Date of Award

2025

Document Type

Thesis

Degree Name

MS in Science

Department

Business Analytics and Information Systems

First Advisor

Ahmad Vakil

Abstract

This study investigates the sustainability risks posed by Guyana’s rapidly expanding oil sector, with particular focus on balancing economic benefits against environmental vulnerabilities. The primary aim is to develop a Sustainability Risk Index (SRI) that captures the multidimensional impacts of offshore oil development using an integrated data-driven framework. Specifically, this thesis examines how emissions, biodiversity loss, oil spill exposure, economic volatility, and social development indicators interact to influence sustainability outcomes in the context of Guyana’s transition into a major petroleum-producing nation. The research does not involve human participants; instead, it draws on publicly available datasets collected from 2015 to 2024. These include environmental impact assessments (EIA) from ExxonMobil’s Uaru project, World Bank and IMF economic indicators, trade and health statistics from Guyana’s Bureau of Statistics, marine ecology surveys, rainfall and deforestation records, and satellite data. The data represents country-level and ecosystem-level observations focused on coastal and offshore regions most directly affected by petroleum activities. The methodology involves compiling and cleaning over 50 structured datasets into a master analytical file. Variables are categorized into environmental, economic, and social dimensions. A composite SRI equation is developed using weighted coefficients (b₀ to bₙ) for each subdimension, based on both empirical literature and exploratory statistical analysis. Supplementary regression and visualization tools within R Studio and Tableau are used to model trends, identify risk intensifiers, and simulate policy tradeoffs across various development scenarios. Comparative benchmarks from other petroleum-dependent economies are also used to contextualize Guyana’s trajectory. The significance of this study lies in its interdisciplinary, data-informed approach to sustainable development planning. The findings offer policymakers, nonprofits, and private sector stakeholders a quantifiable, dynamic tool to monitor and anticipate sustainability risks before they escalate into crises. Moreover, the framework provides a replicable model for other emerging oil economies seeking to avoid the pitfalls of the resource curse while maximizing long-term national benefit.

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