On the Use of Virtual Reality in Mitigating Hypothetical Bias in Choice Experiments

Abstract

Choice experiments have been extensively used in many stated preference studies and disciplines. In order to give external validity to stated preferences, participants must behave the same in an experiment setting as they do in reality. The difference between a decision made in a real experiment and a hypothetical experiment is commonly attributed to "hypothetical bias." In this paper, we investigate whether virtual reality can reduce hypothetical bias in choice experiments. We conducted a set of experiments using the Food and Drug Administration's new Nutrition Facts Label for yogurts. Participants were randomly assigned to non-hypothetical and hypothetical experiments, which differed in terms of visual presentations of the product in question: text, picture, and a virtual grocery store. Given the absence of real markets for the new label at the time of the research, we approximate the real market with a binding choice in our non-hypothetical experiments. Our results suggest that although the hypothetical bias with virtual reality is not statistically significantly different from those using text or picture, it is the smallest. Among participants who did not exhibit high simulator discomfort, results suggest that virtual reality can significantly reduce hypothetical bias in choice experiments.

Consumer valuation of blockchain traceability for beef in the United States

“…For each choice task, we asked respondents to assume they were shopping for a 10‐ounce beef steak and subsequently asked them to make a series of hypothetical purchasing decisions between two beef options and a “neither of these” (no‐buy) option. Including a no‐buy option makes the choice task more realistic because consumers may not purchase items that are unacceptable (Bazzani et al, 2017; Fang et al, 2020; Gao et al, 2016). The two beef options were presented in the same image and stated to be of the same size, quality, taste, and other characteristics.…”

Preferences for tree fruit market attributes among smallholder farmers in Eastern Rwanda

“…Hypothetical bias is one of the ubiquitous issues in relation to the use of DCE that elicit WTP measures. This is due to the hypothetical nature and inherent lack of realism of the choice questions asked that may lead to respondents overstating their WTP since their responses have no real consequences in terms of commitment for the payment of the service in question (Bello & Abdulai, 2016; De‐Magistris et al., 2013; Fang et al., 2021). There are several approaches that can be employed to mitigate the HB.…”

“…The available HB mitigation measures can be broadly categorized into ex‐ante and ex‐post methods. The most common ex‐ante methods include cheap talk (Cummings & Taylor, 1999), honesty priming (De‐Magistris et al., 2013), real talk, consequentiality scripts, solemn oath scripts, opt‐out reminders (Alemu & Olsen, 2018; Ladenburg & Olsen, 2014), and more recently the use of virtual reality (Fang et al., 2021) and 3D videos (Rid et al., 2018). Ex‐post methods such as the certainty calibration scales are based on follow‐up questions that measure respondent certainty about their choices or stated WTP values on a numerical scale (Loomis et al., 2014).…”

“…Ex‐post methods such as the certainty calibration scales are based on follow‐up questions that measure respondent certainty about their choices or stated WTP values on a numerical scale (Loomis et al., 2014). It is important to note that there are several factors that are likely to influence HB and no single mitigation method can be regarded as the “magic bullet” (Fang et al., 2021; Moser et al., 2014; Murphy et al., 2005) and hence the use of a combination of both ex‐post and ex‐ante as complements, depending on context is usually recommended (Whitehead & Cherry, 2007).…”

New Consumer Research Technology for Food Behaviour: Overview and Validity

“…In addition, they conclude that the technology also seems promising to lead consumers to change their behaviour. Fang et al [ 21 ] point out that VR methodology can also help reduce the hypothetical bias (the difference between a real experiment and an imagined one) by introducing a form of realism to the measurement situation.…”