JOURNAL ARTICLE

Generation Z as Innovation Drivers in the Luxury Hospitality Sector. The Case of Cultured Meat.

  • Published In: Gastronomy & Tourism, 2024, v. 8, n. 3. P. 203 1 of 3

  • Database: Business Source Ultimate 2 of 3

  • Authored By: Everett, Sally; Simmill, Jade 3 of 3

Abstract

Research into the market for engineered, in vitro engineered, and cultured meat is limited, partly because it is new and partly due to perceptions that it is both unnatural and untested. This article reports on a study that explores its potential as a unique luxury food experience. Eighteen semistructured interviews were undertaken to explore Generation Z views on and acceptance of cultured meat and its role in the luxury hospitality sector. By drawing on the innovation diffusion model with reference to new cultured meat items such as "The World's Best Burger," the study suggests that, after reassurance about the technological processes involved in creating cultured meat and clear information about what value it adds as a luxury item, participants were open to trying cultured meat when positioned as a luxury good and expressed willingness to repeatedly purchase it despite the cost. Luxury restaurants emerge as powerful conduits for accelerating cultured meat adoption among Generation Z consumers by functioning as reassuring and safe "innovation theaters" that systematically foster each stage of Rogers' adoption process and add new dimensions to the model when applied to this emerging gastronomic context. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Gastronomy & Tourism. 2024/07, Vol. 8, Issue 3, p203
  • Document Type:Article
  • Subject Area:Biography
  • Publication Date:2024
  • ISSN:2169-2971
  • DOI:10.3727/216929824X17207924097199
  • Accession Number:184403256
  • Copyright Statement:Copyright of Gastronomy & Tourism is the property of Cognizant, LLC and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Looking to go deeper into this topic? Look for more articles on EBSCOhost.