This article aims to empirically study “crowd” dynamics in small teams and complement the work presented in Tucci et al. [2016], and Tucci and Viscusi [2017]. As in previous papers, we use as theoretical lens the framework and related typology of “crowd” dynamics discussed in Viscusi and Tucci [2015; 2018]. The framework considers the number of participants a sufficient, but not necessary condition for crowdsourcing, and distinguishes different types of crowd dynamics according to their growth tendency, degree of seriality and the intervening role of properties such as, e.g., density, equality, and goal orientation for distinguishing the distribution of agents within and between the different types of “crowds”, namely between communities, open crowds (multitudes [Virno 2004] e.g., Twitter users), closed crowds (controlled by intermediaries, such as, e.g., Innocentive that restrict growth and provide self-established boundaries), groups as crowd crystals, potentially leading to any of the others. Furthermore, as in previous papers, another goal of the study is to provide the setting for experiments in business domains to investigate how crowd characteristics may lower or increase “crowd capital,” here defined as the total number of crowd units having a demonstrated effectiveness in idea generation or task achievement [Tucci et al. 2016]. This definition adopts a more outcome-oriented perspective compared to other definitions emerging from this research stream [Lenart-Gansiniec 2016]; thus, our definition complements the conceptualization by Prpić & Shukla [2013, p.35035] and Prpić et al.[2015]. Finally, the article aims to contribute to the research on coordination in temporary groups [Valentine and Edmondson 2014] as well as on how dynamically assemble and managing paid experts from the crowd through flash teams [Retelny et al. 2014].