This research investigates consumer information diagnosticity in hybrid marketing environments by examining how consumers reduce uncertainty through visual and algorithmic signals. Adopting a hierarchical framework spanning physiological, cultural, contextual, and systemic dimensions, four studies explore diagnostic evaluation across physical product displays and digital recommendation systems. Study 1 employs eye-tracking and pupillometry (N=32) to demonstrate that wine label brightness modulates cognitive processing depth rather than breadth. High brightness induces front-loading of cognitive resources, enabling efficient early encoding, whereas low brightness triggers compensatory back-loading, leading to prolonged late-stage effort. Study 2 uses a 4×2×2 factorial experiment (N=435) and qualitative interviews (N=30) to reveal that dark red wine color configurations function as high-diagnosticity cultural schemas in Chinese gift-giving contexts, particularly for intermediate wine knowledge consumers facing social uncertainty. Study 3 conducts phenomenological interviews (N=36) with Douyin/TikTok users, identifying a privacy concern: excessive recommendation precision triggers privacy anxiety despite enhancing convenience, creating systemic uncertainty from algorithmic opacity. Study 4 tests AI ethical design features through a between-subjects experiment (N=278) across four countries, establishing that transparency, fairness, privacy, and autonomy restore system diagnosticity through cognitive scaffolding rather than direct affective pathways. The research constructs a unified information diagnosticity framework demonstrating that physical sensory cues and algorithmic signals follow parallel psychological principles. Brightness serves as a physiological moderator, lowering perceptual thresholds; cultural schemas provide social shields, reducing face-related risks; and ethical design features function as cognitive scaffolds, enabling trust reconstruction. Findings offer actionable insights to visual marketing design and algorithmic system transparency.
Questa ricerca esamina la diagnosticità informativa nei contesti di marketing ibridi, analizzando come i consumatori riducano l'incertezza attraverso segnali visivi e algoritmici. Adottando un quadro gerarchico che integra dimensioni fisiologiche, culturali e sistemiche, la tesi indaga i processi di valutazione diagnostica sia nelle esposizioni fisiche dei prodotti sia nei sistemi digitali di raccomandazione. Lo Studio 1, condotto tramite eye-tracking e pupillometria, dimostra che la luminosità cromatica modula il timing dell'elaborazione cognitiva: un'elevata luminosità favorisce un front-loading (codifica precoce ed efficiente), mentre una bassa luminosità induce un back-loading compensatorio, generando uno sforzo prolungato nelle fasi tardive. Lo Studio 2 rivela che le tonalità scure del rosso fungono da schemi culturali ad alta diagnosticità nel contesto del gifting in Cina; per i consumatori con conoscenze intermedie, tali segnali riducono l'incertezza legata al rischio sociale e alla teoria del "volto" (mianzi). Spostandosi sul piano digitale, lo Studio 3 identifica un paradosso sistemico su piattaforme come Douyin: l'eccessiva precisione algoritmica, pur aumentando la comodità, genera ansia per la privacy e incertezza dovuta all'opacità dei processi. Infine, lo Studio 4 dimostra che il design etico dell'IA (trasparenza, equità, autonomia) funge da impalcatura cognitiva (cognitive scaffolding), ripristinando la diagnosticità del sistema e ricostruendo la fiducia attraverso vie cognitive piuttosto che puramente affettive. In sintesi, la ricerca propone un quadro unificato in cui segnali sensoriali e logiche algoritmiche seguono principi psicologici paralleli, offrendo contributi strategici per il marketing visivo e il design dei sistemi di IA trasparenti.
Information Diagnosticity and Uncertainty Mitigation: Integrated Physiological, Cultural, Contextual, and Ethical Perspectives in Consumer Behavior / Ding, L.. - (2026 Feb 11).
Information Diagnosticity and Uncertainty Mitigation: Integrated Physiological, Cultural, Contextual, and Ethical Perspectives in Consumer Behavior
Ding, Liang
2026-02-11
Abstract
This research investigates consumer information diagnosticity in hybrid marketing environments by examining how consumers reduce uncertainty through visual and algorithmic signals. Adopting a hierarchical framework spanning physiological, cultural, contextual, and systemic dimensions, four studies explore diagnostic evaluation across physical product displays and digital recommendation systems. Study 1 employs eye-tracking and pupillometry (N=32) to demonstrate that wine label brightness modulates cognitive processing depth rather than breadth. High brightness induces front-loading of cognitive resources, enabling efficient early encoding, whereas low brightness triggers compensatory back-loading, leading to prolonged late-stage effort. Study 2 uses a 4×2×2 factorial experiment (N=435) and qualitative interviews (N=30) to reveal that dark red wine color configurations function as high-diagnosticity cultural schemas in Chinese gift-giving contexts, particularly for intermediate wine knowledge consumers facing social uncertainty. Study 3 conducts phenomenological interviews (N=36) with Douyin/TikTok users, identifying a privacy concern: excessive recommendation precision triggers privacy anxiety despite enhancing convenience, creating systemic uncertainty from algorithmic opacity. Study 4 tests AI ethical design features through a between-subjects experiment (N=278) across four countries, establishing that transparency, fairness, privacy, and autonomy restore system diagnosticity through cognitive scaffolding rather than direct affective pathways. The research constructs a unified information diagnosticity framework demonstrating that physical sensory cues and algorithmic signals follow parallel psychological principles. Brightness serves as a physiological moderator, lowering perceptual thresholds; cultural schemas provide social shields, reducing face-related risks; and ethical design features function as cognitive scaffolds, enabling trust reconstruction. Findings offer actionable insights to visual marketing design and algorithmic system transparency.| File | Dimensione | Formato | |
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