Boom and Bust Behavior: On the Persistence of Strategic Decision Biases

INTRODUCTION Boom and bust or overshoot and collapse dynamics are common among firms in a large range of different industries. bicycles, semiconductors and running shoes, are examples of industries where boom and bust (Meadows, 1970) as well as industries with pronounced product and/or category lifecycles (Klepper, 1996). 2 The common managerial behavior underpinning boom and bust dynamics (B&B) across all of these industries is aggressive capacity expansion in the boom period when demand typically outstrips supply. Aggressive capacity expansion strategies in the boom phase ultimately result in excess capacity turning the boom into bust fundamental problem is that in many cases capacity adjustments cannot be made quickly enough to match demand. Time delays associated with expanding or reducing capacity require firms to forecast demand and make strategic decisions to initiate capacity changes far in advance. This combination of boundedly rational decision-making and capacity adjustment delays gives rise to boom and bust dynamics (Sterman et al., 2007). The combination is so difficult to manage that agents, including firms, rarely learn from boom and bust experiences. In some cases, the bust phase is so severe that the firms involved go bankrupt and disappear altogether. In other cases, the firms involved survive the bust only to fall into the same trap a few years later. This chapter examines the underlying cognitive and behavioral factors responsible for strategic decisions driving B&B dynamics, discusses the reasons firms do not learn to avoid boom and bust, and identifies tentative strategies for mitigating B&B behavior. At the same time, we shall conjecturally conclude, there might be a positive collective side to B&B behavior fostering accumulation of knowledge and physical infrastructure, especially regarding new technological paradigms. The next section discusses a number of real world cases of boom and bust dynamics. The examples illustrate quite common dynamic behaviors and highlight the crucial role of capacity investment decisions in B&B outcomes. Subsequent sections review the findings 3 from prior experimental research on B&B dynamics and discuss some key decision biases and heuristics that play important roles in B&B decision-making. The final section outlines some tentative strategies for moderating B&B decision-making. In the conclusion, we highlight some of the collectively positive aspects of booms and busts. EXAMPLES OF BOOM AND BUST DYNAMICS There are numerous examples of companies that have experienced B&B dynamics. Examples (Pinson, 1987). This section discusses two brief case examples of organizational B&B dynamics – EMI in …