What Drives Your Decision-Making?—An Economical Perspective with Amit Gandhi


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By Richard Jacobs. Discovered by Player FM and our community — copyright is owned by the publisher, not Player FM, and audio is streamed directly from their servers. Hit the Subscribe button to track updates in Player FM, or paste the feed URL into other podcast apps.

What dictates your decision to buy one type of cereal over the other? Cost? Nutritional content? Or is something else…like the colors of the packaging, or the nostalgic association you have with it from childhood?

The truth is, you might not even be consciously aware of why you make the product purchases you do. But rest assured…others are studying this topic very closely.

Press play to learn:

  • How to distinguish between and understand the deep drivers vs. random factors of decision-making
  • How to bridge the disconnect between perceptual and mathematical models of probability in product purchase decisions
  • Whether and how to use large amounts of unstructured data in decision-making processes

Amit Gandhi is a professor at the University of Pennsylvania and applied economist at Microsoft, where he specializes in industrial organization and econometrics. In simpler terms, he focuses on the use of data in economic models and decision-making processes, whether at the organization, industry, or individual level.

He explains the most common deep drivers of decision-making and their impact on behavioral outcomes, but draws special attention to the ‘random’ factors that impact decisions, but have no real connection to deep drivers like cost and utility. “Do you want to try to design choice architectures that make those things go away, or do you recognize them as part of the human condition and build your product strategy in such a way as to accommodate them?” asks Gandhi. Most of his current research is about answering this question.

Tune in for all the details, and learn more about Gandhi’s work by finding him on Google Scholar. Episode also available on Apple Podcasts: apple.co/30PvU9C

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