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The purpose of the study is to investigate the financing channels and carbon emission abatement preferences of supply chain members, and further examine the optimal contract design of the retailer.

This paper develops a low-carbon supply chain composed of one retailer and one manufacturer, in which the retailer provides trade credit to the manufacturer. Considering the cap-and-trade regulation, the manufacturer with uncertain yield makes decision on whether to invest in emission abatement. There are bank loan and trade credit to finance production for the manufacturer and green credit to finance emission abatement investment. Meanwhile, the retailer may provide the manufacturer with three kinds of contracts to improve emission abatement efficiency, namely, revenue sharing, cost sharing or both sharing.

The results show that the retailer prefers to offer financing service at lower interest rate, but trade (and green) credit financing is always optimal for manufacturer and supply chain. The investment in emission abatement is value-added to all players. The sharing contracts offered by the retailer at lower sharing ratios can realize Pareto improvement of the system regardless of the financing scheme. However, comparing with the revenue or cost sharing contract, the existence of optimal sharing ratios makes the both sharing contract more favorable to the retailer.

The findings provide guidance for the emission-dependent manufacturer in financing and emission abatement decisions, as well as recommendations for the retailer to offer loan service and sharing contract.

This paper integrates green credit into bank loan or trade credit to analyze the financing decision of the manufacturer with uncertain yield and further considers the influence of three kinds of sharing contracts introduced by the retailer on improving operational performance.

This paper aims to present a novel approach to facial recognition that enhances privacy by using radio frequency identification (RFID) technology combined with transformer models, eliminating the need for visual data and thus reducing privacy risks associated with traditional image-based systems.

The proposed RFID-transformer recognition system (RTRS) uses RFID technology to capture signal features such as phase and received signal strength indicator, which are then processed by a transformer model. The model is specifically designed to handle structured RFID data, capturing subtle patterns and dependencies to achieve accurate biometric recognition. The system’s performance was validated through comprehensive experiments involving different environmental conditions and user scenarios.

The experimental results demonstrate that the RTRS system achieves a recognition accuracy of 98.91%, maintaining robust performance across various challenging conditions, including low-light environments and changes in face orientation. In addition, the system provides a high level of privacy preservation by avoiding the collection and storage of visual data.

To the best of the authors’ knowledge, this work introduces the first RFID-based facial recognition system that fully leverages transformer models, offering a privacy-preserving alternative to traditional image-based methods. The system’s ability to perform accurately in diverse scenarios while ensuring user privacy makes it a significant advancement in biometric technology.

Research focusing on psychological capital (PsyCap) has been mainly conducted at the individual level. However, recent research has expanded investigations to the collective level with a greater focus on team-level PsyCap. Although, as demonstrated by recent systematic reviews and meta-analyses, the relationships between individual-level PsyCap and the desirable/undesirable outcomes are fairly established in the literature, less is known about such relationships for team-level PsyCap. One of these important, yet least investigated, research areas is the research stream that focuses on the relationship between team-level PsyCap and the outcomes of health, Well-Being, and safety. This chapter aims to highlight the role of individual-level PsyCap as an important predictor of employees’ health, Well-Being, and safety outcomes, but also to go beyond that to provide insights into the potential role of team-level PsyCap in predicting such outcomes at both individual and team levels. To do so, the chapter first draws upon relevant theories to discuss the empirical research findings focusing on the relationship between individual-level PsyCap and the outcomes of health, Well-Being, and safety. It then focuses on team-level PsyCap from theoretical, conceptualization, and operationalization perspectives and provides insights into how team-level PsyCap might be related to health, Well-Being, and safety outcomes at both individual and team levels. Thus, this chapter proposes new research directions in an area of PsyCap that has been left unexplored.

As an unhealthy dependence on social media platforms, social media addiction (SMA) has become increasingly commonplace in the digital era. The purpose of this paper is to provide a general overview of SMA research and develop a theoretical model that explains how different types of factors contribute to SMA.

Considering the nascent nature of this research area, this study conducted a systematic review to synthesize the burgeoning literature examining influencing factors of SMA. Based on a comprehensive literature search and screening process, 84 articles were included in the final sample.

Analyses showed that antecedents of SMA can be classified into three conceptual levels: individual, environmental and platform. The authors further proposed a theoretical framework to explain the underlying mechanisms behind the relationships amongst different types of variables.

The contributions of this review are two-fold. First, it used a systematic and rigorous approach to summarize the empirical landscape of SMA research, providing theoretical insights and future research directions in this area. Second, the findings could help social media service providers and health professionals propose relevant intervention strategies to mitigate SMA.

This paper aims to investigate the influence of cybersecurity awareness and compliance attitudes on the protective behaviours exhibited by employees. This study also aims to explore the complex correlation between the level of awareness about cybersecurity measures and attitudes towards compliance with these measures. Additionally, it looks at how these factors collectively impact employees’ behaviour to protect organisational assets and information.

This study uses a quantitative research methodology in which primary data are gathered using a survey questionnaire distributed to personnel employed at Vietnamese organisations. The data are analysed, and the validity of the measurement and structural equation model is assessed using a partial least squares–structural equation model approach after the collection of all the survey responses.

The provision of policies and security education, training and awareness programmes are strongly and positively associated with cybersecurity awareness. Moreover, cybersecurity awareness plays an important role in shaping attitudes and intentions towards information security policy compliance (ISPC). Attitude is positively associated with intention towards ISPC and employee protective behaviour. Finally, the intention towards ISPC is significant in shaping employee protective behaviour.

This study contributes to the understanding of the antecedents of cybersecurity in developing countries such as Vietnam. Furthermore, it provides a comprehensive framework for understanding intention and protective behaviour through cybersecurity awareness and compliance attitudes. By combining the theory of planned behaviour and protection motivation theory with institutional governance, this study extends previous research on the effects of these variables on employee protective behaviour.

Despite the importance of green supply chain integration (GSCI) in advancing green innovation (GI) is recognized, it remains unclear how firms can translate their GSCI efforts into GI. Therefore, this study aims to understand how GSCI affects GI, with its dimensions (exploitative GI and exploratory GI), as well as to investigate the mediating role of green knowledge integration capability (GKIC) and the moderating role of blockchain technology (BCT) adoption.

On the basis of data collected from 247 managers working in Indian firms in the automotive industry, the authors tested the proposed model using the PROCESS macro tool via SPSS software.

The empirical results indicate that GSCI is positively associated with both exploitative and exploratory GI, with a higher effect on exploitative GI. In addition, GKIC mediates the link between GSCI and exploitative GI in contrast to exploratory GI. Notably, the relationship between GSCI and GKIC is stronger when BCT adoption is high.

This study opens the black box of how GSCI affects exploitative and exploratory GI by revealing the mediating role of GKIC and the moderating role of BCT adoption. It provides valuable insights for practitioners to translate GSCI efforts into GI through developing GKIC and adopting BCT.

Government employees must comply with policies on information security regulations, online security practices, social networking usage, internet addiction, online cyberthreats and other related habits. These activities are considered cybersecurity behaviors. Government social media (GSM) accounts are increasingly used to educate employees about cybersecurity risks. To support the effectiveness of cybersecurity practices in government organizations, the purpose of this study is to investigate the impacts of GSM and organizational policy compliance on employees’ cybersecurity awareness, motivation and behaviors.

Data were obtained by administering a questionnaire survey to public personnel in Vietnam. A total of 330 valid responses were obtained, and the research hypotheses were tested using partial least squares–structural equation modeling.

First, cybersecurity awareness enhances information protection motivation and employee protective behavior. Second, GSM has positive impacts on cybersecurity knowledge and information protection motivation. Third, there is a strong positive association between information protection motivation and employee protective behavior. Finally, while organizational compliance significantly increases cybersecurity awareness, its impact on employee protective behavior is ind irect.

This research enhances the literature on the behavioral dimension of cybersecurity. The primary objective of this study is to assess the influence of cybersecurity awareness on protective behaviors rather than intents and attitudes alone. Furthermore, this research integrates protection motivation theory and cultivation theory to provide a more thorough assessment of cybersecurity awareness and protective behavior. By investigating the impact of GSM on the level of cybersecurity awareness among employees within government organizations, this study provides valuable insights into the efficacy of recent governmental initiatives aimed at fostering cybersecurity.

This paper aims to explore the effect of different government subsidy decisions and the differences between the consequences of these decisions when supply chain members engage in cooperative green innovation through cost-sharing arrangements.

This paper investigates the optimal decisions for green supply chains under two types of subsidies, including subsidies for green innovation research and development (R&D) costs and subsidies for consumers, by integrating game theory with numerical simulation.

The optimal R&D cost-sharing ratio is found to be 2/3 for manufacturers and 1/3 for retailers. Under any subsidy policy, the supply chain can achieve maximum total profit. When the supply chain adopts the optimal R&D cost-sharing ratio, subsidies for green innovation R&D costs prove to be the most effective in increasing the supply chain’s profit. However, from the perspective of total social welfare, the analysis reveals that government subsidies to consumers are more beneficial for promoting overall social welfare.

Previous studies on green supply chain decisions have primarily focused on either government subsidies or corporate cost sharing in isolation. In contrast, this study combines both government subsidies and cost sharing within a unified framework for a more comprehensive analysis. Additionally, this paper examines the impact of government subsidies on supply chain cost-sharing decisions and their effect on overall social welfare while considering the presence of cost sharing and using the combination of theoretical modeling and simulation analysis.

The integration of e-commerce platforms and artificial intelligence (AI) into the marketing channel ecosystem is challenging the explanatory capacity of traditional channel power theories, indicating a significant yet unaddressed research gap concerning the impact of these digital entities and AI on channel power exercise dynamics. This study adopts a contingency perspective to critically revisit how e-commerce platforms exercise channel power and the ensuing effects on channel conflicts. The purpose of this study is to extend the boundaries of traditional channel power theories, enhancing their relevance in today’s digital marketplace.

Building on channel power theories, the authors developed a framework tested with survey data collected from 262 sellers. This framework incorporates three key contingent variables: inter-platform competition, AI capabilities and platform value co-creation. Regression analysis was used to perform the analyses.

This study finds that intense inter-platform competition mitigates the (positive) negative relationship between platform channel power and the exercise of (non-) coercive power. Moreover, a platform’s AI capabilities and value co-creation activities diminish the potential for channel conflicts induced by the exercise of coercive power. AI capabilities can also strengthen the negative relationship between the exercise of non-coercive power and channel conflicts.

This study contributes to the advancement of traditional channel power theories by integrating contemporary digital elements like AI and platform dynamics. This study provides theoretical and practical insights on navigating channel power in modern marketing environments, offering strategic guidelines for optimizing channel relationships.

Grounded in upper echelons theory (UET) and conflict theory, the purpose of this study is to analyzes the innovative behavior of family firms from the perspective of the cognitive differences between successors and senior managers.

This research employed a sample listed family firms in China. The obtained results were subjected to hierarchical regression analysis, complemented by rigorous model robustness testing through propensity score matching and regression with substitution variables.

Successors engender task conflicts with family members in the top management team (TMT) due to cognitive differences, thereby stimulating corporate innovation. Conversely, successors engender relationship conflicts with non-family members in the TMT, impeding innovation. Furthermore, the performance expectations and the gender of the successor CEO also influence the relationship between cognitive differences and innovation between the successor and the TMT.

This study's originality and value lie in its innovative application of UET and conflict perspectives to dissect the intricate layers of intergenerational cognitive differences and their impact on the innovative behavior of family firms. It augments our comprehension of how the internal dynamics within family firms shape strategic innovation decisions.