Metodología para estimar y evaluar un modelo de gestión del conocimiento mediante ecuaciones estructurales

Abstract

Este artículo presenta una metodología para la estimación y evaluación de un modelo de gestión del conocimiento, utilizando ecuaciones estructurales, que sirven para probar y estimar relaciones causales a partir de datos estadísticos y referentes teóricos sobre la causalidad, mostrando los indicadores más influyentes que se deben intervenir para mejorar la gestión del conocimiento en el área de TI de la universidad Simón en Barranquilla, con base en las variables TIC, Capital Intelectual, Aprendizaje Organizacional e Innovación. Logrando demostrar que el instrumento diseñado es confiable según los resultados de la prueba Alfa de Cronbach y útil para medir la Gestión del Conocimiento, en las variables más influyentes: Las TIC, servicios principales y de infraestructura; el capital intelectual, enfocado al capital estructural, clima organizacional y los procesos de negocios; el aprendizaje organizacional, en el Sistema cultural y el aprendizaje en equipo y la innovación, referida a políticas que motiven la creatividad del personal.

Model of dimensions and variables of corporate social responsibility updated through structural equations

“…Consequently, as shown in the lower part of Table 3 , the 15 determined factors also present standard estimators located in their range (0–1) with their respective significances (***). Consequently, the structural modeling estimators confirm a system of duly related CSR factors that allow for a positive response to H1 insofar as they allow explaining more than the total variance (≥ 0.50) and therefore ratify the factorial analysis carried out [ 29 , 31 ].…”

“…To determine the percentage weights taken to 100% of the factorial system that make up the 15 factors that give shape and content to the CSR model, the level of intensity of each of the factors was verified according to the distribution of the variables and they were determined. the variance relationships (<---) of each of the 66 variables with each of the CSR factors determined CSR [ 29 , 31 ]. Thus, through the analysis of variance of the variables with their respective factors, it was possible to determine a system of estimators that are detailed in Table 4 .…”

“…For this, the psychometric analysis of the items was carried out, which were evaluated through the communality indices (≥ 0.40) and factorial load (≥ 0.50) of the variables to their respective factors. In turn and to confirm the reliability of the instrument, the Cronbach’s Alpha index was verified, requiring a high and consistent estimator (≥ 0.80) [ 29 ].…”

“…In this context, the researchers sensitized the estimators of the variables and the significance indices (***), to confirm that the items are part of the determined factors [ 31 ] and represent with some certainty the reality analyzed [ 18 , 31 ]. Finally, the findings were ratified through the respective goodness-of-fit indices [ 29 , 31 ] after verifying that the estimators meet the required requirements. Notwithstanding the above, it is necessary to indicate that the ESEM analysis delivers statistically significant results when it is unlikely that these are due to chance [ 19 , 29 ].…”

“…Finally, the findings were ratified through the respective goodness-of-fit indices [ 29 , 31 ] after verifying that the estimators meet the required requirements. Notwithstanding the above, it is necessary to indicate that the ESEM analysis delivers statistically significant results when it is unlikely that these are due to chance [ 19 , 29 ]. To do this, the goodness of fit indices were reviewed [ 32 , 33 ].…”