Structural equations model to analyze the incidence of variables related to innovation management in organizations

Abstract

Previous works have demonstrated the possibilities to influence the innovation process in organizations. Although the presented initiatives have their merits, they suffer from a lack of integrated perspective. They are focused on the evaluation of the link between the innovation process and only one of the subsystems of the administration, without considering the implications of the other subsystems. The aim of this article is to define a model of structural equations that summarizes the impact of the variables related to innovation management in organizations. This article first presents the identified variables according to the analyzed literature and then shows which variables were selected by consulting experts on the field. To measure the selected variables some questionnaires were elaborated. The questionnaires were applied in 111 entities of different production sectors. A confirmatory factorial analysis was developed with the obtained measures. Thanks to this analysis, it was possible to verify the incidence of the evaluated variables in the innovation management, allowing the elaboration of the model. The proposed model shows the link between the different variables that contribute to the innovation management process. The analysis confirmed that innovation, as a construct, has a multifactorial nature. The information used as input for the elaboration of the model allowed introducing a new sequence of innovation management from the integrated management of the variables that can influence it. This integrated management ensures effective human resources management, production, and marketing. The findings confirm that innovation needs to be managed in an integrated way with the rest of the administrative subsystems rather than as an isolated process. This way of working allows obtaining better results for the organizations. Based on the multisectorial nature of the research sample, it can be assumed that the obtained results can be corroborated in several fields.