Ítem
Acceso Abierto
Integrating machine learning into business and management in the age of artificial intelligence
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Autores
Ojeda-Sanchez, Carlos A.
Vega Pérez, Carlos Jesús
Batz Liñeiro, Aglaya, DCroz-Barón, David F.
Fecha
2025-12-01
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Editor
Nature Portafolio
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Resumen
Abstract
Machine learning, with its capacity to leverage computational techniques for experiential learning, has profoundly influenced various disciplines, including business and management. Despite its contributions to the progress of these fields and the advent of artificial intelligence presenting new challenges, there remains ambiguity regarding the specific areas of significant advancement and those with potential for further development. This study addresses three central questions: (1) How is the intellectual landscape of machine learning in business and management research organized and structured? (2) What are the primary applications of machine learning in business administration? And (3) What strategic considerations should companies adopt to effectively leverage machine learning in their business applications? By means of co-occurrence analysis of over 9399 peer-reviewed documents retrieved from Scopus discussing machine learning in business and management, we identified fifteen clusters within the literature. This classification serves as a starting point for firms looking to integrate ML into their routines across fifteen distinct topics. Although some firms have appropriated ML, the upsurge of artificial intelligence presents new challenges, including the digital divide, infrastructure and acquisition dilemmas, security concerns especially with outsourced services, and cost-effectiveness in algorithm selection and practical applications.
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Keywords
Machine learning , Computational techniques , Experiential learning , Business , Management , Artificial intelligence , Intellectual landscape , Research organization , Research structure , Primary applications , Business administration , Strategic considerations , Companies , Leverage , Business applications , Co-occurrence analysis , Peer-reviewed documents , Scopus , Literary clusters , Classification , Firms , Integrate ML , Routines , Digital divide , Infrastructure dilemmas , Acquisition dilemmas , Security concerns , Outsourced services , Cost-effectiveness , Algorithm selection , Practical applications
