Explaining social dynamics in coopetition networks using trust awareness

Idea crowd-sourcing are often based on the principle of simultaneous cooperation and competition namely coopetition. Some studies suggest that this model has some benefits in terms of participation and performance within platforms. They combine structural methods, using social network analysis techniques, as well as qualitative methods based on an interpretive content analysis. However, coopetition is still poorly understood mainly at the individual level. Indeed, since cooperation and competition are often view as conflictual situation, we do not know if and how coopetition enhances cooperative and competitive behaviors. Previous research lack support for the societal dimension, including the interactional history, which is an important component that affects the user's behavior. Moreover, little is known about the social dynamics of users and how relationships between them are established. To address these limits, we use an agent-based model as agents endorse interactions and offer well-developed capabilities to formally express and interpret information useful to simulate social dynamics in coopetition networks. To specify agent's behavior, we build a trust model that enables agents to reason about the confidence of others while guiding their decision-making process when they want to interact. The purpose of this study is to explore the micro social dynamics using a trust model to better understand the macro social dynamics in a coopetition network, which could ultimately lead to innovative outcomes and a better performance through a specific platform typology. To evaluate the performance of the platform as well as the evolution of the social dynamics, we run several multi-agent simulations varying the distribution of three agents roles: the cooperators, the competitors, and the coopetitors. Obtained results give us insight on how to enhance the agents motivation within the platform to make it more conducive to generate good ideas.