Too much of a good thing can be harmful. Choice overload, a compelling paradox in consumer psychology, exemplifies this notion with the idea that offering more product options could impede rather than improve consumer satisfaction, even when consumers are free to ignore any available option. After attracting intense interest in the past decades from multiple disciplines, research on choice overload has produced voluminous yet paradoxical findings that are widely perceived as inconsistent even at the meta-analytic level. This paper launches an interdisciplinary inquiry to resolve the inconsistencies on both the conceptual and empirical fronts. Specifically, we identified a surprising butrobust pattern among the existing empirical evidence for the choiceoverload effect and demonstrated through mathematical analysis and extensive simulation studies that the pattern would only likely emerge from one specific type of latent mechanism underlying the moderated choiceoverload effect. The paper discusses the research and practical implications of our findings—namely, the broad promise of analytical meta-analysis (an emerging area for the use of data analytics) and machine learning to address the widely recognized inconsistencies in social and behavioral sciences, and the unique and salient role of the information systems community in developing this new era of meta-analysis.