Increasing Local Fish Consumption: A Bayesian Belief Network Analysis. Issue 1 (1st January 2021)

• Record Type: Journal Article
• Authors: Paredes, Samantha; Pascoe, Sean; Coglan, Louisa; Richards, Carol
• Is Part Of: Journal of international food & agribusiness marketing. Volume 33:Issue 1(2021)
• Page Start: 104
• Page End: 121
• Publication Date: 2021-01-01
• Subjects: Bayesian belief network -- consumer preferences -- COVID-19 -- local fish -- seafood; Food supply -- Periodicals; Food -- Marketing -- Periodicals; Food industry and trade -- Periodicals; 338.10688
• DOI: 10.1080/08974438.2020.1860853
• Languages: English
• ISSNs: 0897-4438

Abstract

Abstract: The impact of the recent coronavirus pandemic on world seafood trade highlighted the vulnerability of the industry to international shocks and prompted calls for more diverse supply chains. In this paper, we assess the potential for increasing supplies of currently exported fish products to the local market using a Bayesian belief network model. Based on a survey of over 1000 Queensland residents, we determine the key drivers of consumption of locally produced fish and highlight the potential to engage in marketing strategies that bring the consumer closer to locally produced product (e.g. community supported fishery).