Consumers' Willingness to Pay for the Color of Salmon: A Choice Experiment with Real Economic Incentives

In most retail markets, sellers post the price and consumers choose which products to buy. We designed an experimental market with posted prices to investigate consumers' willingness to pay for the color of salmon. Salmon fillets varying in color and price were displayed in twenty choice scenarios. In each scenario, the participants chose which of two salmon fillets they wanted to buy. To induce real economic incentives, each participant drew one binding scenario; the participants then had to buy the salmon fillet they had chosen in their binding scenario. The choice data were analyzed with a mixed logit model.     

Consumers' Willingness to Pay for Locally Produced Ground Beef: A Case Study of the Rural Northern Great Plains

This study examined consumers’ preferences and willingness to pay (WTP) for locally produced ground beef with an emphasis on the impacts of product attributes and the heterogeneity caused by rural consumers’ characteristics. We applied the choice-based conjoint technique to analyze data collected from a typical rural town in the Northern Great Plains. The results indicate that location associated product brand differences and leanness were dominant components affecting consumers’ WTP. The premium of locally produced ground beef for consumers with a close tie to local production is $0.48/lb. Cut difference, grass-fed, and organic were trivial factors in determining consumers’ WTP.     

Using Geographically Weighted Choice Models to Account for the Spatial Heterogeneity of Preferences

In this paper, we investigate the use of geographically weighted choice models for modelling spatially clustered preferences. We argue that this is a useful way of generating highly‐detailed spatial maps of willingness to pay for environmental conservation, given the costs of collecting data. The data used in this study come from a discrete choice experiment survey of public preferences for the implementation of a new national forest management and protection programme in Poland. We combine these with high‐resolution spatial data related to local forest characteristics. Using locally estimated discrete choice models we obtain location‐specific estimates of willingness to pay (WTP). Variation in these estimates is explained by characteristics of the forests close to where respondents live. These results are compared with those obtained from a more typical, two stage procedure which uses Bayesian posterior means of the mixed logit model random parameters to calculate location‐specific estimates of WTP. We find that there are indeed strong spatial patterns to the benefits of changes to the management to national forests. People living in areas with more species‐rich forests and those living nearer bigger areas of mixed forests have significantly different WTP values than those living in other locations. This kind of information potentially enables a better distributional analysis of the gains and losses from changes to natural resource management, and better targeting of investments in forest quality.