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Based on the moral licensing theory, this study aims to reveal the mechanism of self-sacrificial leadership inducing abusive supervision from two paths of leader moral credit and leader moral credential. At the same time, it also discusses the moderating effect of leader behavioral integrity on the two paths.

In this study, 434 employees and their direct leaders from six Chinese companies were investigated in a paired survey at three time points, and the empirical data was analyzed using Mplus 7.4 software.

Self-sacrificial leadership has a positive effect on leader abusive supervision through the mediating role of leader moral credit and leader moral credential. In addition, this study also finds that leader behavioral integrity is the “gate” for self-sacrificial leadership to promote abusive supervision, and the leader behavioral integrity has a moderating effect on the process of self-sacrificial leadership influencing on leader moral credit and leader moral credential.

This study explores the evolution of self-sacrificial leadership from “good” to “bad” from the perspective of moral licensing and broadens the research on the mechanism and boundary conditions of self-sacrificial leadership. At the same time, it also provides important reference value for preventing the negative effects of self-sacrificial leadership in organizations.

This study aims to enhance the effectiveness of knowledge markets and overall knowledge management (KM) practices within organisations. By addressing the challenge of internal knowledge stickiness, it seeks to demonstrate how machine learning and AI approaches, specifically a text-based AI method for personality assessment and regression trees for behavioural analysis, can automate and personalise knowledge market incentivisation mechanisms.

The research employs a novel approach by integrating machine learning methodologies to overcome the limitations of traditional statistical methods. A natural language processing (NLP)-based AI tool is used to assess employees’ personalities, and regression tree analysis is applied to predict and categorise behavioural patterns in knowledge-sharing contexts. This approach is designed to capture the complex interplay between individual personality traits and environmental factors, which traditional methods often fail to adequately address.

Cognitive style was confirmed as a key predictor of knowledge-sharing, with extrinsic motivators outweighing intrinsic ones in market-based platforms. These findings underscore the significance of diverse combinations of environmental and individual factors in promoting knowledge sharing, offering key insights that can inform the automatic design of personalised interventions for community managers of such platforms.

This research stands out as it is the first to empirically explore the interaction between the individual and the environment in shaping actual knowledge-sharing behaviours, using advanced methodologies. The increased automation in the process extends the practical contribution of this study, enabling a more efficient, automated assessment process, and thus making critical theoretical and practical advancements in understanding and enhancing knowledge-sharing behaviours.

The chapter explored integrating smart construction techniques in achieving stealth construction objectives, emphasising the development of building cross-sections, visibility management, energy transmission optimisation, and countermeasure implementation. It delved into the multifaceted aspects of smart construction towards achieving stealth construction goals, including environmental protection, enhanced construction safety, accelerated construction duration, cost-effectiveness, and aesthetic considerations. Furthermore, the chapter underscores the importance of leveraging innovative approaches and advanced technologies to meet the evolving demands of stealth construction projects and pave the way for sustainable, safe, and aesthetically pleasing built environments.

This chapter explored health and safety considerations in stealth construction, emphasising the integration of advanced technologies and innovative practices. It commences with a general introduction, followed by a historical overview of safety practices in the construction industry, highlighting the evolution of a safety culture. The chapter examined various health and safety management techniques, including policy formulation, safety training programs, and job safety analysis. Additionally, it discussed current trends such as wearable technology, IoT, VR/AR, and predictive analytics. The unique requirements of stealth construction are addressed, focusing on building cross-section design, visibility, application of radio frequency emission and countermeasures. Finally, it presents a comprehensive approach to achieving stealth construction, emphasising environmental protection, safety, speed, economy, and aesthetics, and provides practical examples to illustrate these concepts.

Drawing upon socio-technical system theory, this study intends to investigate the effects of the congruence and incongruence between artificial intelligence (AI) and explorative learning on supply chain resilience as well as the moderating role of organizational inertia.

Using survey data collected from 170 Chinese manufacturing firms, we performed polynomial regression and response surface analyses to test our hypotheses.

We find that the congruence between AI and explorative learning enhances firms’ supply chain resilience, while the incongruence between these two factors impairs their supply chain resilience. In addition, compared with low–low congruence, high–high congruence between AI and explorative learning improves supply chain resilience to a greater extent. Moreover, organizational inertia attenuates the positive influence of the congruence between AI and explorative learning on supply chain resilience, while it aggravates the negative influence of the incongruence between these two factors on supply chain resilience.

Our study expands the literature on supply chain resilience by demonstrating that the congruence between a firm’s AI (i.e. technical aspect) and explorative learning (i.e. social aspect) boosts its supply chain resilience. More importantly, our study sheds new light on the role of organizational inertia in moderating the congruent effect of AI and explorative learning, thereby extending the boundary condition for socio-technical system theory in the supply chain resilience literature.

This exploratory, descriptive study examines the factors that might influence the success or failure of online peer production communities during their inception stage. It focuses on community-building activities, the roles of users and the dynamics of user interaction, aiming to shed light on practices that could contribute to a community's success at the inception stage.

By comparing two Stack Exchange Q&A communities with the same timelines but opposite outcomes during their beta testing phases, the research utilizes quantitative methods to categorize community activities, define user roles via k-means cluster analysis and examine interaction networks using social network analysis.

Our findings suggest the successful Mathematics Q&A community exhibited several distinct practices during its inception, such as the utilization of both external and internal tools, the development of community-specific tutorials and the strategic use of flagging functions for moderation. Eight user roles were discerned, with roles like content editors, metadata curators and gatekeepers being particularly prominent in the successful community. Additionally, a more densely interconnected user network characterized by active participation was observed in the successful community.

Concentrating on the inception stage of online communities, this study uncovers insights into the dynamics at play in the early life of peer production environments and provides empirical observations that may assist in shaping strategies for new online communities. It stands out by comparing communities within the same period to understand factors that may influence their early success.

By exploring the impact of digital knowledge resources (DKR) on the carbon emission intensity of the pig industry (PCEI), this study aims to reveal the role of DKR in reducing PCEI.

Based on provincial panel data in China from 2011 to 2021, this study uses the entropy and Intergovernmental Panel on Climate Change coefficient methods to calculate the evaluation index system of DKR and PCEI, respectively. Empirical analysis using a panel fixed-effects model examines the influence of DKR on PCEI and its underlying mechanisms.

DKR can significantly reduce PCEI. This conclusion still holds even after undergoing endogeneity treatment and a series of robustness tests. Mechanism test results indicate that DKR can operate indirectly through the mediation mechanism of rural human capital (RHC) and pig breeding technology innovation (PTI), while environmental regulation intensity (ERI) plays a positive moderating role in the relationship between DKR and PCEI. The magnitude of the impact of DKR on PCEI depends on ERI. Further studies found that the impact of DKR on PCEI has obvious heterogeneity characteristics, and the promotion effect is more obvious in regions with good integration degrees and high development potential.

This paper divides DKR into three dimensions: digital technology knowledge (DTK), digital management knowledge (DMK) and digital application knowledge (DAK), providing a new framework for research and enriching the understanding of the relationship between DKR and PCEI. Furthermore, the research results reveal the application potential of DKR in the pig industry, particularly in terms of resource allocation efficiency. This is of great significance for promoting low-carbon development in the pig industry and provides insights for the low-carbon transformation of other industries. In addition, the study emphasizes the moderating effect of ERI on the mechanism of carbon reduction in the pig industry through DKR. This offers a new perspective for understanding the relationship between knowledge management and environmental governance, providing a reference basis for policy formulation in related fields.

This paper further enriches the role of DKR in the livestock industry. Integrating DKR with traditional industries promotes knowledge innovation, information distribution and utilization and scientific decision-making. This has significant value in promoting the development and application of carbon reduction technologies, enhancing industrial competitive advantages, and other aspects.

Based on the theoretical background of stakeholder capitalism, the purpose of this paper is to contribute to the scientific debate on the topic of public–private partnerships (PPPs), considering in particular how this governance structure relates to the pursuit of sustainable development. Specifically, this objective will be pursued with a focus on stakeholder relations and governance aspects, to highlight enablers and barriers in change for sustainability.

The systematic literature review is applied starting with the use of keywords in Web of Science, which leads to the extrapolation of 629 articles on the topic of “PPP and sustainability”. Subsequently, through various skimming steps, 75 papers are sampled. A mixed (quantitative-qualitative) approach is then followed: a co-word semantic network to identify the pattern of discourse and a more in-depth and explanatory analysis of the papers. These quantitative and qualitative tools synergistically work together to evidence the main aspects related to the aim of the paper.

With reference to the governance structure and stakeholders of PPPs, the analyses highlight the shift towards a triadic type of relational governance that considers stakeholders (especially the community) in addition to public–private partners. This can improve the partnership's performance (particularly in sustainable development) and social legitimacy. With reference to the role of PPPs in the implementation of sustainable development, they have positive potential in terms of implementing sustainability and raising stakeholder awareness of it. Nevertheless, PPPs may entail risks to the implementation of sustainability. The findings lead to some concluding remarks on future research opportunities.

The research leads to some managerial implications, such as the need to follow a competitive collaboration approach among stakeholders, to develop relational governance skills and related managerial tools and to incorporate sustainability aspects starting from the design of PPPs.

The originality aspect of this research is the consideration of a PPP by relating it to the pursuit of sustainability. Such an inter-organizational structure could be suitable to deal with the complexity inherent in the implementation of sustainability and is peculiar in terms of governance and stakeholder relations, considering that it is characterised by the presence of several partners of different nature (public and private).

The purpose of this study is to investigate the impact of corporate social responsibility (CSR) on innovation performance and examine the moderating role of social media strategic capability and big data analytics capability. Specifically, the authors explore the effects of both external and internal CSR on innovation performance.

The authors collected data from 221 senior, middle and research and development (R&D) managers of high-tech firms in China, using a questionnaire survey with a six-month interval.

The empirical results show that both external and internal CSR positively influence innovation performance. Furthermore, social media strategic capability has a positive moderating effect on the relationship between CSR and innovation performance, while big data analytics capability moderates the relationship between external CSR and innovation performance.

The data comes from high-tech firms in China, which may limit the generalizability and external validity of the findings. Future studies should replicate this study in other industries and types of organizations.

The study suggests that high-tech firms should engage in both external and internal CSR activities to promote innovation performance. Moreover, leveraging social media strategic capability and big data analytics capability can enhance innovation performance.

This study contributes to the literature on CSR outcomes by empirically exploring the effects of external and internal CSR on innovation performance, thus extending stakeholder theory. Additionally, by revealing the contingency effects of social media strategic capability and big data analytics capability, this study enriching the research on dynamic capabilities theory in the context of digital transformation.

This study examines the vital factors that influence digital marketing adoption among small travel agencies (brick-and-mortar) and the impact of digital marketing adoption on organizational performance modeled as a formative-formative HOC.

This empirical study builds on diffusion of innovation (DOI) theory and technology-organization-environment (TOE) framework to identify the factors of digital marketing adoption by small travel agencies. Data were collected from 226 small travel agents in India using purposive and snowball sampling. Partial least square-structural equation modelling (PLS-SEM) is used to analyze the reflectively and formatively measured constructs.

The findings reveal significant constructs of digital marketing adoption by small travel agencies. The study also establishes the positive impact of digital marketing adoption on organizational performance. Trust partially mediates the impact of technological factors (relative advantage, security concerns) and organizational factor (knowledge) on digital marketing adoption.

The study provides methodological contribution to the literature by applying confirmatory composite analysis (CCA) approach in PLS-SEM. The study contributes to the literature by integrating DOI theory and TOE framework. The study enriches the literature on trust as it recognizes the crucial role of trust as a mediating construct.

The study provides useful implications to marketing practitioners of small travel agencies. The study shows strong predictive capacity and can be generalized throughout diverse samples.

The study adds value to the literature as it explores the digital marketing adoption among the under researched small travel agencies by integrating DOI-TOE theory. The study uniquely proposes and validates organizational performance as a formative-formative higher-order construct.