Transportation service has a major impact on economic development and growth. Efficient management in transportation allows organizations to handle complicated situations. The studies in my dissertation focus on developing novel methodologies, strategies and decisions to help address three different practical demands from organizations by using business analytical tools. Although we present our methodologies in three particular business contexts, the frameworks of three essays can be easily generalized to other industries.
The first essay is to explore the strategy for global market expansion of a private air medical company. We assess the global medical aviation market and identify the most suitable regions for the company. We combine the Analytic Hierarchy Process (AHP) and the Grey Number theory (GN) to analyze the potential foreign market. We evaluate all countries and areas in the world and make our recommendations through our novel AHP-GN model.
The second essay targets a booming industry-the China express delivery industry. With rapid development of e-commerce in China, its express industry has experienced phenomenal growth in recent years. Investors are particularly eager to discover how to gain a better understanding of the market and compare between operating express delivery firms to understand their respective strengths and weaknesses. We investigate the top 12 express delivery companies in China and evaluate their independent business performance. The Analytical Network Process (ANP), a multi-criteria decision-making methodology, is used to develop an evaluation framework. In addition to the ANP method, we employ the center-point triangular whitenization weight function to convert uncertain information into a unique value and rank the 12 express delivery companies.
The third essay studies the car-sharing industry. The three fundamental management issues in car-sharing industry are: 1). Branch Station Location Selection; 2). Station Size/Capacity; 3). Strategies for imbalance of vehicle distribution at each station. In this study, we develop novel approaches to address these questions. Our models require few inputs and offer quick analytic results. Application of the models to the Zipcar setting is used to illustrate our models and to derive managerial insights
