The demand for aviation has been steadily growing over the past few decades and will keep increasing in the future. The anticipated growth of traffic demand will cause the current airspace system, one that is already burdened by heavy operations and inefficient usage, to become even more congested than its current state. Because busy airports in the United States (U.S.) are becoming "bottlenecks" of the National Airspace System (NAS), it is of great importance to discover the most efficient means of using existing facilities to improve airport operations. This dissertation aims at designing an efficient airport surface operations management system that substantially contributes to the modernized NAS. First, a global comparison is conducted in the major airports within the U.S. and Europe in order to understand, compare, and explore the differences of surface operational efficiency in two systems. The comparison results are then presented for each airport pair with respect to various operational performance metrics, as well as airport capacity and different demand patterns. A detailed summary of the associated Air Traffic Management (ATM) strategies that are implemented in the U.S. and Europe can be found towards the end of this work. These strategies include: a single Air Navigation Service Provider (ANSP) in the U.S. and multiple ANSPs in Europe, airline scheduling and demand management differences, mixed usage of Instrument Flight Rule (IFR) and Visual Flight Rules (VFR) operations in the U.S., and varying gate management policies in two regions. For global comparison, unimpeded taxi time is the reference time used for measuring taxi performance. It has been noted that different methodologies are currently used to benchmark taxi times by the performance analysis groups in the U.S. and Europe, namely the Federal Aviation Authority (FAA) and EUROCONTROL. The consistent methodology to measure taxi efficiency is needed for the facilitation of global benchmarking. Therefore, after an in-depth factual comparison conducted for two varying methodologies, new methods to measure unimpeded taxi times are explored through various tools, including simulation software and projection of historical surveillance data. Moreover, a sophisticated statistical model is proposed as a state-of-the-art method to measure taxi efficiency while quantifying the impact of various factors to taxi inefficiency and supporting decision-makers with reliable measurements to improve the operational performance. Lastly, a real-time integrated airport surface operations management (RTI-ASOM) is presented to fulfil the third objective of this dissertation. It provides optimal trajectories for each aircraft between gates and runways with the objective of minimizing taxi delay and maximizing runway throughput. The use of Mixed Integer Linear Programming (MIP) formulation, Dynamic Programming for decomposition, and CPLEX optimization can permit the use of an efficient solution algorithm that can instantly solve the large-scale optimization problem. Examples are shown based on one-day track data at LaGuardia Airport (LGA) in New York City. In additional to base scenarios with historical data, simulation through MATLAB is constructed to provide further comparable scenarios, which can demonstrate a significant reduction of taxi times and improvement of runway utilization in RTI-ASOM. By strategically holding departures at gates, the application of RTI-ASOM also reduces excess delay on the airport surface, decreases fuel consumption at airports, and mitigates the consequential environmental impacts.