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      How Green Human Resource Management Can Promote Green Employee Behavior in China: A Technology Acceptance Model Perspective

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      Sustainability
      MDPI AG

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          Abstract

          Green human resource management (GHRM) in the environmental management of organizations has gradually become a key issue in academic circles, and its impact on employees’ green behavior has received increasing attention. However, few studies have explored its impact from the perspective of information delivery. Based on an analysis of the literature, this research discusses the influence route of five types of GHRM practices (employee life cycle, rewards, education and training, employee empowerment, and manager involvement) on employee green behavior in the workplace and the mediating effects of information needs based on the technology acceptance model. Using cross-sectional survey data from enterprises in the People’s Republic of China, the proposed theoretical model was tested and the results showed that employee life cycle, education and training, employee empowerment, and manager involvement all significantly affect the in-role and extra-role green behavior of employees positively, while rewards only significantly predict extra-role behaviors. Information need plays a mediating role on the influence route of the employee life cycle, education and training, and manager involvement on the green behavior of the employees in the workplace.

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          Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology

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            User Acceptance of Computer Technology: A Comparison of Two Theoretical Models

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              A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies

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                Author and article information

                Journal
                SUSTDE
                Sustainability
                Sustainability
                MDPI AG
                2071-1050
                October 2019
                September 29 2019
                : 11
                : 19
                : 5408
                Article
                10.3390/su11195408
                ff0fff22-bad8-4a18-8c8a-a610ffa5a927
                © 2019

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

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