Anchors on prices of consumer goods only hold when decisions are hypothetical

We elicit willingness to pay for different types of consumption goods, systematically manipulating irrelevant anchors (high vs. low) and incentives to provide true valuations (hypothetical questions vs. Becker-DeGroot-Marschak mechanism). On top of a strong hypothetical bias, we find that anchors only make a substantial, significant difference in the case of hypothetical data, the first experiments to directly document such an interaction. This finding suggests that hypothetical market research methods may deliver lower quality data. Moreover, it contributes to the discussion examining the mechanism underlying the anchoring effect, suggesting it could partly be caused by insufficient conscious effort to drift away from the anchor.

Videos Improve Attention and Cheap Talk in Online Surveys

Cheap Talk (CT) is a mainstay technique among stated preference practitioners to reduce Hypothetical Bias (HB). The usefulness of CT may be questionable in online surveys due to the limited control researchers have on participant engagement. In the context of an online choice experiment on hotels, we compare a control group of respondents who receives a CT script as a traditional passage of text versus a group who must answer an attention-check question to verify their comprehension of the script as well as another group who receives the CT script as a video and then answer the attention-check question. We find that compared to the control group, simply offering the attention-check question reduced willingness to pay (WTP), and those who answer the attention-check question correctly behaved differently to those who did not. Overall, video CT script is shown to improve attention and be more effective in reducing potential HB than a text-based script.

Mobility surveys beyond stated preference: introducing MyTrips, an SP-off-RP survey tool, and results of two case studies

When introducing new mobility offers or measures to influence traffic, stated preference (SP) surveys are often used to assess their impact. In SP surveys, respondents do not answer questions about their actual behaviour, but about hypothetical settings. Therefore, answers are often biased. To minimise this hypothetical bias, so-called stated preference-off-revealed preference (SP-off-RP) surveys were developed. They base SP questions on respondents’ revealed behaviour and place unknown scenarios in a familiar context. Until now, this method was applied mostly to scenarios investigating the willingness to pay. The application to more complex mode or route choice problems, which require the calculation of routes, has not yet been done. In this paper, the MyTrips survey tool for the collection of SP-off-RP data based on respondents’ actual mobility behaviour is presented. SP questions are based on alternatives to typical routes of respondents, which are calculated on the fly with an intermodal router. MyTrips includes a larger survey and collects mobility diaries for one day representing respondents’ daily routine, calculates alternative routes and creates SP questions based on a Bayesian optimal design. Results from two case studies investigating behaviour changes are presented. The first case study investigated the extension of a subway line in Vienna, Austria. The second case study focused on the introduction of micro transit vehicles in a rural setting, replacing infrequent bus services. Results of the two case studies show a difference in response behaviour between SP and RP settings and suggest a reduction of hypothetical bias. For the latter study, a Latent Class SP-off-RP model was estimated. It shows that availability and accessibility of public transport are the main influences on the willingness to use it, independent of other household characteristics.

Preprint: Mobility surveys beyond stated preference: Introducing MyTrips, an SP-off-RP survey tool, and results of two case studies

When introducing new mobility offers or measures to influence traffic, stated preference (SP) surveys are often used to assess their impact. In SP surveys respondents do not answer questions about their actual behavior but about hypothetical settings. Therefore, answers are often biased. To minimise this hypothetical bias, so-called stated preference-off-revealed preference (SP-off-RP)surveys were developed. They base SP questions on respondents’ revealedbehavior and place unknown scenarios in a familiar context. Until now this method was applied mostly to scenarios investigating the willingness to pay. The application to more complex mode or route choice problems, which require the calculation of routes, has not yet been done. In this paper, the MyTrips survey tool for the collection of SP-off-RP data based on respondents’ actual mobility behavior is presented. SP questions are based on alternatives to typical routes of respondents, which are calculated on the fly with an intermodal router. MyTrips includes a larger survey and collectsmobility diaries for one day representing respondents’ daily routine, calculates alternative routes and creates SP questions based on a Bayesian optimal design. Results from two case studies investigating behavior changes are presented. The first case study investigated the extension of a subway line in Vienna,Austria. The second case study focused on the introduction of micro transit vehicles in a rural setting, replacing infrequent bus services. Results of the two case studies show a difference in response behaviour between SP and RP settings and suggest a reduction of hypothetical bias. For the latter study a Latent Class SP-off-RP model was estimated. It shows that availability and accessibility of public transport are the main influence on the willingness to use it independent of other household characteristics.

Developing the Questionnaire

This chapter outlines the essential topics for developing and testing a questionnaire for a discrete choice experiment survey. It addresses issues such as the description of the environmental good, pretesting of the survey, incentive compatibility, consequentiality or mitigation of hypothetical bias. For the latter, cheap talk scripts, opt-out reminders or an oath script are discussed. Moreover, the use of instructional choice sets, the identification of protest responses and strategic bidders are considered. Finally, issues related to the payment vehicle and the cost vector design are the subject of this section.