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Decision Sciences: How the Game is Played

All in a Day's Work

All in a Day's Work - click here for detailsImagine you are a cab driver. What you earn in a given day varies according to the weather, time of year, conventions in town, and other factors. As a rational person, you want to maximize both your income and your leisure time. To achieve that, you should work more hours when wages are high and fewer hours when wages are low.

What that means is that cab drivers should work more hours on busy days and fewer hours on slow days. Do they? Not at all; they do the opposite.

Colin Camerer of the California Institute of Technology made this discovery when he and his colleagues interviewed a large sample of cab drivers. They found that the cabbies decide how many hours to work by setting a target amount of money they want to make each day. When they reach their target, they stop working. So on busy days, they work fewer hours than on slow days.

Why? Camerer suggested that working an extra hour simply may not be worth an hour of leisure time; in the language of economics, the marginal utility is too low. On the other hand, it may not be the money as much as cab drivers' feelings about the money—or, more precisely, how they think they may feel if they depart from their usual working habits.

NSF has supported Camerer and others in their efforts to explain this and other paradoxes that characterize human economic behavior. From the beginning, decision science research has had the goal of a better fix on people's feelings about wages, leisure, and tradeoffs between them, with implications for labor relations, productivity, and competitiveness across a wide spectrum of industries.

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Practical Payoffs
Polls, Markets, and Allocations
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Questioning Utility Theory
Why We Make Foolish Decisions
The Fruits of Economic Research Are Everywhere
All in a Day's Work
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