Prontidão para tecnologia, inteligência de produto e customização em massa como preditores do valor de uso no contexto dos smart products

Abstract

Digital transformation has attracted considerable interest from the academic and business community because of its huge impact on products and services. In this sense, the importance of theoretical and empirical research in the fields of Technology Readiness, Product Intelligence, Mass Customization and Value in Use motivates further studies and deepening the relationships between these areas. From the perspective of analyzing these phenomena, is inserted the context of Smart Products, which represents a considerable marketshare of products embedded with information and communication technology. Thus, a better understanding of the Value in Use predictors is a research opportunity. The purpose of this thesis was to propose and test a Theoretical Model that allows to analyze the relations between the Technology Readiness, Product Intelligence, Mass Customization constructs as predictors of Value in Use in the context of Smart Products. This research involved a crosssectional survey with smartphone users, the object of study that best characterizes the dimensions of analysis, seeking to analyze the relationships between the model constructs. Data were statistically analyzed using multivariate analysis techniques, more pecifically by the Structural Equation Modeling technique, to explain the studied phenomenon. As results, this work verified the behavior of these constructs, demonstrating that the proposed theoretical model presents satisfactory fit indices. The most prominent contribution is the validation of the relationships between the tested constructs, showing that Technology Readiness positively influences Product Intelligence, Mass Customization and Value in Use; Product Intelligence positively influences Mass Customization; and that Mass Customization positively influences Value in Use in the context of Smart Products. Additionally, it was evidenced that Product Intelligence does not affect the Use Value of Smart Products users. In terms of predictive power, the model showed that 61.2% of Value in Use is explained by theantecedent constructs, thus showing why some products have a higher perception of Value in Use than others. Thus, the study contributes to the evolution of the understanding of the tested constructs, enhancing the understanding of each individual construct and providing empirical evidence of its relationship as determinants of Value in Use, allowing to contribute theoretically and managerially to emerging themes such as Product Intelligence and Value in Use.