
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.
Uncanny Valley Theory, Digital Marketing, Purchase Intention, Innovative Work Behavior
Uncanny Valley Theory, Digital Marketing, Purchase Intention, Innovative Work Behavior
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
