Semester of Graduation
Summer 2025
Degree
Master of Construction Management (MCM)
Department
Burt S. Turner Department of Construction Management
Document Type
Thesis
Abstract
The industrial sector in the United States accounted for 33% of total energy consumption in 2022. Small and medium-sized enterprises (SMEs), which comprise 99.9% of U.S. businesses present a critical opportunity for energy efficiency improvements. Although energy audits provide actionable Assessment Recommendations (ARs) to reduce consumption, high implementation costs remain a key barrier to adoption.
While prior studies have explored rebate programs, most are limited to residential and commercial sectors or focus narrowly on specific technologies or geographic areas for the industrial sector. The objective of this study is to empirically investigate the “Incentivized Assessment Recommendation” (IAR) trends and to evaluate the cost-effectiveness of IIoT adoption as a representative “Not Incentivized Assessment Recommendation” (NIAR). This research addressed two research questions: (1) How frequently are IARs issued, and which types are most common across U.S. SMEs? (2) Do the estimated annual cost savings from IIoT, as a case study for NIARs, significantly exceed their initial implementation costs?
To address these questions, the study analyzed 164,308 ARs from 22,097 industrial assessments in the publicly available Industrial Training & Assessment Center (ITAC) database. Descriptive statistics were used to assess IAR trends, geographic distribution, and implementation rates. A non-parametric Mann-Whitney U test was applied to evaluate the cost-effectiveness of IIoT adoption by comparing implementation costs (IMPCOST) and projected annual savings (PSAVED).
Results indicated that IARs gradually increased since their emergence in 1991, reaching 20% of all ARs by 2024. However, IARs remain a minority in comparison with NIAR. The most common IARs were related to lighting and motor systems. Nonetheless, implementation rates varied, with some IARs, particularly solar energy systems, showing low adoption despite rebate eligibility. Additionally, the statistical analysis of IIoT ARs confirmed a significant difference between implementation cost and projected annual savings of IIoT-related recommendations.
Finally, the outcome of this research can provide insights into the adoption patterns of IARs and cost effectiveness of IIoT as a case study of NIARs to support more informed decision-making for SMEs and guide future energy policy development.
Date
7-19-2025
Recommended Citation
Ghafari, Fatemeh, "Empirical Analysis of Incentivized Energy Assessment Recommendations and IIoT Cost-effectiveness in U.S. SMEs" (2025). LSU Master's Theses. 6195.
https://repository.lsu.edu/gradschool_theses/6195
Committee Chair
Chao Wang