Publications
Publications
  • June 2012
  • Article
  • Journal of Consumer Research

Consequence-Cause Matching: Looking to the Consequences of Events to Infer Their Causes

By: Robyn A. LeBoeuf and Michael I. Norton
  • Format:Print
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Abstract

We show that people non-normatively infer event causes from event consequences. For example, people inferred that a product failure (computer crash) had a large cause (widespread computer virus) if it had a large consequence (job loss), but that the identical failure was more likely to have a smaller cause (cooling fan malfunction) if the consequence was small-even though the consequences were objectively uninformative about the causes. Across experiments, participants' inferences about event causes were systematically affected by how similar (in both size and valence) those causes were to event consequences. Additional experiments further suggested that this "consequence-cause matching" arises because people are motivated to see the world as predictable, and because matching is an accessible schema that helps them to fulfill this motivation.

Keywords

Causal Inference; Product; Forecasting and Prediction; Motivation and Incentives; Failure

Citation

LeBoeuf, Robyn A., and Michael I. Norton. "Consequence-Cause Matching: Looking to the Consequences of Events to Infer Their Causes." Journal of Consumer Research 39, no. 1 (June 2012): 128–141.

About The Author

Michael I. Norton

Negotiation, Organizations & Markets
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