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Seasonality Effects on Consumers Preferences Over Quality Attributes of Different Beef Products

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  • Ali Ardeshiri
  • Spring Sampson
  • Joffre Swait

Abstract

Using discrete choice modelling, the study investigates 946 American consumers willingness-to-pay and preferences for diverse beef products. A novel experiment was used to elicit the number of beef products that each consumer would purchase. The range of products explored in this study included ground, diced, roast, and six cuts of steaks (sirloin, tenderloin, flank, flap, New York and cowboy or rib-eye). The outcome of the study suggests that US consumers vary in their preferences for beef products by season. The presence of a USDA certification logo is by far the most important factor affecting consumers willingness to pay for all beef cuts, which is also heavily dependent on season. In relation to packaging, US consumers have mixed preference for different beef products by season. The results from a scaled adjusted ordered logit model showed that after price, safety-related attributes such as certification logos, types of packaging, and antibiotic free and organic products are a stronger influence on American consumers choice. Furthermore, US consumers on average purchase diced and roast products more often in winter slow cooking season, than in summer, whereas New York strip and flank steak are more popular in the summer grilling season. This study provides valuable insights for businesses as well as policymakers to make inform decisions while considering how consumers relatively value among different labelling and product attributes by season and better address any ethical, safety and aesthetic concerns that consumers might have.

Suggested Citation

  • Ali Ardeshiri & Spring Sampson & Joffre Swait, 2019. "Seasonality Effects on Consumers Preferences Over Quality Attributes of Different Beef Products," Papers 1902.02419, arXiv.org.
    • Handle: RePEc:arx:papers:1902.02419
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    File URL: http://arxiv.org/pdf/1902.02419
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    References listed on IDEAS

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