44 research outputs found
Role of car segment and fuel type in the choice of alternative fuel vehicles: A cross-nested logit model for the English market
\ua9 2023 The Authors. In this article, we study the role of car segment and fuel type in the choice of alternative fuel vehicles and in the prediction of its market. For this purpose, we propose a joint choice cross-nested logit model to understand the demand for alternative fuel vehicles (AFV) and to study substitutional patterns between fuel types and vehicle segments with a full revealed preference approach, using only publicly available real data at disaggregate (household) level in England. Our results show that, as hypothesised, fuel type choice is not independent from car segment choice. The correlation patterns in the chosen specification reveal that individual car alternatives belonging to the same car segment are strongly correlated, while a weaker correlation exists between alternatives from different segments which share the same fuel type. The results suggest that creating awareness for cleaner fuel alternatives might be more effective if a targeted approach that considers these substitutional patterns is used. From a policy standpoint, while purchase prices play an important role and government policies have been concentrated in reducing the gap between ICE vehicles and AFVs in this dimension, our models stress the relevance of the operating cost variable, suggesting that its effect might also be crucial in the purchase decision
Studying patterns of use of transport modes through data mining - Application to U.S. national household travel survey data set
Data collection activities related to travel require large amounts of financial and human resources to be conducted successfully. When available resources are scarce, the information hidden in these data sets needs to be exploited, both to increase their added value and to gain support among decision makers not to discontinue such efforts. This study assessed the use of a data mining technique, association analysis, to understand better the patterns of mode use from the 2009 U.S. National Household Travel Survey. Only variables related to self-reported levels of use of the different transportation means are considered, along with those useful to the socioeconomic characterization of the respondents. Association rules potentially showed a substitution effect between cars and public transportation, in economic terms but such an effect was not observed between public transportation and nonmotorized modes (e.g., bicycling and walking). This effect was a policy-relevant finding, because transit marketing should be targeted to car drivers rather than to bikers or walkers for real improvement in the environmental performance of any transportation system. Given the competitive advantage of private modes extensively discussed in the literature, modal diversion from car to transit is seldom observed in practice. However, after such a factor was controlled, the results suggest that modal diversion should mainly occur from cars to transit rather than from nonmotorized modes to transi
From mode choice to modal diversion: A new behavioural paradigm and an application to the study of the demand for innovative transport services
We analyse past research efforts that focus on modal diversion in the transport sector, as opposed to the classical mode choice concept, showing the added value of this alternative framework that emerges from the existing scientific literature. The modal diversion paradigm is then used to assess the relative importance of the technical performances of transport services on one hand and of the subjective factors of its potential users on the other, when forecasting the use of a new means among a group of white-collars working in a French research institute. We quantitatively show that multimodal habits and cognitive attitudes have an importance that is in general not negligible for this group, compared to that of the transport services performances, even if only these latter are routinely considered by engineers and planners. Beyond this, we find that the role of self-related factors further increased when the group was less familiar with the technological background and the subsequent operation of the new system, such as in the case of demand responsive transport service
Evaluating active travel and health economic impacts of small streetscape schemes: An exploratory study in London
Abstract
Introduction
This article proposes a low-cost approach that transport authorities can use to evaluate small-scale active travel interventions, including estimating health economic benefits from uptake of walking and/or cycling.
Methods
The method combines post-intervention intercept surveys with the re-use of routinely collected count data. While inferior to more robust, longitudinal methods, the approach represents good value use of primary and secondary data at a far lower cost, for interventions unlikely otherwise to be evaluated at all. It makes use of government-supported tools that estimate physical activity health benefits from increased active travel.
Findings
The article describes an example in which a residential street was closed to through motor traffic, which led to a decline of 90% in motor traffic volume and uplift in pedestrian and cycle counts. This example is exploratory in nature due to sample size (124 respondents). The intercept survey of pedestrians and cyclists found uplift in perceived quality of the local environment across various indicators. Results suggested that around a third of the increase in pedestrian and cycle counts post-scheme represents new journeys, mainly via mode shift, with most of the remaining two-thirds being diverted journeys. This information is used alongside the before-and-after count data to estimate new cycling and walking trips induced by the route improvement. Finally, the article estimates the health economic benefit resulting from increased physical activity, of approximately ÂŁ500,000 over 20 years.
Conclusions
The article demonstrates a method for estimating active traveluptake and associated health benefits for smaller schemes. If applied over a number of schemes, the results could then be used to create an evidence base that could be used in assessing possible benefits of future schemes
Let's Make Love: Whiteness, Cleanliness and Sexuality in the French Reception of Marilyn Monroe
Copyright © by SAGE PublicationsRichard Dyerâs seminal work on whiteness in film considers Marilyn Monroe as the epitome of an institutionally racist Hollywood system that imagines the most desirable woman to be blonde, given that blondeness is understood as a guarantee of whiteness. This article adds to other recent scholarship on Monroe that has sought to complicate this reading by examining other meanings that can be attributed to her bleached blonde hair. By closely analyzing media texts that discussed Monroe in 1950s France, this article demonstrates the way in which her performance of ideal American female sexuality was read through the prism of Monroe as icon of cleanliness and (linked) modernity. It examines the way in which Monroeâs modernity allowed her to partially escape the traditional feminine private sphere and it concludes that Monroeâs bleached blonde hair can be seen in this context as having liberatory potential
Contre l'Econométrie
Domarchi Jean. Contre l'Econométrie. In: Annales. Economies, sociétés, civilisations. 13ᔠannée, N. 2, 1958. pp. 308-321
L'Angleterre des Tudors et des Stuarts (Ă suivre)
Domarchi Jean. L'Angleterre des Tudors et des Stuarts (Ă suivre). In: Annales. Ăconomies, SociĂ©tĂ©s, Civilisations. 26á” annĂ©e, N. 5, 1971. pp. 1003-1020
H. R. Trevor-Roper, Religion, the Reformation and Social Change.
Domarchi Jean. H. R. Trevor-Roper, Religion, the Reformation and Social Change.. In: Annales. Economies, sociétés, civilisations. 23ᔠannée, N. 2, 1968. pp. 414-415
H. R. Trevor-Roper, Religion, the Reformation and Social Change.
Domarchi Jean. H. R. Trevor-Roper, Religion, the Reformation and Social Change.. In: Annales. Economies, sociétés, civilisations. 23ᔠannée, N. 2, 1968. pp. 414-415
Electric vehicle forecasts: a review of models and methods including diffusion and substitution effects
Governments worldwide are investing in innovative transport technologies to foster their development and widespread adoptions. Since accurate predictions are essential for evaluating public policies, great efforts have been devoted to forecast the potential demand and adoption times of these innovations. However, this proves to be challenging, and it often fails to deliver accurate predictions. Learning a lesson to guide future work is critical but difficult because forecast figures depend on modelling methods and assumptions, and exhibit a great variability in methodologies, data and contexts. This paper provides a critical review of the models and methods employed in the literature to forecast the demand for electric vehicles (EVs), with a focus on the methods for incorporating choice behaviour into diffusion modelling. The review complements and extends previous works in three ways: (1) it focuses specifically on the ways in which fuel type choice has been incorporated into diffusion models or vice-versa; (2) it includes a discussion on forecast accuracy, contrasting the predictions with the actual figures available and estimating an average root mean square error and (3) it compares models and methods in terms of their strengths and limitations, and their implications in forecasting accuracy. In doing that, it also contributes discussing the literature published between 2019 and 2021. The analysis shows that EV demand estimation requires solving the non-trivial issue of jointly modelling the factors that induce diffusion in a social network and the instrumental and psychological elements that might favour household adoption considering the available alternatives. Mixed models that integrate disaggregate micro-simulation tools to capture social interaction and discrete choice models for individual behaviour appear as an interesting approach, but like almost all methods analysed failed to deliver satisfactory results or accurate predictions even when using sophisticated modelling techniques. Further improvement in various components is still needed, in particular in the input data, which regardless of the method used, is key to the accuracy of any forecasting exercise.</p