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149 results on '"Voltes-Dorta, Augusto"'

2. A Multilayered Block Network Model to Forecast Large Dynamic Transportation Graphs: an Application to US Air Transport

Author

Rodriguez-Deniz, Hector, Villani, Mattias, and Voltes-Dorta, Augusto

Subjects
Statistics - Machine Learning, Computer Science - Machine Learning, Statistics - Applications, Statistics - Methodology
Abstract

Dynamic transportation networks have been analyzed for years by means of static graph-based indicators in order to study the temporal evolution of relevant network components, and to reveal complex dependencies that would not be easily detected by a direct inspection of the data. This paper presents a state-of-the-art probabilistic latent network model to forecast multilayer dynamic graphs that are increasingly common in transportation and proposes a community-based extension to reduce the computational burden. Flexible time series analysis is obtained by modeling the probability of edges between vertices through latent Gaussian processes. The models and Bayesian inference are illustrated on a sample of 10-year data from four major airlines within the US air transportation system. Results show how the estimated latent parameters from the models are related to the airline's connectivity dynamics, and their ability to project the multilayer graph into the future for out-of-sample full network forecasts, while stochastic blockmodeling allows for the identification of relevant communities. Reliable network predictions would allow policy-makers to better understand the dynamics of the transport system, and help in their planning on e.g. route development, or the deployment of new regulations.

Published
2019

7. List of contributors

Author

Burghouwt, Guillaume, primary, Buyle, Sven, additional, Cambini, Carlo, additional, Cavusoglu, S. Sera, additional, Congiu, Raffaele, additional, Cunha, Duarte, additional, de Wit, Jaap, additional, Dewulf, Wouter, additional, Fearon, Colm, additional, Forbes, Silke, additional, Khammash, Laura, additional, Li, Yufei, additional, Macário, Rosário, additional, Marques, Carlos Filipe, additional, Martini, Gianmaria, additional, Martín, Juan Carlos, additional, McLaughlin, Heather, additional, Musso, Antonio, additional, Mustapha, Chaouki, additional, Piccioni, Cristiana, additional, Reis, Vasco, additional, Stolfa, Andrea, additional, Strandenes, Siri P., additional, Van Asch, Thomas, additional, Van de Voorde, Eddy, additional, van Houten, Lisanne, additional, and Voltes-Dorta, Augusto, additional

Published
2022
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18. Contributors

Author

Albalate, Daniel, primary, Budd, Thomas, additional, Decroly, Jean-Michel, additional, Dobruszkes, Frédéric, additional, Duval, David Timothy, additional, Fageda, Xavier, additional, Fichert, Frank, additional, Goetz, Andrew R., additional, Graham, Anne, additional, Halpern, Nigel, additional, Hanke, Michael, additional, Henderson, Isaac Levi, additional, Humphreys, Claire, additional, Martín, Juan Carlos, additional, Metz, David, additional, O’Connell, John F., additional, Ramos-Pérez, David, additional, Ryley, Tim, additional, Tsui, Wai Hong Kan, additional, Voltes-Dorta, Augusto, additional, and Wattanacharoensil, Walanchalee, additional

Published
2019
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30. A multilayered block network model to forecast large dynamic transportation graphs : An application to US air transport

Author

Rodriguez Déniz, Héctor, Villani, Mattias, Voltes-Dorta, Augusto, Rodriguez Déniz, Héctor, Villani, Mattias, and Voltes-Dorta, Augusto

Abstract

Dynamic transportation networks have been analyzed for years by means of static graph-based indicators in order to study the temporal evolution of relevant network components, and to reveal complex dependencies that would not be easily detected by a direct inspection of the data. This paper presents a state-of-the-art probabilistic latent network model to forecast multilayer dynamic graphs that are increasingly common in transportation and proposes a community-based extension to reduce the computational burden. Flexible time series analysis is obtained by modeling the probability of edges between vertices through latent Gaussian processes. The models and Bayesian inference are illustrated on a sample of 10-year data from four major airlines within the US air transportation system. Results show how the estimated latent parameters from the models are related to the airlines’ connectivity dynamics, and their ability to project the multilayer graph into the future for out-of-sample full network forecasts, while stochastic blockmodeling allows for the identification of relevant communities. Reliable network predictions would allow policy-makers to better understand the dynamics of the transport system, and help in their planning on e.g. route development, or the deployment of new regulations., Funding: Wallenberg AI, Autonomous Systems and Software Program (WASP) - Knut and Alice Wallenberg Foundation, Sweden

Published
2022
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45. The spatial and quality dimensions of Airbnb markets.

Author

Voltes-Dorta, Augusto and Inchausti-Sintes, Federico

Subjects
PRODUCT differentiation, PRICE increases, SPACE in economics, SHARING economy
Abstract

Airbnb is now present in many tourist destinations worldwide. With the pricing power in the hands of the individual hosts, the assessment of competition is of great relevance. Despite the many studies on the drivers of Airbnb prices, there is no contribution yet on how quality affects the spatial dimensions of Airbnb markets. We aim to fill this gap with a case study of Bristol (United Kingdom). Using standard regression techniques, we find a quality-moderated spatial decay in the price effects of competition in local Airbnb markets. Thus, the price of a given listing is affected negatively by other listings within a set of radii that decrease with product differentiation. Beyond this local market boundary, the existence of other listings may increase prices, as demand is driven to the neighborhood- or city-wide markets because of the diversity of tourism accommodation. [ABSTRACT FROM AUTHOR]

Published
2021
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50. The Impact of Accommodation Taxes on Outbound Travel Demand from the United Kingdom to European Destinations.

Author

Heffer-Flaata, Hedvig, Voltes-Dorta, Augusto, and Suau-Sanchez, Pere

Subjects
*ELASTICITY (Economics), *TAXATION, *HOTEL rooms
Abstract

Despite the progressive introduction of accommodation taxes in many European cities, there is no consensus in the literature as to whether they have positive or negative effects. This may be related to the lack of estimates of the elasticity of visitor demand to accommodation taxes. To fill this gap, we carry out two panel-data regressions using a data set of airline travelers from UK cities to Spanish, French, and Italian destinations between 2012 and 2018. The results from the two-stage least squares regressions indicate that UK international travelers are indeed sensitive to hotel taxes. However, the impact of these taxes differs between peak and off-peak periods and across destination countries, with French destinations showing the most negative effect on visitor flows. The analysis of tax elasticities at a destination level also reveals the lack of a significant negative impact on visitor flows to major cities like Venice or Barcelona. [ABSTRACT FROM AUTHOR]

Published
2021
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