Ekundayo Shittu
Professor of Engineering Management and Systems Engineering, George Washington University
Area of Expertise: Environment and Technology
Ekundayo Shittu is a professor in the Department of Engineering Management and Systems Engineering at George Washington University. He conducts basic and applied research that takes a systems engineering approach to aid decision making under uncertainty on investments into energy technology portfolios, and the economics of climate change response policies. Shittu leads the System Modeling Laboratory for Economic Decision.
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Gai, D. H. B., & Shittu, E. (2022). Stochastic Dominance of Renewables to Replace Hydropower Under Policy Uncertainty. IEEE Access, 10, 45855–45869.
Abstract: Regional energy managers and decision-makers face a world where climate change is introducing uncertainty over future power generation, as well as financial impacts from potential carbon taxation. A unique opportunity to explore is the rising interest in hydropower substitution with renewable resources, either to promote ecosystem services such as increasing the survivability of migratory fish or mitigating future loss of generation due to severe drought conditions. To address these concerns, a case study of the Columbia River Basin was conducted to evaluate the substitution of four Lower Snake River dams. A multistage methodology was chosen to evaluate grid adequacy, climate change performance, and the implications of tax uncertainty on the substitution portfolios. A specialized energy model was used to provide the adequacy and input for a Monte Carlo simulation to test the impact of an uncertain tax. The outcome is a carbon tax strategy region that suggests preferences under different taxes for risk-averse decision makers, alongside adequacy and climate metrics. We conclude that policymakers should consider a carbon tax between $86 and $132 to incentivize a portfolio that marginally reduces emissions compared to the pre-dam removal baseline or a tax greater than $135 to incentivize another portfolio that significantly reduces emissions. This study makes three important contributions: (1) it provides a methodology for evaluating electricity generating portfolios in the presence of a carbon tax, (2) it evaluates adequacy metrics for technology substitutions with intermittent alternatives and climate change impacts, and (3) it offers specific guidance for energy policy making.
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Kumbaroğlu, G., Canaz, C., Deason, J., & Shittu, E. (2020). Profitable Decarbonization through E-Mobility. Energies, 13(16), Article 16.
Abstract: This paper focuses on the interdependent relationship of power generation, transportation and CO2 emissions to evaluate the impact of electric vehicle deployment on power generation and CO2 emissions. The value of this evaluation is in the employment of a large-scale, bottom-up, national energy modeling system that encompasses the complex relationships of producing, transforming, transmitting and supplying energy to meet the useful demand characteristics with great technological detail. One of such models employed in this analysis is the BUEMS model. The BUEMS model provides evidence of win-win policy options that lead to profitable decarbonization using Turkey’s data in BUEMS. Specifically, the result shows that a ban on diesel fueled vehicles reduces lifetime emissions as well as lifetime costs. Furthermore, model results highlight the cost-effective emission reduction potential of e-buses in urban transportation. More insights from the results indicate that the marginal cost of emission reduction through e-bus transportation is much lower than that through other policy measures such as carbon taxation in transport. This paper highlights the crucial role the electricity sector plays in the sustainability of e-mobility and the value of related policy prescriptions.
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Ogunrinde, O., & Shittu, E. (2023). Efficiency and Productivity of Renewable Energy Technologies: Evidence from U.S. Investor-Owned Utilities Across Regional Markets. Utilities Policy, 82, 101560.
Abstract: This study employs a Data Envelopment Analysis (DEA) modeling technique to investigate the efficiency and productivity of renewable energy (RE) adoption across technologically diverse electricity-generating utilities. By employing metrics capturing policy effects, the study evaluates the RE adoption efficiency and productivity using a dynamic DEA model and the Malmquist DEA technique. First, the findings reveal that RE adoption is not significantly different across regional electricity markets. Second, the study revealed that RE adoption increased over the last three years. The total mean productivity change over the entire study period showed a mean improvement of 4.8%.
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Ogunrinde, O., Shittu, E., & Dhanda, K. K. (2022). Distilling the Interplay Between Corporate Environmental Management, Financial, and Emissions Performance: Evidence From U.S. Firms. IEEE Transactions on Engineering Management, 69(6), 3407–3435.
Abstract: This article investigates the relationship between firms’ carbon intensity, carbon management practices, and their financial performance. The extant literature on firms’ financial performance and their environmental performance has mostly considered a single dimension of firms’ environmental performance leading to restricted, and often, mixed outcomes. With panel data collected on financial statements and climate change related activities from 136 corporate firms in the U.S. between 2011 and 2018, this article integrates a process dimension based on an environmental management score with an outcome dimension represented by firms’ carbon emissions intensity. A regression model is employed to investigate the relationships between corporate environmental performance and corporate financial performance. We find evidence of a nonlinear relationship between corporate firms’ environmental performance and financial performance across both high and low-carbon intensive sectors. Specifically, we find that for firms in the high-carbon intensive sector, a U-shaped relationship exists between firms’ corporate environmental performance outcome dimension and their financial performance while for the low-carbon intensive sector, the converse is the case. The results show that the interaction between the outcome dimension of environmental performance and financial performance is moderated by the process dimension of environmental performance for firms in the low- and high-carbon intensive sectors.
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Shittu, E., Adewumi, F., Ene, N., Keluo-Udeke, S. C., & Wonodi, C. (2022). Examining Psychosocial Factors and Community Mitigation Practices to Limit the Spread of COVID-19: Evidence from Nigeria. Healthcare (Basel, Switzerland), 10(3), 585.
Abstract: We examine the psychosocial factors influencing community adoption of non-pharmaceutical interventions (NPI) to limit the spread of COVID-19. Using data from 990 respondents in communities across Nigeria, we examine the correlation of health behaviors and socioeconomic indicators. We conduct logistic regression to estimate the relationship between mask wearing as a health-seeking NPI with demographic and socioeconomic variables. We estimate separate models in the sensitivity robustness checks with other NPIs and control for differences across sex, age, education, number in household, and the presence of a student in the respondent’s household. A crucial finding is that health-seeking NPI behaviors are statistically significantly affected in different ways by the menu of socioeconomic indicators. The control for age, sex, education, and household size indicates that there is intersectionality of how these factors influence specific mitigation practices. We find that women are more likely to engage in mask wearing, hand washing, and use of hand sanitizers and tissues than men, and the provision of palliatives and access to family supplies significantly enhances community mitigation. Palliatives and access to family supplies enhance most healthseeking behaviors. The implication for pandemic mitigation policy is that minimizing incidence rates requires having responsive initiatives such as information updates on pandemic progression.
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Shittu, E., Tibrewala, A., Kalla, S., & Wang, X. (2021). Meta-Analysis of the Strategies for Self-Healing and Resilience in Power Systems. Advances in Applied Energy, 4, 100036.
Abstract: This paper presents a survey of the literature on the strategies to enhance the resilience of power systems while shedding lights on the research gaps. Using a deductive methodology on the literature covering the resilience of power systems, we reviewed more than two hundred peer-reviewed articles spanning the 2010–2019 decade. We find that there is vacuum on the level of integration that considers the interdependence of local or decentralized decision making in an adaptive power system. This gap is widened by the absence of policies to enhance resilience in power networks. While there is significant coverage and convergence of research on algorithms for solving the multi-objective problem in optimization routines, there are still uncharted territories on how to incorporate system degradation while designing these self-restoration systems. We posit that a shift to a smarter, cleaner and more resilient power network requires sustained investments rather than disaster-induced responses.
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Shittu, E., & Weigelt, C. (2022). When the Wind Blows: Incumbents’ Sourcing Strategies for Wind Power. IEEE Transactions on Engineering Management, 1–20.
Abstract: While extant research on sustainability transitions discusses how innovations are nurtured in protective market spaces before causing change in established industries, we know less about how characteristics of these protective market spaces, policy, and resource endowments impact incumbents’ sustainability transition pathways for a new technology. We distinguish between incumbents’ choice to embrace innovation by contracting for wind power or direct ownership of windfarms. We contribute to recent calls in the literature to open the “black box” surrounding the heterogeneity in incumbents’ responses to sustainability transitions. In a sample of 801 windfarm transactions over a 14-year-time period (2004–2017), we find that characteristics of protective market spaces affect incumbents’ response: incumbents facing less experienced niche actors (windfarm developers) and acquiring greater capacities of the innovation (wind power) are more likely to own a windfarm than contract for wind power. Moreover, if the innovation has greater physical distance from incumbents’ operations, ownership is the incumbent’s likely response to innovation. As policies for the innovation persists, incumbents are more likely to own a windfarm than contract for wind power. However, that relationship is weakened for firms more established in existing technologies. We contribute to the literature by demonstrating that market characteristics and policy impact heterogeneity in incumbents’ sustainability transitions.
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van Dorp, J.R., Shittu, E. The Generalized Two-Sided Beta Distribution with Applications in Project Risk Analysis. J Stat Theory Pract 17, 38 (2023).
Abstract: A novel smooth, three-parameter, asymmetric two-sided distribution with bounded support is constructed via a half-symmetric beta distribution. Denoting that novel asymmetric distribution the generalized two-sided beta (GTSB) distribution, it is characterized by a mode (or anti-mode) parameter together with two branch power parameters. GTSB distributions serve as a smooth alternative for generalized two- sided power distributions. Some properties of the GTSB family of distributions shall be derived. Two separate algorithms to solve for the power parameters of the GTSB distribution shall be presented. The first algorithm ensures matching of the most likely value, specified through expert judgment, as well as the PERT mean and PERT vari- ance, popular in project management. The latter result is a novel PERT contribution by itself. The second algorithm solves for the power parameters from a lower and upper quantile constraint. The application of the GTSB distribution shall be demonstrated in illustrative PERT example(s).
