Designing efficient stated choice experiments in the presence of reference alternatives

Rose, John M.; Bliemer, Michiel C.J.; Hensher, David A.; Collins, Andrew T.

doi:10.1016/j.trb.2007.09.002

Cited by 386 publications

(184 citation statements)

References 14 publications

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“…Crowding levels on bus, train and metro were represented with diagrams, two examples of different levels of bus and train crowding are shown in Figure 2 (in line with the combinations of attribute levels identified in a D-optimal design, see Rose et al, 2008). The pictorial displays of the number of people sitting and standing in each mode is from above (i.e., a bird's eye view), which is a common representation in the few stated choice studies that have considered crowding.…”

Section: Data Descriptionmentioning

confidence: 72%

Crowding in public transport systems: Effects on users, operation and implications for the estimation of demand

Tirachini

Hensher

Rose

2013

Transportation Research Part A: Policy and Practice

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205

149

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The effects of high passenger density at bus stops, at rail stations, inside buses and trains are diverse. . This paper examines the multiple dimensions of passenger crowding related to public transport demand, supply and operations, including effects on operating speed, waiting time, travel time reliability, passengers' wellbeing, valuation of waiting and invehicle time savings, route and bus choice, and optimal levels of frequency, vehicle size and fare. Secondly, crowding externalities are estimated for rail and bus services in Sydney, in order to show the impact of crowding on the estimated value of in-vehicle time savings and demand prediction. Using Multinomial Logit (MNL) and Error Components models, we show that alternative assumptions concerning the threshold load factor that triggers a crowding externality effect do have an influence on the value of travel time (VTTS) for low occupancy levels (all passengers sitting); however, for high occupancy levels, alternative crowding models estimate similar VTTS. Importantly, if demand for a public transport service is estimated without explicit consideration of crowding as a source of disutility for passengers, demand will be overestimated if the service is designed to have a number of standees beyond a threshold, as analytically shown using a MNL choice model. 2

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Section: Data Descriptionmentioning

confidence: 72%

Crowding in public transport systems: Effects on users, operation and implications for the estimation of demand

Tirachini

Hensher

Rose

2013

Transportation Research Part A: Policy and Practice

Self Cite

205

149

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“…The three alternatives were described by five attributes, namely free flow time, slowed down time, trip travel time variability, vehicle running cost and toll cost. A D-efficient design was used in the generation of the SC questionnaires (see for example Rose et al 2008). For a more detailed description of the survey in the context of a recent application, see Hess et al (2008).…”

Section: Empirical Application Datamentioning

confidence: 99%

Using conditioning on observed choices to retrieve individual-specific attribute processing strategies

Hess

Hensher

2010

Transportation Research Part B: Methodological

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With the growing reliance on Stated Choice (SC) data, researchers are increasingly interested in understanding how respondents process the information presented to them in such surveys. Specifically, it has been argued that some respondents may simplify the choice tasks by consistently ignoring one or more of the attributes describing the alternatives, and direct questions put to respondents after the completion of SC surveys support this hypothesis. However, in the general context of issues with response quality in SC data, there are certainly grounds for questioning the reliability of stated attribute processing strategies. In this paper, we take a different approach by attempting to infer attribute processing strategies through the analysis of respondent-specific coefficient distributions obtained through conditioning on observed choices. Our results suggest that a share of respondents do indeed ignore a subset of explanatory variables. However, there is also some evidence that the inferred attribute processing strategies are not necessarily consistent with the stated attribute processing strategies. Additionally, there is some evidence that respondents who claim to have ignored a certain attribute may simply have assigned it lesser importance. The results produced by the inferring approach not only lead to slightly better fit but also more consistent results.

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“…Ding, 2007;Rousseas and Hart, 1951) and individual customisation of SC choice tasks to respondent specific experiences (e.g. Rose et al, 2008;Train and Wilson, 2007) represent just two approaches researchers have taken to improve the realism of SC choice tasks. It is with the latter approach that this paper is concerned.…”

Section: Statedmentioning

confidence: 99%

Should Reference Alternatives in Pivot Design SC Surveys be Treated Differently?

Hess

Rose

2008

Environ Resource Econ

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Analysts are increasingly making use of pivot style Stated Choice (SC) data in the estimation of choice models. These datasets often contain a reference alternative whose attributes remain invariant across replications for the same respondent. This paper presents evidence to suggest that respondents react differently to the attributes of these reference alternatives and those of purely hypothetical alternatives. While some such evidence exists in the existing literature, this paper goes further and details a number of different departures from a common treatment of the two types of alternatives, relating both to the observed part of utility and the error term.

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Designing efficient stated choice experiments in the presence of reference alternatives

Cited by 386 publications

References 14 publications

Crowding in public transport systems: Effects on users, operation and implications for the estimation of demand

Crowding in public transport systems: Effects on users, operation and implications for the estimation of demand

Using conditioning on observed choices to retrieve individual-specific attribute processing strategies

Should Reference Alternatives in Pivot Design SC Surveys be Treated Differently?

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