Learning to Be Creative: A Mutually Exciting Spatiotemporal Point Process Model for Idea Generation in Open Innovation

2021 | Information Systems Research | Citations: 5

Authors: Aggarwal, Vipul; Hwang, Elina H.; Tan, Yong

Abstract: This study investigates the creative idea generation process in an open innovati ... Expand

Abstract: This study investigates the creative idea generation process in an open innovation platform. The idea generation process is simultaneously influenced by multiple activities: knowledge acquisition from participants’ interactions with each other’s ideas, deliberate practice through persistent participation, and learning through failures. Due to the dynamic interplay across these activities, it is challenging to identify each activity’s influence on creative ideation outcomes using reduced-form regression analysis. To overcome these challenges, we employ a comprehensive empirical framework, the mutually exciting spatiotemporal point process model with unobserved heterogeneity, which endogenizes the occurrences of these activities in continuous time and allows for user-dependent effects. By utilizing the activity stream data of 13,028 participants from 2010 to 2016 in an open innovation platform, we uncovered synergistic effects of these activities on creative outcomes. We find that knowledge acquired through interaction with others (i.e., stimulus ideas) plays a vital role in the creative ideation process, but their effect is more nuanced than what we have known so far. In contrast to the prior belief that distant analogies, stimulus ideas outside of a problem domain, spur creativity, we find that distant analogies lead to failures. Yet, we further find that such failures are indispensable to the creative ideation process because failures motivate idea generators (1) to acquire more knowledge by increasing their future interactions with other participants’ ideas (learning from others), and (2) to persist in generating ideas that lead to improvements in their ability to apply the acquired knowledge and to identify innovation tasks that are relevant to their stock of acquired knowledge (learning by doing). Our results indicate that failures are a stronger driver of the learning activities than successes. Based on our findings, we offer insights on how to cultivate creativity in an open innovation setting. Collapse

Topics: knowledge acquisition idea generation open innovation innovation management logistics management

Methods: business process modeling data transformation computational algorithm stochastic model regression analysis method

Theories: creativity theory