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Instigated by the trend of collaborative economics, taking into consideration the particularities pointed out by Simis (2015), such as a new social, economic and technological scenario, this paper aims to identify which factors serve as motivators for collaboration among the technologies of this scenario.

In this paper, the authors analyzed Waze, an application that works based on traffic information made available by the users of the platform. For the development of this qualitative work, aspects that served as the basis for the interview script applied were classified into three different categories: utilization, personal values and gamification; the latter being an important aspect for collaboration in the application in question. Two distinct groups were interviewed; one of regular users of Waze, and the other of advanced users, who also work voluntarily in the maintenance of the app.

The results indicate that personal values are determinant factors for both groups; however, there are distinct incentives for the different users interviewed, like reciprocity, altruism and empathy. The first one is an important aspect to share information by the regular users, while the other ones are characteristics advanced users.

The study presents some limitations in terms of the restricted group and focus on only one of the many collaborative technological social, as well as lacking on-site analysis of the use of Waze.

This is a valid research when taking into consideration studies that approach the app Waze, as the issues explored in this paper are new in the academic studies considering previous app’s analyses that are related to functionality.

The results presented in this study help to understand the current relationship between sharing economy and the technology provided to those who use these platforms.

This research opens the horizon for future studies applied on other collaborative technological user platforms, to see if the results would be similar and construct a user journey in relation to information sharing through experimental monitoring.