Towards A Smarter Energy Metering System For A Smarter City: A Regression-Based Model From Users’ Perspective

Abstract

A smart meter is an Internet of Things (IoT) device that can measure, control, and predict how much gas, water, and electricity a household consumes and automatically sends this data to the provider, for billing and monitoring services. Although smart energy meters have great capabilities, this technology is currently experiencing very low adoption rates in many developing countries. In addition, some smart energy meters that are currently used in many developed countries and cities could be improved for better performance and more features. Therefore, this research is aimed at proposing a relatively new smarter energy meter and validating it from users’ perspectives in a developing country, the United Arab Emirates (UAE). A quantitative approach was deployed to validate the proposed smart meter model through gathering 266 survey responses in the UAE, in order to empirically understand what perceived values could impact a user’s intention to use this smart meter. The research data were analyzed by using descriptive statistics and regression tests of SEM-PLS. The research results indicated that the responded users’ intention to use smart meter is impacted by several perceived values; including epistemic values, emotional values, monetary values, and convenience values, but at different significant levels. Finally, the research concludes with theoretical and practical implications, along with some directions for future research.