Determining Consumer Purchase Intentions Based on Innovative Work Behavior: A Qualitative Study Within the Framework of The Uncanny Valley Theory

Advances in artificial intelligence technologies have led to the widespread use of human-like systems in marketing communications. Applications such as virtual influencers, chatbots, and humanoid robots are becoming increasingly realistic to facilitate consumer interaction. However, these applications can cause discomfort among consumers, especially after a certain level of realism is achieved. This phenomenon is explained in literature as the ‘uncanny valley’ effect. This study aims to examine the effects of interactions between information technology sector employees and human-like digital entities on their purchase intentions and innovative work behaviors within the framework of the Uncanny Valley Theory. The research was conducted with IT sector employees in an internal customer role. These participants also have the potential to represent external customer behavior as users of products and services. The research findings reveal that innovative work behavior is a complex process that influences consumer purchase intentions. Innovative products consider not only the functionality of the product but also human-like qualities such as reliability, emotionality, practicality of use and social acceptance. Therefore, the findings obtained because of this study not only fill the gap in literature but also comprehensively address the behavioral effects from both the internal customer (employee) and external customer (consumer) perspectives.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-12-31
DOI
https://doi.org/10.5281/zenodo.18148403
Primary Topic
AI in Service Interactions
Type
article
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article

Determining Consumer Purchase Intentions Based on Innovative Work Behavior: A Qualitative Study Within the Framework of The Uncanny Valley Theory

Sefa Ceyhan, Begüm Maral, Ayben CEYHAN GÜNAY
Zenodo (CERN European Organization for Nuclear Research)
AI in Service Interactions
article

Determining Consumer Purchase Intentions Based on Innovative Work Behavior: A Qualitative Study Within the Framework of The Uncanny Valley Theory

Sefa Ceyhan, Begüm Maral, Ayben CEYHAN GÜNAY
article en

Abstract

Advances in artificial intelligence technologies have led to the widespread use of human-like systems in marketing communications. Applications such as virtual influencers, chatbots, and humanoid robots are becoming increasingly realistic to facilitate consumer interaction. However, these applications can cause discomfort among consumers, especially after a certain level of realism is achieved. This phenomenon is explained in literature as the ‘uncanny valley’ effect. This study aims to examine the effects of interactions between information technology sector employees and human-like digital entities on their purchase intentions and innovative work behaviors within the framework of the Uncanny Valley Theory. The research was conducted with IT sector employees in an internal customer role. These participants also have the potential to represent external customer behavior as users of products and services. The research findings reveal that innovative work behavior is a complex process that influences consumer purchase intentions. Innovative products consider not only the functionality of the product but also human-like qualities such as reliability, emotionality, practicality of use and social acceptance. Therefore, the findings obtained because of this study not only fill the gap in literature but also comprehensively address the behavioral effects from both the internal customer (employee) and external customer (consumer) perspectives.

Zenodo (CERN European Organization for Nuclear Research)
İstanbul Nişantaşı Üniversitesi (TR)
Decent work and economic growth
Openalex Percentile: Top 17%
AI in Service Interactions
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Determining Consumer Purchase Intentions Based on Innovative Work Behavior: A Qualitative Study Within the Framework of The Uncanny Valley Theory — Sefa Ceyhan, Begüm Maral, et al. · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS