2022
DOI: 10.1002/csr.2425
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Does duration of team governance decrease corporate carbon emission intensity

Abstract: The study explores the effects of duration of team governance (DTG) on carbon emission intensity of 608 U.S. listed corporations merged three official datasets of Carbon Disclosure Project (CDP), Compuatat and BoardEx over the period 2009-2018, using unbalanced panel data analysis. It bridges three theoretical approaches: group development theory (GDT), social identity theory (SIT) and resource dependence theory (RDT) and applies econometric analysis techniques to investigate corporate carbon emission intensit… Show more

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Cited by 2 publications
(2 citation statements)
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References 120 publications
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“…In this case, the machine might identify themes that could be explored through traditional approaches such as grounded theory and thematic analysis. Later in the analysis, researchers could use supervised machine learning (Miric, Jia & Huang, 2023) to assess the extent to which the human- Xia, Zhu and Cai's (2023) research would involve using identical datasets and analytical methods to reproduce the analysis of how team governance duration affects carbon emission intensity, specifically verifying the inverted U-shaped pattern identified. This reproducibility effort could extend to examining the moderating effects of team size and gender diversity and the mediating role of low-carbon innovation, thus reinforcing the study's conclusions and contributing to the knowledge of sustainable corporate practices.…”
Section: Constructive Reproducibility Studiesmentioning
confidence: 99%
See 1 more Smart Citation
“…In this case, the machine might identify themes that could be explored through traditional approaches such as grounded theory and thematic analysis. Later in the analysis, researchers could use supervised machine learning (Miric, Jia & Huang, 2023) to assess the extent to which the human- Xia, Zhu and Cai's (2023) research would involve using identical datasets and analytical methods to reproduce the analysis of how team governance duration affects carbon emission intensity, specifically verifying the inverted U-shaped pattern identified. This reproducibility effort could extend to examining the moderating effects of team size and gender diversity and the mediating role of low-carbon innovation, thus reinforcing the study's conclusions and contributing to the knowledge of sustainable corporate practices.…”
Section: Constructive Reproducibility Studiesmentioning
confidence: 99%
“…A study conducted by Xia, Zhu and Cai (2023) examined how team governance duration influences carbon emission intensity, integrating resource dependency theory, group development theory, and social identity theory using data from Compustat, BoardEx, and The Carbon Disclosure Project. To conduct a reproducibility study, researchers could utilize the same datasets and analytical methods to verify the results.…”
Section: Type Of Empirical Studymentioning
confidence: 99%