Gastronomic Consumers’ Attitudes Toward AI-Generated Food Images: Exploring Different Perceptions Based on Generational Segmentation

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41110%2F24%3A100618" target="_blank" >RIV/60460709:41110/24:100618 - isvavai.cz</a>

Výsledek na webu

<a href="https://link-springer-com.infozdroje.czu.cz/chapter/10.1007/978-981-97-1552-7_8" target="_blank" >https://link-springer-com.infozdroje.czu.cz/chapter/10.1007/978-981-97-1552-7_8</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-981-97-1552-7_8" target="_blank" >10.1007/978-981-97-1552-7_8</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Gastronomic Consumers’ Attitudes Toward AI-Generated Food Images: Exploring Different Perceptions Based on Generational Segmentation

Popis výsledku v původním jazyce

The paper aims to identify the differences in attitudes of particular generational segments of gastronomy consumers toward AI-generated food marketing images. DALL-E engine was used to generate 56 images of dishes, which were initially ranked by professional chefs and reduced to a final set of 18 images used for four photo-elicitation focus groups. Qualitative evaluation of the data showed three topics to be crucial during the discussion of agents: the ability to recognize the meal or ingredient (M/I-R), preference toward presented food, and ability to recognize pictures as artificial (AR). There were significant differences in the meaning construction of such topics based on particular generational segments, i.e., Baby Boomers (BB), Generation X (GX), Generation Y (GY), or Generation Z (GZ). Findings show that GZ manifested the highest M/I-R scores but the lowest AR scores. GZ also preferred dishes for which M/I-R was manifested over those with missing M/I-R. GY and GX showed lower M/I-R scores as well as low AR scores. However, GY and GX showed a will to experiment by choosing dishes independently on M/I-R manifestation. BB segment showed the lowest M/I-R scores, but it was the only segment able to achieve high AR scores. As for the GZ, the BB segment also preferred dishes with M/I-R manifestation over the unidentified dishes. The results present marketing implications, especially since the BB segment is the most (and only) suspicious group toward AI-generated food images as it tends to elaborate deeper analysis of the presented images, leading to increased artificiality recognition.

Název v anglickém jazyce

Gastronomic Consumers’ Attitudes Toward AI-Generated Food Images: Exploring Different Perceptions Based on Generational Segmentation

Popis výsledku anglicky

The paper aims to identify the differences in attitudes of particular generational segments of gastronomy consumers toward AI-generated food marketing images. DALL-E engine was used to generate 56 images of dishes, which were initially ranked by professional chefs and reduced to a final set of 18 images used for four photo-elicitation focus groups. Qualitative evaluation of the data showed three topics to be crucial during the discussion of agents: the ability to recognize the meal or ingredient (M/I-R), preference toward presented food, and ability to recognize pictures as artificial (AR). There were significant differences in the meaning construction of such topics based on particular generational segments, i.e., Baby Boomers (BB), Generation X (GX), Generation Y (GY), or Generation Z (GZ). Findings show that GZ manifested the highest M/I-R scores but the lowest AR scores. GZ also preferred dishes for which M/I-R was manifested over those with missing M/I-R. GY and GX showed lower M/I-R scores as well as low AR scores. However, GY and GX showed a will to experiment by choosing dishes independently on M/I-R manifestation. BB segment showed the lowest M/I-R scores, but it was the only segment able to achieve high AR scores. As for the GZ, the BB segment also preferred dishes with M/I-R manifestation over the unidentified dishes. The results present marketing implications, especially since the BB segment is the most (and only) suspicious group toward AI-generated food images as it tends to elaborate deeper analysis of the presented images, leading to increased artificiality recognition.

Druh

J_SC - Článek v periodiku v databázi SCOPUS

CEP obor

—

OECD FORD obor

50900 - Other social sciences

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Smart Innovation, Systems and Technologies

ISSN

2190-3018

e-ISSN

2190-3018

Svazek periodika

386

Číslo periodika v rámci svazku

Neuvedeno

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

15

Strana od-do

105-119

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-85196847194