Abstract
Big data analytics (BDA), as an important tool, is now available to
companies who are struggling with problems related to sustainability. However, there
are not many case studies of BDA in the academic literature, despite the fact that it has
the potential to increase the eco-efficiency of manufacturing. This study focuses
specifically on the manufacturing sector to investigate the impact of BDA on green
innovation (GI), competitive advantage (CA), and environmental performance (EP) in
the context of the manufacturing industry. Big data analytics, also known as BDA, is a
relatively new field that has emerged as a result of the growth of contemporary
computers and their various uses. The relatively new subjects of business data analytics
(BDA) and business analytics (BA) have piqued the attention of both working
professionals and academics.
The purpose of this article is to conduct an analysis of the influence that Big Data has
had on four important performance indicators: innovation, competitive advantage,
productivity growth, and support with decision-making. Big data may help
organizations obtain vital insights about their consumers, products, and operations,
despite the fact that it does come with a few negatives. Businesses are in a better
position to quickly implement new ideas, provide better service to customers, increase
efficiency, make decisions that are better informed, and ultimately outperform their
rivals when they have access to data insights. The expansion in both the amount and quality of the data that is now accessible has led to improvements in the capacities of
organizations as well as the opening of new doors leading to growth. Businesses are
renouncing established practices in favor of new, inventive, and innovative techniques
in order to redefine creativity, competitiveness, and productivity. It is vital, for the sake
of achieving sustainable objectives, to have an understanding of big data analytics as a
critical component of the road map for green innovation, competitive advantage, and
ecological performance.