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This study explores the determinants of public willingness to comply with COVID-19 regulations to address the research gap at the intersection of public health and law enforcement within the unique sociocultural context of Taiwan.

Utilizing survey data from New Taipei City in 2021, the analysis involved multiple linear regression models to assess the influences of psychological conditions (i.e. distress and self-efficacy), community compliance and perceptions of government (i.e. general trust in government and specific perceptions of police procedural justice) on compliance tendencies while controlling for individual demographics.

The results indicated that self-efficacy, perceived community compliance, trust in government, and police procedural justice are positively associated with public compliance with COVID-19 regulations. Among these variables, trust in government and police procedural justice were identified as the most prominent factors, followed by self-efficacy and perceived community compliance. As demographic factors such as age, gender and education did not significantly affect willingness to comply, psychological, social and governmental influences are more powerful determinants of compliance than static demographic characteristics.

This study provides empirical evidence from Taiwan on the factors shaping public compliance during an unprecedented global pandemic. It highlights the importance of fostering governmental trust and enhancing police procedural justice during periods of stability to secure compliance with public health directives in times of crisis.

This study adopts the elaboration likelihood model and configuration perspectives to explore the internal mechanisms underlying the influence of live streaming on consumer trust building and purchase intention.

This study invited 757 experienced live streaming e-commerce users from Chinese platforms such as TikTok and RED, who participated in survey by filling questionnaires collected online. The research employed a mixed-method approach using SEM and fsQCA. SEM was utilized to analyze quantitative data to determine the direct and mediated relationships within product trust, while fsQCA served as a complement to identify the combinations of conditions that enhance product trust.

The findings reveal three important insights. Firstly, in the context of live streaming e-commerce, both product characteristics and streamer characteristics significantly influence consumers' trust in products. The para-social interaction plays a partial mediating role in the relationship between streamer characteristics and product trust. Secondly, four distinct paths are identified that contribute to enhancing product trust in live streaming e-commerce. Thirdly, PSI emerging as a core condition across all four paths, underscores the importance for merchants to foster positive social interactions with consumers beyond the live streaming environment.

This study enhances understanding of the dynamic live streaming e-commerce industry, offering insights into consumer behavior and practical guidance for merchants seeking to build engaged, trustworthy customer relationships.

Online games are highly popular Internet applications. Some games enable players to save game progress and accumulate experiences or changes to avatars during gameplay, whereas some other games do not, requiring players to restart from the beginning each time. That is, games differ in avatar accumulability. However, we do not know whether games should be designed to permit avatar accumulability or not and how it affects players’ gameplay experience and therefore game outcomes, indicating gaps. Research addressing these gaps can inform game makers in designing games that effectively strengthen their players’ game loyalty.

We used social identity theory (SIT) to construct a theoretical model. To test this model, three waves of survey data were gathered from the same 778 participants.

These findings uniquely indicate that avatar accumulability fosters avatar identification and increases players’ focused immersion, thus increasing players’ loyalty.

Game providers could include game features that enable players to accumulate their avatars’ in-game skins, levels, items (weapons and equipment) and experience points. This accumulability can help strengthen players’ game loyalty.

Overall, our study extends SIT by adding a new trigger (avatar accumulability) and two novel consequences of avatar identification (image protection and focused immersion) in avatar-related systems (games or gamified systems). The new trigger offers an actionable means to apply SIT, while the novel consequences verify the value of applying SIT to study online games.

The purpose of this paper is to present a high-precision method for localizing the Target Ball of an industrial robot, using Binocular Stereo Vision (BSV).

The steps for modeling the kinematics of a flexible robot include three steps. First, the kinematic model was developed, and robot motion tests were conducted, which is multiple sets of static joint angle motions. The kinematic parameters were calibrated based on a laser tracker and BSV, respectively. Second, the dynamics model was developed and operate the robot to perform motions, which is Fourier series excitation trajectories. The dynamics parameters were calibrated. Third, the static joint angles were brought into the dynamics model to calculate the external forces and moments of each joint. The stiffness parameters were calibrated.

The experimental results show that after calibrating the kinematic parameters of the Target Ball, the Target Ball positioning error approximately 4.597 mm. After calibrating the kinematic parameters of the Spherically Mounted Retro and stiffness parameters, the Target Ball positioning error is reduced from about 6.962 mm to approximately 4.956 mm, which is close to 4.597 mm.

The limitation of the approach is that, kinematic model and dynamics model are both required. Therefore, the high openness degree of robot is required, the robot needs to support path planning functions and joint moment extraction. However, some mature commercial robots do not support this.

In this paper, the stiffness model could effectively replace the calibration of the kinematic parameters of the load.

ESG issues are gaining increasing attention from investors, but the environmental, social and governance (ESG) rating disagreement caused by different standards of rating agencies misleads investors' investment decisions. This can lead to an increased risk of stock price crashes, causing turbulence in the financial markets and reducing investors' confidence. The paper investigates whether ESG rating disagreement of the current period increases stock price crash risk and the mechanism to mitigate this impact.

With the sample of the listed companies of Shanghai and Shenzhen Stock Exchanges from 2010 to 2022 this paper examines the impact of ESG rating disagreement itself on stock price crash risk. Moreover, this paper examines the mechanisms by analyzing the moderating effect of distraction of investors; digital economy and corporate intelligence maturity.

This paper finds that ESG rating disagreement itself would amplify the stock price crash risk. When exploring the moderating effect of institutional investors' distraction, digital economic development level and corporate intelligence, the paper found that they would mitigate the impact of ESG rating disagreement on stock price crash risk. The relationship between ESG rating disagreement and stock price crash risk is more pronounced in the context of heavily-polluted, state-owned enterprises (SOEs) and enterprises with star analysts.

Currently, few articles discuss ESG rating disagreement, especially the impact of current ESG rating disagreement on stock price crash risk. This paper focuses on this topic and provides strategies to mitigate the impact of current ESG rating divergence on stock price crash risk.

This study examines the role of digital transformation intentions in enhancing the perceived resilience of firms, with a focus on China’s manufacturing sector. It investigates the mediating role of knowledge sharing and the moderating impact of transformational leadership.

A quantitative approach was employed, collecting data from 347 manufacturing firms. Participants included managers and MBA students involved in digital transformation projects. The study utilized statistical analysis to explore the relationships between digital transformation intentions, knowledge sharing, transformational leadership and perceived firm resilience.

The analysis reveals that knowledge sharing is a critical mediating factor between digital transformation intentions and perceived firm resilience. Additionally, transformational leadership significantly strengthens this relationship, highlighting its importance in the successful implementation of digital initiatives.

The study is geographically and sectorally limited to China’s manufacturing sector, which may affect the generalizability of the findings. Future research could explore other sectors and regions to validate and extend the results.

The findings underscore the necessity of integrating digital transformation initiatives with effective leadership and knowledge management practices. Firms that foster transformational leadership and facilitate knowledge sharing are better equipped to enhance their resilience in the face of global disruptions.

This research offers a deep understanding of how digital transformation intentions, mediated by knowledge sharing and supported by transformational leadership, contribute to perceived firm resilience. It provides valuable insights for both academic research and practical applications in the field of management.

The study aims to investigate the implementation of green supply chain management (GSCM) in the footwear industry. It focuses on identifying key factors (dimensions and corresponding sub-dimensions) that promote GSCM and examines the importance and relevance of these factors in improving sustainability and competitive advantage within the footwear manufacturing supply chain.

A literature review and expert interviews were conducted to identify the factors for GSCM in the footwear industry. The DEMATEL-based ANP (DANP) method was used to analyze the importance and interrelationships of the identified dimensions and sub-dimensions. The data were collected through questionnaires and analyzed across different levels of the supply chain to compare the significant factors affecting GSCM implementation.

The study reveals that green purchasing is the core dimension, playing a critical role in the footwear industry. Organizational and environmental management emerges as the most influential causal factors, strongly correlated with other factors. However, as to sub-dimensions, different level of supply chain members should focus on different sub-dimensions.

This research provides valuable insights into the key dimensions and sub-dimensions and their causal relationships in the footwear industry. It offers practical suggestions for manufacturers to prioritize organizational and environmental management as a strategic approach to maximize the benefits of GSCM.

This paper examines the ability of those governmental reforms adopted in response to the COVID-19 outbreak to affect earnings management (EM).

The paper focuses on the Italian decision to suspend the recapitalization obligation to guarantee the respect of the going concern’s assumption. By analysing a sample of unlisted entities, this analysis uses different techniques to detect EM before and after the suspension of that obligation.

The results suggest that EM decreased after the decision to suspend recapitalization obligations.

Accounting quality depends on not only accounting standards but also management practices in response to those government measures instituted during the COVID-19 outbreak.

The results are a novelty in the literature. In terms of the institutional theory, they provide evidence of EM decrease, thereby validating the assumption that regulation can enable and empower social actors – particularly their actions – despite the visions of repression and constraint conjured by that concept. Isomorphism theory supports the thesis and results that indicate that EM decreases not only in emerging markets, where corporate governance mechanisms are less able to obstruct EM, but also in the developed countries. Thus, insightful and novel conceptualizations can still be achieved by using institutional theory. Yet the findings also extend agency theory assumptions and demonstrate that also the issuance of less severe regulation can reduce agency costs and, in turn, also EM.

Although previous research has recognized the pivotal role of mobile social media in knowledge sharing among project members, little is known about what factors affect knowledge sharing in mobile social media groups (MSMGs). Against this background, using normative social influence theory, this study attempts to explore factors influencing knowledge sharing in MSMGs.

Data from 205 Chinese construction project members are collected and used for analysis. Ordinary least squares regression by Stata 16 is used to test the proposed hypotheses.

Concerning role norms, gender difference in knowledge sharing behavior (KSB) is found, while it is not the case for knowledge quality (KQ). Work experience is found to positively affect KQ, but shows no influence on KSB. As for group norms, the inverted-U relationship between number of members and KSB is partially supported. In addition, organizational norms generally exhibit the greatest influence on both KSB and KQ among the three forms of norms.

This study deepens the understanding of knowledge sharing factors in mobile social media environments and affords practical implications for how to make full use of social media for knowledge management within construction project teams.

Building a smart city is a necessary path to achieve sustainable urban development. Smart city public–private partnership (PPP) project is a necessary measure to build a smart city. Since there are many participants in smart city PPP projects, there are problems such as uneven distribution of risks; therefore, in order to ensure the normal construction and operation of the project, the reasonable sharing of risks among the participants becomes an urgent problem to be solved. In order to make each participant clearly understand the risk sharing of smart city PPP projects, this paper aims to establish a scientific and practical risk sharing model.

This paper uses the literature review method and the Delphi method to construct a risk index system for smart city PPP projects and then calculates the objective and subjective weights of each risk index through the Entropy Weight (EW) and G1 methods, respectively, and uses the combined assignment method to find the comprehensive weights. Considering the nature of the risk sharing problem, this paper constructs a risk sharing model for smart city PPP projects by initially sharing the risks of smart city PPP projects through Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to determine the independently borne risks and the jointly borne risks and then determines the sharing ratio of the jointly borne risks based on utility theory.

Finally, this paper verifies the applicability and feasibility of the risk-sharing model through empirical analysis, using the smart city of Suzhou Industrial Park as a research case. It is hoped that this study can provide a useful reference for the risk sharing of PPP projects in smart cities.

In this paper, the authors calculate the portfolio assignment by EW-G1 and construct a risk-sharing model by TOPSIS-Utility Theory (UT), which is applied for the first time in the study of risk sharing in smart cities.