Fish demand in the U.S. Great Lakes region in the face of seafood mislabeling

Abstract

The rapid globalization of seafood trade over the past few decades has triggered heightened vulnerability for fraud within the seafood supply network. Consumer perceptions of these vulnerabilities are not limited to imported seafood products, as spillover effects are likely to influence purchasing behavior for domestically produced seafood as well. Using a between-sample survey experiment with 1,272 respondents in differing informational settings, we investigate whether consumer WTP for local seafood is impacted by information regarding seafood fraud. Consistent with previous studies, our results indicate that consumers broadly derive positive utility from consuming locally sourced relatively to imported seafood. Upon further disaggregation, however, we find that for one consumer segment, which we term the price-sensitive group, localness does not command a significant positive premium. Most importantly, we demonstrate that information regarding international seafood fraud largely did not alter local seafood demand. That said, we find some evidence of a negative spillover effect of the information treatment on US-labeled seafood in one of the consumer subgroups.

Keywords:

• Aquaculture
• consumer demand
• food fraud

Notes

1 Seafood species groups covered by SIMP include Abalone, Atlantic Cod, Blue Crab (Atlantic), Dolphinfish (Mahi Mahi), Grouper, King Crab (RED), Pacific Cod, Red Snapper, Sea Cucumber, Sharks, Shrimp, Swordfish and Tunas (Albacore, Bigeye, Skipjack, Yellowfin, and Bluefin) (Warner et al., 2013).

2 In a move to comprehensively capture other lesser-known fraudulent opportunities, Fox et al. (2018) extends the scope of seafood fraud to include modern day slavery and animal welfare infractions. For the purposes of this study, we examine seafood fraud outside of these latter ethical considerations.

3 United States represents any other state outside the Great Lakes region.

4 The ACS estimates are restricted to the adult population residing in the Great Lakes region, while the NHANES applies to the US population subgroup who indicated seafood consumption in the past 30 days.

5 One might be concerned about potential anchoring bias in consumers’ reported levels of seafood fraud concern due to non-randomization of the slider position between subjects, ex-ante. Given that the slider was positioned at 50 by default, we conduct a simple t-test of the null that the average level of concern is not different from 50. We reject this null in favor of the alternative at the 1% level (p-value <0.0001), indicating that the consumers’ average level of concern is significantly different from 50.

6 Balance test results are presented in Tables 2 and 4.

7 While the Akaike and Bayesian Information Criteria indicate that extending the number of “latent” classes does improve the model fit, doing so yields unwieldy results and overcomplicates model interpretation. In particular, the estimated standard errors of some coefficients become substantially larger; in part, because of the small number of observations assigned to some classes (Heckman & Singer, 1984).

8 The average mWTP estimates are calculated using the class probability estimates as weights.

Additional information

Funding

This research was supported by the Great Lakes Aquaculture Collaborative, NOAA grant #NA19OAR4170388.