Toward <scp>D2A</scp>: Enhancing Luxury Fashion With Seamless and Immersive Phygital Customer Experiences
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT This study explores direct‐to‐avatar (D2A) strategies—where brands engage directly with consumer avatars in virtual environments—in the luxury fashion retail sector, focusing on enhancing customer engagement and creating a seamless phygital (physical + digital) experience through virtual immersion. Situated at the crossroads of physical and digital realms, this research assesses how immersive experiences contribute to perceived seamlessness and customer engagement within D2A and direct‐to‐consumer (D2C) frameworks. Employing a mixed‐method approach, including qualitative interviews with luxury fashion brand managers and three experimental design studies, this paper addresses the relatively underexplored effects of immersive experiences in marketing. Our findings reveal that immersion in D2A significantly boosts customer perceptions of channel seamlessness and engagement, with empowerment playing a key amplifying role in the seamlessness–engagement relationship. This paper enriches digital marketing strategies by highlighting the pivotal role of D2A in crafting engaging and unified customer experiences, offering luxury fashion marketing managers practical insights to thrive in the phygital landscape.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it