Description–experience gap under imperfect information

Purpose

Capital project delivery, such as the delivery of transportation networks and industrial facilities, often suffers losses due to overly aggressive planning. Planners often are overly optimistic about the chance of success while underestimating risks. The purpose of this paper is to examine the hypothesis that these biases are from the difficulties most decision makers face when interpreting probabilistic information.

Design/methodology/approach

Three behavioral experiments were conducted to test the theoretical fitness of the paradigms proposed by the description–experience gap literature, namely, the sampling errors effect, the recency effect and statistical information format. College students were recruited to participate in a series of estimating tasks. And their estimating results were compared given different levels of information completeness.

Findings

It was found that the existing paradigms could predict risk decision making in the risk-averse estimating scenarios where test subjects were required to give a relatively conservative estimate, but they seemed to be less effective in predicting decisions in the risk-seeking estimating scenario, where test subjects were asked to give a relatively aggressive estimate.

Originality/value

Based on these findings, an integrative model is proposed to explain the observations pertaining to aggressive planning in capital projects. Two dimensions are deemed to be relevant: including risk-taking intentions, and an information uncertainty continuum that ranges from an implicit experience-based information representation to an explicit description-based information representation.