Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Book Chapter Faculty Publications- Book Chapter Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Radhika, P.; kumar, Jyothi Title A name given to the resource Sustainable development and catalysts for inclusive start-up growth in corporate management: Using machine learning Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Navigating Strategic Partnerships for Sustainable Startup Growth;pp.303-333 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.4018/979-8-3693-4066-0.ch012" target="_blank" rel="noreferrer noopener">https://doi.org/10.4018/979-8-3693-4066-0.ch012</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105000211863?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105000211863?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Radhika P., Christ University, India; kumar J., Christ University, India Description An account of the resource This chapter explores the role of machine learning in enhancing corporate sustainability, governance, and performance, and its connection to social impacts. Incorporating machine learning algorithms into companies' processes can enhance resource utilization and reduce their environmental footprint. Combining machine learning algorithms can offer valuable insights into stakeholder engagement, such as customer preferences, employee satisfaction, and community expectations, enabling responsible decision-making and advancing social responsibility goals through responsible decision-making. In addition, machine learning in corporate governance has been used in monitoring compliance, detection of fraud, and enhancement of transparency. The technologies mentioned enhanced operations performance, fostered trust and accountability, and enhanced a firm's social image. The chapter presents case studies demonstrating how machine learning can foster socially responsible, sustainable, and performance-oriented businesses, emphasizing ethical considerations in data privacy. 2025, IGI Global Scientific Publishing. All rights reserved. Publisher An entity responsible for making the resource available IGI Global Relation A related resource ISBN: 979-836934067-7; 979-836934066-0; Language A language of the resource English Type The nature or genre of the resource Book chapter Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online