Understanding Consumer Demand for New Transport Technologies and Services, and Implications for the Future of Mobility

Vij, Akshay

doi:10.1007/978-3-030-12180-8_5

Cited by 3 publications

(1 citation statement)

References 38 publications

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“…Para os autores, a sensação de segurança experimentada pelo usuário, avaliações de conforto do veículo, preço e tempo total de viagem são algumas razões importantes que podem justificar o uso do serviço. Vij (2020) e Lasmar Junior et al (2017 fazem uma análise de novas formas de mobilidade urbana, como por exemplo o Ridesharing 6 , Carsharing 7 , Bikesharing 8 e veículos autônomos, onde a Uber é um dos principais exemplos do Carsharing e um dos principais investidores em veículos autônomos. Além disso, os autores destacam novos modelos de negócios que as fabricantes de automóveis estão desenvolvendo com o objetivo de se ajustarem ao mercado, evitando maiores perdas.…”

Section: Revisão De Literaturaunclassified

A plataforma Uber e o mercado de automóveis no Brasil

Lopes Soyer,

Aparecida Fernandes

2023

Eco.Reg.

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O presente estudo teve como objetivo analisar o comportamento da demanda brasileira de automóveis a partir da entrada da plataforma Uber no mercado, considerando variáveis microeconômicas, macroeconômicas, crédito e a Plataforma Uber. O método utilizado foi o Binomial Negativo, pois o estudo abrange dados de contagem, positivos e discretos, com superdispersão. Os resultados obtidos sugerem que na presença da Plataforma Uber, houve uma redução em 26,6% na taxa de incidência mensal de emplacamentos de carros. Nesse contexto, é importante que a indústria automobilística esteja apta a fazer transformações, até mesmo, de paradigmas.

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Section: Revisão De Literaturaunclassified

A plataforma Uber e o mercado de automóveis no Brasil

Lopes Soyer,

Aparecida Fernandes

2023

Eco.Reg.

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Fusing Repeated Cross-Sectional Revealed Preference Datasets based on Rational Inattention Theory: Accounting for Changing Modal Preferences

Hossain,

Habib

2024

Transportation Research Record: Journal of the Transportation R

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To address the methodological limitation of cross-sectional studies and the data constraints of longitudinal/panel studies, this paper presents a model-based method to fuse repeated cross-sectional travel survey data based on the theory of rational inattention (RI) in discrete choice modeling. In the proposed framework, older cross-sectional data are used to model the prior probability of choice alternatives, and more recent cross-sectional data are used to capture conditional heterogeneous choices. The fusion method is theoretically more robust and computationally less burdensome than existing data pooling techniques. The method is empirically tested using data from two cycles of a large-sample post-secondary student travel survey in the Greater Toronto and Hamilton Area to investigate the commuting mode choices of post-secondary students. Parameter estimates of the RI-based multinomial logit (MNL) model indicate that the proposed method can generate behaviorally consistent results. Validation of the estimated model using a holdout sample indicates its improved forecasting performance compared with the classical random utility maximizing MNL model. The fusion method can be extended to more than two cycles of repeated cross-sectional data by updating the prior probabilities whenever new cross-sectional data become available. Thus, the study presents a continuous framework for fusing information from multiple time points using repeated cross-sectional datasets to capture preference evolution better and enhance the forecasting robustness of discrete choice models.

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Carsharing: Business models, and role of the decision maker

Rotaris¹,

Bumbulovic²

2020

Economics and Policy of Energy and the Environment

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Individuals' mobility needs are constantly increasing both in urban and in less-densely popu-lated areas. Private transport activities are intensifying, creating unsustainable environmental pressure and absorbing a too large amount of resources, forcing to social exclusion the popu-lation segments which cannot bear the cost of private transport. Car sharing has proven to be a viable solution to alleviate at least partially these problems. Many different business models are used to provide the service. Organizational and technical innovations have changed the market, opening the supply to new providers and serving segments of the latent demand which were not reached by the traditional operators. The role played by the decision marker to sup-port the development of this market in its various forms has been essential and will still be crit-ical in order to guide a smooth transition from the private use of traditional vehicles to the shared use of autonomous ones. The purpose of this paper is to shed light on these changing characteristics of the carsharing market with a special focus on the Italian context.

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Understanding Consumer Demand for New Transport Technologies and Services, and Implications for the Future of Mobility

Cited by 3 publications

References 38 publications

A plataforma Uber e o mercado de automóveis no Brasil

A plataforma Uber e o mercado de automóveis no Brasil

Fusing Repeated Cross-Sectional Revealed Preference Datasets based on Rational Inattention Theory: Accounting for Changing Modal Preferences

Carsharing: Business models, and role of the decision maker

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