Truace
Subscribe
68/100

Moderate evidence

ProblemPublished recordLifestyleProblem Space

Full story
More
Export record JSONEmailLinkedInX

Does Conversational Artificial Intelligence Affect Parasocial Displacement? A Study on Consumer Brand Affinity in Digital Market Ecosystems

Truvace record
TRV-2026-2595raw data (JSON)
Version
v1Published
First published
Evidence type
Controlled or validated comparison
Sources
1 sourcePeer-reviewed
sha256
6c0401445db9…check it

With the widespread adoption of conversational artificial intelligence (Conv-AI), consumers have recently reshaped how they search, evaluate, and build relationships with brands. Accessibility and bidirectional communication have created a dynamic interface for the digital ecosystem. Yet despite a growing body of research, the field remains focused on productivity gains and the convenience of AI in digital commerce. But there is very little about how this Conv-AI intermediation affects the emotional aspect of co…

The problem

In three preregistered experiments with 791 participants, brand love was lower when consumers met brands through a conversational AI agent than through direct brand exposure, and emerging brands were more exposed than heritage brands.

Sources

1 on file
  1. Journal of Theoretical and Applied Electronic Commerce Researchdoi:10.3390/jtaer21080264
    Peer-reviewed2026-08-07

Cite this record

v1

Truvace Impact Record TRV-2026-2595, v1: “Does Conversational Artificial Intelligence Affect Parasocial Displacement? A Study on Consumer Brand Affinity in Digital Market Ecosystems.” Truvace, 2026-11-12. /record/TRV-2026-2595 (accessed on the day you copy it). sha256 6c0401445db92df2…

Change history

1 version

Every change made to this record since it was first published, and why. Nothing has changed since it went up.

  1. Publishedv16c0401445db9…

    Certified into the record

Check this record hasn’t been altered

Check this record hasn’t been altered
How to check it yourself, without trusting this page

Download any version from /api/record/TRV-2026-2595 and hash its canonical field yourself, for example with shasum -a 256. You should get its content_hash. Each version’s text also ends with prev:and the hash of the version before it (version 1 points to 64 zeros). If anyone had changed a single character of any version after it was saved, those hashes wouldn’t line up.