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The purpose of this study is to understand the leadership humour style and the mechanism through which leadership humour style transforms into follower’s workplace positive and negative outcomes such as thriving at work and burnout. It uses comprehensive elaboration theory and relational process theory to explore self-disclosure and perceived similarity as two new constructs to assess their relation to intrapsychic (self-enhancing and self-defeating) and interpersonal (affiliative and aggressive) leader’s humour style, respectively.

An exploratory qualitative study through semi-structured interviews was conducted with 10 leaders to understand the different aspects of leadership humour and their outcomes. Based on these dimensions, a questionnaire was created and sent to 200 respondents, and 158 responses were received. The empirical analysis of data was done by building structural equation modeling using smart partial least square.

The empirical study has shown that self-enhancing leadership humour is related to self-disclosure, and both affiliative and aggressive leadership humour styles are related to perceived similarity. When looking at the two critical outcomes of leadership humour, both perceived similarity and self-disclosure were related to social intimacy and thriving at work. The mediation effect showed that self-enhancing humour leads to self-disclosure which increases social intimacy leading to improving thriving at work and aggressive humour leads to norm violation which further leads to burnout.

The study has used the mixed methodology to understand leadership humour and its outcomes by conducting in-depth interviews with leaders and also provides empirical evidence related to leadership humour style by using the survey to collect data from the followers capturing their perceptions. And very critically, it has explored self-disclosure and perceived similarity as two new constructs to see their relation to leadership humour style and positive and negative outcomes at the workplace.

This study aims to investigate the predictive role of team personality composition in facilitating shared leadership through team member exchange (TMX), while also to examine the moderating effect of organizational culture.

The authors conducted a two-stage online survey and selected the customer service teams, claims teams and financial teams of 26 Chinese insurance companies as the research samples. The authors finally obtained validated questionnaires from 107 teams with 457 members. The hypothesized relationships were tested using SPSS 25.0 and Mplus.

The results indicate that both team relationship-oriented and task-oriented personality composition have significant positive effects on shared leadership with team-member exchange serving as a full mediator for both paths. As a boundary condition, organizational culture (i.e. including internal integration values and external adaptation values) has a moderating effect on the influence of TMX on shared leadership.

The study investigates the predictive role of team personality composition on shared leadership, which complements the empirical studies of shared leadership antecedents in the literature. Drawing on social exchange perspective, the authors find out that TMX serves as a mediator between team personality composition and shared leadership. The authors also identify the moderating effect of organizational culture on the emergence of shared leadership. The research emphasizes the contextual boundary condition in this process.

This paper aims to contribute to the literature on corporate and leadership responsibility by proposing a relational business model for shared responsibility.

First, a literature review on corporate and leadership responsibility is presented and discussed. This is followed by an overview of existing public and private regulations and future perspectives that enforce and/or foster corporate and leadership responsibility. Based on the concepts of relational economics, relational leadership and proactive regulation, the theoretical foundations of a relational business model are derived. In addition, a decision model for the empirical application of the relational business model in ethical dilemma situations is developed and presented.

Theoretical elaboration of a relational business model and an associated relational decision-making approach.

This study contributes to a new way of doing business in terms of shared responsibility. Furthermore, corporate responsibility and leadership responsibility are usually researched as two distinct fields, with the former referring to the meso level and the latter to the micro level. A relational approach, which views leadership as a relational phenomenon, contributes to bridging both concepts.

The purpose of this paper is to explore a new grey relational analysis model to measure the coupling relationship between the indicators for the water environment status assessment. Meanwhile, the model deals with the problem that the changing of indicator order may result in the changing of the degree of grey relation.

The binary index submatrix of the sample matrix is given first. Then the product of the matrix and its own transpose is used to measure the characteristics of the index and the coupling relationship between the indicators. Thirdly, the grey relational coefficient is defined based on the matrix norm, and a grey coupling relational analysis model is proposed.

The paper provides a novel grey relational analysis model based on the norm of matrix. The properties, normalization, symmetry, relational order invariance to the multiplicative, are studied. The paper also shows that the model performs very well on the water environment status assessment in the eight cities along the Yangtze River.

The model in this paper has supplemented and improved the grey relational analysis theory for panel data.

The model of pay-for-knowledge incentivizes individuals with financial rewards for sharing their expertise, facilitating a transactional exchange between knowledge providers (sellers) and seekers (buyers). While this model is effective in promoting paid contributions, its influence on free knowledge exchanges remains ambiguous, creating uncertainty about its overall impact on platform knowledge ecosystems. This study aims to explore the mechanim of how knowledge payment influences free knowledge contribution. Based on relational signaling theory, this study posits that a buyer’s payment for knowledge acts as a positive relational signal in the buyer–seller relationship and examines how the signaling effect varies across different social contexts through attribution theory.

This paper empirically tests the hypotheses by analyzing a data set comprising 630 instances from 359 unique knowledge sellers on Zhihu, a prominent knowledge-sharing platform in China. This paper use zero-inflated negative binomial models to conduct this analysis.

The findings reveal that when buyers pay for knowledge, this action positively influences sellers to contribute knowledge for free. However, the strength of this influence is moderated by the platform’s social functions: appreciation feedback tends to weaken this effect, while social network ties enhance it.

Prior research has predominantly focused on the financial incentives of pay-for-knowledge and its spillover effects on unpaid users’ activities. This study shifts the focus to the social dimensions of pay-for-knowledge, arguing that buyer-initiated knowledge payments signal buyers’ commitment to foster reciprocal relationships with sellers. It expands the literature on the relationship between knowledge payment and contribution, moving beyond financial incentives to include social factors, thus enriching our understanding of the interplay between paid and free knowledge activities. Additionally, the empirical evidence supports the efficacy of pay-for-knowledge in promoting both free and paid contributions within knowledge-sharing platforms.

While the theory and practice of open innovation networks are flourishing, green innovation in manufacturing small and medium-sized enterprises (SMEs) is stagnant. This study explores the mechanism driving green innovation in manufacturing SMEs under open innovation networks based on the role of innovation platforms' relational governance.

A quantitative study was conducted using questionnaires to collect data from 270 manufacturing SMEs in Zhejiang Province and employing a structural equation model to test the developed hypotheses.

The results revealed that innovation platforms' relational governance positively affects green innovation in manufacturing SMEs. Furthermore, the collaborative innovation atmosphere and risk perception mediate this relationship through a respective mediating role and a chain-mediating role.

This study is the first to empirically investigate the mechanism of the influence of innovation platforms' relational governance on green innovation in manufacturing SMEs, provide a new perspective for understanding the antecedents of green innovation under open innovation networks, and expand the theoretical research on open innovation management.

This study assesses how relational factors and buyer-supplier relationship commitment (BSRC) influence supply chain integration (SCI) and firm performance in Bangladesh's apparel manufacturing sector. Firm performance includes operational performance and innovation performance.

Grounded in the social exchange theory, a survey data-based structural equation modeling (SEM) approach is applied. Based on two experts and four executives' opinions and an in-depth literature review, 28 measurement items were identified in the close-ended questionnaire design. Further, 144 valid questionnaires from the manufacturer-supplier dyads in Bangladesh were collected and used for SEM analysis.

Our study reveals that relational factors positively influence BSRC. BSRC directly impacts SCI, operational, and innovation performance, whereas SCI is significantly related to operational and innovation performance. Besides, SCI mediates the two relationships: BSRC and operational performance; and BSRC and innovation performance.

Our results contribute to the literature and offer a new way to understand relationships that connect relational factors of BSRC, BSRC, and outcomes not only by examining the focal firm but also by examining its dyadic supplier partner separately. Separate assessment in the dyad displays some similar and dissimilar results. Moreover, we suggest practical implications for managers to enhance firm performance by focusing on the significance of linking relational factors, BSRC, and SCI.

This study aims to explore the interaction of “contractual governance – relational governance – governmental governance” mechanisms and proposes hypotheses about the effects of megaproject governance on governance performance from both theoretical and practical perspectives.

In this paper, a megaproject governance model is developed to explain the relationship between governance mechanisms and governance performance. The model is based on related literature and explores the interactions between governance mechanisms and how they work to improve governance performance. The structural equation model (SEM) is adopted to explore the influence path on governance performance for megaprojects.

The results indicate that: (a) The findings highlight the positive role of project governance mechanisms on governance performance. (b) Contractual governance, relational governance, and governmental governance directly affect governance performance. In addition, contractual governance mediates governance performance through relational governance and governmental governance; governmental governance mediates governance performance through contractual governance and relational governance. (c) Contractual governance, relational governance, and governmental governance play a positive role in governance performance.

Governmental governance is added to project governance theory and the empirical research method is used to explore the interaction between contractual governance, relational governance, and governmental governance of megaprojects. The SEM is used to systematically explore the paths of megaproject governance mechanisms on governance performance, considering the interactive role of the “contractual governance - relational governance - governmental governance” and the mediating role.

The study reveals the impact path of multidimensional megaproject governance mechanisms on governance performance. In this paper, the empirical findings can help the project participants by providing a decision-making basis for good governance and references for the governments to promote the construction of a micro-institutional environment for megaprojects.

The contributions of this study are (1) to add an exploration of governmental governance to the existing project governance theory, and (2) to consider the interactions of the “contractual governance – relational governance – governmental governance” mechanisms, and (3) to explore their effects on governance performance, including direct and mediating effects. This study contributes to a comprehensive understanding of megaproject governance by considering governmental governance and the interactions of the three governance mechanisms. Understanding the impact of megaproject governance on governance performance could assist project stakeholders and provide decision guidance for good governance.

This study investigates the influence of market and hierarchy organizational cultures on international project performance and examines the mediating role of relational capital.

In-depth interviews and a cross-sectional questionnaire survey were conducted to collect primary data within international projects. Hierarchical regression analysis was used to test the hypotheses based on data collected from 62 respondents.

The results reveal that both market and hierarchy cultures affect international project performance positively. Additionally, communication, cooperation and trust help enhance project performance; however, commitment is not. This study also proves the mediating role of relational capital between organizational culture and project performance.

This study selected only two types of organizational culture represented by Chinese construction enterprises. Future studies can explore the mediating role of relational capital between other varieties of organizational culture and project performance.

Given the high complexity and risks faced by projects abroad, both organizational culture, the internal environmental factor and relational capital being the external resource, are crucial for project success. This study clarifies the relationship between organizational culture, relational capital and project performance overseas. Empirical evidence to enhance international project performance for construction enterprises is provided. This study also makes contributions to international contractors who want to implement projects in developing countries.

The present study aimed to explore the consequences of perceived authenticity in artificial intelligence (AI) assistants and develop a serial-mediation architecture specifying causation of loyalty in human–AI relationships. It intended to assess the predictive power of the developed model based on a training-holdout sample procedure. It further attempted to map and examine the predictors of loyalty, strengthening such relationship.

Partial least squares structural equation modeling (PLS-SEM) based on bootstrapping technique was employed to examine the higher-order effects pertaining to human–AI relational intricacies. The sample size of the study comprised of 412 AI assistant users belonging to millennial generation. PLS-Predict algorithm was used to assess the predictive power of the model, while importance-performance analysis was executed to assess the effectiveness of the predictor variables on a two-dimensional map.

A positive relationship was found between “Perceived Authenticity” and “Loyalty,” which was serially mediated by “Perceived-Quality” and “Animacy” in human–AI relational context. The construct “Loyalty” remained a significant predictor of “Emotional-Attachment” and “Word-of-Mouth.” The model possessed high predictive power. Mapping analysis delivered contradictory result, indicating “authenticity” as the most significant predictor of “loyalty,” but the least effective on performance dimension.

The findings of the study may assist marketers to understand the relevance of AI authenticity and examine the critical behavioral consequences underlying customer retention and extension strategies.

The study is pioneer to introduce a hybrid AI authenticity model and establish its predictive power in explaining the transactional and communal view of human reciprocation in human–AI relationship. It exclusively provided relative assessment of the predictors of loyalty on a two-dimensional map.