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© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

Although employee green creativity is recognized as the key to the innovation in green enterprises, few studies explores the measurement of green creativity for employees. To address the gap, the present study identifies the major dimensions of employee green creativity and develops a comprehensive, reliable, and valid measurement instrument. According to the 4P’s model of creativity, four core dimensions of employee green creativity are identified, namely, green creative motivation, thinking, behavior, and outcome. Strictly adhering to the process of scale development, employee green creativity scale (EGCS) is constructed and validated. We first develop the items of employee green creativity based on literature review and expertise from academics and practitioners. Next, we examine the validation of EGCS through exploratory and confirmatory factor analysis using a sample from three large-scale green enterprises (N = 460). Further, we also check the nomological validity of EGCS by testing the effects of determinants (e.g., green transformational leadership, shared vision, and green self-efficacy) on employee green creativity using a new sample from another two green enterprises (N = 169). Results reveal that EGCS is a reliable and valid instrument for capturing employee green creativity in multiple contexts. Theoretical and practical implications are discussed.

Details

Title
Measuring Green Creativity for Employees in Green Enterprises: Scale Development and Validation
Author
Jiang, Hui 1 ; Wang, Kaichao 2 ; Lu, Zhibin 2 ; Liu, Yifei 2 ; Wang, Yu 3 ; Li, Gang 4 

 School of Information Management and Artificial Intelligence, Zhejiang University of Finance and Economics, Hangzhou 310018, China; [email protected] (H.J.); [email protected] (K.W.); [email protected] (Z.L.); [email protected] (Y.L.); School of Management, Zhejiang University, Hangzhou 310058, China 
 School of Information Management and Artificial Intelligence, Zhejiang University of Finance and Economics, Hangzhou 310018, China; [email protected] (H.J.); [email protected] (K.W.); [email protected] (Z.L.); [email protected] (Y.L.) 
 Institute of Science and Technology for Development of Shandong, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250014, China; [email protected] 
 Shandong Computer Science Center (National Supercomputer Center in Jinan), Qilu University of Technology (Shandong Academy of Sciences), Jinan 250014, China 
First page
275
Publication year
2021
Publication date
2021
Publisher
MDPI AG
e-ISSN
20711050
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2524970673
Copyright
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.