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In the period of organizational change and transformation, the attitude of employees towards change has become a key factor in the success of organizational change. Based on the uncertainty management theory (UMT), the paper considers authentic leadership as an important antecedent of employee resistance to change and explores the mediating role of perceived uncertainty and the moderating role of uncertainty avoidance between authentic leadership and employee resistance to change.

The paper conducted a questionnaire survey study and a scenario experimental study. In study 1, the authors collected two stages of data from 256 employees in Central China, one month apart. In study 2, the authors designed a scenario experiment and invited 130 Chinese adults to participate.

The authors find that authentic leadership can effectively reduce employee resistance to change by reducing employee perceived uncertainty. In addition, for individuals with a higher (vs lower) degree of uncertainty avoidance, the direct impact of authentic leadership on perceived uncertainty and the indirect impact of authentic leadership on resistance to change through perceived uncertainty are both stronger (vs lower).

The presented results reveal the mechanism between authentic leadership and employee resistance to change from cognitive perspective and depict an important step toward understanding how authentic leadership and employee uncertainty avoidance interact and how they interact with employee resistance to change.

The purpose of this study is to investigate the phenomenon of knowledge transfer between employees and coworkers. That is, when and why employees engage in knowledge seeking or knowledge sabotage when confronted with coworkers with higher relative overqualification.

This study collected survey data from 315 employee-coworker pairs in East China at three-time points.

The results showed that when the cooperative goal interdependence between employee and coworker is high, the perception of coworker’s relative overqualification will cause benign envy of employees, which in turn promote employees to engage in knowledge seeking from coworker. However, when the competitive goal interdependence between employee and coworker is high, the perception of coworker’s relative overqualification will cause malicious envy of employees, which in turn promote employees to engage in knowledge sabotage toward coworker.

This research not only expands the theoretical perspective and outcomes of relative overqualification but also enriches the mechanism of knowledge seeking and knowledge sabotage. Meanwhile, this study also provides practical guidance for enterprises to reduce knowledge sabotage.

To overcome the limitations of traditional multi-attribute decision making (MADM) methods, which only provide deterministic rankings of decision objects, this paper proposes a novel multi-attribute 3WD model. This model presents three-parameter interval grey number decision-theoretic rough sets (TPIGNDTRSs), aiming to offer a reasoned interpretation of loss functions in grey environments and ensure objective assessment of conditional probabilities.

Firstly, the traditional equivalence relation is replaced with the probabilistic dominance relation (PDR), categorizing decision objects into two state sets in DTRS for more objective conditional probabilities. Secondly, as the three-parameter interval grey number (TPIGN) introduces the most probable value on the basis of the traditional two-parameter interval grey number, it provides a more comprehensive method for describing grey information. Consequently, integrating TPIGN into DTRS refines the interpretations of loss functions in grey environments. Finally, by utilizing two main sorting techniques, relative kernel and degree of accuracy ranking and possibility ranking, two types of 3WD rules with TPIGNDTRSs, are constructed.

This study has successfully developed and validated a new multi-attribute 3WD model. The model was tested in two distinct domains: evaluating innovation efficiency in high-tech enterprises and recommending movies in a practical case. The findings reveal that the model can effectively integrate relevant information of high-tech enterprises, provide the government with enterprise-level assessments, and gather consumer preferences to recommend the most suitable movies.

This study treats the loss function as grey information in the 3WD model but overlooks the grey nature of evaluation values, limiting its applicability. Additionally, the model’s reliance on subjective expert judgments and historical data to establish the loss function may affect its objectivity. The implications of this research are that the novel model overcomes traditional MADM limitations, enhancing decision-making quality and efficiency in complex and grey scenarios. The model’s successful application in evaluating high-tech enterprises and recommending movies illustrates its dual value in both theory and practice.

Initially, the model proposed in this study is of significant importance for the development of the 3WD field, as it successfully addresses the challenges of uncertain loss functions and unknown conditional probabilities in grey information environments. Moreover, by integrating the 3WD model with MADM problems, it has broken through the bottlenecks of traditional MADM methods, offering new perspectives and strategies for solving MADM issues. Therefore, this research not only advances theoretical research but also provides powerful tools for practical applications.

Aligning employees' goals with organizational goals is an overarching objective of an organization to increase employees' outcomes and, ultimately, the firm's performance. Employees' perceived goal congruence is proposed to be an important mediator of the effect of high-performance work systems (HPWS) on organizational citizenship behaviors (OCB). In this paper, the authors proposed and tested a moderated mediation model that depicted how servant leadership increased or restrained these effects.

This study used data from 56 managers and 322 employees working in Bangladeshi organizations. The study conducted cross-level analyses using hierarchical linear modeling (HLM) to examine the hypothetical relationships among variables.

This study revealed that employees' perceived goal congruence mediated the influence of HPWS on OCB. Consistent with the moderated mediation prediction, employee-perceived goal congruence mediated the relationship between HPWS and OCB when servant leadership is high.

This study examined how and when HPWS affects OCB by incorporating perceived goal congruence and servant leadership as mediating and moderating variables, respectively.

Fairness concerns in the supply chain management have recently caught much attention in the OM research community. The combined effect of fairness and competition on supply chain coordination and the interplay between them, however, have yet to be thoroughly examined.

The authors study a multiplayer supply chain with one supplier and two competing retailers with fairness concerns by a three-player Stackelberg game model. This theoretical study provides equilibrium solutions under different ranges of fairness and competition combinations. Besides theoretical analysis, the authors also conduct standard economic experiments and estimate structural parameters using experimental data.

The authors find that a simple wholesale price can coordinate the whole supply chain with certain conditions of fairness and competition. Moreover, although fairness concerns always decrease the wholesale price and increase retailers' profit share, downstream competition weakens such effects and decreases downstream players' market share. The experiments confirm the existence of fairness concerns and the interaction of competition and fairness, as shown in the theoretical analysis.

A more comprehensive model with both distributional and peer-induced fairness considered could generate better insights in the interactive impact of competition and fairness. Moreover, the authors followed the previous channel competition literature and modeled the demand with linear demand function which makes the game decisions trackable in closed form solution. A more general demand function could result in different solutions and thus new insights.

The authors’ work provides a comprehensive theoretical study of the interaction between fairness concerns and competition and clarifies the in-depth connection between the effects of competition and fairness concerns in the literature.

The traditional Chinese culture has always emphasized the authority of leaders and their “top-down” influence over subordinates tangled with “bottom-up” management. Paternalistic leadership can both nurture and restrict growth in mega-construction projects, due to the unique consequences (i.e. positive vs negative implications) for project teams. Hence, the present study aimed to explore the impact of paternalistic leadership (PL), team members’ voice (TMV) and team resilience (TR) on the mega-construction project success (MPS) in China's Belt and Road Initiative (BRI).

A surveyed-based sample of project professionals (N = 563) directly linked with the BRI was employed for statistical estimations with partial least squares (PLS) structural equation modeling (SEM).

Paternalistic leadership styles, including authoritarian leadership (AL), moral leadership (ML) and benevolent leadership (BL), significantly influence the mega-construction project success in BRI. The findings empirically validated that both BL and ML increase the likelihood of mega-construction project success. However, AL could impose a threat through its underlying negative influence. In addition, leaders with benevolence and morality have a positive influence on TMV and TR, while leaders with authoritarianism signal a negative impact. Furthermore, both TMV and TR significantly and positively mediate the relationships between AL-MPS (Model-1), BL-MPS (Model-2) and ML-MPS (Model-3), respectively.

The present study is a groundbreaking endeavor that fills a crucial research gap by investigating mega-construction project success in the BRI through paternalistic leadership, project team members' voice and team resilience in a multi-mediation model. These novel findings offer valuable strategic insights for managing mega-construction projects in countries with paternalistic solid cultural foundations, enabling project managers to navigate cultural nuances and optimize megaproject outcomes.

The pressing issues of climate change and environmental degradation call for a reevaluation of how we approach economic activities. Both leaders and corporations are now shifting their focus, toward adopting practices and embracing the concept of circular economy (CE). Within this context, the Food and Beverage (F&B) sector, which significantly contributes to greenhouse gas (GHG) emissions, holds the potential for undergoing transformations. This study aims to explore the role that Artificial Intelligence (AI) can play in facilitating the adoption of CE principles, within the F&B sector.

This research employs the Best Worst Method, a technique in multi-criteria decision-making. It focuses on identifying and ranking the challenges in implementing AI-driven CE in the F&B sector, with expert insights enhancing the ranking’s credibility and precision.

The study reveals and prioritizes barriers to AI-supported CE in the F&B sector and offers actionable insights. It also outlines strategies to overcome these barriers, providing a targeted roadmap for businesses seeking sustainable practices.

This research is socially significant as it supports the F&B industry’s shift to sustainable practices. It identifies key barriers and solutions, contributing to global climate change mitigation and sustainable development.

The research addresses a gap in literature at the intersection of AI and CE in the F&B sector. It introduces a system to rank challenges and strategies, offering distinct insights for academia and industry stakeholders.

The study focuses on drug safety regulation capture, reveals the inner mechanism and evolutionary characteristics of drug safety regulation capture and provides suggestions for effective regulation by pharmacovigilance.

The article introduces prospect theory into the game strategy analysis of drug safety events, constructs a benefit perception matrix based on psychological perception and analyzes the risk selection strategies and constraints on stable outcomes for both drug companies and drug regulatory authorities. Moreover, simulation was used to analyze the choice of results of different parameters on the game strategy.

The results found that the system does not have a stable equilibrium strategy under the role of cognitive psychology. The risk transfer coefficient, penalty cost, risk loss, regulatory benefit, regulatory success probability and risk discount coefficient directly acted in the direction of system evolution toward the system stable strategy. There is a critical effect on the behavioral strategies of drug manufacturers and drug supervisors, which exceeds a certain intensity before the behavioral strategies in repeated games tend to stabilize.

In this article, the authors constructed the perceived benefit matrix through the prospect value function to analyze the behavioral evolution game strategies of drug companies and FDA in the regulatory process, and to evaluate the evolution law of each factor.

This study aims to analyse how the adoption of Industry 4.0 technologies can help different types of agri-food supply chains introduce and manage innovations in response to the challenges and opportunities that emerged following the COVID-19 pandemic.

A systematic literature review methodology was used to bring together the most relevant contributions from different disciplines and provide comprehensive results on the use of I4.0 technologies in the agri-food industry.

Four technological clusters are identified, which group together the I4.0 technologies based on the applications in the agri-food industry, the objectives and the advantages provided. In addition, three types of agri-food supply chains have been identified and their configuration and dynamics have been studied. Finally, the I4.0 technologies most suited for each type of supply chain have been identified, and suggestions on how to effectively introduce and manage innovations at different levels of the supply chain are provided.

The study highlights how the effective adoption of I4.0 technologies in the agri-food industry depends on the characteristics of the supply chains. Technologies can be used for different purposes and managers should carefully consider the objectives to be achieved and the synergies between technologies and supply chain dynamics.