Title
Company Family, Innovation and Colombian Graphic Industry: A Bayesian Estimation of a Logistical Model.
Abstract
This study presents a comparative analysis of the management of innovation among family and non-family companies of the Graphic Communication Industry in Colombia. For which a questionnaire was applied in order to know the divergences in the innovation process carried out by these two types of organizations. From this, the methodology of Generalized Linear Models (MLG) was used and the Bayesian inference was used on the parameters of the model, analyzing the effect of the family business, the products that commercialize on the management of innovation in goods observed as a product tangible Obtaining in this way, the identification of some characteristics of innovation management and divergences with non-family companies, among them: a tendency towards the type of preferred innovation, the different sources and objectives to innovate, and the factors that hinder its process of innovation.
Year
Venue
Field
2018
DMBD
Graphic communication,Bayesian inference,Markov chain Monte Carlo,Computer science,Knowledge management,Generalized linear model,Artificial intelligence,Innovation management,Innovation process,Logistic regression,Bayes estimator,Machine learning
DocType
Citations 
PageRank 
Conference
0
0.34
References 
Authors
0
7