharing. The results have practical implications for university managers, entrepreneurship education actors, administrators, policymakers and entrepreneurial ecosystem actors, by demonstrating how social networks can amplify the dissemination of ideas and entrepreneurial spirit.

This research explores how entrepreneurship and social networks can help faculty members have a stronger influence in academic settings. It also fills in the gaps in knowledge about how human resource management and entrepreneurship can work together to create a more communicative and innovative academic environment. Additionally, this study brings new ideas to existing literature by looking at how gender differences can affect employee voice, particularly emphasizing the importance of women in leadership roles at universities. This study is also the first to delve into how entrepreneurship and social networks, along with gender perceptions, play a role in shaping the voice of employees in a public university.

This paper aims to design a deep reinforcement learning (DRL)-based variable impedance control policy that supports stability analysis for robot force tracking in complex geometric environments.

The DRL-based variable impedance controller explores and pre-learns the optimal policy for impedance parameter tuning in simulation scenarios with randomly generated workpieces. The trained results are then used as feedforward inputs to improve the force-tracking performance of the robot during contact. Based on Lyapunov’s theory, the stability of the proposed control policy is analysed to illustrate the interpretability of the results.

Simulations and experiments are performed on different types of complex environments. The results show that the proposed method is not only theoretically feasible but also has better force-tracking effects in practice.

Compared with most other DRL-based control policies, the proposed method possesses stability and interpretability, effectively avoids the overfitting phenomenon and thus has better simulation-to-real deployment results.

Innovation capabilities, changes in customer expectations and continuous supply chain (SC) network disruptions bring complexity and challenges to manufacturing firms (MFs). This study examines the influence of uncertainty, supplier innovation, cost reduction and integration of third-party logistics (3PLs) and fourth-party logistics (4PLs) on logistics outsourcing adoption.

Based on data collected from 180 managers in MFs in Jordan, our proposed research model was tested using partial least squares-SEM (PLS-SEM).

The findings suggest that supplier innovation and integration with 3PLs and 4PLs are key enablers of adopting logistics outsourcing in the manufacturing sector. Further, the findings indicate no significant impact of uncertainty and cost reduction as logistics outsourcing enablers. The results also suggest that integration with 3PLs and 4PLs mediate fully and positively the path between supplier innovation and logistics outsourcing adoption.

This study contributes to the manufacturing literature by providing a better understanding of the main enablers of logistics outsourcing in the manufacturing sector, simultaneously tackling dependence and enhancing adoption performance in the innovation and disruptions SC era. Further, it expands the understanding of the integration between SC partners in these twofold roles.

This study proposes a novel method to improve the accuracy of overall equipment effectiveness (OEE) estimation in the metallurgical industry. This is achieved by modeling the frequency and severity of stoppage events as random variables.

An analysis of 80,000 datasets from a metal-mechanical firm (2020–2022) was performed using the loss distribution approach (LDA) and Monte Carlo simulation (MCS). The data were further adjusted with a product price index to account for inflation.

The variance analysis revealed supporting colleagues (59.8% of variance contribution), food breaks (29.8%) and refreshments (9.0%) as the events with the strongest influence on operating losses.

This study provides a more rigorous approach to operational risk management and OEE measurement in the metal-mechanical sector. The developed algorithm supports the establishment of risk management guidelines and facilitates targeted OEE improvement efforts.

This research introduces a novel OEE estimation method specifically for the metallurgical industry, utilizing LDA and MCS to improve accuracy compared to existing techniques.

This study aims to propose a cloud platform architecture considering information sharing based on blockchain to realize the security and convenience of enterprise information sharing in the automotive supply chain.

A bilateral matching model considering enterprises information contribution stimulates information sharing and improves the efficiency and quality of supply and demand matching. Three smart contracts are used to complete the information sharing process and match supply and demand in the automotive supply chain.

The system is tested on the local Ganache private chain, and the decentralized web page is designed based on the architecture prototype.

Solve the problem of information island in automobile supply chain.

This study explores how establishing an agile supply chain ecosystem (ASCE) during the COVID-19 pandemic impacts three listed auto firms’ financial and customer performance in China. Drawing on the theory of supply chain resilience, responsiveness and restoration (3R capabilities), we collect, mine and analyze unstructured social media data from Dongfeng Motor Corporation (DFM), BYD Company Limited (BYD) and SAIC Motor Corporation Limited (SAIC), all of which have production plants in Wuhan.

Data mining was conducted on 3,528 comments involving DFM, BYD and SAIC from 190 uploaders in the stages of “Early COVID-19 Period (January 23-May 31, 2020)” and “Enhanced Preparedness and Vaccine Launch Period (September 8, 2020–January 15, 2021)”. Our conceptual model of an ASCE was tested by adopting structural equation modelling and verified by the DFM case study.

The study finds that the 3R capabilities of the supply chain have a positive effect on establishing an automotive agile supply chain ecosystem. Establishing the automotive agile supply chain ecosystem has promoted corporate financial performance and customer performance, but the mechanism of action presents a delayed feature.

This study refines the definitions and application of the 3Rs concerning an ASCE in the automotive industry. Through text mining technology and statistical analysis methods, we uncover and discuss the impact of COVID-19 on the performance of three auto companies in China and examine how ASCE establishment plays a role. Constructing an ASCE provides a theoretical basis and realistic approach for the long-term and healthy development of the automotive supply chain.

With respect to severe working conditions such as heavy load and impact, this paper aims to investigate the friction reduction and anti-wear performance of kaolin and molybdenum dialkyl dithiophosphate (MoDDP) composite lubricant additives to improve the lubrication effect of a single additive.

A four-ball friction test was carried out to determine the optimal concentration of kaolin and organic molybdenum additives and the tribological properties of the kaolin/MoDDP composite lubricant additives. A ring block test of composite lubricant additives was designed to investigate its lubrication performance under the severe working conditions of low speed, heavy load and impact.

The results showed that the optimal addition mass fractions of kaolin and MoDDP were 4.0 and 1.5 Wt.%, respectively, when kaolin and MoDDP were used as single lubricant additives. Compared with the single additive, the 4.0 Wt.% kaolin/1.5 Wt.% MoDDP composite lubricant additive showed excellent friction reduction and anti-wear effects under heavy load and impact conditions. Physicochemical analysis of the wear surface revealed that the lamellar kaolin additive and MoDDP had excellent synergistic effects, and the friction process promoted the generation of lubricant films containing a chemically reactive layer of MoS₂, MoO₂, FeS₂ and Fe₂O₃ and a physically adsorbent layer containing SiO₂ and Al₂O₃, which play important roles in anti-wear and friction reduction.

The excellent friction reduction and anti-wear effects of lamellar silicate minerals and the excellent antioxidant properties and good synergistic effects of molybdenum were comprehensively used to develop the composite additives with great lubricating properties.