A SEQUENTIAL LEARNING ANALYSIS OF DECISIONS IN ORGANIZATIONS TO ESCALATE INVESTMENTS DESPITE CONTINUING COSTS OR LOSSES

Abstract

Reinforcement process may underlie decisions frequently found in organizations to escalate investments of time, money and other resources in strategies (e.g., product development, capital investment, plant expansion) that do not result in immediate reinforces. Whereas cognitive biases have been proffered in previous explanations, the present analysis suggested that this persistence is a form of resistance to extinction arising from experiences with past investments that were variably reinforced. This explanation was examined in two experiments by varying the pattern of returns and losses subjects experienced for investment decisions prior to experiencing a series losses. Consistent with the proposed explanation, two conditions resulted in higher levels of recommitment during continuous losses: (a) training using a variable schedule of partial reinforcement, and (b) no training on the task. Results indicate that behavior analysis can be used to understand and control situations in organizations that are prone to escalation, such as investments in the research and development of new product lines and extensions of further loans to customers.

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