S
Su Qin
Researcher at Chinese Ministry of Education
Publications - 6
Citations - 125
Su Qin is an academic researcher from Chinese Ministry of Education. The author has contributed to research in topics: Competitive advantage & Performance management. The author has an hindex of 2, co-authored 5 publications receiving 21 citations. Previous affiliations of Su Qin include Xi'an Jiaotong University.
Papers
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Journal ArticleDOI
Enhancing the FIRM’S green performance through green HRM: The moderating role of green innovation culture
Paul Kivinda Muisyo,Su Qin +1 more
TL;DR: Wang et al. as mentioned in this paper examined the effects of green human resource practices and green innovation culture on firm green performance and found that green innovation which includes green product innovation culture and green process innovation culture enhances the firm's green performance.
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The effect of green HRM practices on green competitive advantage of manufacturing firms
TL;DR: Wang et al. as mentioned in this paper investigated the effects of green human resource management (GHRM) and green innovation culture (GIC) on a manufacturing firm's green competitive advantage (GCA).
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Implications of GHRM on organisational citizenship behaviour: the mediating role of enablers of green culture
Paul Kivinda Muisyo,Su Qin,Thu Hau Ho,Mercy Muthoni Julius,Tsirinirinantenaina Barisoava Andriamandresy +4 more
TL;DR: In this paper, the authors examined how firms can build collective organisational citizenship behavior towards the environment (OCBE) from green human resource management (GHRM) practices, and found that GHRM practices that include developing green abilities, green motivation and green opportunities support the development of the EGC.
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Green HRM and employer branding: the role of collective affective commitment to environmental management change and environmental reputation
TL;DR: In this article, the authors develop a conceptual framework through which they examine the complex psychological mechanisms behind signaling and person-organization fit theories, and develop a novel conceptual framework for analyzing the signaling and P-O fit theories.