Date of Award
Doctor of Philosophy in Information Systems (DISS)
College of Engineering and Computing
Maxine S. Cohen
Steven D. Zink
EMIS, Energy behavior, Energy consumption, Energy Data, Smart Meter, Web Portal
The Energy Industry utilizes Energy Management Information Systems (EMIS) smart meters to monitor utility consumers’ energy consumption, communicate energy consumption information to consumers, and to collect a plethora of energy consumption data about consumer usage. The EMIS energy consumption information is typically presented to utility consumers via a smart meter web portal. The hope is that EMIS web portal use will aid utility consumers in managing their energy consumption by helping them make effective decisions regarding their energy usage. However, little research exists that evaluates the effectiveness or success of an EMIS smart meter web portal from a utility consumer perspective. The research goal was to measure EMIS smart meter web portal success based on the DeLone and McLean Information Success Model. The objective of the study was to investigate the success constructs system quality, information quality, service quality, use, and user satisfaction, and determine their contribution to EMIS success, which was measured as net benefits. The research model used in this study employed Structural Equation Modeling (SEM) based on Partial Least Squares (PLS) to determine the validity and reliability of the measurement model and to evaluate the hypothetical relationships in the structural model. The significant validity and reliability measures obtained in this study indicate that the DeLone and McLean Information Success Model (2003) has the potential for use in future EMIS studies. The determinants responsible for explaining the variance in net benefits were EMIS use and user satisfaction. Based on the research findings, several implications and future research are stated and proposed.
Gwendolyn D. Stripling. 2017. An Empirical Assessment of Energy Management Information System Success Using Structural Equation Modeling. Doctoral dissertation. Nova Southeastern University. Retrieved from NSUWorks, College of Engineering and Computing. (1019)