Using virtual environments to improve the realism of choice experiments: a case study about coastal erosion management

Matthews, Y.; Scarpa, R.; Marsh, D.

Abstract

Choice experiment surveys are commonly used to assess the general public's willingness to pay for different levels of environmental quality. However, respondents need to understand what they are valuing or they will make potentially wrong assumptions based on different experiences and frames of reference. Three-dimensional computer generated models or Virtual Environments (VE) have so far seen little use in economics research, probably due to the complexity and cost of developing and delivering them to study participants. The few studies that have used them find that VE are superior to static image presentations in helping people evaluate complex data. For this study we developed virtual environments for a choice experiment about coastal erosion management using free, easy-to-use software and Google Earth© satellite imagery and presented these to respondents as video tours. Our results indicate that the VE treatment reduced choice error, reduced left-right bias and improved respondent engagement and retention when compared with static images. There were also differences in WTP between the two groups.

Citation

Matthews, Y., Scarpa, R., & Marsh, D. (2017). Using virtual environments to improve the realism of choice experiments: a case study about coastal erosion management. Journal of Environmental Economics and Management, 81, 193-208. https://doi.org/10.1016/j.jeem.2016.08.001

• Journal Article Type: Article
• Acceptance Date: Aug 7, 2016
• Online Publication Date: Aug 13, 2016
• Publication Date: 2017-01
• Deposit Date: Aug 10, 2016
• Publicly Available Date: Feb 13, 2018
• Journal: Journal of Environmental Economics and Management
• Print ISSN: 0095-0696
• Electronic ISSN: 1096-0449
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 81
• Pages: 193-208
• DOI: https://doi.org/10.1016/j.jeem.2016.08.001
• Public URL: https://durham-repository.worktribe.com/output/1399374