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The purpose of the research is to examine the impact of leader humor on employee job crafting. Using the insights from self-determination theory (SDT), we investigate the underlying mechanism of employees’ flow at work and the moderating role of employees’ playfulness trait.

We adopted a three-wave field survey of 306 employees recruited from various industries. The moderated mediation model was examined using latent structural equation model analysis.

Results revealed that leader humor positively affected employees’ flow at work and subsequent job crafting. Moreover, both the direct effect of leader humor on employees’ flow at work and the indirect effect of leader humor on employees’ job crafting via flow at work were amplified by employees’ playfulness trait.

Leaders are encouraged to use jokes and humorous language to facilitate job crafting among playful subordinates. Organizations can create a work environment conducive to flow at work through job redesign, regardless of employees’ levels of playfulness trait.

The paper uncovers the critical role of flow in the relationship between leader humor and employee job crafting and identifies employees’ playfulness trait as a boundary condition in which leader humor works.

The purpose of this paper is to examine the effect of employees' self-efficacy on employees' organizational identification. Based on a self-verification perspective, this paper focuses on the mediating role of leader–member exchange social comparison (LMXSC) and the moderating role of perceived organizational justice.

The authors conducted a field survey (Study 1) of 207 employees recruited from multiple financial organizations and tested a moderated mediation model using Hayes's (2018) PROCESS macro. The authors conducted another scenario-based experiment (Study 2) using a sample of 151 employees recruited online to further establish causality in our model.

Results suggest that employees' self-efficacy is positively associated with their LMXSC, which, in turn, positively impacts employees' organizational identification. The positive relationship between LMXSC and organizational identification is stronger when employees' perceived organizational justice is higher. The indirect effect of self-efficacy on organizational identification through LMXSC is also strengthened by perceived organizational justice.

Managers are encouraged to develop employees' self-efficacy and to create a fair environment to promote employees' identification with the organization.

This research extends organizational identification literature by examining how and when employees' self-efficacy, a dispositional predictor, leads to employees' identification with the organization from a self-verification perspective.

Prior studies have mainly attributed customer incivility to dispositional characteristics, whereas little attention has been paid to exploring service employees' role in triggering or reducing customer incivility. The purpose of the present study is to propose and test a model in which service employees' emotional labor strategies affect customer incivility via influencing customers' self-esteem threat, as well as examine the moderating role of customer's perception of service climate.

Based on a matched sample consisting of 317 employee-customer dyads in China, multiple regression analysis and indirect effect tests were employed to test our model.

The study shows that employee surface acting is positively related to customer incivility, whereas deep acting is negatively associated with customer incivility. Moreover, customer self-esteem threat mediates the relationship between both types of emotional labor and customer incivility. Customer perception of service climate moderates the relationship between deep acting and customer self-esteem threat.

The current research broadens the antecedents of customer incivility from the employee perspective and sheds more light on the role of customer self-esteem in the interactions between employees and customers. It also demonstrates a complementary relationship between service climate and individual employees' emotional labor strategies, thereby expanding the existing understanding of the management of employees' emotional labor.

Nurses' work engagement is critical for the service quality of the hospital. Thus, investigation on the influencing factors of nurses' work engagement has become an important issue. This study addresses this issue by exploring the effect of daily family-to-work conflict (FWC) on next-day work engagement among Chinese nurses.

The theoretical model was tested using 555 experience sampling data from 61 nurses collected for 10 workdays in China.

Nurses' daily FWC is associated with their next-day ego depletion. Moreover, increased ego depletion ultimately reduces their next-day work engagement. In addition, a between-individual factor of frequency of perceived patient gratitude mitigates the effect of FWC on ego depletion and the indirect effect on work engagement via ego depletion.

This study is important to the management of health-care organizations as it carries significant implications for theory and practice toward understanding the influence of FWC among nurses. On the one hand, the authors apply the job demands-resources (JD-R) model as the overarching theoretical framework, which contributes to the authors’ understanding of how FWC impairs work engagement. On the other hand, the authors extend extant theoretical models of FWC by identifying the frequency of perceived patient gratitude as an important contextual factor that counteracts the negative effects of FWC among nurses. Moreover, organizations could encourage patients to express their gratitude to nurses by providing more channels, such as thank-you notes, to offer nurses some support for overcoming the destructive effect of FWC.

The purpose of this paper is to explore the structure of leader communication style in the context of organizational change. In doing so, the authors intend to shed more light on how leaders can effectively communicate change projects to their subordinates, which is viewed as the key to implementing change initiatives.

This paper builds an integrated conceptual model for understanding leader’s communication style and subordinates’ commitment to change. By analyzing subordinates’ different fears of change, the paper further proposes a multidimensional structure of leader communication style in the context of change. The authors then develop a scale to measure these different dimensions and test the relationship between the proposed communication style and subordinates’ affective commitment to change.

Leader communication style in the context of change is found to be composed of five dimensions: hope orientation, reality orientation, subordinate orientation, support orientation, and enforcement orientation. A cross-level field study of 31 teams and 194 members shows that hope orientation, subordinate orientation, and support orientation are positively associated with subordinates’ affective commitment to change.

This paper identifies a new structure of leader communication style that will lead to a richer understanding of how leaders communicate to their subordinates in the context of change. It also contributes to the leadership literature by implying effective ways of communicating change projects.

The purpose of this work is to construct a grey entropy comprehensive evaluation model to measure the regional green innovation vitality (GIV) of 31 provinces in China.

The traditional grey relational proximity and grey relational similarity degree are integrated into the novel comprehensive grey evaluation framework. The evaluation system of regional green innovation vitality is constructed from three dimensions: economic development vitality, innovative transformation power and environmental protection efficacy. The weights of each indicator are obtained by the entropy weight method. The GIV of 31 provinces in China is measured based on provincial panel data from 2016 to 2020. The ward clustering and K-nearest-neighbor (KNN) algorithms are utilized to explore the regional green innovation discrepancies and promotion paths.

The novel grey evaluation method exhibits stronger ability to capture intrinsic patterns compared with two separate traditional grey relational models. Green innovation vitality shows obvious regional discrepancies. The Matthew effect of China's regional GIV is obvious, showing a basic trend of strong in the eastern but weak in the western areas. The comprehensive innovation vitality of economically developed provinces exhibits steady increasing trend year by year, while the innovation vitality of less developed regions shows an overall steady state of no fluctuation.

The grey entropy comprehensive relational model in this study is applied for the measurement and evaluation of regional GIV, which improves the one-sidedness of traditional grey relational analysis on the proximity or similarity among sequences. In addition, a three-dimensional evaluation system of regional GIV is constructed, which provides the practical guidance for the research of regional development strategic planning as well as promotion paths.

A comprehensive grey entropy relational model based on traditional grey incidence analysis (GIA) in terms of proximity and similarity is proposed. The three-dimensional evaluation system of China's regional GIV is constructed, which provides a new research perspective for regional innovation evaluation and expands the application scope of grey system theory.

The purpose of this paper is to examine the impact of Chinese youth’s attention to and involvement with Chinese soccer and its professional league, the Chinese Super League (CSL), on their level of satisfaction.

A survey study was employed to test the hypotheses. Research participants (n=948) were students from five major universities that represented each of the five main geographic regions of China. Data were randomly assigned into two halves: one half for CFA (n=474) and the other half for structural equation modeling (SEM) (n=474). Mplus 7.0 was used to conduct both the CFA and SEM.

The findings of this study indicated an overall lack of attention to and involvement with Chinese soccer and CSL among Chinese youths. Discussions have been presented on the causes of the lack of youth passion for Chinese soccer and suggestions have been articulated to improve the effectiveness and efficiency of policy formulation, business operation and marketing strategy.

The present study built on the extant sport management literature, demonstrated the complexity of consumers’ cognition and conation in the professional soccer setting, and revealed counter-intuitive relationship between attitudinal traits and behavioral patterns, which in turn provided unique insights for Chinese professional soccer marketers, managers and administrators.

Given the regional heterogeneity of economic development, electricity consumption in various regions exhibits a discrepant growth pattern. The purpose of this study is to construct a grey system forecasting model with intelligent parameters for predicting provincial electricity consumption in China.

First, parameter optimization and structural expansion are simultaneously integrated into a unified grey system prediction framework, enhancing its adaptive capabilities. Second, by setting the minimum simulation percentage error as the optimization goal, the authors apply the particle swarm optimization (PSO) algorithm to search for the optimal grey generation order and background value coefficient. Third, to assess the performance across diverse power consumption systems, the authors use two electricity consumption cases and select eight other benchmark models to analyze the simulation and prediction errors. Further, the authors conduct simulations and trend predictions using data from all 31 provinces in China, analyzing and predicting the development trends in electricity consumption for each province from 2021 to 2026.

The study identifies significant heterogeneity in the development trends of electricity consumption systems among diverse provinces in China. The grey prediction model, optimized with multiple intelligent parameters, demonstrates superior adaptability and dynamic adjustment capabilities compared to traditional fixed-parameter models. Outperforming benchmark models across various evaluation indicators such as root mean square error (RMSE), average percentage error and Theil’s index, the new model establishes its robustness in predicting electricity system behavior.

Acknowledging the limitations of traditional grey prediction models in capturing diverse growth patterns under fixed-generation orders, single structures and unadjustable background values, this study proposes a fractional grey intelligent prediction model with multiple parameter optimization. By incorporating multiple parameter optimizations and structure expansion, it substantiates the model’s superiority in forecasting provincial electricity consumption.