PLS-SEM linear regression model to evaluate the effect of dynamic capabilities in the process of improving competitiveness in companies

PLS-SEM linear regression model to evaluate the effect of dynamic capabilities in the process of improving competitiveness in companies

Innovation is positively correlated with the competitiveness of companies. The knowledge of companies, characterized by their dynamic capabilities, influences their innovation and competitiveness. The objective of this work was to determine a linear regression model that allows determining the impac...

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Main Authors: García-Martínez, Rafael, Poblano-Ojinaga, Eduardo Rafael, Noriega-Morales, Salvador Anacleto
Format: Online
Language:spa
Published: Universidad Autónoma de Tamaulipas 2024
Online Access:https://revistaciencia.uat.edu.mx/index.php/CienciaUAT/article/view/1843
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spelling oai:ojs.pkp.sfu.ca:article-18432024-07-20T01:00:24Z PLS-SEM linear regression model to evaluate the effect of dynamic capabilities in the process of improving competitiveness in companies Modelo de regresión lineal PLS-SEM para evaluar el efecto de las capacidades dinámicas en el proceso de mejoramiento de la competitividad en las empresas García-Martínez, Rafael Poblano-Ojinaga, Eduardo Rafael Noriega-Morales, Salvador Anacleto innovación inteligencia competitiva capital intelectual gestión del conocimiento PLS-SEM innovation competitive intelligence intellectual capital knowledge management PLS-SEM Innovation is positively correlated with the competitiveness of companies. The knowledge of companies, characterized by their dynamic capabilities, influences their innovation and competitiveness. The objective of this work was to determine a linear regression model that allows determining the impact of dynamic capabilities on the Innovation Capacity (CIn) of companies. A multivariate linear regression model was built in which the causal relationship between dynamic capabilities intellectual capital (CI), competitive intelligence (IC), know-ledge management (GC), and absorption capacity (CA) was established with the CIn; model with which the critical factors and their effect on CIn are identified, in the implementing the innovation improvement process. This model was built using the structural equations model, with a partial least squares method, using a sample of 196 companies in the City of Hermosillo, Sonora, Mexico. The estimated model has an adequate explanatory and predictive capacity, in which the IC was the critical factor that had the greatest effect on CIn, followed by CG and CI, while CA has no significant impact on CIn. The developed model is applicable in the management and implementation of improvements in the CIn of companies located in study zone and probably in other regions. La innovación está correlacionada positivamente con la competitividad de las empresas. Sus conocimientos, caracterizados como sus capacidades dinámicas, influyen en la innovación y la competitividad de las mismas. El objetivo del presente trabajo fue determinar un modelo de regresión lineal, que permita determinar el impacto que las capacidades dinámicas tienen sobre la capacidad de innovación (CIn) de las empresas. Se construyó un modelo de regresión lineal multivariado en el que se estableció la relación causal de las capacidades dinámicas capital intelectual (CI); inteligencia competitiva (IC); gestión del conocimiento (GC) y capacidad de absorción (CA), con la CIn; modelo con el que se identifican cuáles son los factores críticos y su efecto sobre la CIn, en la implementación del proceso de mejora de la innovación. Dicho modelo, se construyó utilizando el método de ecuaciones estructurales, con mínimos cuadrados parciales, con una muestra de 196 empresas ubicadas en la ciudad de Hermosillo, Sonora, México. El modelo estimado presentó una adecuada capacidad explicativa y predictiva, en la que la IC fue el factor crítico que mayor efecto tuvo sobre la CIn, seguido por la GC y el CI, mientras que CA no tuvo efecto significativo sobre la CIn. El modelo desarrollado es aplicable en la gestión e implementación de mejoras en la CIn de empresas ubicadas en la zona estudiada, y probablemente en otras regiones. Universidad Autónoma de Tamaulipas 2024-04-09 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf text/html https://revistaciencia.uat.edu.mx/index.php/CienciaUAT/article/view/1843 10.29059/cienciauat.v19i1.1843 CienciaUAT; Vol. 19, No. 1. July-December 2024; 140-156 CienciaUAT; Vol. 19, No. 1: julio-diciembre 2024; 140-156 2007-7858 2007-7521 spa https://revistaciencia.uat.edu.mx/index.php/CienciaUAT/article/view/1843/1230 https://revistaciencia.uat.edu.mx/index.php/CienciaUAT/article/view/1843/1206 Derechos de autor 2024 Universidad Autónoma de Tamaulipas https://creativecommons.org/licenses/by-nc-sa/4.0
institution CIENCIA UAT
collection OJS
language spa
format Online
author García-Martínez, Rafael
Poblano-Ojinaga, Eduardo Rafael
Noriega-Morales, Salvador Anacleto
spellingShingle García-Martínez, Rafael
Poblano-Ojinaga, Eduardo Rafael
Noriega-Morales, Salvador Anacleto
PLS-SEM linear regression model to evaluate the effect of dynamic capabilities in the process of improving competitiveness in companies
author_facet García-Martínez, Rafael
Poblano-Ojinaga, Eduardo Rafael
Noriega-Morales, Salvador Anacleto
author_sort García-Martínez, Rafael
title PLS-SEM linear regression model to evaluate the effect of dynamic capabilities in the process of improving competitiveness in companies
title_short PLS-SEM linear regression model to evaluate the effect of dynamic capabilities in the process of improving competitiveness in companies
title_full PLS-SEM linear regression model to evaluate the effect of dynamic capabilities in the process of improving competitiveness in companies
title_fullStr PLS-SEM linear regression model to evaluate the effect of dynamic capabilities in the process of improving competitiveness in companies
title_full_unstemmed PLS-SEM linear regression model to evaluate the effect of dynamic capabilities in the process of improving competitiveness in companies
title_sort pls-sem linear regression model to evaluate the effect of dynamic capabilities in the process of improving competitiveness in companies
description Innovation is positively correlated with the competitiveness of companies. The knowledge of companies, characterized by their dynamic capabilities, influences their innovation and competitiveness. The objective of this work was to determine a linear regression model that allows determining the impact of dynamic capabilities on the Innovation Capacity (CIn) of companies. A multivariate linear regression model was built in which the causal relationship between dynamic capabilities intellectual capital (CI), competitive intelligence (IC), know-ledge management (GC), and absorption capacity (CA) was established with the CIn; model with which the critical factors and their effect on CIn are identified, in the implementing the innovation improvement process. This model was built using the structural equations model, with a partial least squares method, using a sample of 196 companies in the City of Hermosillo, Sonora, Mexico. The estimated model has an adequate explanatory and predictive capacity, in which the IC was the critical factor that had the greatest effect on CIn, followed by CG and CI, while CA has no significant impact on CIn. The developed model is applicable in the management and implementation of improvements in the CIn of companies located in study zone and probably in other regions.
publisher Universidad Autónoma de Tamaulipas
publishDate 2024
url https://revistaciencia.uat.edu.mx/index.php/CienciaUAT/article/view/1843
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