Results 291 to 300 of about 2,664,884 (384)

What drives students' green intentions? A psychological approach. [PDF]

open access: yesBMC Psychol
Hou ACY, Duong NT, Pham VK, Pham Thi TD.
europepmc   +1 more source

Mind the Gap—An Empirical Analysis of the Attitude‐Behaviour Gap in Grocery Retailing

open access: yesJournal of Consumer Behaviour, EarlyView.
ABSTRACT The attitude‐behaviour gap describes the mismatch between what consumers express in terms of preferences and how they actually behave when making purchase decisions. This gap is particularly relevant for organic food, where consumers often show strong positive attitudes but do not consistently buy organic products.
Kevin Ermecke   +3 more
wiley   +1 more source

AI Hallucinations in Tourism: How Errors Impact Consumer Trust and Recommendation Acceptance

open access: yesJournal of Consumer Behaviour, EarlyView.
ABSTRACT Generative artificial intelligence (GenAI) is quickly transforming travel planning; however, its outputs can include hallucinations, which are plausible yet false statements that can undermine user judgement. Eliminating hallucinations in GenAI technology is currently impossible.
Francisco Rejón‐Guardia   +2 more
wiley   +1 more source

Claiming Food Ethics as a Pillar of Food Security. [PDF]

open access: yesFoods
Balan IM   +9 more
europepmc   +1 more source

The Xenocentric Mindset: Cultural and Personality Drivers Behind Consumer Preferences

open access: yesJournal of Consumer Behaviour, EarlyView.
ABSTRACT This study examines the psychological and cultural dimensions that influence consumer xenocentrism in Brazil and Iran, focusing on horizontal–vertical individualism–collectivism and the “Big Five” personality traits—extraversion, agreeableness, conscientiousness, neuroticism, and intellect/imagination.
José I. Rojas‐Méndez   +3 more
wiley   +1 more source

Decoding Emotional Signatures of Ethical Ads: An Analysis of Actor‐Viewer Synchrony

open access: yesJournal of Consumer Behaviour, EarlyView.
ABSTRACT We examine whether ethical advertisements differ from conventional ads in their on‐screen emotional signatures and whether those signatures transfer to actor‐viewer synchrony. Study 1 analyses 138 professionally produced YouTube ads using Automated Facial Expression Recognition (AFER) and Convolutional Neural Networks (CNN) to quantify actor ...
Vik Naidoo, Nicolas Hamelin
wiley   +1 more source

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