Embedded big data in packaged foods

Examining consumer sentiment during the purchasing process post-Covid-19

Bibliographic Data

ID21295285
AuthorsEmre Yaşar (0000-0003-1573-0930, Isparta University of Applied Sciences), Mahmut Demir (0000-0002-6371-4348, Isparta University of Applied Sciences), Turgay Taşdemir (0000-0002-4705-4116, Isparta University of Applied Sciences)
Year2023
Volume125
Issue10
Pages3623-3639
Publication date2023-10-10
Open AccessYes
TypeARTICLE
VenueBritish Food Journal (JOURNAL)
Journal identifiersISSN: 0007-070X • E-ISSN: 1758-4108
PublisherEmerald (PUBLISHER)
DOI10.1108/bfj-12-2022-1124
OpenAlexW4380568962
LanguageEN
Citations received1
References cited59

Purpose This study aims to examine consumers' purchasing and consumption behavior regarding big data embedded in packaged food post-Covid-19. The second purpose is to determine whether consumer purchasing behavior varies depending on the variety and volume of big data on food packages. Design/methodology/approach Semi-structured interviews were conducted to investigate consumer sentiment regarding big embedded data in packaged foods during purchasing. Based on samples from packaged foods sold in international chain stores, interview data collected from 24 participants were subjected to systematic analytical procedures. Findings The results revealed that before Covid-19, consumers had positive thoughts about the expiration date, brand, and product contents but did not care much about other data. At the same time, post-Covid-19, there were changes in their attitudes and behaviors on this issue. Post-Covid-19, it has been observed that consumers have positive attitudes and behaviors toward human health and food safety issues regarding unprocessed big data in packaged foods. Originality/value This study provides a different perspective on consumer purchasing behavior through big data on packaged foods post-Covid-19. Embedded information in packaged foods provides important data regarding consumer purchasing behavior. As a powerful source of consumer sentiment, this data also provides a reference for consumer purchasing decisions

Advertising · Big data · Business · Consumer behaviour · Consumption (sociology) · Coronavirus disease 2019 (COVID-19) · Originality · Product (mathematics) · Purchasing · Variety (cybernetics) · Computer Science · Consumer Attitudes and Food Labeling · Consumer Behavior in Brand Consumption and Identification · Consumer Packaging Perceptions and Trends · Marketing · Medicine · Psychology

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