Zachary Fulker | Searcharxiv

arXiv2024

Cooperation in the Gig Economy: Insights from Upwork Freelancers

Existing literature predominantly focuses on how freelancers individually complete tasks and projects. Our study examines freelancers' willingness to work collaboratively. We report results from a survey of 122 freelancers on a leading online labor market platform (Upwork) and examine freelancers' preferences for collaboration and explore several antecedents of cooperative behaviors. We then test if actual cooperative behavior matches with freelancers' stated preferences through an incentivized social dilemma experiment. We find that respondents cooperate at a higher rate (85%) than reported in previous comparable studies (between 50-75%). This high rate of cooperation may be explained by an ingroup bias. Using a sequential mediation model we demonstrate the importance of a sense of shared expectations and accountability for cooperation. We contribute to a better understanding of the potential for collaborative work on online labor market platforms by assessing if and what social factors and collective culture exist among freelancers. We discuss the implications of our results for platform designers by highlighting the importance of platform features that promote shared expectations and improve accountability. Overall, contrary to existing literature and predictions, our results suggest that freelancers in our sample display traits that are more consistent with belonging to a coherent group with a shared collective culture, rather than being anonymous actors in a transaction-based market.

cs.HC↗

arXiv2024

Spontaneous emergence of groups and signaling diversity in dynamic networks

We study the coevolution of network structure and signaling behavior. We model agents who can preferentially associate with others in a dynamic network while they also learn to play a simple sender-receiver game. We have four major findings. First, signaling interactions in dynamic networks are sufficient to cause the endogenous formation of distinct signaling groups, even in an initially homogeneous population. Second, dynamic networks allow the emergence of novel {\em hybrid} signaling groups that do not converge on a single common signaling system but are instead composed of different yet complementary signaling strategies. We show that the presence of these hybrid groups promotes stable diversity in signaling among other groups in the population. Third, we find important distinctions in information processing capacity of different groups: hybrid groups diffuse information more quickly initially but at the cost of taking longer to reach all group members. Fourth, our findings pertain to all common interest signaling games, are robust across many parameters, and mitigate known problems of inefficient communication.

cs.SI↗