Data science in sustainable entrepreneurship: A multidisciplinary field of applications

Brij B. Gupta, Akshat Gaurav, Varsha Arya and Wadee Alhalabi

Technological Forecasting and Social Change, 2024, vol. 209, issue C

Abstract: Defined as the merging of social and environmental sustainability into corporate operations, sustainable entrepreneurship has embraced data science more and more to improve operational effectiveness and decision-making. Using statistics, machine learning, and computer science to uncover insights from challenging datasets, this interdisciplinary method blends the ideas of sustainability with sophisticated data analysis approaches. Our research supports the choice of this issue by stressing the urgent requirement of sophisticated analytical instruments to negotiate the complexity of sustainable business practices. We compare our proposed model against Logistic Regression, Feedforward Neural Networks, and Support Vector Machines (SVMs). This not only shows how better CNN models are for certain uses but also highlights the general possibilities of data science in promoting sustainability in business. Our results highlight the transforming ability of sophisticated machine learning methods in promoting informed, sustainable decision-making and supporting the more general conversation on sustainable business.

Keywords: Sustainable entrepreneurship; Data science; Big data; Research trends (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0040162524005961
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:209:y:2024:i:c:s0040162524005961

DOI: 10.1016/j.techfore.2024.123798

Access Statistics for this article

Technological Forecasting and Social Change is currently edited by Fred Phillips

More articles in Technological Forecasting and Social Change from Elsevier
Bibliographic data for series maintained by Catherine Liu ().