<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>0012-7353</journal-id>
<journal-title><![CDATA[DYNA]]></journal-title>
<abbrev-journal-title><![CDATA[Dyna rev.fac.nac.minas]]></abbrev-journal-title>
<issn>0012-7353</issn>
<publisher>
<publisher-name><![CDATA[Universidad Nacional de Colombia]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0012-73532025000300016</article-id>
<article-id pub-id-type="doi">10.15446/dyna.v92n237.116880</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[Emerging trends in Retail analytics: a bibliometric analysis of the last decade]]></article-title>
<article-title xml:lang="es"><![CDATA[Tendencias emergentes en la analítica del Retail: un análisis bibliométrico de la última década]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Velásquez-Henao]]></surname>
<given-names><![CDATA[Juan David]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad Nacional de Colombia Facultad de Minas ]]></institution>
<addr-line><![CDATA[Medellín ]]></addr-line>
<country>Colombia</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>06</month>
<year>2025</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>06</month>
<year>2025</year>
</pub-date>
<volume>92</volume>
<numero>237</numero>
<fpage>16</fpage>
<lpage>29</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_arttext&amp;pid=S0012-73532025000300016&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_abstract&amp;pid=S0012-73532025000300016&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_pdf&amp;pid=S0012-73532025000300016&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract Retail analytics has become a transformative force, leveraging data-driven insights to optimize operations, personalize customer experiences, forecast demand, and enhance supply chain efficiency. This study provides a comprehensive bibliometric analysis of 563 documents indexed in Scopus, profiling the evolution of retail analytics over the past ten years. Key findings include 131 emerging topics clustered into 13 core trends. The analysis highlights the growing application of artificial intelligence, machine learning, and big data to drive decision-making, improve profitability, and enhance competitiveness in the retail industry. This paper addresses critical questions of "what," "where," "when," and "who" in retail analytics research, identifying areas of innovation and future growth, especially in predictive analytics, customer insights, and business operations optimization.]]></p></abstract>
<abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen La analítica del retail se ha convertido en una fuerza transformadora que aprovecha los conocimientos basados en datos para optimizar las operaciones, personalizar las experiencias de los clientes, pronosticar la demanda y mejorar la eficiencia de la cadena de suministro. Este estudio proporciona un análisis bibliométrico exhaustivo de 563 documentos indexados en Scopus, que perfilan la evolución de la analítica del comercio minorista en los últimos diez años. Los hallazgos clave incluyen 131 temas emergentes agrupados en 13 tendencias centrales. El análisis destaca la creciente aplicación de la inteligencia artificial, el aprendizaje automático y el big data para impulsar la toma de decisiones, mejorar la rentabilidad y mejorar la competitividad en la industria minorista. Este documento aborda preguntas críticas de "qué", "dónde", "cuándo" y "quién" en la investigación de la analítica del comercio minorista, identificando áreas de innovación y crecimiento futuro, especialmente en análisis predictivos, conocimientos del cliente y optimización de las operaciones comerciales.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[Retail analytics]]></kwd>
<kwd lng="en"><![CDATA[Artificial Intelligence]]></kwd>
<kwd lng="en"><![CDATA[machine learning]]></kwd>
<kwd lng="en"><![CDATA[research profile]]></kwd>
<kwd lng="en"><![CDATA[tech mining]]></kwd>
<kwd lng="en"><![CDATA[text analysis]]></kwd>
<kwd lng="es"><![CDATA[Retail analytics]]></kwd>
<kwd lng="es"><![CDATA[Inteligencia Artificial]]></kwd>
<kwd lng="es"><![CDATA[aprendizaje de máquinas]]></kwd>
<kwd lng="es"><![CDATA[perfil investigativo]]></kwd>
<kwd lng="es"><![CDATA[minería de tecnología]]></kwd>
<kwd lng="es"><![CDATA[análisis de texto]]></kwd>
</kwd-group>
</article-meta>
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