<?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>0186-1042</journal-id>
<journal-title><![CDATA[Contaduría y administración]]></journal-title>
<abbrev-journal-title><![CDATA[Contad. Adm]]></abbrev-journal-title>
<issn>0186-1042</issn>
<publisher>
<publisher-name><![CDATA[Universidad Nacional Autónoma de México, Facultad de Contaduría y Administración]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0186-10422024000400105</article-id>
<article-id pub-id-type="doi">10.22201/fca.24488410e.2024.5053</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Predictores de permanencia en el empleo basados en el heurístico de anclaje y ajuste]]></article-title>
<article-title xml:lang="en"><![CDATA[Predictors of employment tenure based on the anchoring and adjustment heuristics]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Segura Mojica]]></surname>
<given-names><![CDATA[Francisco Javier]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Arana Bravo]]></surname>
<given-names><![CDATA[Mariana Karen]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Tecnológico Nacional de México  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>México</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Instituto Tecnológico de San Luis Potosí  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Mexico</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>12</month>
<year>2024</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>12</month>
<year>2024</year>
</pub-date>
<volume>69</volume>
<numero>4</numero>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S0186-10422024000400105&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S0186-10422024000400105&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S0186-10422024000400105&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen El objetivo de este trabajo es identificar variables que inciden sobre la propensión de los trabajadores industriales a dejar el empleo de manera prematura, y con base en lo anterior, diseñar un modelo predictivo para estimar las probabilidades de que un candidato permanezca la menos un año en el empleo. Se utiliza como marco de referencia el enfoque de los Factores Psicosociales; la Teoría de la Autodeterminación (Gagné y Deci, 2005); la Teoría de la Discrepancia (Locke, 1970); y la Economía Conductual (Kahneman y Tversky, 1979, 1984, 1996 y 2000). Se realizó una investigación de tipo cuantitativo, alcance correlacional y diseño transversal no experimental. Como instrumento de recolección de información se utilizó el cuestionario y como herramientas de análisis y modelado se usó estadística descriptiva, regresión logística y el algoritmo de aprendizaje no supervisado de K-Means. Se encontró que la probabilidad de rotar es una función de factores sociodemográficos y psicosociales, y que es posible caracterizar un perfil de estabilidad-rotación en el empleo. Las variables asociadas al heurístico de anclaje y ajuste ejercen influencia sobre la probabilidad de permanencia mínima de un año en un candidato a ocupar una vacante. Sin embargo, entre los factores sociodemográficos los predictores más relevantes son la edad y el número de empleos anteriores, mientras que, en lo referente al perfil psicosocial, los principales predictores son salario y prestaciones y relación con los superiores. La percepción de incertidumbre respecto al mercado de trabajo no ejerce una influencia relevante sobre la probabilidad de permanencia.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract The objective of this work is to identify variables that affect the propensity of industrial workers to leave employment prematurely, and based on the above, to design a predictive model to estimate the probabilities probability that a candidate will remain at least one year. It uses as a frame of reference the approach of Psychosocial Factors; the Theory of Self-Determination (Gagné and Deci, 2005); the Theory of Discrepancy (Locke, 1970); and the Behavioral Economy (Kahneman and Tversky, 1979, 1984, 1996 and 2000). We conducted quantitative research, correlative scope and nonexperimental cross-sectional design. The questionnaire was used as an information-gathering tool and descriptive statistics, logistic regression and the unsupervised learning algorithm of K-Means were used as analysis and modeling tools. It was found that the probability of rotating is a function of sociodemographic and psychosocial factors, and that it is possible to characterize a stability-rotation profile in employment. The variables associated with the anchoring and adjustment heuristic influence the probability of a minimum stay of one year in a candidate to fill a vacancy. However, among the socio-demographic factors, the most relevant predictors are age and the number of previous jobs, while, in terms of psychosocial profile, the main predictors are salary and benefits and relationship with superiors. The perception of uncertainty regarding the labour market does not have a significant influence on the probability of permanence.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[rotación de personal]]></kwd>
<kwd lng="es"><![CDATA[intención rotadora]]></kwd>
<kwd lng="es"><![CDATA[heurístico de anclaje y ajuste]]></kwd>
<kwd lng="es"><![CDATA[factores psicosociales]]></kwd>
<kwd lng="en"><![CDATA[staff turnover]]></kwd>
<kwd lng="en"><![CDATA[intention to rotate]]></kwd>
<kwd lng="en"><![CDATA[anchoring and adjustment heuristic]]></kwd>
<kwd lng="en"><![CDATA[psychosocial factors]]></kwd>
</kwd-group>
</article-meta>
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