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This paper reports exploratory findings about teaching in the metaverse using a virtual reality (VR) platform and head-mounted displays. This paper addresses three research questions: Is the metaverse an appropriate platform for teaching Lean? What are the benefits and problems of this approach over traditional classroom methods? What are the future implications for teaching Lean in the VR-enabled metaverse?

The research presented in this paper is exploratory. A critical realism approach is adopted using action research through the preparation, delivery and review of the first four masterclasses entitled Leading Intelligent Lean offered by Gemba (formerly The Leadership Network). The data collection methods included a pre-workshop questionnaire, participant observation, focus groups and end-of-course surveys.

It was found that Lean can be taught successfully in the metaverse. There are many related benefits, particularly in terms of the high levels of immersion and the “wow” factor. Remaining technological limitations are reduced by continually improving the metaverse platform and the course content and delivery. The authors conclude that the metaverse is a useful addition to teaching Lean – and is especially promising when used in a blended teaching approach.

To the best of the authors’ knowledge, this is the first report of teaching Lean in a VR-enabled metaverse and one of the first of teaching and learning in the metaverse regardless of topic. The respective problems and benefits of this approach versus teaching in a traditional classroom setting are discussed.

This paper aims to propose the mechanism of cross-network effect embedded, which can help cross-border e-commerce (CBEC) platforms strengthen cooperative relationships with sellers more equitably and effectively by using the network structural characteristics of the platforms themselves.

A two-stage evolutionary game model has been used to confirm the influence factors. The mathematical derivation of evolutionary game analysis is combined with the simulation method to examine the role of cross-network effect in cooperation. The evolutionary game model based on the cross-network effect is proposed to achieve better adaptability to the study of cooperation strategy from the two-sided market perspective.

The evolutionary game model captures the interactions of cross-network effect and the influence factors from a dynamic perspective. The cross-network effect has a certain substitution on the revenue-sharing rate of SMEs. CBEC platforms can enhance the connection between consumers and the website by improving the level of construction, which is a good way to attract sellers more cost-effectively and efficiently.

This study provides a new method for the validation of the cross-network effect, especially when data collection is difficult. But this method is only a numerical simulation. So the conclusions still need to be further tested empirically. Besides, researchers are advised to explore the relationship between the added user scale and the cross-network effect in some specificCBEC platforms.

This study provides a new method for the validation of the cross-network effect, especially when data collection is difficult. But this method is only a numerical simulation. So the conclusions still need to be further tested empirically. Besides, researchers are advised to explore the relationship between the added user scale and the cross-network effect in some specific CBEC platforms.

Investigations that study cooperation strategy from the cross-network effect perspective in CBEC are limited. The research figured out which influence factors are affected by the cross-network effect in cooperation. A two-stage evolutionary game model was proposed to explain the interaction of the factors. The evolutionary game analysis with a simulation method was combined to highlight the role of cross-network effect on cooperation strategy to give a deeper investigation into the sustainable cooperation ofCBEC.

A substantial amount of research has examined the firm value impact of corporate social responsibility (CSR). Nevertheless, the findings have been inconsistent, prompting researchers to identify contingencies under which the impact varies. This study examines how information technology (IT)-enabled knowledge capabilities moderate the relationship between CSR and firm value.

We conducted the ordinary least squares (OLS) regression analysis on a sample of S&P 500 companies spanning from 2010 to 2017. We employed additional methods to test the robustness of the results, including the generalized method of moments (GMM) estimator and the two-stage least squares (2SLS) method.

The results show that IT-enabled absorptive capability (IT-AC) and IT-enabled social integration capability (IT-SIC) positively moderate the CSR–value relationship. Further, their moderating effects vary in distinct ways when environmental dynamism changes, hinting at the distinct underlying rationales behind the moderating roles of IT-AC and IT-SIC.

This study improves the understanding of the business value of CSR and IT. It has limitations in generalizability due to the use of secondary data.

This study provides practical guidelines to managers about how to strategically leverage IT resources for the creation of CSR value.

Encouraging businesses to enhance their CSR efforts and uphold sustainability extends beyond our immediate benefit and impacts future generations as well. However, due to an imbalance between costs and returns, companies often refrain from being wholeheartedly devoted to CSR. Our insights on guiding companies to derive more value from CSR can inspire their greater investment in CSR. Meanwhile, companies can obtain additional returns from deployed IT.

This study extends the IT business value literature by revealing how IT generates firm value in the context of CSR. It also adds critical insights into the mixed findings in previous research regarding the CSR–firm value link. The study’s findings offer useful guidance on the strategic deployment and utilization of IT resources to facilitate the creation of CSR value.

In this study, the expectancy disconfirmation model (EDM) was applied to explain the formation of public health emergency preparedness cooperative behavior (EPCB) as well as considering the roles of official media exposure and positive emotions.

The analysis was based on a sample of 374 respondents collected during the coronavirus (COVID-19) pandemic. A t-test was used to examine the differences in variables by sex, age and educational background. Hypothesis testing was conducted using structural equation modeling. Amos 24.0 and R 4.0.3 were used to analyze the data.

The results indicated that (1) official media exposure has a positive impact on expectations for and perceived performance of public services, as well as positive emotions; (2) the EDM can be used to explain public satisfaction with government public health services; and (3) public satisfaction and positive emotions have positive effects on EPCB; (4) EDM and positive emotions mediate the relationship between official media exposure and EPCB.

This study provides practical implications for increasing the EPCB from the perspective of risk communication.

This study explores whether herd behavior exists for equity crowdfunding investors in China and whether this herding is rational.

Based on signaling theory and social learning theory, two hypotheses were proposed. This study employed two approaches to collect data. First, this paper analyzed 3,041 investments on an equity crowdfunding platform in China using Python programming and built a panel data model. Second, based on a unique experiment design, this study conducted several relevant herd behavior simulation experiments.

We found that investors in the Chinese equity crowdfunding market exhibit herd behavior and that this herding is rational. Project attributes play a negative role in moderating the relationship between the current investment amount and cumulative investments. Experimental results further support our findings.

This study contributes to the emerging literature on herding in crowdfunding by focusing on equity crowdfunding in China. We are the first to explore whether Chinese equity crowdfunding investors exhibit rational herding behavior. The study is also original in applying social learning theory to equity crowdfunding and in using both actual crowdfunding campaigns and experimental approaches to collect data. This study has valuable implications to practice.

This study aims to propose a series of numerical and surrogate models to investigate the aerodynamic pressure inside cracks in high-speed railway tunnel linings and to predict the stress intensity factors (SIFs) at the crack tip.

A computational fluid dynamics (CFD) model is used to calculate the aerodynamic pressure exerted on two cracked surfaces. The simulation uses the viscous unsteady κ-ε turbulence model. Using this CFD model, the spatial and temporal distribution of aerodynamic pressure inside longitudinal, oblique and circumferential cracks are analyzed. The mechanism behind the pressure variation in tunnel lining cracks is revealed by the air density field. Furthermore, a response surface model (RSM) is proposed to predict the maximum SIF at the crack tip of circumferential cracks and analyze its influential parameters.

The initial compression wave amplifies and oscillates in cracks in tunnel linings, resulting from an increase in air density at the crack front. The maximum pressure in the circumferential crack is 2.27 and 1.76 times higher than that in the longitudinal and oblique cracks, respectively. The RSM accurately predicts the SIF at the crack tip of circumferential cracks. The SIF at the crack tip is most affected by variations in train velocities, followed by the depth and length of the cracks.

The mechanism behind the variation of aerodynamic pressure in tunnel lining cracks is revealed. In addition, a reliable surrogate model is proposed to predict the mechanical response of the crack tip under aerodynamic pressures.

Given the current friction and wear challenges faced by automobile parts and bearings, this study aims to identify a novel texture for creating anti-friction and wear-resistant surfaces. This includes detailing the preparation process with the objective of mitigating friction and wear in working conditions.

Femtosecond laser technology was used to create a mango-shaped texture on the surface of GCr15 bearing steel. The optimized processing technology of the texture surface was obtained through adjusting the laser scanning speed. The tribological behavior of the laser-textured surface was investigated using a reciprocating tribometer.

The friction coefficient of the mango-shaped texture surface is 25% lower than that of the conventional surface, this can be attributed to the reduced contact area between the friction ball and the micro-textured surface, leading to stress concentration at the extrusion edge and a larger stress distribution area on the contact part of the ball and disk compared to the conventional surface and the function of the micro-texture in storing wear chips during the sliding process, thereby reducing secondary wear.

The mango-shaped textured surface in this study demonstrates effective solutions for some of the friction and wear issues, offering significant benefits for equipment operation under light load conditions.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-04-2024-0127/

The purpose of this paper is to explore how small and medium-sized enterprises (SMEs) in China leverage their strengths to engage stakeholders in knowledge co-creation processes and get mutual benefit via knowledge-based view (KBV).

Based on KBV, the authors conduct a multiple-case study of five SMEs in China to embrace the knowledge co-creation practice using semi-structured interview, organizational documents and onsite observation.

This study highlights how SMEs leverage their strengths to engage stakeholder to co-create knowledge and practice for the better capturing and utilization of external and internal knowledge. The authors identify three processes of knowledge co-creation for SMEs based on knowledge sharing, knowledge integration and knowledge application in the B2B context. This study finds that SMEs engage their stakeholders in knowledge sharing by building and maintaining trust. The knowledge integration process was driven by the owner’s openness. Mutual learning facilitates the knowledge application process of SMEs.

This study relies on a limited number of case studies and considers only firms’ perspective to analyze the SMEs co-create knowledge with their stakeholders. Further studies could examine the challenge of knowledge co-creation in multiple stakeholders’ relationships in B2B contexts, i.e. in relation to product and service innovation with complexity and uncertainly.

Managers need to make choices when designing knowledge co-creation process in collaborative product development activities. The use of online and offline approaches can help balance requirements in terms of joint problem-solving across firms, the efficiency of knowledge co-creation and effective of knowledge leakage.

The conceptualization of knowledge co-creation as knowledge sharing and knowledge integration and knowledge application extends existing perspective on knowledge co-creation as either a transfer of knowledge or as revealing the novel situation of pertinent knowledge with entirely assimilate it. The findings point to the complexity of knowledge co-creation as a process influenced by stakeholder engagement, perspectives on knowledge, trust of multiple stakeholders, openness of firm boundaries and mutual learning of SMEs with their stakeholders.

Promoting electric vehicles (EVs) is an effective way to achieve carbon neutrality. If EVs are widely adopted, this will undoubtedly be good for the environment. The purpose of this study is to analyze the impact of network externalities and subsidy on the strategies of manufacturer under a carbon neutrality constraint.

In this paper, the authors propose a game-theoretic framework in an EVs supply chain consisting of a government, a manufacturer and a group of consumers. The authors examine two subsidy options and explain the choice of optimal strategies for government and manufacturer.

First, the authors find that the both network externalities of charging stations and government subsidy can promote the EV market. Second, under a relaxed carbon neutrality constraint, even if the government’s purchase subsidy investment is larger than the carbon emission reduction technology subsidy investment, the purchase subsidy policy is still optimal. Third, under a strict carbon neutrality constraint, when the cost coefficient of carbon emission reduction and the effectiveness of carbon emission reduction technology are larger, social welfare will instead decrease with the increase of the effectiveness of emission reduction technology and then, the manufacturer’s investment in carbon emission reduction technology is lower. In the extended model, the authors find the effectiveness of carbon emission reduction technology can also promote the EV market and social welfare (or consumer surplus) is the same whatever the subsidy strategy.

The network externalities of charging stations and the subsidy effect of the government have a superimposition effect on the promotion of EVs. When the network effect of charging stations is relatively strong, government can withdraw from the subsidized market. When the network effect of charging stations is relatively weak, government can intervene appropriately.

Comparing previous studies, this study reveals the impact of government intervention, network effects and carbon neutrality constraints on the EV supply chain. From a sustainability perspective, these insights are compelling for both EV manufacturers and policymakers.

This study aims to examine whether the adoption of artificial intelligence (AI) by audit firms and their clients affects audit efficiency and audit quality.

This study empirically examines the abovementioned research question based on data from China for the years 2011 to 2020. It uses audit report lag as a proxy for audit efficiency and the likelihood of annual report restatement as a proxy for audit quality. It adopts the propensity score matching and the two-stage OLS regression model to address the endogeneity issue led by firms’ innate complicated functions.

The findings show that when audit firms and their clients use AI separately, there's a positive link between AI use and audit report lag. However, when audit firms and clients use AI together, there's a negative link between AI use and audit report delays that enhance overall audit efficiency. Next, the authors observe a negative link between AI use and the likelihood of a restatement. Finally, the authors find that the association between AI adoption and audit quality is driven by increased audit effort lag. Results are consistent and robust to endogeneity tests and sensitivity analyses.

Findings can complement the audit quality and corporate governance literature by clarifying that external audit must evolve through digitalization and the incorporation of newly developed digital tools, such as AI.