“Compete, Cooperate... Why not both?” Player orientation and hybrid vs. competitive mechanics in gamified crowdsourcing with JellyfishGO!

Abstract

Sustaining participant engagement while maintaining data quality is a central challenge for games with a purpose (GWAPs). In this article we examine whether player orientation (according to Bartle’s taxonomy) shapes contribution volume under competitive and hybrid (intra-team cooperation + light inter-team rivalry) GWAP mechanics. Although the design provisioned a purely cooperative arm, too few cooperative-only sessions materialised for session-level analysis, so the empirical comparison is Competitive versus Hybrid. To test this, we ran a one-week quasi-experimental field trial of JellyfishGO!, an Augmented Reality (AR) GWAP, with 64 participants in 32 two-person teams. Players completed a six-item Player-Type Decision (PTD) at profiling and the 24-item Hexad post-play; high-resolution logs captured captures, missions, badges, team matches and leaderboard dynamics. Across model-free contrasts, robust Ordinary Least Squares (OLS) and multilevel count models (with exposure offsets), Hybrid configurations produced the largest and most robust throughput gains: Hybrid sessions were longer and showed higher captures/minute, with Incidence-Rate Ratio ( I R R ) estimates for Hybrid vs Competitive in a compact window ≈ 1.47 -1.91 (robust to trimming, negative-binomial re-specification and jackknife). Modelled Arm × Bartle interactions were small and imprecise, giving limited evidence that PTD labels systematically moderate the Hybrid boost; Killers did exhibit pronounced short bursts in Hybrid contexts. Session-level consensus quality was effectively invariant, limiting fidelity inference. We conclude that hybrid team structures are a promising route to raise contribution volume (throughput) in mixed populations-but must be paired with layered quality controls (redundancy, rolling consensus, fraud detection) and larger, preregistered future replications to clarify Mechanic × Orientation × Task interactions.