Bayesian paired comparison with the bpcs package

This article introduces the bpcs R package (Bayesian Paired Comparison in Stan) and the statistical models implemented in the package. This package aims to facilitate the use of Bayesian models for paired comparison data in behavioral research. Bayesian analysis of paired comparison data allows parameter estimation even in conditions where the maximum likelihood does not exist, allows easy extension of paired comparison models, provides straightforward interpretation of the results with credible intervals, has better control of type I error, has more robust evidence towards the null hypothesis, allows propagation of uncertainties, includes prior information, and performs well when handling models with many parameters and latent variables. The bpcs package provides a consistent interface for R users and several functions to evaluate the posterior distribution of all parameters to estimate the posterior distribution of any contest between items and to obtain the posterior distribution of the ranks. Three reanalyses of recent studies that used the frequentist Bradley–Terry model are presented. These reanalyses are conducted with the Bayesian models of the bpcs package, and all the code used to fit the models, generate the figures, and the tables are available in the online appendix

Understanding daily car use: Driving habits, motives, attitudes, and norms across trip purposes

This paper presents a classification of motives considered as relevant when selecting a mode of transport, and it examines the relative importance of driving habits, car attitudes, descriptive norms and motives for transport mode choices for commuting, shopping, leisure and child-related trips. A survey was sent by post to 3000 Swedish residents in metropolitan, semi-rural and rural areas (with a response rate of 34.6%). Through an ordinal factor analysis, three classes of motives were extracted: Perceived outcomes, Symbolic and Instrumental motives. Hierarchical proportional odds logistic regression and hierarchical linear regression models assess the relative importance of socio-demographic variables, motives, descriptive norms, car attitudes and driving habits for each kind of trip. These models indicate that the impact of socio-demographic and psychological variables varies across trip purposes. Commuting and child- related trips were primarily predicted by socio-demographic variables. Leisure and shopping trips were mostly predicted by driving habit. Driving habit was a common and strong predictor among all trip purposes. These results are evidence of the power of script-based trips to generate habitual travel behaviours across different trip purposes. Conclusions are made in the light of the usefulness of these results to practitioners and researchers who aim to foster sustainable transportation and to reduce private car use

A future without drivers? Comparing users\u27, urban planners\u27 and developers\u27 assumptions, hopes, and concerns about autonomous vehicles

AimThis study identifies and compares perceptions of autonomous vehicle (AV) implementation among three Swedish stakeholder groups: Future Users, Urban Planners, and Developers.MethodSemi-structured comparative focus groups were conducted separately with each of the three groups of stakeholders and the transcripts were analysed in broad themes using thematic analysis.ResultsAssumptions, hopes, concerns, and direction of development were the main themes that emerged from the analysis. Assumptions included electrification of vehicles, changes in travel demand, and the need for regulations; Hopes included the idea that AVs will contribute to a more accessible and safer transport system; Concerns included overtrust in AV technology, a possible detrimental impact on the city in the form of congestion and higher demand for investments in infrastructure that could outcompete other modes of transport; and Direction of development and their own role, where the need for collaboration between stakeholders and implementation of AVs in connection with society’s needs were emphasised.ConclusionsAVs were seen to lead to both positive and negative consequences depending on implementation and the development of society. The study shows that dialogue between different stakeholders is lacking but it is desired for the inclusive implementation of AV