<?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>0121-5051</journal-id>
<journal-title><![CDATA[Innovar]]></journal-title>
<abbrev-journal-title><![CDATA[Innovar]]></abbrev-journal-title>
<issn>0121-5051</issn>
<publisher>
<publisher-name><![CDATA[Facultad de Ciencias Económicas. Universidad Nacional de Colombia.]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0121-50512024000300002</article-id>
<article-id pub-id-type="doi">10.15446/innovar.v34n93.100588</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Determinantes del éxito financiero en la industria cinematográfica mexicana como estrategia para la toma de decisiones y mitigación de riesgos]]></article-title>
<article-title xml:lang="en"><![CDATA[DETERMINANTS OF FINANCIAL SUCCESS IN THE MEXICAN FILM INDUSTRY AS A STRATEGY FOR DECISION-MAKING AND RISK MITIGATION]]></article-title>
<article-title xml:lang="pt"><![CDATA[DETERMINANTES DO SUCESSO FINANCEIRO NA INDÚSTRIA CINEMATOGRÁFICA MEXICANA COMO ESTRATÉGIA PARA TOMAR DECISÕES PARA REDUZIR RISCOS]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Gómez Meneses]]></surname>
<given-names><![CDATA[Fabio Enrique]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Torres Bravo]]></surname>
<given-names><![CDATA[Sara Isabel]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad de Monterrey  ]]></institution>
<addr-line><![CDATA[Monterrey ]]></addr-line>
<country>México</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Universidad de Monterrey  ]]></institution>
<addr-line><![CDATA[Monterrey ]]></addr-line>
<country>México</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>09</month>
<year>2024</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>09</month>
<year>2024</year>
</pub-date>
<volume>34</volume>
<numero>93</numero>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_arttext&amp;pid=S0121-50512024000300002&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_abstract&amp;pid=S0121-50512024000300002&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_pdf&amp;pid=S0121-50512024000300002&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen La incertidumbre financiera existente en la industria cinematográfica ha sido evidente en los últimos años, razón por la cual en el desarrollo de esta investigación se pretende determinar qué factores impactan o no en el éxito financiero de una película mexicana, como estrategia para la toma de decisiones y la mitigación de riesgos. Lo anterior se llevará a cabo mediante la realización de un análisis de correlación, la aplicación de una regresión múltiple lineal y la simulación de modelos predictivos en el software estadístico SPSS, lo que permitirá la creación de un modelo econométrico de regresión múltiple, obteniendo así una herramienta predictiva que pueda ser utilizada en la industria cinematográfica de México. Los resultados más relevantes evidencian que las variables con comportamientos más significativos son la cantidad de salas de cine donde es distribuida una película y el poder que tienen los críticos. La utilización del modelo de predicción creado contribuye significativamente a reducir el impacto de la incertidumbre financiera, generando confianza para todos los inversionistas de proyectos cinematográficos y aportando en la mejora de los ingresos que una película pueda obtener. La principal limitación del modelo es la ausencia de variables adicionales que lo complementarían y mejorarían como, por ejemplo, la cantidad de semanas de distribución y la inversión en publicidad.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract The financial uncertainty prevalent in the film industry has been evident in recent years. Therefore, the aim of this research is to determine which factors impact the financial success of a Mexican film, serving as a strategy for decision-making and risk mitigation. This will be achieved through correlation analysis, the application of multiple linear regression, and predictive model simulation using the statistical software SPSS. These methods will facilitate the creation of an econometric multiple regression model, providing a predictive tool that can be applied in the Mexican film industry. Our main findings indicate that the variables with the most significant behaviors are the number of movie theaters where a film is distributed and the influence of film critics. The use of the prediction model significantly contributes to reducing the impact of financial uncertainty, instilling confidence among film project investors and enhancing a film's revenue potential. The primary limitation of the proposed model is the absence of additional variables that could complement and improve it, such as the number of weeks for distribution and the investment in advertising.]]></p></abstract>
<abstract abstract-type="short" xml:lang="pt"><p><![CDATA[Resumo a incerteza financeira na indústria cinematográfica tem sido evidente nos últimos anos, razão pela qual esta pesquisa visa determinar quais fatores impactam ou não o sucesso financeiro de um filme mexicano, como estratégia para a tomada de decisões e para a redução de riscos. Isso será feito por meio de uma análise de correlação, da aplicação de uma regressão linear múltipla e da simulação de modelos preditivos no software estatístico SPSS, o que permitirá a criação de um modelo econométrico de regressão múltipla, obtendo assim uma ferramenta preditiva que pode ser usada na indústria cinematográfica mexicana. Os resultados mais relevantes mostram que as variáveis com os comportamentos mais significativos são o número de salas de cinema em que um filme é distribuído e o poder da crítica. O uso do modelo de previsão criado contribui significativamente para reduzir o impacto da incerteza financeira, gerando confiança para todos os investidores em projetos cinematográficos e contribuindo para a melhoria do lucro que um filme pode obter. A principal limitação do modelo é a ausência de variáveis adicionais que o complementariam e melhorariam, como o número de semanas de distribuição e o investimento em publicidade.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[éxito financiero]]></kwd>
<kwd lng="es"><![CDATA[industria cinematográfica]]></kwd>
<kwd lng="es"><![CDATA[ingresos por taquilla]]></kwd>
<kwd lng="es"><![CDATA[regresión múltiple lineal]]></kwd>
<kwd lng="es"><![CDATA[riesgos]]></kwd>
<kwd lng="en"><![CDATA[Financial success]]></kwd>
<kwd lng="en"><![CDATA[film industry]]></kwd>
<kwd lng="en"><![CDATA[box office revenue]]></kwd>
<kwd lng="en"><![CDATA[multiple linear regression]]></kwd>
<kwd lng="en"><![CDATA[risks]]></kwd>
<kwd lng="pt"><![CDATA[sucesso financeiro]]></kwd>
<kwd lng="pt"><![CDATA[indústria cinematográfica]]></kwd>
<kwd lng="pt"><![CDATA[renda de bilheteria]]></kwd>
<kwd lng="pt"><![CDATA[regressão linear múltipla]]></kwd>
<kwd lng="pt"><![CDATA[riscos]]></kwd>
<kwd lng="es"><![CDATA[M20]]></kwd>
<kwd lng="es"><![CDATA[M21]]></kwd>
<kwd lng="es"><![CDATA[Z19]]></kwd>
</kwd-group>
</article-meta>
</front><back>
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