Improving Corporate Environmental Performance Through Big Data Analytics Implementation: The Role of Industry Environment

Big data analytics (BDA) has recently received significant public interest and is widely considered as a transformative technology set to improve organizations’ environmental performance. However, prior empirical studies have yielded inconsistent findings. Based on organizational learning theory, our paper utilized a longitudinal approach to understand the relationships between big data analytics implementation and corporate environmental performance. This project also investigates the role of industry environment in influencing on these relationships. This project employed longitudinal data from 172 firms covering 2408 firm-year observations from Fortune 200 firms. We employed “the generalized method of moments (GMMs) technique” to test the study assumptions. Our analysis shows that a one-unit improvement in BDA leads to, on average, a 2.8% improvement in corporate environmental performance (CEP). In addition, the impact of BDA on CEP is greater in more complex and dynamic settings. This project offers meaningful implications for scholars and managers to understand the influence of BDA on CEP across various settings. Moreover, this study provides a more refined comprehension of the performance ramifications of BDA, consequently addressing the essential enquiries of how and when BDA can improve environmental performance.

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Publication Details

Journal
Sustainability
Published
2025-03-26
DOI
https://doi.org/10.3390/su17072928
Citations
2
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
4.57
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article

Improving Corporate Environmental Performance Through Big Data Analytics Implementation: The Role of Industry Environment

Gomaa Agag, Ahmed Alyahya
2 citations
Sustainability
Big Data and Business Intelligence
4.57
article

Improving Corporate Environmental Performance Through Big Data Analytics Implementation: The Role of Industry Environment

Gomaa Agag, Ahmed Alyahya
article en
2 citations

Abstract

Big data analytics (BDA) has recently received significant public interest and is widely considered as a transformative technology set to improve organizations’ environmental performance. However, prior empirical studies have yielded inconsistent findings. Based on organizational learning theory, our paper utilized a longitudinal approach to understand the relationships between big data analytics implementation and corporate environmental performance. This project also investigates the role of industry environment in influencing on these relationships. This project employed longitudinal data from 172 firms covering 2408 firm-year observations from Fortune 200 firms. We employed “the generalized method of moments (GMMs) technique” to test the study assumptions. Our analysis shows that a one-unit improvement in BDA leads to, on average, a 2.8% improvement in corporate environmental performance (CEP). In addition, the impact of BDA on CEP is greater in more complex and dynamic settings. This project offers meaningful implications for scholars and managers to understand the influence of BDA on CEP across various settings. Moreover, this study provides a more refined comprehension of the performance ramifications of BDA, consequently addressing the essential enquiries of how and when BDA can improve environmental performance.

SustainabilityVol. 17(7)
King Faisal University (SA), Nottingham Trent University (GB)
Openalex Percentile: Top 7%
Big Data and Business Intelligence
4.57
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