Abstract
Economic progress, over the last two decades, has largely been at the cost of the environment with inefficient and wasteful uses of natural resources. As a result, countries across the globe are now battling with climate change to save the earth from further environmental damage. For promoting sustainability, the present research aims to present a conceptual chapter by examining the application of machine learning on sustainability, as analyzed with the triple bottom-line method. Machine learning uses training data and algorithms and mimics human decision-making. Algorithms identify the relationships and associations between the available data to make decisions. In the context of sustainability, research has used machine learning to promote the three Ps that are dependent on the environment, namely, people, profit, and planet. This study summarizes prior research to offer a framework and identify research gaps for further investigation.
Original language | English |
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Title of host publication | Machine Learning for Business Analytics |
Subtitle of host publication | Real-Time Data Analysis for Decision-Making |
Publisher | Taylor and Francis Inc. |
Pages | 17-28 |
Number of pages | 12 |
ISBN (Electronic) | 9781000615425 |
ISBN (Print) | 9781032072814 |
DOIs | |
Publication status | Published - 01-01-2022 |
All Science Journal Classification (ASJC) codes
- Economics, Econometrics and Finance(all)
- Business, Management and Accounting(all)