Prof. Emmanuel Amponsah Donkor


Dept: Civil Engineering
Room 13 (Ground Floor), Provost Block

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Research Areas/Interests


    Selected Technical Projects are as follows:

    • Debt Sizing under Uncertainty for Project Finance—Investigated the use of probabilistic constraints in modeling the debt financing decision under conditions of debt heterogeneity and uncertainty. He developed a stochastic financial model that uses simulation optimization to select an optimal mix of fixed-rate debt instruments from different sources, with the objective of maximizing NPV while limiting default risk. [See “Optimal capital structure and financial risk of project finance investments”, published by The Engineering Economist, in February 2013].
    • Ranking Risky Capital Investments—Developed a spreadsheet model for conducting empirical tests of stochastic dominance when comparing alternative capital investment plans under uncertainty. This framework uses bootstrap and simulation methodology to compute the p-values required for making first and second-order dominance inferences. [See “Empirical tests of stochastic dominance in capital investment planning: a spreadsheet framework”, published by The Engineering Economist in October 2013].
    • Water Utility Performance Analysis—Used Ratio and Percentage Analyses to evaluate the performance of the Ghana Water and Sewerage Corporation over a ten-year period. He developed a problem tree to identify the underlying causes of poor performance and investigated the appropriateness of a PSP model for the Ghanaian drinking water industry. He presented results to water sector professionals.
    • Customer Satisfaction Study---Investigated the effect of customer satisfaction on water utility business performance, and showed that satisfied customers are less of a threat to performance than dissatisfied customers. The study was published in the October 2013 issue of Journal American Water Works Association. [See “Effect of customer satisfaction on water utility business performance”].
    • Billing for Water. In order to help commercial managers of water utilities better estimate volumetric consumption when metered records are deficient in some way, Dr. Donkor developed a statistical model and showed that demographic variables and spatial location needs to be taken into account when determining average monthly water consumption. The study was published in the December 2013 issue of Journal American Water Works Association. [ See “Improving the estimation of volumetric water sales for billing”].
    • Water Demand Forecasting Study. Under consulting engagements with the American Water Works Association, Dr. Donkor led a team of four to review current methods and models for forecasting urban water demand, and presented results at two AWWA/NOAA workshops. The study was published in Sept. 2013 as “Urban water demand forecasting: A review of methods and models”, by Journal of Water Resources Planning and Management.
    • Water Utility Cost Modeling—To enable policy makers make decisions on price regulation and the need for systems consolidation, Dr. Donkor formulated and estimated an econometric cost function for small towns water utilities in Ghana. From the model he identified key drivers of water utility costs, assessed the level of scale economies in the industry, and evaluated the relative performance of utilities.

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