Estimating commuter rail demand to Kendall Square along the Grand Junction Corridor

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 113-114).Since acquiring the Grand Junction Railroad in June 2010 from CSX, the Massachusetts Bay Transit Authority (MBTA) has explored the possibility of using the line for commuter rail service. In addition the Grand Junction right-of-way has been the subject of other proposals, including a multi-use path by the City of Cambridge and a Bus Rapid Transit (BRT) line as part of the MBTA's Urban Ring study. In September of 2010, our team was asked to examine the possibility of adding passenger service along the Grand Junction Railroad in Cambridge, MA. This new service would allow the current Worcester/Framingham commuter rail line to serve both North and South stations. In response, we performed an analysis based on the existing conditions of the railroad and projected future growth of the Kendall Square business area. To perform this analysis a demand model was developed using the 2010 MIT Transportation Survey and 2000 Census Bureau Journey to Work data. The demand model was used to forecast ridership on the Grand Junction Railroad, for multiple alternatives which included the addition of a commuter rail station at Kendall Square, use of diesel multiple units to improve frequency, and a short high frequency route starting at Auburndale. The results of the analysis demonstrate that a high frequency service from Worcester along the Grand Junction Corridor attracts the most riders, approximately 1,800 peak morning commuters. With the Auburndale service and lower frequency Worcester trains having moderate ridership estimates. This forecast combined four types of riders: new inbound riders to Kendall Square, redirected inbound riders to Kendall Square, new inbound riders to Boston, and redirected reverse riders from North Station. In addition to demonstrating how the demand model and the rider survey dataset were developed this report provides a framework for a more detailed study into potential uses for passenger service along the Grand Junction Railroad.by Adam Bockelie and James Dohm.M.Eng

Ancillary services in the airline industry : passenger choice and revenue management optimization

Thesis: Ph. D. in Transportation, Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2019Cataloged from PDF version of thesis.Includes bibliographical references (pages 274-282).The recent proliferation of ancillary services means that airline passengers can face substantially different ancillary service prices and offerings based on their itinerary and fare class selection. At the same time, airlines have become interested in accounting for this supplementary revenue stream in their revenue management (RM) systems to maximize total, not just ticket, revenue. This thesis develops models for both of these issues, with a goal of providing a better understanding of how ancillary services affect the airline industry. We develop the Ancillary Choice Model (ACM) to describe how passengers make purchase decisions about ancillary services in conjunction with the selection of a fare class. We model two extremes of passenger knowledge and awareness of ancillary services, which we term simultaneous and sequential. We show that under the simultaneous model, the presence and price of ancillary services can affect the fare class selection of a passenger, even when all fare classes have the same ancillary prices. The second part of this thesis studies total revenue optimization. We provide a detailed assessment of a prior total revenue maximization approach, the Optimizer Increment (01), proving that it can be an optimal revenue management strategy under limited conditions, but also showing through the Passenger Origin-Destination Simulator (PODS) that it decreases revenue in more realistic environments. We then develop a new revenue management optimization model, the Ancillary Choice Dynamic Program (ACDP), which maximizes total revenue by explicitly including the revenue and fare class choice impacts of ancillary services. We describe an Ancillary Marginal Demand (AMD) and Ancillary Marginal Revenue (AMR) transformation that can be used as heuristics to provide the ancillary and choice awareness benefits of ACDP to existing RM optimization models.by Adam Bockelie.Ph. D. in TransportationPh.D.inTransportation Massachusetts Institute of Technology, Department of Civil and Environmental Engineerin

Dynamic offer generation in airline revenue management

Abstract The New Distribution Capability and new retailing platforms will enable airlines to respond to shopping requests with bundled offers of flights and ancillary services, representing an evolution from traditional, flight-focused optimization. Assembling an attractive set of offers to display to customers therefore represents a new joint pricing and assortment optimization problem in airline revenue management. In this paper, we introduce an initial optimization approach for the selection and pricing of a la carte and bundled flight and ancillary offers. First, we propose a customer choice model that captures the impact of ancillary bundles on flight itinerary choice. We then calculate prices for each offer from a continuous range of price points and display the offer set that maximizes expected revenue for a given customer segment. We illustrate the approach using a single-flight, single-ancillary base case and discuss extensions to more complex environments. Tests in the Passenger Origin–Destination Simulator (PODS) show that dynamic offer generation (DOG) can increase net revenue when used by one or more airlines in a competitive network, assuming that the airlines are able to accurately segment incoming requests and estimate the average willingness-to-pay of each segment. We find that the majority of the revenue gains of DOG are due to competitive effects from the dynamic pricing of the flight component of the offer. The bundling mechanism of DOG is a secondary source of revenue gain that can be realized when customers take bundled ancillary services into account when choosing the flight. Our results provide insight for practitioners that are implementing offer optimization systems and processes. For example, in line with the previous literature on bundle pricing, we find that in transparent distribution channels an ancillary service should be bundled with the flight when the valuation for the ancillary is high or when its marginal cost of provision is low. We close by discussing the strategic and managerial implications of a move from traditional distribution strategies to a next-generation, offer-focused approach

Shorebird patches as fingerprints of fractal coastline fluctuations due to climate change

Introduction: The Florida coast is one of the most species-rich ecosystems in the world. This paper focuses on the sensitivity of the habitat of threatened and endangered shorebirds to sea level rise induced by climate change, and on the relationship of the habitat with the coastline evolution. We consider the resident Snowy Plover (Charadrius alexandrinus nivosus), and the migrant Piping Plover (Charadrius melodus) and Red Knot (Calidris canutus) along the Gulf Coast of Mexico in Florida. Methods: We analyze and model the coupled dynamics of habitat patches of these imperiled shorebirds and of the shoreline geomorphology dictated by land cover change with consideration of the coastal wetlands. The land cover is modeled from 2006 to 2100 as a function of the A1B sea level rise scenario rescaled to 2 m. Using a maximum-entropy habitat suitability model and a set of macroecological criteria we delineate breeding and wintering patches for each year simulated. Results: Evidence of coupled ecogeomorphological dynamics was found by considering the fractal dimension of shorebird occurrence patterns and of the coastline. A scaling relationship between the fractal dimensions of the species patches and of the coastline was detected. The predicted power law of the patch size emerged from scale-free habitat patterns and was validated against 9 years of observations. We predict an overall 16% loss of the coastal landforms from inundation. Despite the changes in the coastline that cause habitat loss, fragmentation, and variations of patch connectivity, shorebirds self-organize by preserving a power-law distribution of the patch size in time. Yet, the probability of finding large patches is predicted to be smaller in 2100 than in 2006. The Piping Plover showed the highest fluctuation in the patch fractal dimension; thus, it is the species at greatest risk of decline. Conclusions: We propose a parsimonious modeling framework to capture macroscale ecogeomorphological patterns of coastal ecosystems. Our results suggest the potential use of the fractal dimension of a coastline as a fingerprint of climatic change effects on shoreline-dependent species. Thus, the fractal dimension is a potential metric to aid decision-makers in conservation interventions of species subjected to sea level rise or other anthropic stressors that affect their coastline habitat.United States. Dept. of Defense (Strategic Environmental Research and Development Program, Project SI-1699