Modeling and debiasing resource saving judgments
Journal Title: Judgment and Decision Making - Year 2014, Vol 9, Issue 5
Abstract
Svenson (2011) showed that choices of one of two alternative productivity increases to save production resources (e.g., man-months) were biased. Judgments of resource savings following a speed increase from a low production speed line were underestimated and following an increase of a high production speed line overestimated. The objective formula for computing savings includes differences between inverse speeds and this is intuitively very problematic for most people. The purpose of the present studies was to explore ways of ameliorating or eliminating the bias. Study 1 was a control study asking participants to increase the production speed of one production line to save the same amount of production resources (man-months) as was saved by a speed increase in a reference line. The increases judged to match the reference alternatives showed the same bias as in the earlier research on choices. In Study 2 the same task and problems were used as in Study 1, but the participants were asked first to judge the resource saving of the reference alternative in a pair of alternatives before they proceeded to the matching task. This weakened the average bias only slightly. In Study 3, the participants were asked to judge the resources saved from each of two successive increases of the same single production line (other than those of the matching task) before they continued to the matching problems. In this way a participant could realize that a second production speed increase from a higher speed (e.g., from 40 to 60 items /man-month) gives less resource savings than the same speed increase from a first lower speed (e.g., from 20 to 40 items/man-month. Following this, the judgments of the same problems as in the other studies improved and the bias decreased significantly but it did not disappear. To be able to make optimal decisions about productivity increases, people need information about the bias and/or reformulations of the problems.
Authors and Affiliations
Ola Svenson, Nichel Gonzalez and Gabriella Eriksson
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