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<metadata xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:dc="http://purl.org/dc/elements/1.1/"><dc:title>Meta analysis of business valuation solutions –are AI based methods better?</dc:title><dc:creator>Herman,	Aljaž	(Avtor)
	</dc:creator><dc:creator>Mumel,	Damijan	(Avtor)
	</dc:creator><dc:creator>Jagrič,	Timotej	(Avtor)
	</dc:creator><dc:subject>business valuation</dc:subject><dc:subject>traditional and advanced valuation methods</dc:subject><dc:subject>machine learning</dc:subject><dc:subject>neural networks</dc:subject><dc:subject>artificial intelligence</dc:subject><dc:description>Purpose of the article–this article addresses the challenge of accurately assessing business value in today's dynamic environment, exploring  the  limitations  of  traditional  valuation  methods  and  the potential of modern, technology-driven approaches.Research methodology–the study uses qualitative research methods, including  content  analysis,  deductive  reasoning,  and  comparative analysis, to review various business valuation techniques.Findings –the research finds that traditional methods like Discounted Cash Flow and Relative Valuation are outdated, failing to capture all value factors. Modern approaches, such as simulation-based valuation, machine learning, and neural networks, combine traditional methods with advanced techniques. These methodologies utilize vast datasets and  sophisticated  algorithms,  enhancing  predictive  accuracy  and understanding of market dynamics. Neural networks excel in analysing complex  patterns  and  adapting  to market  shifts.  However,  no  single method can capture all nuances, necessitating diverse approaches and acknowledging the subjective nature of valuations</dc:description><dc:publisher>Doba Epis</dc:publisher><dc:date>2024</dc:date><dc:date>2025-04-09 03:06:52</dc:date><dc:type>Znanstveno delo</dc:type><dc:identifier>92440</dc:identifier><dc:identifier>UDK: 004.8</dc:identifier><dc:identifier>COBISS_ID: 219901955</dc:identifier><dc:identifier>DOI: 10.32015/JIBM.2024.16.2.6</dc:identifier><dc:identifier>ISSN pri članku: 1855-6175</dc:identifier><dc:language>sl</dc:language></metadata>
