Expectancy Theory
What is the Expectancy Theory?
Expectancy theory posits that individuals choose to engage in certain behaviors based on the expected outcomes. According to this theory, the decision to act in a particular way is influenced by the anticipated rewards and the belief that the behavior will lead to the desired result. Developed by Victor Vroom, this theory highlights three key components: expectancy (belief that effort leads to performance), instrumentality (belief that performance leads to rewards), and valence (value placed on the rewards).
The Basic Idea
When people ask me how I spent last summer, I tell them that I studied for the LSAT from May through August. This typically results in musings of how terrible it must have been and questions of how I motivated myself. While studying for the test was a stressful experience, it was nowhere close to being terrible. I was motivated to study because I knew that it would be a valuable step toward my larger goal, which was getting into law school. I expected that increasing my efforts to study would increase my chances of a high score, which I believed would help me achieve my overall goal.
My experience was one that followed expectancy theory, which assumes that people are motivated to engage in certain behaviors because of their expected outcomes.1 Thus, the values associated with said outcomes are the discerning factors for choosing one behavior over another. Expectancy theory separates the decision making process into expectancy (efforts will lead to high performance), instrumentality (performance will lead to predicted outcomes), and valence (predicted outcomes are desirable).
Motivation depends on how much we want something and how likely we think we are to get it.
– Victor Vroom, pioneer of the expectancy theory of motivation
About the Authors
Dan Pilat
Dan is a Co-Founder and Managing Director at The Decision Lab. He is a bestselling author of Intention - a book he wrote with Wiley on the mindful application of behavioral science in organizations. Dan has a background in organizational decision making, with a BComm in Decision & Information Systems from McGill University. He has worked on enterprise-level behavioral architecture at TD Securities and BMO Capital Markets, where he advised management on the implementation of systems processing billions of dollars per week. Driven by an appetite for the latest in technology, Dan created a course on business intelligence and lectured at McGill University, and has applied behavioral science to topics such as augmented and virtual reality.
Dr. Sekoul Krastev
Dr. Sekoul Krastev is a decision scientist and Co-Founder of The Decision Lab, one of the world's leading behavioral science consultancies. His team works with large organizations—Fortune 500 companies, governments, foundations and supernationals—to apply behavioral science and decision theory for social good. He holds a PhD in neuroscience from McGill University and is currently a visiting scholar at NYU. His work has been featured in academic journals as well as in The New York Times, Forbes, and Bloomberg. He is also the author of Intention (Wiley, 2024), a bestselling book on the science of human agency. Before founding The Decision Lab, he worked at the Boston Consulting Group and Google.
