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Cited by 981

The DOI matches its Crossref record; 119 of the 119 references it cites were found in a registry or an index.

Employee Green Behavior: A Theoretical Framework, Multilevel Review, and Future Research Agenda

Open access
Norton, Thomas A., Parker, Stacey L., Zacher, Hannes, Ashkanasy, Neal M.·2015·Organization & Environment

Abstract

We propose a conceptual model based on person–environment interaction, job performance, and motivational theories to structure a multilevel review of the employee green behavior (EGB) literature and agenda for future research. We differentiate between required EGB prescribed by the organization and voluntary EGB performed at the employees’ discretion. The review investigates institutional-, organizational-, leader-, team-, and employee-level antecedents and outcomes of EGB and factors that mediate and moderate these relationships. We offer suggestions to facilitate the development of the field, and call for future research to adopt a multilevel perspective and to investigate the outcomes of EGB.

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Crossref · 10.1177/1086026615575773

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Metadata

Authors
Norton, T. A., Parker, S. L., Zacher, H., & Ashkanasy, N. M.
Venue
Organization & Environment
Published
2015-03
Volume
28
Issue
1
Pages
103-125
ISSN
  • 1086-0266 (ISSN-L)
  • 1552-7417
OpenAlex
W1978348294
Cited by
981
References
119
FWCI
64.05
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Employee Green Behavior: A Theoretical Framework, Multilevel Review, and Future Research Agenda. https://app.cochat.ai/papers/10.1177/1086026615575773
The paper
Norton, T. A., Parker, S. L., Zacher, H., & Ashkanasy, N. M. (2015). Employee Green Behavior: A Theoretical Framework, Multilevel Review, and Future Research Agenda. Organization & Environment. https://doi.org/10.1177/1086026615575773

Data sources

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.