Smart Cities and Awareness of Sustainable Communities Related to Demand Response Programs: Data Processing with First-Order and Hierarchical Confirmatory Factor Analyses

Abstract

The mentality of electricity consumers is one of the most important entities that must be addressed when dealing with issues in the operation of power systems. Consumers are used to being completely passive, but recently these things have changed as significant progress of Information and Communication Technologies (ICT) and Internet of Things (IoT) has gained momentum. In this paper, we propose a statistical measurement model using a covariance structure, specifically a first-order confirmatory factor analysis (CFA) using SAS CALIS procedure to identify the factors that could contribute to the change of attitude within energy communities. Furthermore, this research identifies latent constructs and indicates which observed variables load on or measure them. For the simulation, two complex data sets of questionnaires created by the Irish Commission for Energy Regulation (CER) were analyzed, demonstrating the influence of some exogenous variables on the items of the questionnaires. The results revealed that there is a relevant relationship between the social–economic and the behavioral factors and the observed variables. Furthermore, the models provided a good fit to the data, as measured by the performance indicators.