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.

中文翻译：

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通过分析镜头调和选择过载的矛盾发现

太多的好事可能是有害的。选择超载是消费者心理学中一个引人注目的悖论，它举例说明了这一概念，即提供更多产品选择可能会阻碍而不是提高消费者满意度，即使消费者可以自由地忽略任何可用的选择。在过去几十年吸引了多个学科的强烈兴趣之后，关于选择超载的研究产生了大量但自相矛盾的发现，即使在元分析水平上也被广泛认为是不一致的。本文发起了一项跨学科调查，以解决概念和经验方面的不一致。具体来说，我们在现有的选择过载效应经验证据中发现了一种令人惊讶的稳健模式，并通过数学分析和广泛的模拟研究证明，该模式可能只出现在一种特定类型的潜在机制中，这种潜在机制是缓和的选择过载效应的基础。本文讨论了我们的研究结果的研究和实际意义——即分析元分析（使用数据分析的新兴领域）和机器学习在解决社会和行为科学中广泛认可的不一致性方面的广泛前景，以及信息系统社区在发展这个元分析的新时代中的独特而突出的作用。