This paper explores the relation between decision theoretic conceptions of risk and the conceptions held by executives. It considers recent studies of risk attitudes and behavior among managers against the background of conceptions of risk derived from theories of choice. We conclude that managers take risks and exhibit risk preferences, but the processes that generate those observables are somewhat removed from the classical processes of choosing from among alternative actions in terms of the mean (expected value) and variance (risk) of the probability distributions over possible outcomes. We identify three major ways in which the conceptions of risk and risk taking held by these managers lead to orientations to risk that are different from what might be expected from a decision theory perspective: Managers are quite insensitive to estimates of the probabilities of possible outcomes; their decisions are particularly affected by the way their attention is focused on critical performance targets; and they make a sharp distinction between taking risks and gambling. These differences, along with closely related observations drawn from other studies of individual and organizational choice, indicate that the behavioral phenomenon of risk taking in organizational settings will be imperfectly understood within a classical conception of risk.decision making, risk, management

Empirical investigations of decision making indicate that the level of individual or organizational risk taking is responsive to a risk taker's changing fortune. Several nonstationary random-walk models of risk taking are developed to describe this phenomenon. The models portray a risk taker's history as the cumulated realizations of a series of independent draws from a normal probability distribution of possible outcomes. This performance distribution is assumed to have an unchanging mean and a variance (risk) that changes. The changes are seen as determined by (a) a focus of attention on 1 of 2 reference points (an adaptive aspiration for resources and the survival point) and (b) the relation between current resources and the focal point. The models are elaborated by examining the impact of adaptive aspirations and attention focus on risk taking over time in a cohort of risk takers and in a renewing population of risk takers.Theories of decision making under uncertainty most commonly assume that returns to decisions are draws from a probability distribution that is conditional on the choice made. Decision makers are generally assumed to prefer alternatives with higher expected values to those with lower ones, but they also are assumed to consider the riskiness of an alternative. Riskiness is associated with lack of certainty about the precise outcome of a choice and thus with variation in the probability distribution. Psychological studies of risk preference and risk taking emphasize the ways in which such variability affects choice.Empirical investigations of choices by individuals and organizations indicate that preferences for variability are not constant but are responsive to changing fortune. The mechanisms of response are familiar to students of the psychology of decision making, but they yield a somewhat complicated picture:1. Risk taking and danger. Risk taking appears to be affected by threats to survival. The reported effects, however, appear to be contradictory. On the one hand, it has been observed that increasing threats to survival stimulate greater and greater risk taking, presumably in an effort to escape the threats (Bowman, 1982;Bromiley & Wiseman, 1989;Mayhew, 1979). On the other hand, danger has been portrayed as leading to rigidity and to extreme forms of risk aversion (Greenhalgh,

Organizations that go through rare and unusual events, whether they are costly or beneficial, face the challenge of interpreting and learning from these experiences. Although research suggests that organizations respond to this challenge in a variety of ways, we lack a framework for comparing and analyzing how organizational learning is affected by rare events. This paper develops such a framework. We begin by first outlining two views of rare events. The first view defines rare events as probability estimates, usually calculated from the frequency of the event. The second view defines rare events as opportunities for unique sensemaking based on the enacted salience of specific features of the rare events. We next use these definitions to explore how rare events trigger learning, and then examine the kind of learning processes that are triggered by rare events. We conclude with a discussion of promising areas of research on learning from rare events.

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Research summary:This study draws on the resource-based view and the behavioral theory of the firm to gain new insights about the effect of performance relative to aspiration level (i.e., performance feedback) on the decision to enter new markets. Results show an inverted U-shaped relationship between performance both below and above aspiration level, and the probability of firms to enter new markets. That is, when firms are well below or well above their aspiration level, they significantly change their behavior. This article develops a theoretical framework to clarify and organize these findings.Managerial summary: This study examines the effect of performance feedback, and particularly, large discrepancies between firm performance and aspiration level on the decision to enter new markets. It provides support to the role of performance feedback in affecting the decision to enter new markets, a factor that has received relatively little attention in the extensive literature that has examined the inducements of such moves. Results show that, as performance falls below or rises above aspiration, a firm's probability of entering new markets increases up to a certain point after which this relationship decreases. This shows that the tendency to enter new markets is different for firms that are in the neighborhood of aspiration level compared to those that are well below or above it. into markets during a period as an event. For robustness test, we used the number of new markets as our dependent variable and re-estimated the models. The main results did not change.