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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.

Effectively predicting research and development project portfolio benefit (R&D PPB) could assist organizations in monitoring the execution of research and development project portfolio (R&D PP). However, due to the uncertainty and complexity of R&D PPB, current research remains lacking a valid R&D PPB prediction tool. Therefore, an R&D PPB prediction model is proposed via a backpropagation neural network (BPNN).

The R&D PPB prediction model is constructed via a refined immune genetic algorithm coupling backpropagation neural network (RIGA-BPNN). Firstly, considering the characteristics of R&D PP, benefit evaluation criteria are identified. Secondly, the benefit criteria values are derived as input variables to the model via trapezoidal fuzzy numbers, and then the R&D PPB value is determined as the output variable through the CRITIC method. Thirdly, a refined immune genetic algorithm (RIGA) is designed to optimize BPNN by enhancing polyfitness, crossover and mutation probabilities. Lastly, the R&D PPB prediction model is constructed via the RIGA-BPNN, followed by training and testing.

The accuracy of the R&D PPB prediction model stands at 99.26%. In addition, the comparative experiment results indicate that the proposed model surpasses BPNN and the immune genetic algorithm coupling backpropagation neural network (IGA-BPNN) in both convergence speed and accuracy, showcasing superior performance in R&D PPB prediction. This study enriches the R&D PPB predicting methodology by providing managers with an effective benefits management tool.

The research implications of this study encompass three aspects. First, this study provides a profound insight into R&D PPB prediction and enriches the research in PP fields. Secondly, during the construction of the R&D PPB prediction model, the utilization of the composite system synergy model for quantifying synergy contributes to a comprehensive understanding of intricate interactions among benefits. Lastly, in this research, a RIGA is proposed for optimizing the BPNN to efficiently predict R&D PPB.

This study carries threefold implications for the practice of R&D PPM. To begin with, the approach proposed serves as an effective tool for managers to predict R&D PPB. Then, the model excels in efficiency and flexibility. Furthermore, the proposed model could be used to tackle additional challenges in R&D PPM, such as gauging the potential risk level of R&D PP.

Effective predicting of R&D PPB enables organizations to allocate their limited resources more strategically, ensuring optimal use of capital, manpower and time. By accurately predicting benefit, an organization can prioritize high-potential initiatives, thereby improving innovation efficiency and reducing the risk of failed investments. This approach not only strengthens market competitiveness but also positions organizations to adapt more effectively to changing market conditions, fostering long-term growth and sustainability in a competitive business environment.

Incorporating the characteristics of R&D PP and quantifying the synergy between benefits, this study facilitates a more insightful R&D PPB prediction. Additionally, improvements to the polyfitness, crossover and mutation probabilities of IGA are made, and the aforementioned RIGA is applied to optimize the BPNN. It significantly enhances the prediction accuracy and convergence speed of the neural network, improving the effectiveness of the R&D PPB prediction model.

The consideration of the substitution phenomenon in the project portfolio selection problem can improve the robustness of project portfolio selection and help enterprises better achieve their strategic objectives. However, the existence of inter-project risk propagation will have a negative impact on project substitution. This paper proposes a new framework for project portfolio selection and constructs a risk propagation model based on strategic objectives to study the impact of risk propagation on substitution in the project portfolio.

The authors first construct a risk propagation model based on strategic objectives to describe the risk propagation between projects. Then the project substitution phenomenon based on risk propagation is put forward, and the calculation method of substitution loss is given. Finally, a robust project portfolio selection framework based on strategic objectives considering risk propagation is constructed.

The analysis of a case study demonstrates that (1) With the increase of risk intensity, the strategic loss of the same project portfolio increases linearly, and under the same risk intensity, the more projects in the portfolio, the stronger the robustness. (2) Considering risk propagation, the effect of project substitution is significantly weakened, and the strategic loss rate of the project portfolio is significantly increased compared with that of a direct attack.

This study is the first to take the project substitution into account in the project portfolio selection process. Moreover, the authors describe inter-project risk propagation and analyze the impact of risk propagation on the project substitution phenomenon. Finally, the authors extend the evaluation index of robustness. This paper puts forward a new way to solve the problem of project portfolio selection.

The study examines the relationship between CEO characteristics and corporate social responsibility (CSR) in China. Previous studies showed that good CSR behaviour could enhance the firm’s financial performance. CEOs are responsible for major decision-making, including CSR policies. This chapter uses all A-share listed firms in China from 2011 to 2020. The authors find that CEO’s gender, age, educational background, and career experience have positive relationships with CSR. This chapter enriches the current literature on the effects of CEO characteristics and highlights the important roles of CEO characteristics in CSR activities.

In the realm of open innovation (OI) networks, coopetition—where competition and cooperation coexist—plays a pivotal role in shaping the dynamics between diverse projects. This dual relationship is crucial for the propagation of knowledge and the bolstering of the network's overall resilience. While competition drives the quality of products and services, thereby reinforcing network resilience, cooperation facilitates knowledge diffusion, which is essential for the network's robustness.

We delve into the interplay between coopetition intensity and network resilience through the lens of knowledge diffusion. Our methodology begins with a sensitivity analysis to gauge the direct effects of coopetition on resilience. This is followed by a principal component analysis to identify the key determinants of coopetition intensity among projects. Finally, we utilize linear regression and moderation analysis to explore the mediating role of knowledge diffusion in the resilience of OI networks.

Our work is grounded in network theory, which provides a robust theoretical framework for understanding project coopetition and knowledge diffusion within the OI paradigm. This research not only offers a nuanced understanding of coopetition's impact on OI network resilience but also highlights the significance of knowledge diffusion as a critical mediating variable.

1) Identifies the significant influences in project coopetition (competition and cooperation). (2) Puts the conceptual framework and calculation method of the open innovation network resilience based on the project coopetition and knowledge diffusion. (3) Explores the moderating role of knowledge diffusion in project coopetition influencing open innovation networks resilience. (4) Measures the influence of project coopetition relationship on open innovation network resilience from the perspective of knowledge diffusion. (5) Encourages project management to consider the portfolios of coopetition.

This paper aims to provide a reference for the development of digital transformation from the perspective of manufacturing process links.

This paper applies canonical correlation analysis based on digital technology patents in the key links of manufacturing industries (product design, procurement, product manufacturing, warehousing and transportation, and wholesale and retail) and the related indicators of economic benefits of regions in China.

(1) The degree of digitalization of manufacturing process links is significantly correlated with economic benefits. (2) The improvement of the degree of digitalization in the “product design” link, the “warehousing and transportation” link, the “product manufacturing” link and the “wholesale and retail” link has significant impacts on the economic benefits of manufacturing industry. (3) The digital degree of the “procurement” link has no obvious influence on the economic benefits of manufacturing industry.

The research results can provide reference for the formulation and implementation of micro policies. The strategy of improving the level of digital transformation of key links of manufacturing industry is put forward to better promote both the digital transformation of manufacturing industry and economic development.

This paper innovatively studies the relationship between digitalization of manufacturing process links and economic benefits. The findings can provide theoretical and empirical support for the digital transformation of China's manufacturing industry and high-quality development of economy.

Explore the impact of Party organization embedding on firm green governance.

The regression analysis method.

The findings show that Party organization embedding significantly enhances the green governance effects of firms, with this effect being more pronounced in environments with high-quality internal control. Moreover, the study reveals that Party organization embedding facilitates green governance through mechanisms such as reducing agency costs and optimizing management decisions. Agency costs have a negative transmission effect, while management decisions have a positive transmission effect, with the quality of internal control playing a crucial moderating role.

Most existing studies on firm green governance have focused on aspects such as the heterogeneity of management teams (Liu, 2019; Wu et al., 2019), executive green cognition (Fineman and Clarke, 1996; Huang and Wei, 2023), organizational structure and the involvement of controlling families (Bertrand and Schoar, 2006; Symeou et al., 2019), with limited attention to the unique role of Party organizations’ incentive and restraint mechanisms, supervisory power and management functions in firm green governance. Additionally, while scholars have examined the impact of political embedding in firms, including Party organization embedding as a specific form of political embedding, and find that it affects various aspects of business performance (Chang and Wong, 2004; Gu and Yang, 2023), governance quality (Li et al., 2020; Huang and Yang, 2024), agency costs (Qian, 2000; Wang and Ma, 2014), excessive management compensation (Chang and Wong, 2004; Chen et al., 2014), social externalities and audit needs (Faccio, 2006; Cheng, 2022), there is still insufficient discussion on how Party organization embedding promotes firm green governance. Particularly in the context of China’s unique system and using Chinese data, there is a need for more in-depth research on the impact of Party organization embedding on firm green governance. This paper addresses this research gap by empirical analysis.

Overall, this study has significant theoretical and practical implications. Theoretically, it enriches the literature on Party organization embedding and firm green governance, filling a gap in the intersection research of firm governance and green governance. Practically, on the one hand, this paper’s findings demonstrate that the involvement of Party organizations in firm governance plays a significant role in enhancing green governance. This supports the modernization of firm governance in China, establishes a micro-level foundation for achieving the strategic goals of “carbon peaking and carbon neutrality” and offers empirically-backed insights into green transformation for policymakers. The research also provides practical policy recommendations for strengthening Party building efforts within firms and optimizing government-business relations, thereby facilitating the deep integration of Party building with business operations. On the other hand, this study highlights that the unique feature of China’s corporate governance system, Party organization embedding, can effectively enhance green governance. This offers empirical support for leveraging the strengths of China’s firm governance model and provides valuable governance strategies for firms in other countries and regions to improve their green governance practices.

This study’s social implications are significant as it highlights the broader societal benefits that arise from integrating Party organization involvement into firm governance structures, especially within the context of green governance. By improving the green governance practices of firms, Party organization embedding helps to address pressing environmental issues such as pollution, carbon emissions and resource depletion, which ultimately contributes to healthier living environments and a more sustainable society. The emphasis on green governance supports China’s national strategy for sustainable development and demonstrates a governance model that balances economic growth with environmental stewardship. Additionally, the study underscores the role of Party organizations in fostering social responsibility, equity and cohesion by ensuring that firm decision-making aligns with both economic and social welfare goals. This model of governance provides a framework that can serve as a reference for other countries and regions looking to enhance environmental protection efforts while maintaining social stability and economic progress.

This study offers original insights by exploring the distinctive role of Party organization embedding in enhancing firm green governance within the unique context of China’s political and economic systems. Unlike previous research, which has primarily focused on conventional governance structures, this paper delves into the underexplored area of how Party organizations influence firm-level green governance. By examining the direct and indirect effects of Party organization embedding, this study expands current understanding of corporate governance models that integrate political structures, providing a novel perspective on how firms can achieve both economic and environmental objectives. The findings not only contribute to the literature on green governance but also present a valuable model for emerging economies that are pursuing sustainable development. This research thus provides a meaningful addition to the dialogue on corporate governance innovation and environmental responsibility.

There is a pressing need for research on the difference in entrepreneurial performance influenced by the integration of migrant workers’ psychological capital and entrepreneurial opportunity identification. In addition, there is limited research on the association of entrepreneurial performance with different dimensions of psychological capital and how these dimensions affect the entrepreneurial performance of migrant workers. This research will partially address this gap in knowledge by assessing the influence of psychological capital and entrepreneurial opportunity identification on the entrepreneurial performance of migrant workers in China.

This paper conducts a theoretical analysis of psychological capital, entrepreneurial opportunity identification and entrepreneurial performance and proposes a theoretical model of entrepreneurial opportunity identification acting as the intermediary role between psychological capital and the entrepreneurial performance of migrant workers. Based on the data collected from 899 rural households in Shaanxi Province, a structural equation model and a bootstrap method are used to verify the association between psychological capital, entrepreneurial opportunity identification and entrepreneurial performance.

Both entrepreneurial opportunity identification and psychological capital are conducive to the improvement of entrepreneurial performance. However, the entrepreneurial opportunity identification is found to exert a more significant impact on the entrepreneurial performance of migrant workers than psychological capital does. Findings have also revealed that the intermediary role of entrepreneurial opportunity identification is more prominent in the relationship between adventure and innovation and the entrepreneurial performance of migrant workers than that of self-confidence and optimism and entrepreneurial performance of migrant workers.

Based on the results of empirical analysis, the paper proposes corresponding policy recommendations for guiding migrant workers to capitalize on their psychological capital, identify entrepreneurial opportunities, weigh up entrepreneurial risks and ultimately improve their entrepreneurial performance.

This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies.

This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.

Corporate social responsibility (CSR) provides a means to strengthen a firm's competitive position. Companies are able to achieve this through imitating the CSR activities of close rivals within their industry. Visibility of the competitive interconnection between focal and peer firm and resource ability are factors that determine the validity of this approach.

The briefing saves busy executives, strategists and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

Megaproject supply chains involve multiple layers of stakeholders, leading to complex relationships and risks. The role of social interactions within these networks is unexplored. Therefore, an analysis of construction supply chain risk management from the perspective of social networks is essential to identify related stakeholders, their relationships and the social network risk factors.

About 65 risk factors, identified from literature and interviews, informed the development of a questionnaire for the study. Online questionnaires administered in Ghana and South Africa produced 120 valid responses. Feedback from the responses was ranked and assessed to determine the overall social network risk levels using the Normalised Mean and Fuzzy synthesis analysis methods.

About 24 risk factors were identified and classified into six groups: Client/Consultant-related, Community-related, Government-related, Industry Perception-related, Supplier-related and Stakeholder Opportunism. The top five social network risks identified include bribery, supplier monopoly, incomplete design teams, poor communication and lack of collaboration.

The study provides detailed evaluations of social network risks in Africa, and the findings will help in developing strategies to mitigate supply chain disruptions caused by these challenges.

This study contributes to the literature on supply chain risk management by offering context-specific insights into the social network perspective of megaprojects in Africa, which differs from those in developed countries.