EconPapers    
Economics at your fingertips  
 

How nostalgic feelings impact Pokémon Go players – integrating childhood brand nostalgia into the technology acceptance theory

David Harborth and Sebastian Pape

Behaviour and Information Technology, 2020, vol. 39, issue 12, 1276-1296

Abstract: The augmented reality smartphone game Pokémon Go is one of the biggest commercial successes in the last years, posing the question concerning the factors contributing to the game’s success. An apparent distinction to other games is the strong brand Pokémon. We derive a research model based on the established theory of technology acceptance, which includes an established construct for nostalgic feelings – childhood brand nostalgia – and theorise on how it is related to beliefs about technology characteristics and the intention to play the game. For this purpose, we adapt one of the most prominent technology acceptance models for the consumer context and for hedonic information systems, the UTAUT2 model. Based on our model, we conduct a study with 418 active German players aged between 18 and 35. Our results indicate that the effect of childhood brand nostalgia on behavioural intention is fully mediated by the belief constructs. Thus, nostalgic feelings about Pokémon influence the intention of users through altering beliefs concerning Pokémon. We include nostalgic feelings in a technology acceptance model for the first time, therefore contributing to the theoretical advance in the IS domain. The results can be used to enhance the technology acceptance of newly designed products.

Date: 2020
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/0144929X.2019.1662486 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tbitxx:v:39:y:2020:i:12:p:1276-1296

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/tbit20

DOI: 10.1080/0144929X.2019.1662486

Access Statistics for this article

Behaviour and Information Technology is currently edited by Dr Panos P Markopoulos

More articles in Behaviour and Information Technology from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-03-20
Handle: RePEc:taf:tbitxx:v:39:y:2020:i:12:p:1276-1296