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      A mediated–moderated model for green human resource management: An employee perspective

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      Frontiers in Environmental Science
      Frontiers Media SA

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          Abstract

          In general, all types and sizes of organizations are responsible for the degradation of the environment. However, manufacturing companies are considered one of the most significant sources of environmental pollution and are pressured to adopt practices to mitigate environmental degradation. Therefore, this research explores the direct and indirect effects of green human resource management (GHRM) on the Chinese manufacturing firm’s environmental performance. To this end, we share a closed-ended questionnaire via a web-based survey to collect data from 306 employees. Data analysis was performed using partial least square structural equation modeling techniques (i.e., PLS algorithm, bootstrapping, and blindfolding). Our research finds a positive and significant effect of GHRM on employee and firm environmental performance. In addition, this research evidenced a partial mediation of employee environmental performance. Moreover, our study evidenced that the effect of GHRM on employee environmental performance will be more substantial when there is more involvement of employees’ environmental orientation. This study suggests that manufacturing companies must incorporate GHRM practices, promote green behaviors, respect individual environmental values, and encourage employees to implement those practices for the betterment of firms and the natural environment.

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          Common method biases in behavioral research: A critical review of the literature and recommended remedies.

          Interest in the problem of method biases has a long history in the behavioral sciences. Despite this, a comprehensive summary of the potential sources of method biases and how to control for them does not exist. Therefore, the purpose of this article is to examine the extent to which method biases influence behavioral research results, identify potential sources of method biases, discuss the cognitive processes through which method biases influence responses to measures, evaluate the many different procedural and statistical techniques that can be used to control method biases, and provide recommendations for how to select appropriate procedural and statistical remedies for different types of research settings.
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            A new criterion for assessing discriminant validity in variance-based structural equation modeling

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              When to use and how to report the results of PLS-SEM

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                Author and article information

                Journal
                Frontiers in Environmental Science
                Front. Environ. Sci.
                Frontiers Media SA
                2296-665X
                September 6 2022
                September 6 2022
                : 10
                Article
                10.3389/fenvs.2022.973692
                dfe68119-11c9-4516-882e-dce5b755d41f
                © 2022

                Free to read

                https://creativecommons.org/licenses/by/4.0/

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