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We present a summary of important computational issues and opportunities that arise from the use of semi-aggregate data (where the explanatory data for choice scenarios are not necessarily unique for each decision-maker) in discrete choice models. These data are encountered with large transactional databases that have limited consumer information, a common feature in some transportation planning applications, such as airline itinerary choice modeling. We developed a freeware software package called Larch, written in Python and C++, to take advantage of these kind of data to greatly speed the estimation of discrete choice model parameters. Benchmarking experiments against Stata (a commonly used commercial package), Biogeme (a commonly used freeware package), and ALOGIT (a highly specialized commercial package for discrete choice modeling) based on an industry dataset for airline itinerary choice modeling applications shows that the size of the input estimation files are 50–100 times larger in Stata and Biogeme, respectively. Estimation times are also much faster in ALOGIT and Larch; e.g. , for a small itinerary choice problem, a multinomial logit model estimated in ALOGIT or Larch converged in less than one second whereas the same model took almost 15 seconds in Stata and more than three minutes in Biogeme. [ABSTRACT FROM AUTHOR]

Abstract: Historically, peaked schedules have been used with hub-and-spoke networks to maximize passenger connection opportunities. Although peaked schedules can generate more attractive connecting itineraries and revenue for an airline, they are costly to operate because additional manpower and equipment resources are needed to serve the peak periods. Several airlines experimented with depeaking their hubs as a way to reduce costs and improve operations in the 2000s. Prior studies have quantified operational improvements and cost savings associated with depeaking; however, none have quantified revenue impacts. We use difference-in-differences methods to quantify revenue and operational impacts associated with depeaking for five U.S. hubs. Results show that depeaking tends to improve operations, but may negatively impact revenue per available seat mile (RASM). In some cases, revenue losses exceed reported cost savings. [Copyright &y& Elsevier]

The article presents a study on the influence of bus design factors on door crowding and quantified its impact on operational performance and passenger safety, particularly in the case of Dhaka, Bangladesh. Results showed the effect of door placement, aisle length, presence of a front seating area and service type on door crowding. Analysis revealed the association between door crowding and longer marginal passenger boarding times and increased number of unsafe boarding and alighting movements.

Abstract: There has been an increase in the number of involuntary denied airline passenger boardings in the US. A denied boarding is influenced by multiple factors other than compensation amounts, including the accuracy, magnitude, and variability associated with no-show forecasts, load factors, and carriers’ day of departure operating policies. We describe how these and other factors influence denied boardings, why they differ across US carriers, and why carriers have strong internal incentives to reduce denied boardings. [Copyright &y& Elsevier]

Abstract: This study investigates when and why business travelers make changes to their airline itineraries. Results are based on tickets purchased over a 9-month period by employees of a university in Atlanta, US. The ability to track repeat passengers purchases across time allows analysis of how passenger cancellation behavior differs by frequency of travel as well as by carrier. Results indicate that frequent travelers and those purchasing from Delta versus AirTran are more likely to request ticketing changes. Other factors influencing cancellation behavior include the time from ticket purchase, time before flight departure, and whether the itinerary is for the outbound or inbound portion of a trip. [Copyright &y& Elsevier]

This is the first study of airline travelers’ no-show and standby behavior based on passenger and directional outbound/inbound itinerary data. The paper describes passengers’ behavior based on estimation of a multinomial logit model for domestic US itineraries departing in March 2001 or March 2002. This enables us to explore behavioral differences based on passenger and itinerary characteristics as well as identify differences in rescheduling behavior occurring after September 11, 2001. Benefits of using passenger data to improve forecasting accuracy and support a broad range of managerial decisions are described. [Copyright &y& Elsevier]

New air service routes are viewed as an important driver of local and regional economic growth by some communities. In the United States (U.S.), this recognition has led to an increase in: (1) the number of airports offering air service incentive agreements, and (2) the frequency with which new agreements are initiated. Despite the recognized economic importance of air service incentives, and an identified need for a database categorizing U.S. air service incentives, no such database existed. This project fills that gap by compiling a database for all 382 U.S. commercial airports included in the Federal Aviation Administration's 2017 Terminal Area Forecast and makes it publicly available to other researchers via an online geographic information system (GIS) tool. In this paper, we describe this new database, provide a descriptive analysis of air service incentive agreements in the U.S., and identify topics future research can investigate using our database. It is our hope that this database will serve as a foundation on which to build new research related to air service incentive programs. • Researchers created a comprehensive database of air service incentive programs (ASIPs) in the U.S. • The ASIP database is available to researchers as an online GIS tool. • The database provides descriptions of the ASIPs for all commercial U.S. airports. • This paper identifies research topics that could be investigated using our database. [ABSTRACT FROM AUTHOR]