Date of Award


Document Type

Dissertation - Open Access

Degree Name

Doctor of Philosophy in Aviation Business Administration


College of Business

Committee Chair

Li Zou, Ph.D.

First Committee Member

Hari Adhikari, Ph.D.

Second Committee Member

Nickolas D. Macchiarella, Ph.D


An understanding of industry phenomena and optimization techniques within the upstream energy industry’s transportation sector is markedly absent in the extant literature and suitable for rigorous investigation. This manuscript presents analyses related to the optimization of offshore worker transportation and econometric analyses of factors influencing commercial helicopter operators’ stock returns, which are represented throughout the manuscript as Part I and Part II, respectively.

The global energy industry transports supplies and personnel via helicopter to offshore locations and has been increasingly focusing on optimizing upstream logistics. Using a unique sample of deepwater and ultra-deepwater permanent offshore locations in the Gulf of Mexico, transportation networks consisting of 58 locations operated by 19 firms are optimized via a randomized greedy algorithm. The model developed in Part I has been found to effectively solve the complex transportation problem and simulation results show the potential advantages of alternative clustered and integrated network structures, as compared to an independent firm-level structure. The evaluation of clustered and integrated network structures, which allow ride sharing via energy firm cooperation, provides evidence that such network structures may yield cost reductions for participating firms.

The extent to which commercial helicopter operators’ stock returns are related to commodity prices and other relevant industry variables is absent in the extant literature. Often, firms attribute favorable results to internal factors whereas unfavorable results are attributed to external factors. Using a unique data set from 2013-2018, the current research identifies structural relationships between crude oil prices, natural gas prices, the rotary rig count, a subset of the overall market, firms’ degree of diversification and stock returns of commercial helicopter operators. Empirical analyses developed in Part II show that the prevalent price of crude oil and the overall market environment possess explanatory power of commercial helicopter firms’ stock returns, ceteris paribus. Specifically, 10% increases in the crude oil price and the S&P 500 index yield a 2.7% and 8.0% increase in stock returns, respectively.

Collectively, the abovementioned parts of this manuscript provide rigorous, quantitative analyses of topics unrepresented within the extant literature, which are foundational for future practice and research. Specifically, new knowledge regarding a practical approach to model development and solution deliverance for the transportation of offshore workers to their respective locations and factors influencing commercial helicopter operators’ stock returns has been appropriately designed and empirically evaluated.