Douglas Fearing is an Assistant Professor of Business Administration in the Technology and Operations Management Unit, teaching the Technology and Operations Management course in the MBA required curriculum.
His research is directed at techniques for evaluating and improving the performance of complex systems, primarily in the airline industry. He is particularly interested in mitigating airport and airspace congestion by increasing the coordination between airlines and governmental managing agencies. Professor Fearing's paper on coordinating air traffic-flow management programs was awarded the Anna Valicek Medal by the airline industry group AGIFORS. A secondary research interest is applying performance evaluation techniques to sports management, and his coauthored work in this area has been highlighted in The Wall Street Journal and Slate.
Professor Fearing received his Ph.D. in operations research from the Massachusetts Institute of Technology, where he was recognized for the quality of his teaching. After earning his bachelor's degree in computer science at Carnegie Mellon University, he spent five years at Trilogy, a software company in Austin, Texas, working on engagements with Ford, British Airways, and Goodyear. Based on his sports management research, he has consulted for Titleist and the Tampa Bay Rays. Professor Fearing and his wife have two young children.
Publications
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Article
| EURO Journal on Transportation and Logistics
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Demand and Capacity Management in Air Transportation
Cynthia Barnhart, Douglas S. Fearing, Amedeo Odoni and Vikrant Vaze
This paper summarizes research trends and opportunities in the area of managing air transportation demand and capacity. Capacity constraints and resulting congestion and low schedule reliability currently impose large costs on airlines and their passengers. Significant capacity increases that would solve these problems are not expected in the near- or medium-term. The paper outlines first a number of directions for effecting improvement through marginal capacity increases and better management of demand and available capacity. It then describes strategic initiatives airlines and civil aviation authorities might undertake over time horizons of months to years as well as tactical measures that may be adopted on a daily basis in response to dynamic, "real time" developments like poor weather or schedule disruptions. Research challenges in these areas are identified and classified in terms of specifying, allocating, and utilizing capacity. The first two categories reflect challenges faced by infrastructure providers; the last category, challenges faced by airlines.
Keywords: air transportation;
demand management;
capacity management;
mathematical modeling;
congestion and delays;
trends and opportunities;
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Journal Article
| Transportation Science
| Forthcoming
Equitable and Efficient Coordination in Traffic Flow Management
Cynthia Barnhart, Dimitris Bertsimas, Constantine Caramanis and Douglas S. Fearing
When air traffic demand is projected to exceed capacity, the FAA implements Traffic Flow Management programs. Independently, these programs maintain a first-scheduled, first-served invariant, which is the accepted standard of fairness within the industry. Coordinating conflicting programs requires a careful balance between equity and efficiency. In our work, we first develop a fairness metric to measure deviation from first-scheduled, first-served in the presence of program conflicts. Next, we develop an IP formulation that minimizes a convex approximation of this metric. We further develop an exponential penalty approach and show that its computational performance is far superior and its trade-off between delay and fairness compares favorably. In our results, we demonstrate the effectiveness of these models using historical and hypothetical scenarios. Additionally, we demonstrate that the exponential penalty approach exhibits exceptional computational performance, implying practical viability. Our results suggest that this approach could lead to system-wide savings on the order of $25 million to $50 million per year.
Keywords: traffic flow management;
ground holding programs;
equitable flight delay;
Equity;
Saving;
Management;
Management Practices and Processes;
Demand and Consumers;
Performance Capacity;
Performance Efficiency;
Conflict and Resolution;
System;
Aerospace Industry;
Citation: Barnhart, Cynthia, Dimitris Bertsimas, Constantine Caramanis, and Douglas S. Fearing. "Equitable and Efficient Coordination in Traffic Flow Management." Transportation Science (forthcoming).
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Article
| Journal of Quantitative Analysis in Sports
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How to Catch a Tiger: Understanding Putting Performance on the PGA TOUR
Douglas Fearing, Jason Acimovic and Stephen C. Graves
Existing performance metrics utilized by the PGA TOUR have biases towards specific styles of play, which make relative player comparisons challenging. Our goal is to evaluate golfers in a way that eliminates these biases and to better understand how the best players maintain their advantage. Through a working agreement with the PGA TOUR, we have obtained access to proprietary "ShotLink" data that pinpoints the location of every shot taken on the PGA TOUR. Using these data, we develop distance-based models for two components of putting performance: the probability of making the putt and the remaining distance to the pin conditioned on missing. The first is modeled through a logistic regression, the second through a gamma regression. Both models fit the data well and provide interesting insights into the game. Additionally, by describing the act of putting using a simple Markov chain, we are able to combine these two models to characterize the putts-to-go for the field from any distance on the green for the PGA TOUR. The results of this Markov model match both the empirical expectation and variance of putts-to-go. We use our models to evaluate putting performance in terms of the strokes or putts gained per round relative to the field. Using this metric, we can determine what portion of a player's overall performance is due to advantage (or loss) gained through putting, and conversely, what portion of the player's performance is derived off the green. We demonstrate with examples how our metric eliminates significant biases that exist in the PGA TOUR's Putting Average statistic. Lastly, extending the concept of putts gained to evaluate player-specific performance, we show how our models can be used to quickly test situational hypotheses, such as differences between putting for par and birdie and performance under pressure.
Keywords: Performance Evaluation;
Prejudice and Bias;
Mission and Purpose;
Agreements and Arrangements;
Geographic Location;
Performance Expectations;
Competitive Advantage;
Mathematical Methods;
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Journal Article
| Transportation Research Record
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Evaluating Air Traffic Flow Management in a Collaborative Decision-Making Environment
Douglas Fearing and Cynthia Barnhart
The Collaborative Decision-Making (CDM) framework introduced into ground delay programs in the late 1990s is an integral component of the FAA's Traffic Flow Management (TFM) procedures. CDM allows the FAA to act as a mediator when managing TFM programs, transferring as much decision making as possible to the individual airlines. Although this approach has been highly successful in practice, it creates a new question for the research community: How should proposed enhancements to TFM be evaluated in a CDM environment? A sequential evaluation procedure, developed in this paper, addresses this question. The procedure includes airline disruption responses and a quasi-compression operation, attempting to mimic the three-stage CDM process. To model airline disruption responses, an integer optimization model was developed to balance operational and passenger considerations in determining which flights to cancel, swap, or delay. The value of this procedure is demonstrated by analyzing an optimization-based TFM approach in the CDM environment.
Keywords: Decision Making;
Framework;
Management Analysis, Tools, and Techniques;
Management Practices and Processes;
Research;
Strategy;
Valuation;
Aerospace Industry;
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Other Unpublished Work
| 2012
Managing Air Traffic Disruptions through Strategic Prioritization
Douglas S. Fearing and Ian A. Kash
The costs of congestion in the U.S. air transportation system are substantial, with a recent study estimating these costs at over $30 billion for domestic operations in 2007. On the day of operations, if demand is expected to significantly outstrip available capacity (e.g., due to a severe storm), the Federal Aviation Administration (FAA) implements Air Traffic Flow Management (ATFM) initiatives to resolve these imbalances. The most common ATFM initiative enacted is a ground delay program (GDP). In a GDP, arrival slots into a congested airport are rationed to satisfy the projected capacity constraints. These arrival slots determine the expected delay for each flight, which is realized as ground holding at the departure airport. The current approach for allocating ATFM capacity, Ration by Schedule (RBS), treats impacted flights equivalently regardless of the aircraft size, passenger load, mix of connecting passengers, etc. We extend this approach to develop a prioritized rationing scheme, Ration by Prioritized Schedule (RBPS), and show that significant benefits can be achieved through prioritization, even in the face of airline recovery responses. Subsequently, we develop a strategic prioritization game, a non-monetary, market-based scheme for allocating flight priorities which allows airlines to trade-off priorities across airports. In addition to having nice equilibrium properties, we show that our bidding and allocation scheme is capable of achieving some of the benefits of congestion pricing, which has been widely studied in the literature but has met with significant resistance in practice.
Keywords: Balance and Stability;
Cost;
Performance Capacity;
Management Practices and Processes;
Price;
Air Transportation Industry;
United States;
Citation: Fearing, Douglas S., and Ian A. Kash. "Managing Air Traffic Disruptions through Strategic Prioritization." 2012.
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Conference Presentation
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Mar
2013
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2
Mar
2013
The Value of Flexibility in Baseball Roster Construction
Timothy Chan and Douglas S. Fearing
Drawing inspiration from the theory of production flexibility in manufacturing networks, we provide the first optimization-based analysis of the value of positional flexibility (the ability of a player to play multiple positions) for a major league baseball team in the presence of injury risk. First, we develop novel statistical models to estimate (1) the likelihood and duration of player injuries during the regular season, and (2) fielding abilities at secondary fielding positions. Next, we develop a robust optimization model to calculate the degradation in team performance due to injuries. Finally, we apply this model to measure the difference in performance between a team with players who have positional flexibility and a team that does not. We find that using 2012 rosters, flexibility was expected to create from 3% (White Sox) to 15% (Cubs) in value for each team, measured in runs above replacement. In analyzing the results, we find that platoon advantages (e.g., having left-handed batters face right-handed pitchers) form an important component of flexibility. As a secondary finding, based on our statistical analysis of injuries, we find that the likelihood of injury increases with age, but the duration of injury does not.
Citation: Chan, Timothy, and Douglas S. Fearing. "The Value of Flexibility in Baseball Roster Construction." Paper presented at the MIT Sloan Sports Analytics Conference, Boston, MA, March 1–2, 2013.
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Other Paper
| 2010
Modeling Passenger Travel and Delays in the National Air Transportation System
C. Barnhart, D. Fearing and V. Vaze
Many of the existing methods for evaluating an airline's on-time performance are based on flight-centric measures of delay. However, recent research has demonstrated that passenger delays depend on many factors in addition to flight delays. For instance, significant passenger delays result from flight cancellations and missed connections, which themselves depend on a significant number of factors. Unfortunately, lack of publicly available passenger travel data has made it difficult for researchers to explore the nature of these relationships. In this paper, we develop methodologies to model historical travel and delays for U.S. domestic passengers. We develop a discrete choice model for estimating historical passenger travel and extend a previously-developed greedy re-accommodation heuristic for estimating the resulting passenger delays. We report and analyze the estimated passenger delays for calendar year 2007, developing insights into factors that affect the performance of the National Air Transportation System in the United States.
Keywords: Performance Evaluation;
Research;
Business History;
Relationships;
Air Transportation Industry;
United States;
Citation: Barnhart, C., D. Fearing, and V. Vaze. "Modeling Passenger Travel and Delays in the National Air Transportation System."
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Other Paper
| 2010
Analyzing Air Travel Disruptions in the National Air Transportation System
C. Barnhart, D. Fearing and V. Vaze
Many of the existing methods for evaluating an airline's on-time performance are based on flight-centric measures of flight delay. However, recent research has demonstrated that as much as 50% of passenger delays are caused by passenger travel disruptions, either flight cancelations or missed connections. The propensity for disruptions varies significantly across airports and carriers, based on key factors such as scheduling practices, network structures, and passenger connections. In this paper, we analyze the causes and costs of U.S. passenger travel disruptions by applying data analysis and statistical modeling to historical flight and passenger data. The passenger travel and delay data we use for our analysis is estimated from publicly available data sources using a methodology previously developed to disaggregate passenger demand data. We find that cancelations, which are the largest cause of disruption-related passenger delays, vary substantially across carriers, even when accounting for baseline variability across airports. Passenger and operational considerations also play a significant role in cancelation decisions. Regarding missed connections, much of the variability can be explained just by flight delays for the airport and carrier, though flight schedule construction is also a critical factor. Highly peaked (or banked) flight schedules tend to reduce connection times and therefore increase the risk of missed connections. Last, we demonstrate the importance of a variety of factors on the ease of re-accommodating disrupted passengers.
Keywords: Customer Focus and Relationships;
Decisions;
Data and Data Sets;
Time Management;
Measurement and Metrics;
Service Delivery;
Service Operations;
Networks;
Mathematical Methods;
Air Transportation Industry;
United States;
Citation: Barnhart, C., D. Fearing, and V. Vaze. "Analyzing Air Travel Disruptions in the National Air Transportation System."
Research Summary
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Research Summary
Airline Schedule Disruptions
by
Douglas S. Fearing
Increasing congestion and frequent schedule disruptions throughout the National Air Transportation System, both at airports and en route, have led to significant flight and passenger delays. Professor Fearing's primary research focus is on measuring and reducing these costs. He approaches the problem of congestion and disruptions from a perspective that encompasses the concerns of all major stakeholders - regulators, airlines, and passengers - in order to expand the potential savings and to facilitate acceptance.
Performance Measurement
Professor Fearing has researched and developed new tools for measuring performance of the National Air Transportation System. These tools use statistical and optimization techniques, and incorporate the concerns of multiple stakeholders. One such tool is a novel and justifiable fairness metric for evaluating schedule allocation techniques used during severe disruptions. To measure passenger impacts and facilitate passenger-centric research endeavors, Professor Fearing has helped develop a statistical approach for estimating historical passenger travel and delays.
Improvement Opportunities
Using the tools described above, Professor Fearing has shown that there are significant opportunities for cost savings in the coordination of Traffic-Flow Management (TFM) programs. Specifically, he has shown that applying an optimization-based approach to managing these programs could lead to savings on the order of $50 million per year in the United States. The paper describing this research was selected by the airline industry group AGIFORS as the winner of its 2009 Anna Valicek Medal. His current research focuses on the trade-offs between capacity and predictability in the construction of these programs. Keywords: performance measurement;
air transportation;
traffic flow management;
Air Transportation Industry;
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Research Summary
Sports Management
by
Douglas S. Fearing
Professor Fearing's secondary research interest in sports management shares an emphasis on developing new metrics to help understand and improve performance. Keywords: sports management;
Sports Industry;
Teaching
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Teaching Interest
Overview
by
Douglas S. Fearing
In the MBA program, Professor Fearing teaches Technology and Operations Management (TOM), a required first-year MBA course.
In January 2013 he traveled with a cohort of students to Sao Paolo, Brazil as part of the FIELD 2 Global Immersion program, also a requirement of the first-year MBA curriculum. The FIELD program gives students the opportunity to study business opportunities in emerging markets.
He is currently teaching Stochastic Modeling for the spring 2013 semester. He developed this course for the TOM Operations Management doctoral required curriculum. It covers the modeling, analysis, and control of stochastic systems.
Awards & Honors
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Douglas S. Fearing: Winner of the 2013 Alpha Award for Best Research Paper at the 2013 Sloan Sports Analytics Conference for his paper with Timothy Chan, "The Value of Flexibility in Baseball Roster Construction."
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Douglas S. Fearing: Won the 2011 INFORMS Aviation Applications Section Dissertation Prize for "The Case for Coordination: Equity, Efficiency, and Passenger Impacts in Air Traffic Flow Managment" (MIT, 2010).
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Douglas S. Fearing: Received the 2009 MIT Graduate Student Council Teaching Award.
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Douglas S. Fearing: Received the MIT Sloan School of Management Outstanding Teaching Assistant Award in 2009.
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Douglas S. Fearing: Received the Graduate Research Award for 2009/2010 from the Airport Cooperative Research Program.
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Douglas S. Fearing: Received the MIT Center for Transportation and Logistics UPS Ph.D. Fellowship for 2009/2010.
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Douglas S. Fearing: Received the 2009 Anna Valicek Award from AGIFORS (the Airline Group of the International Federation of Operational Research Societies).
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