ACRP Graduate Student Paper - Understanding the Role of Online Media Platforms in Airport Capital Projects and Community Outreach
Max Li, Massachusetts Institute of Technology (MIT)Show Abstract
Megan Ryerson, University of Pennsylvania
Community outreach and engagement efforts are critical to an airport's role as an ever-evolving transportation infrastructure and regional economic driver. As online social media platforms continue to grow in both popularity and influence, a new engagement channel between airports and the public is emerging. However, the motivations behind and effectiveness of these social media channels remain unclear. In this work, we address this knowledge gap by better understanding the advantages, impact, and best practices of this newly emerging engagement channel available to airports. Focusing specifically on airport YouTube channels, we first document quantitative viewership metrics, and examine common content characteristics within airport YouTube videos. We then conduct interviews and site visits with relevant airport stakeholders regarding the motivations and workflow behind these videos. Finally, we facilitate sample focus groups designed to survey public perceptions regarding the effectiveness and value of these videos. We synthesize through COMBATED some action items, recommendations, and best practices from the four aforementioned project phases; in short, to maximize content effectiveness and community engagement potential, our resultant COMBATED framework emphasizes (C) consistency and community; (O) organizational structure; (M) momentum; (B) branding and buy-in; (A) activity; (T) two-way engagement; (E) enthusiasm; and (D) depth.
ASSESSMENT OF SOCIOECONOMIC IMPACT DIVERSIFICATION FROM TRANSPORT INFRASTRUCTURE PROJECTS: THE CASE OF A NEW REGIONAL AIRPORT
Dimitrios Dimitriou (email@example.com), Democritus University of ThraceShow Abstract
Maria SARTZETAKI, Democritus University of Thrace
In most of the cases the decision to invest in a new airport is not simple, mainly, because the complications in planning process, the amount of capital need to invest before the business establishment and the high number of stakeholders involved in decision process. The decision process is more complicated in restricted economic conditions and financing assumptions, where the project business plan performance is strongly related to regional development prospects and future airport business outputs in medium-long time horizon. This paper provides the evaluation methodology approach into a context to support decisions towards airport development projects. The proposed methodology provides an evaluation framework based on a combination of an ex ante assessment analysis taking into consideration the airport economic impact and its contribution to regional economy. The Input Output analysis framework is used to determine the economic footprint of the airport development and a series of key performance indicators is introduced to review the project performance in a given economic system. The case study focused on new airport in Heraklion of Crete (at Kasteli valley), which is one of the most attractive tourist destinations in south-east Mediterranean. Conventional wisdom is to present a systematic approach appropriate to apply is relevant projects, providing the essential tool to support decisions at level of strategic planning.
Long-Distance Airport Substitution and Air Market Leakage: Empirical Investigations in the U.S. Midwest
Kaleab Yirgu, University of AlbertaShow Abstract
Amy Kim (firstname.lastname@example.org), University of Alberta
Megan Ryerson, University of Pennsylvania
We investigate airport choice in three areas of the Midwest United States served by small and medium airports, where air travelers may instead choose to drive to a larger hub airport. We evaluate the proportion of travelers that bypass their local airport in order to travel from a large hub airport; these passengers are said to “leak” from their local airport to the large airport. We apply a hierarchical logit choice model, which accounts for air service attributes and airport access qualities, to millions of air travel itinerary records focusing on three large hub airports in the Midwest and their surrounding local airports. Results show that, in two of the three case study airports, a comparable increase in mean number of flight legs at both local and substitute airports promotes leakage. Distance to airport more strongly affects local airport choice than substitute airport choice for areas served by Gerald R. Ford International and Dane County Regional airports but influences substitute airport choice more at Milwaukee Mitchell International. Furthermore, findings confirm that a significant increase in total flight frequency at large hub (substitute) airports leads to a very modest increment in leakage to those airports. Overall, our study provides further empirical evidence of long distance airport “leakage” in parts of the Midwest, and its implications can be used by small airports seeking to further understand the airport choice of travelers within their local markets.
Social Sustainability Practices in Small Hub Airports in the United States
Caroline Marete, Purdue UniversityShow Abstract
Mary Johnson, Purdue University
Airports have economic impact on communities. In addition, there are impacts to the community in terms of environment and social aspects. Many of these impacts are influenced by airport management decisions. Airport sustainability may be thought of as having four primary areas: environmental, economic, operational, and social. The primary objective of this study is to better understand the adoption of social sustainability practices in small hub airport planning in the United States. The small hub airports in this study had previously participated in the Federal Aviation Administration (FAA) Airport Improvement Program (AIP) for sustainability planning and have published their sustainability masterplans. The standalone sustainability management plans or integrated sustainable master plans from six airports were gathered and examined as part of an exploratory case study analysis. The findings show that small hub airports appear to focus on economic sustainability more than on social sustainability. Additionally, social sustainability practices for these six small hub airports focus on four stakeholder categories: passengers and travelers, employees, communities and local businesses, and concessionaires and tenants. Small hub airports in this study included more practices related to stakeholder engagement and community involvement. Keywords: Small hub Airports, Airport Planning, Airport Sustainability, Sustainable Development, Social Sustainability, Sustainability Reporting, Federal Aviation Administration (FAA) Airport Improvement Program (AIP)
Route Optimization for Energy Efficient Airport Shuttle Operations – a Case Study from Dallas Fort Worth International Airport
Devon Sigler (Devon.Sigler@NREL.gov), National Renewable Energy Laboratory (NREL)Show Abstract
Qichao Wang, National Renewable Energy Laboratory (NREL)
Zhaocai Liu, National Renewable Energy Laboratory (NREL)
Venu Garikapati, National Renewable Energy Laboratory (NREL)
Andrew Kotz, National Renewable Energy Laboratory (NREL)
Caleb Phillips, National Renewable Energy Laboratory (NREL)
Monte Lunacek, National Renewable Energy Laboratory (NREL)
Kenneth Kelly, National Renewable Energy Laboratory (NREL)
Air travel and requisite surface traffic supporting passenger arrival/departure constitutes a significant portion of travel and emissions in cities with large airports. The priority of airport ground transport management teams is to provide passengers with a seamless travel experience, so it is understandable that the airport shuttle routes might not be optimized for minimizing energy consumption. Solutions that meet the dual objective of reducing energy consumption from airport shuttle operations without compromising on passenger travel experience are key to improving system efficiency. There is currently a dearth of research and tools that can inform airports in making such decisions. Addressing this need, this research effort puts forth an optimization model that generates optimal shuttle routes for a given set of constraints, and a discrete-event simulator that evaluates the optimal solutions in a stochastic environment to understand the tradeoffs between passenger wait times, and shuttle energy consumption. The proposed set of tools are tested in the context of optimizing airport shuttles routes within the Dallas Fort Worth International Airport (DFW). In addition to shuttle spatial positioning, and passenger demand information, high-fidelity vehicle data was collected using data loggers installed on DFW shuttles. Results show that 20% energy reduction in shuttle operations is possible with a modest increase in passenger wait times. The tools developed in this research effort are designed to be generalizable and can help optimize shuttle operations planning at any major airport.
Nudging consumers toward greener air travel by adding carbon to the equation in online flight search
Angela Sanguinetti, University of California, DavisShow Abstract
Nina Amenta, University of California, Davis
This study explores the potential to promote lower-emissions air travel by providing consumers with information about the carbon emissions of alternative flight choices in the context of online flight search and booking. We surveyed over 450 employees of the University of California, Davis, asking them to choose among hypothetical flight options for university-related business trips. Emissions estimates for flight alternatives were prominently displayed alongside cost, layovers and airport, and the lowest-emissions flight was labeled “Greenest Flight”. We found an impressive rate of willingness to pay for lower-emissions flights: around $200/ton of CO2E saved, a magnitude higher than that seen in carbon offsets programs. In a second step of analysis, we estimated the carbon and cost impacts if the university were to adopt a flight-search interface that prioritizes carbon emissions information and displays alternatives from multiple regional airports in their employee travel-booking portal. We estimated potential annual savings of 79 tons of CO2E, while reducing airfare costs by $56,000, mainly due to an increased willingness of travelers to take advantage of cheaper nonstop (lower-emissions) flights from a more distant airport in the region over indirect flights from their preferred airport for medium-distance flights. Institutionalizing this “nudge” within organizations with large travel budgets could have an industry-wide impact in aviation.
ACRP Graduate Student Paper - Automatic Speech Recognition for Air Traffic Control Communications
Sandeep Badrinath, Massachusetts Institute of Technology (MIT)Show Abstract
Hamsa Balakrishnan, Massachusetts Institute of Technology (MIT)
A significant fraction of communications between air traffic controllers and pilots is through speech, via radio channels. Automatic transcription of air traffic control (ATC) communications has the potential to improve system safety, operational performance, conformance monitoring, and to enhance air traffic controller training. We present an automatic speech recognition model tailored to the ATC domain that can transcribe ATC voice to text. The transcribed text is used to extract operational information such as call-sign and runway number. The models are based on recent improvements in machine learning techniques for speech recognition and natural language processing. We evaluate the performance of the model on diverse datasets.
Evaluation of air transportation network reliability during the COVID-19 pandemic: preliminary analysis
Joseph Pham, University of MinnesotaShow Abstract
Mingfeng Shang, University of Minnesota
Raphael Stern (email@example.com), University of Minnesota
In December 2019, the novel coronavirus that caused COVID-19 was first discovered in Wuhan, China. The outbreak rapidly spread to other countries and across the globe. One area that has been significantly disrupted as a result of the COVID-19 pandemic is transportation. Specifically, the global airline industry has seen a major shift in demand as people have started to travel less. With that in mind, the goal of this study is to quantify how significantly COVID-19 impacted the air transportation networks in the US. We look at air transportation network efficiency and reliability before and during the COVID-19 pandemic and use graph theoretic measures to quantify the impact both from the network operator perspective and from the perspective of the individual passenger. The results show that the number of daily flights in the US reduced up to 62% comparing with pre-COVID time, while statistical measures of abnormality indicated highly atypical behavior. Using the aviation network in the US, we evaluate the network efficiency of each airline and find that, from the network operator's perspective, air network efficiency is increased for 6 out of 8 airlines considered during the pandemic as a result of a more streamlined route network. However, for individual passengers, we find that more flight segments are required to reach a destination, with medium and small hub airports being the most heavily effected by lost of connectivity.
Exploration of Control Chart Capabilities to Distinguish Random and Anomalous Rare-Events Patterns in Aviation Incident Data
John Shortle, George Mason UniversityShow Abstract
Oleksandra Donnelly, George Mason University
Aviation is an extremely safe mode of transportation. Incidents and accidents are rare. As a result, time-series plots of incident counts may have a high variance, fluctuating up and down. It may be difficult to know whether sudden changes in the incident counts represent fundamental underlying changes in the National Airspace System (assignable causes) or are just attributable to noise (chance causes). Control charts have been widely used in manufacturing to help differentiate between these two types of causes. This paper implements and applies a control-chart methodology to aviation incident and accident data. While standard control charts are based on the assumption of normally distributed data, rare-event counts often follow a Poisson distribution. This paper uses both a standard (normal-based) control chart as well as a Poisson-based control chart. Several case studies applying the methodology to various accident/incident datasets are presented. The datasets investigated include NTSB incidents, Part 91 fatal accidents, Part 121 fatal accidents, near-mid-air collisions, and diverted flights.
Short-Term Forecasting of Air Cargo Demand from a European Airport Hub to the United States during COVID-19
Britt Verhoeven, Vrije Universiteit, AmsterdamShow Abstract
Nimo Van Hout, Vrije Universiteit, Amsterdam
Archika Devaraj, Vrije Universiteit, Amsterdam
Hans Zwitzer, KLM Royal Dutch Airlines
Terry Crapts, KLM Royal Dutch Airlines
Andrei Ion, KLM Royal Dutch Airlines
Thomas Koch, Vrije Universiteit
Elenna Dugundji, Vrije Universiteit, Amsterdam
Air cargo is mostly transported on passenger flights. During the COVID-19 outbreak, there have been worldwide restrictions on passenger transportation. Therefore, airlines experienced a capacity problem for air cargo. Better insight of air cargo demand during COVID-19 could contribute to the better arrangement of capacity by accordingly adapting flight schedules for cargo. The aim of this research was to make short-term predictions of air cargo demand between a major European airport hub and the United States during the COVID-19 pandemic. This was done for the month of May in 2020 by making 14-day predictions. The same was done for the year 2019 to observe whether the models performed well in the absence of the pandemic. The data set was compiled using data provided by a major commercial airline and exogenous features, such as stock market indices, foreign currency exchange rates and healthcare related predictions during COVID-19. To make the predictions, two classes of machine learning models for time series were compared: Autoregressive Integrated Moving Average (ARIMA) and Long Short-Term Memory (LSTM). In the year 2020, the best performing model among the ARIMA-based models is the Seasonal ARIMA including the exogenous feature Schedule . During the year 2019 the Seasonal ARIMA model without exogenous features generates the most accurate predictions. Among the LSTM models, the multivariate LSTM models outperform the univariate LSTM models in both years. Nonetheless, the ARIMA-based models are more accurate than the multivariate LSTM model in this research. Keywords: Air Cargo, COVID-19, Airlines, ARIMA, LSTM
Contribution of the Modernization of Viracopos Airport to the Economic Development of the Metropolitan Region of Campinas, SP, Brazil
Michelle Bandeira, Aeronautics Institute of TechnologyShow Abstract
Mauro Zackiewicz, Aeronautics Institute of Technology
Anderson Correia, Aeronautics Institute of Technology
Marcelo Xavier Guterres, Instituto Tecnologico de Aeronautica
Luiz Antonio Tozi, Aeronautics Institute of Technology
Bruna Almeida, Aeronautics Institute of Technology
This study proposes the application of the IO-Tables method to identify and evaluate the effects generated by the modernization of an airport infrastructure in the economy of a city or region in Brazil. Viracopos / Campinas International Airport was chosen, as a case study, due to recent changes in its administrative governance and operation profile, in addition to its importance for transport logistics in the metropolitan region of Campinas. The results of applying this method and estimates show that the social impacts of investments made by the public and private sectors at the airport were largely positive for society. Comparatively, in relation to the Brazilian economy, the direct and induced effects had a greater performance for the region of Campinas; however, the indirect effects performed below the national value. In summary, the influence of the economic development of one of the main airports in the country, facing the Metropolitan Region of Campinas, is positive and quite plausible, which shows that the direct, indirect and induced effects are important in the evaluation of the investment in the airport infrastructure of a region. Finally, it is important to highlight that this paper is innovative in Brazil and intends to highlight the contributions of the investments of the infrastructure installed for the development of the respective regions, developing methodologies and tools to support public and private decision makers.
Drivers and Effects of Merger and Acquisitions in the Airline Industry: A Case Study of Hong Kong
Jeff Lap In Man, Hong Kong Polytechnic UniversityShow Abstract
Min Xu, Hong Kong Polytechnic University
Saad Ahmed, Hong Kong Polytechnic University
The present study aims to figure out the drivers and motives behind merger and acquisitions (M&As) and their effects in the post-M&As scenarios, considering the case study of the acquisition of HK Express by Cathay Pacific in 2019. First, commercial situational analysis of four Hong Kong-based airlines has been done to understand the current and future scenarios. To identify the drivers behind M&As, several quantitative and qualitative research methods and techniques have been used such as interviews, collection, and analysis of market share data, on-time performance data, etc. These data are analyzed through linear regression, paired T-test, etc. We analyzed the case of Cathay Pacific acquisition in three steps: pre-acquisition stage, peri-acquisition stage, and post-acquisition stage. A total of 8 drivers of airline acquisition have been identified. They include weakening of the acquiree, strengthening of the acquirer, financial situation of the acquiree, compatibility of network, compatibility of business model, concerns of airport slots, branding of acquiree and external business environment. To examine the changes and effects of M&As, an improved Fishcer and Platzer model is used to study dimensions of post-merger effects. We figure out 5 different dimensions of effects brought by the acquisition including operational services, investor confidence, internal confidence, possible structural changes of the Cathay Group, and the possible changes towards the external business environment. This study may serve as a useful reference for relevant stakeholders.
ACRP Graduate Student Paper - The Competitive Effects of Joint Ventures in the International Airline Industry
Guofu Tan, University of Southern CaliforniaShow Abstract
Yinqi Zhang, University of Southern California
In the past two decades, many international airline carriers have expanded their cooperation by forming various joint ventures (JVs). One key feature of these JVs is that they allow carriers to determine certain airfares jointly and integrate their operations as a single carrier in the market for international air travel. In this paper, we try to evaluate the impact of JVs on airfares. We focus on a set of behind-to-gateway markets between a non-gateway U.S. city and a foreign gateway city, where both online and codeshare flights are offered, to study how the airfares of online flights are affected after carriers form JVs. We develop a new hypothesis that JVs increase the airfares of online flights. Based on this hypothesis, we build an empirical model to evaluate the Oneworld alliance’s transatlantic JV established in July 2010. Our empirical analysis, which uses the U.S. Department of Transportation (DOT)’s Airline Origin and Destination Survey (DB1B) international data from 2008 to 2013, indicates that Oneworld Transatlantic JV increased airfares of online flights by about three to four percent in the behind-to-gateway markets. Previous studies, which often emphasized the airfare reductions of codeshare flights in the connecting markets which include all kinds of non-gateway-to-gateway markets, may have overestimated the benefits to consumers from JVs. The DOT can better protect consumers by evaluating plausible airfare increases in online flights in the behind-to-gateway markets when reviewing new applications for JVs.
Will we fly again? Modelling air travel demand in light of COVID-19 through a London case study
Francesco Manca, Imperial College LondonShow Abstract
Aruna Sivakumar, Imperial College London
Jacek Pawlak, Imperial College London
Norbert Brodzinski, Imperial College London
The COVID-19 pandemic and associated travel restrictions have created an unprecedented challenge for the air transport industry, which before the pandemic was facing almost the exact opposite set of problems. Instead of growing demand and need for capacity expansion warring against environmental concerns, the sector is now facing a slump in demand and the continuing uncertainty regarding impacts of the pandemic on people’s willingness to fly. To shed light on consumer attitudes towards air travel during and post the pandemic, the study presents an analysis that draws upon recently collected survey data (April-June 2020), including both stated and revealed preference components, of 388 respondents who travelled from a London airport in 2019. A number of hypothetical travel scenarios taking into account circumstances and attitudes related to COVID-19 were explored. The data is analysed using a hybrid choice modelling approach to integrate latent constructs related to attitudinal characteristics. The analysis confirms the impact of consumer health concerns on their willingness to travel, as a function of travel characteristics, i.e. cost and number of transfers. It also provides insights into preference heterogeneity as a function of sociodemographic characteristics. However, no significant effects were observed concerning perceptions of safety arising from wearing a mask, or concerns over the necessity to quarantine. We also observe results suggesting that some respondents may perceive virtual substitutes for business travel, e.g. video calls and similar software, as only a temporary measure, and seek to return to travelling as soon as it is possible to do so safely.
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