Testing for inertia effect when a new tram is implemented

González, Rosa Marina; Marrero, Ángel S.; Cherchi, Elisabetta

doi:10.1016/j.tra.2017.02.007

Cited by 19 publications

(27 citation statements)

References 31 publications

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“…Other relevant research includes studies of the impact of inertia on adopting the new alternative which requires a combination of revealed-preference (RP) and stated-preference (SP) data or launching SP surveys twice, i.e. before and after the implementation of the novel facility/ service (González et al, 2017;Jensen et al, 2013). It has also been suggested that intrinsic personal preference might be a driving factor of choosing a specific alternative (International Air Transport Association, 2003), and that habit could act as a barrier to the change in mode choice bahviour and breaking old habits can potentially result in mode shift (Blainey et al, 2012;Thøgersen, 2006).…”

Section: Variety-seeking Analysismentioning

confidence: 99%

Accounting for the impact of variety-seeking: Theory and application to HSR-air intermodality in China

Song

Hess

Dekker

2018

Journal of Air Transport Management

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While variety-seeking has been analysed intensively in consumer marketing, little is known about its impact in the transport world where many novel travel services have emerged in recent years. In this paper, we investigate how variety-seeking could influence intercity travellers' mode choice decisions in the new context of HSR (high-speed rail)-air intermodality in China. The study is based on data collected in Shanghai, including responses to stated choice tasks and attitudinal statements on variety-seeking. An integrated choice and latent variable (ICLV) model is proposed with a view to provide us with a more behaviourally realistic explanation of respondents' choice decisions. The research findings suggest that variety-seeking has different impacts across modes, where variety seekers would be more likely to choose the newly-introduced integrated HSR-air option whereas variety avoiders have a higher propensity to choose car-air or traditional separate HSR-air alternative. Meanwhile, this study also examines the impact of various level-ofservice attributes in mode choice behaviour, with results implying that long layover would heavily impair the attractiveness of integrated HSR-air service, and integrated luggage handling service is favourable to attract intermodal passengers while the effect of integrated ticketing system remains ambiguous.

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Section: Variety-seeking Analysismentioning

confidence: 99%

Accounting for the impact of variety-seeking: Theory and application to HSR-air intermodality in China

Song

Hess

Dekker

2018

Journal of Air Transport Management

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“…Cantillo et al (2007) developed inertia models, which were later extended by Yáñez et al (2010). Similarly, González et al (2017) analysed positive and negative inertia in mode choice with revealed preference (RP) and stated preference (SP) data, based on a mixed logit model formulation. Cherchi et al (2013) used hybrid choice models to represent inertia by measuring the tendency to stick with the same alternative (inertia) via lagged variables.…”

Section: Introductionmentioning

confidence: 99%

The influence of panel effects and inertia on travel cost elasticities for car use and public transport

et al. 2021

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Studies on the impact of changes in travel costs on car and public transport use are typically based on cross-sectional travel survey data or time series analysis and do not capture intrapersonal variation in travel patterns, which can result in biased cost elasticities. This paper examines the influence of panel effects and inertia in travel behaviour on travel cost sensitiveness, based on four waves of the Mobility Panel for the Netherlands (comprising around 90,000 trips). This paper analyses the monetary costs of travel. Panel effects reflect (within wave) intrapersonal variations in mode choice, based on three-day trip diary data available for each wave. The impact of intrapersonal variation on cost sensitiveness is shown by comparing mode choice models with panel effects (mixed logit mode choice models with error components) and without panel effects (multinomial logit models). Inertia represents variability in mode choice between waves, measured as the effect of mode choice decisions made in a previous wave on the decisions made in the current wave. Additionally, all mode choice models include socio-economic and spatial variables but also mode preferences and life events. The effect of inertia on travel cost elasticities is measured by estimating mixed logit mode choice models with and without inertia effects. The main conclusion is that the inclusion of intrapersonal effects tends to increase cost sensitiveness whereas the inclusion of inertia effects decreases travel cost sensitiveness for car and public transport modes. Car users are identified as inert travellers, whereas public transport users show a lower tendency to maintain their usual mode choice. This paper reveals the inertia effects over four waves of repeated respondent’s data repeated yearly.

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“…A more complex formulation is needed to consider the effects of the direct social interaction by comparing the responses between the experiments SP1 and SP2. For this specific purpose, we adapt the methodology used to take into consideration the presence of inertia/habit (or propensity to change if inertia is negative) presented in previous travel behaviour research (Cantillo et al, 2007;Cherchi & Manca, 2011;González et al, 2017). As described in these studies, the inertia is the effect of "previous valuation of alternatives" on the present choice.…”

Section: Social Influence and Specification Of The Social Interaction Variablementioning

confidence: 99%

The effect of social influence and social interactions on the adoption of a new technology: The use of bike sharing in a student population

Manca

Sivakumar

Polak

2019

Transportation Research Part C: Emerging Technologies

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The present study investigates how social influence and social interactions can affect the adoption of new technologies, using stated preference (SP) survey data combined with an "accelerated reality" experience of social interaction among the respondents. Specifically, the intention to use a pro-environmental transport mode (the bike sharing) during a public transport strike within a cohort of students has been analysed. Previous studies have modelled social influence effects using SP data by providing a hypothetical scenario with simulated interactions or information about social conformity processes (i.e. social adoption) during the survey. In our paper, in addition to the impact of assumed social norms, the effect of live/real social interactions is included in the survey. SP survey is developed to investigate the effect of Level-of-Service attributes on the hypothetical choices in the scenario of a public transport strike. Besides the pre-defined attributes characterising the alternatives in the SP design, the survey includes techniques to acquire information on conformity and social interactions. Specifically, the interviewees undertake a before and after stated preference experiment (SP1 and SP2), with a period of group discussion in between the two parts. This SP experiment involves different cognitive and interpersonal mechanisms, such as the functional information exchange on benefits and drawbacks of cycling and bike sharing. The aim is to establish whether hypothetical scenarios of social conformity are different from real/live social interactions and whether these social influence processes actually affect the individuals' mode choice. A joint SP1/SP2 mixed logit (ML) model has been estimated to explore the choice behaviour of individuals and allows us to incorporate the inertia/propensity to change behaviour between SP1 and SP2. Moreover, considering the "Reflexive Layers of Influence" (RLI) framework, the processes generated by social interactions (diffusion, translation and reflexivity) are measured and incorporated in the model. We finally show the effect of these social influence variables on the goodness-of-fit of the models and choice simulation for prediction. We also draw conclusions about the value of such enhanced choice models in understanding and predicting the impacts of social interactions on choice behaviour in the context of new transport technologies.

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Testing for inertia effect when a new tram is implemented

Abstract: This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International licence Newcastle University ePrints -eprint.ncl.ac.uk

Cited by 19 publications

References 31 publications

Accounting for the impact of variety-seeking: Theory and application to HSR-air intermodality in China

Accounting for the impact of variety-seeking: Theory and application to HSR-air intermodality in China

The influence of panel effects and inertia on travel cost elasticities for car use and public transport

The effect of social influence and social interactions on the adoption of a new technology: The use of bike sharing in a student population

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