An in-app purchase framework for location-based AR games: the case of Pokémon Go

Although location-based augmented reality (AR) games are popular in recent years, the motivation of in-app purchases still needs further investigation. The purpose of this paper is to investigate the antecedents of the intention to make a purchase in location-based AR games.

This research develops a conceptual model and hypotheses based on the theory of perceived values and satisfaction to investigate the antecedents. An online questionnaire was developed and distributed on popular websites to collect data, and 662 usable responses were collected from the players of Pokémon Go in Taiwan.

In total, 22 hypotheses were validated by using partial least squares techniques. Among the antecedents of in-app purchases intention in the model, the perceived value and satisfaction were found to have strong direct effects. The antecedents of the perceived value (flow, design aesthetic, social self-expression and good price) have direct influences on the perceived value of all players. Design aesthetic, reward and the perceived value were found to have a direct impact on all players’ satisfaction. Moreover, the differences between paying users and non-paying users were discussed and verified.

The model demonstrated relatively good explanatory power for purchase intention in the context of location-based AR game. The proposed model can provide insights to location-based AR game developers to design their games and marketing strategies.