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Cited by 180

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Value Congruence: A Study of Green Transformational Leadership and Employee Green Behavior

Open access
Wang, Xingdong, Zhou, Kong, Liu, Wenxing·2018·Frontiers in Psychology

Abstract

This study examined the extent to which the impact of green transformational leadership on employee green behavior through follower perceptions of value congruence. Path analyzing on data from 193 subordinate-leader dyads showed that followers' value congruence with their leader mediated the effects of green transformational leadership on employee green behavior. Results also supported that green identity moderated the indirect effect of green transformational leadership on employee green behavior through value congruence, such that the indirect effect was more positive when green identity was high than when it was low. These findings provided valuable contribution to green transformational leadership, value congruence, and employee green behavior by exploring the relationship between them. Practical implications and directions for future research are also discussed.

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Metadata

Authors
Wang, X., Zhou, K., & Liu, W.
Venue
Frontiers in Psychology
Published
2018-10-09
Volume
9
Pages
1946-1946
ISSN
1664-1078 (ISSN-L)
OpenAlex
W2897154407
Cited by
180
References
2
FWCI
17.70
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Value Congruence: A Study of Green Transformational Leadership and Employee Green Behavior. https://app.cochat.ai/papers/10.3389/fpsyg.2018.01946
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Wang, X., Zhou, K., & Liu, W. (2018). Value Congruence: A Study of Green Transformational Leadership and Employee Green Behavior. Frontiers in Psychology. https://doi.org/10.3389/fpsyg.2018.01946

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.