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

Ahmed Alyahya and Gomaa Agag ()
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Ahmed Alyahya: Information Systems Department, College of Computer Science and Information Technology, King Faisal University, Al-Ahsa 31982, Saudi Arabia
Gomaa Agag: Nottingham Business School, Nottingham Trent University, Nottingham NG1 4FQ, UK

Sustainability, 2025, vol. 17, issue 7, 1-22

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.

Keywords: big data analytics; corporate environmental performance; dynamism; complexity; munificence; longitudinal examination (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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