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The purpose of this study is to build a link between narcissistic supervision and employees' change-oriented organizational citizenship behaviors (OCBs). On the basis of the social dynamics of state paranoia theory, the study examines the relationship between narcissistic supervision and employees' change-oriented OCBs, and explores how this relationship is mediated by psychological safety and affective organizational commitment.

Using data collected from a sample of 183 employee–leader dyads from a technology company in China, the study examines the mediating effects of psychological safety and affective organizational commitment on the relationship between narcissistic supervision and employees' change-oriented OCBs. Structural equation modeling is used to analyze the data.

The results indicate that narcissistic supervision has a negative effect on psychological safety and affective organizational commitment; psychological safety mediates the relationship between narcissistic supervision and affective organizational commitment; and affective organizational commitment mediates the relationship between psychological safety and employees' change-oriented OCBs. The results also show that the negative effect of narcissistic supervision on employees' change-oriented OCBs is mediated by psychological safety and subsequently affective organizational commitment.

This study contributes to the literature by linking narcissistic supervision and employees' change-oriented OCBs and suggesting that psychological safety and affective organizational commitment are two critical mediators of this relationship. This study not only advances research on the “dark side” of narcissistic supervision, but also sheds light on the underlying mechanism of narcissistic supervision and employees' change-oriented OCBs from the psychological and emotional perspectives.

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.

For solving the dilemma between the cognitive cost and value of the uncertainty and negative feedback loop formed by them in the knowledge transfer process, the purpose of this paper is to attempt to construct a new web‐based knowledge flow model to find an alternative diffusion path which had become the inevitable choice in achieving Industry‐University collaboration.

In view of this, based on the statistical data compilation of the Universities of Science and Technology of China from 2002 to 2008, the visual diagrams, econometric model and grey incidence model were used to analyze the situation of the technology innovation and technology transformation on the combined learning with research in Jiangsu. Then, the conceptual model and the organization management pattern for network‐based Industry‐University‐Research collaboration was put forward.

The results are convincing: the new web‐based knowledge flow model in this paper could overcome barriers in the knowledge flow process of the Industry‐University collaboration with the innovation and the integration of the cross‐border and also promote the exchange of knowledge especially for tacit knowledge and value‐added mobile and can also improve the regional technological innovation ability and technology transformation capabilities.

The paper succeeds in constructing the web‐based knowledge flow model to develop the Industry‐University collaboration and help improve regional innovation and technology transformation.

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.