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Paper Type

ERF

Abstract

The playful design of technology (gamification) is an emerging concept enjoying widespread prominence. However, related projects oftentimes fail, which can be attributed to the inconclusive picture of empirical results. Research already identified the need to differentiate between different groups of users and personalize playful systems in order to be more engaging. Surprisingly, existing taxonomies do not adequately consider the effect of the context and postulate intra-individual stability of motivation across contexts. The paper at hand tests the validity of this assumption. Accordingly, we consult assumptions of the self-determination theory and the social identity approach using two different cases of application (i.e., a software supporting users to ride the bicycle and a software supporting local retailers) to test the external validity of motivation based on the affordances of the context. For this, we will use different statistical tools (e.g., factor- and cluster analyses) to ensure validity of the derived empirical insights.

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Aug 10th, 12:00 AM

Two-Faced Users? Exploring Motivational Taxonomies of Playful Systems

The playful design of technology (gamification) is an emerging concept enjoying widespread prominence. However, related projects oftentimes fail, which can be attributed to the inconclusive picture of empirical results. Research already identified the need to differentiate between different groups of users and personalize playful systems in order to be more engaging. Surprisingly, existing taxonomies do not adequately consider the effect of the context and postulate intra-individual stability of motivation across contexts. The paper at hand tests the validity of this assumption. Accordingly, we consult assumptions of the self-determination theory and the social identity approach using two different cases of application (i.e., a software supporting users to ride the bicycle and a software supporting local retailers) to test the external validity of motivation based on the affordances of the context. For this, we will use different statistical tools (e.g., factor- and cluster analyses) to ensure validity of the derived empirical insights.

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