Double Jeopardy in digital entertainment: a replication corner study using Steam data

Abstract We replicate the Double Jeopardy (DJ) law using Steam data and a loyalty measure aligned with the DJ construct. Using 2350 games across five genres, loyalty is defined as user-level share of category requirements (SCR) within genre, with multi-genre playtime allocated by equal weights. Spearman correlations with bootstrap confidence intervals show DJ for Action, Strategy, and RPG (ρ = 0. 215–0. 281, CIs excluding zero), while Simulation and Adventure are inconclusive. Results are robust to alternative loyalty measures and to restricting SCR to users with multiple games in a genre. Age stratification indicates weaker effects for newer releases. These findings extend DJ to experiential digital products while delineating boundary conditions by genre and market maturity.