Date of Award

2019

Degree Type

Dissertation

Degree Name

Doctor of Philosophy in Industrial and Systems Engineering

Department

Mechanical, Industrial and Systems Engineering

First Advisor

Jyh-Honge Wang

Abstract

Energy consumption has a complex relationship with its physical, demographic, and behavioral characteristics. The literature review showed that renewable energy is an increasingly important issue in energy security and sustainability. The research on renewable energy consumption identifies the driving and obstructing factors. Renewable energy growth is associated with complex, interacting variables and requires concerted, multidisciplinary efforts for effective research and development. Thus, the aim of this study is to demonstrate the importance of findings that influence renewable energy consumption among 22 states. Our study seeks to understand and assert the complex energy perspective via the relationship between factors and nature of causality. We considered 17 factors in our study that were proposed to identify and examine the relationship between each factor and renewable energy consumption among 22 states. A Vector Autoregressive model is used to evaluate this relationship. Therefore, this study demonstrates and discusses significant factors that Granger impacts in renewable energy consumption. The results demonstrated that the annual renewable energy consumption among 22 states can be predicted by relevant energy, and socio-economic factors. Most importantly, combining outcomes from PCA of energy consumption and socio-economic factors greatly improves the accuracy of prediction. At the state level, most states tend to share similar energy and socioeconomic patterns, as evidenced by the clustering analysis. Furthermore, MANOVA results illustrate total energy as the measure that differs between high-emission states and low-emission states. Moreover, academic research has recognized the role of social acceptance in the use of renewable energy. This study sought to understand how the user’s physical, demographic, socioeconomic, and behavioral characteristics impact their acceptance of using renewable energy in the residential sector in the United States. Twenty-two states, responsible for 20% or more of the energy production generated from renewable sources, were included in the study. This study tested the Theory of Planned Behavior (TPB) research model and included the construct “willingness to pay” to predict consumers’ intention to use renewable energy. The study found that the average household income in the residential sector has an important impact on consumers’ intention to use renewable energy per the TPB model. The study’s results were found consistent with the theory of the TPB structure equation modeling where the subjective norm (perceived behavioral control) and willingness to pay significantly affected consumers’ intention to use renewable energy, while the attitude toward behavior was not. The study concluded that the average household income affected and explained consumers’ behavior path which predicted their intention to use renewable energy in the residential sector in the US. Limitations of the study and suggestions for future research were discussed.

Available for download on Thursday, July 15, 2021

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