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Computer vision and deep learning (DL) methods have been investigated for personal protective equipment (PPE) monitoring and detection for construction workers’ safety. However, it is still challenging to implement automated safety monitoring methods in near real time or in a time-efficient manner in real construction practices. Therefore, this study developed a novel solution to enhance the time efficiency to achieve near-real-time safety glove detection and meanwhile preserve data privacy.

The developed method comprises two primary components: (1) transfer learning methods to detect safety gloves and (2) edge computing to improve time efficiency and data privacy. To compare the developed edge computing-based method with the currently widely used cloud computing-based methods, a comprehensive comparative analysis was conducted from both the implementation and theory perspectives, providing insights into the developed approach’s performance.

Three DL models achieved mean average precision (mAP) scores ranging from 74.92% to 84.31% for safety glove detection. The other two methods by combining object detection and classification achieved mAP as 89.91% for hand detection and 100% for glove classification. From both implementation and theory perspectives, the edge computing-based method detected gloves faster than the cloud computing-based method. The edge computing-based method achieved a detection latency of 36%–68% shorter than the cloud computing-based method in the implementation perspective. The findings highlight edge computing’s potential for near-real-time detection with improved data privacy.

This study implemented and evaluated DL-based safety monitoring methods on different computing infrastructures to investigate their time efficiency. This study contributes to existing knowledge by demonstrating how edge computing can be used with DL models (without sacrificing their performance) to improve PPE-glove monitoring in a time-efficient manner as well as maintain data privacy.

Grounded in upper echelon (UE) theory, this study aims to examine the role of managerial competencies (business experience, financial literacy and digital literacy) in sustainable development strategy, with resource management as a mediator.

The empirical data collection is conducted through a survey completed by 297 top management teams of small and medium-sized enterprises (SMEs) operating in Pakistan. Structural equation modelling in Smart PLS is used to substantiate the hypotheses.

The findings reveal that financially and digitally literate managers significantly contribute to the sustainable development strategies of SMEs. However, experienced managers do not focus significantly on sustainable development strategies. Resource management partially mediates the nexus between financial literacy and sustainable development strategy, as well as between digital literacy and sustainable development strategy. In contrast, resource management does not mediate the nexus between business experience and sustainable development strategy.

This study recommends that SMEs should prioritize managers with digital and financial literacy over those with experience. SMEs led by a management team with digital and financial literacy are more effective in resource management for sustainable development practices, whereas experienced managers may not significantly prioritize managing resources for sustainability.

While research based on the UE theory significantly contributes to the body of knowledge on sustainable development, the role of managerial competencies, particularly business experience, financial literacy and digital literacy, in sustainable development strategy via resource management is neglected. This research fills this gap in the context of UE theory and thereby enriches the literature.

This study aims to investigate the relationship between corporate sustainable development goals (SDGs) disclosure and analyst forecast quality.

The study focuses on a sample of 95 Italian-listed companies preparing the mandatory non-financial declaration (NFD) according to the Global Reporting Initiative (GRI) standards over a five-year period (2017–2021), corresponding to an unbalanced sample of 438 observations. Analyst forecast quality was proxied by earnings forecast accuracy (FA) and earnings forecast dispersion (FD), built on data retrieved from the Refinitiv database. A manual content analysis was performed on NFDs to derive an SDG disclosure score (SDGD) for each sampled company.

This study provides empirical evidence suggesting that voluntary SDG disclosure matters to the capital market in that it helps enhance the information environment of companies, evidenced by improved analyst forecast quality. In particular, this study highlighted that SDG disclosure positively influences analyst FA while negatively affecting analyst FD.

This study focuses on the Italian context, which has idiosyncratic characteristics regarding the structure of the financial market, the composition of corporate ownership and experience in non-financial reporting practices.

This study indicates to corporate managers that following GRI standards may represent the right way to better integrate SDG disclosure in corporate non-financial reports and increase the relevance of such information for investors and other capital market participants.

To the best of the authors’ knowledge, this is the first study that empirically examines the association between SDG disclosure and analyst forecast quality.

In the context of Industry 4.0, intelligent construction technologies (ICT) represented by information technology and networking will undoubtedly provide new impetus to the development of the prefabricated building supply chain (PBSC), but they will also bring various potential risks. So far, there is a large lack of research on the comprehensive consideration of the risks associated with the intelligent transformation of PBSC based on the information sharing perspective, and the critical risks and interactions are still unclear, making it difficult to identify efficient risk mitigation strategies. Therefore, this paper aims to reveal the interactions between stakeholders and clarify the critical risk nodes and interactions in information sharing of PBSC (IS-PBSC), and propose targeted risk mitigation strategies.

Firstly, this paper creatively delineates the risks and critical stakeholders of IS-PBSC. Secondly, Data is collected through questionnaires to understand the degree of risks impact. Thirdly, with the help of NetMiner 4 software, social network analysis is conducted and IS-PBSC risk network is established to reveal critical risk nodes and interactions. Finally, further targeted discussion of critical risk nodes, the effectiveness and reasonableness of the risk mitigation strategies are proposed and verified through NetMiner 4 software simulation.

The results show that the critical risks cover the entire process of information sharing, with the lack of information management norms and other information assurance-related risks accounting for the largest proportion. In addition, the government dominates in risk control, followed by other stakeholders. The implementation of risk mitigation strategies is effective, with the overall network density reduced by 41.15% and network cohesion reduced by 24%.

In the context of Industry 4.0, ICT represented by information technology and networking will undoubtedly provide new impetus to the development of the PBSC, but they will also bring various potential risks. So far, there is a large lack of research on the comprehensive consideration of the risks associated with the intelligent transformation of PBSC based on the information sharing perspective, and the critical risks and interactions are still unclear, making it difficult to identify efficient risk mitigation strategies.

Based on the results of risk network visualization analysis, this paper proposes an ICT-based IS-PBSC mechanism that promotes the development of the integration of ICT and PBSC while safeguarding the benefits of various stakeholders.

This paper aims to explore the pathways connecting perceived social isolation, perceived stress, hedonic browsing and e-impulse buying in social commerce.

A theoretical model was proposed. Data from 394 young adults was analyzed using structural equation modeling to test the hypothesized relationships in the model.

Perceived social isolation is associated with elevated levels of perceived stress and engagement in hedonic browsing. Young consumers often turn to hedonic browsing as a coping mechanism for stress, and both stress and hedonic browsing play significant roles in fostering impulsive purchases. Perceived stress fully mediates the influence of perceived social isolation on hedonic browsing. Conversely, hedonic browsing partially mediates the impact of perceived stress on e-impulse buying.

Businesses can use the findings to develop effective marketing strategies that entice customers to purchase on social commerce platforms. Moreover, the findings offer valuable insights for young consumers, providing them with an understanding of the complexities of impulsive buying in social commerce. This knowledge can empower them to make informed decisions and exercise enhanced control over their purchasing habits. Furthermore, the findings could be used as a basis for developing targeted interventions to reduce unnecessary purchases, particularly during challenging times that necessitate social isolation.

This study offers new empirical insights into the ways in which perceived social isolation, perceived stress and hedonic browsing contribute to the heightened prevalence of e-impulse buying in social commerce.

This study investigates the relationship between female CEOs and SMEs’ financing decisions. The study also examined the moderating role of ownership structure (female, foreign, and state ownership) in female CEO-SMEs’ financing decisions.

The study has applied Generalized Least Square (GLS) and Binomial Logistic Regression. The study has used firm-level data from 2,700 Small and Medium Enterprises (SMEs) in the Chinese economy.

The results suggest that female CEOs use debt financing. However, the financing decision of female CEOs varies if we account for female ownership, foreign ownership, state ownership, firm association with big firms, and the industry in which the firm operates. This study also provides robust evidence that female CEOs utilize debt financing under certain conditions and that female CEOs prefer long-term debt financing to short-term debt financing when considering debt maturity choices.

Recent studies report a negative relationship between female CEOs and financing decisions based on the rationale that females are risk-averse and choose less risky financing compared to their male counterparts. This study posits new evidence that female CEO financing decisions are not always risk averse if we consider female ownership, foreign ownership, state ownership, firm association with big firms, and the industry in which the firm operates. Thus, we contribute to the corporate governance literature, and this study implies a corporate financing policy.

This research examines the impact of the National Rural E-commerce Comprehensive Demonstration Project (NRECDP) on poverty reduction and income growth in rural China.

The study develops a theoretical framework, which considers the role of geographical, technological, institutional and cultural factors for the e-commerce poverty alleviation (e-CPA) model. Empirically, this study applies the difference-in-differences (DID) model and the event study approach to evaluate the effectiveness of NRECDP on the basis of large-scale county-level and household-level panel data spanning 2010 to 2020.

The study found that the NRECDP, as a government-led, information and communication technology (ICT)-enabled, market-based program, has led to a significant increase in per capita output of primary industry employees, as well as in the disposable income of rural residents, especially those in national-level poverty-stricken (NP) counties. The interventions of the NRECDP achieved these positive outcomes through transportation and Internet infrastructure improvement, ICT adoption and human capital accumulation in impoverished towns and villages in remote rural areas. These effects are larger in the eastern region of China, followed by the central region, whereas the weakest effects were found in the western region. However, we found little evidence of the NRECDP increasing household developmental expenditure.

The study findings have important practical and policy implications for rural e-commerce development and self-sustained poverty alleviation solutions. The research revealed the significance of government NRECDP interventions for increasing rural income, reducing living costs, and empowering the rural population in its multiple social roles, namely, as consumers, producers, employees and microentrepreneurs. The local cultural context may also play a role in ICT adoption and entrepreneurship cultivation with a downstream effect on the effectiveness of e-CPA practices. Policymakers would need to ensure a supportive entrepreneur-friendly environment for rural e-commerce development and continue implementing progressive policies for poverty alleviation.

This study explores poverty alleviation issues in China by developing for the first time a multi-faceted framework that is subsequently tested by both county-level and household-level large-scale observations. Also, it is the first study to provide nationwide empirical evidence on the effectiveness of e-CPA in narrowing down the spatial and digital divides in China. In addition to the impact of geography, technology and governmental support, this study also sheds light on the role of culture in the adoption and diffusion of digital technologies and as a source of local entrepreneurial opportunities.

In order to solve the decision-making problem that the attributive weight and attributive value are both interval grey numbers, this paper tries to construct a multi-attribute grey decision-making model based on generalized greyness of interval grey number.

Firstly, according to the nature of the generalized gresness of interval grey number, the generalized weighted greyness distance between interval grey numbers is given, and the transformation relationship between greyness distance and real number distance is analyzed. Then according to the objective function that the square sum of generalized weighted greyness distances from the decision scheme to the best scheme and the worst scheme is the minimum, a multi-attribute grey decision-making model is constructed, and the simplified form of the model is given. Finally, the grey decision-making model proposed in this paper is applied to the evaluation of technological innovation capability of 6 provinces in China to verify the effectiveness of the model.

The results show that the grey decision-making model proposed in this paper has a strict mathematical foundation, clear physical meaning, simple calculation and easy programming. The application example shows that the grey decision model in this paper is feasible and effective. The research results not only enrich the grey system theory, but also provide a new way for the decision-making problem that the attributive weights and attributive values are interval grey numbers.

The decision-making model proposed in this paper does not need to seek the optimal solution of the attributive weight and the attributive value, and can save the decision-making labor and capital investment. The model in this paper is also suitable for the decision-making problem that deals with the coexistence of interval grey numbers and real numbers.

The paper succeeds in realizing the multi-attribute grey decision-making model based on generalized gresness and its simplified forms, which provide a new method for grey decision analysis.

Virtual wine experiences (VWEs) replaced in-person wine experiences during the Covid-19 pandemic and continue to be offered by some actors. This study aims to investigate the factors driving interest in VWEs and identify relevant traits of potential consumers to help assess VWEs long-term potential.

A representative sample of 399 Oregon and California wine consumers answered a structured online survey. The authors combine ordered logistic regression and qualitative techniques to analyze the data.

VWEs may effectively attract potential wine consumers and tourists. High interest in VWEs is associated with strong wine involvement and intentions to visit wine regions. Digitization, aversion to travel-related risk and convenience are other relevant drivers of VWE interest. The segmentation analysis revealed that consumers with a potentially higher interest in VWE have distinct traits.

Wineries and wine tourism destinations could leverage VWEs to attract wine tourists and consumers. The authors discuss specific characteristics of high-interest consumers.

Participants in VWEs interact with hosts and explore products in real time. This engagement has long-term marketing potential for attracting them as customers or visitors. The study provides strategic information for practitioners and academics on VWE interest drivers and potential demand, which is currently missing from the literature.

As an effective measure for reducing energy consumption and achieving carbon neutrality, prefabricated building projects (PBPs) have attracted considerable attention in China. Although the Chinese Government has vigorously promoted PBPs, neither developers nor consumers have high recognition of PBPs. This study aimed to explore the decision-making behaviour of governments, developers and consumers in promoting the development of prefabricated buildings in China and to better optimise the incentive strategies for prefabricated buildings in China.

Based on prospect and evolutionary game theories, an evolutionary game model of three stakeholders in the development of PBPs – government, developers and consumers – was constructed. Combined with the system dynamics theory, the incentive policy behaviour and influencing factors of the three parties in the evolutionary game model were analysed.

The results showed that the initial probability of the three parties affects the decision-making behaviour of each party and that of other stakeholders. Government subsidies to developers are more sensitive than developers themselves. There is a certain threshold for the scope of government subsidies to consumers, and exceeding this threshold does not promote the development of PBPs. Based on the results, policy recommendations to the government, developers and consumers were proposed to enhance PBP development.

This study provides suggestions for governments to formulate reasonable incentive policies for prefabricated buildings and a specific theoretical basis for the sound development of prefabricated buildings.