Paul J. H. Schoemaker

Sources of Bias in Assessment Procedures for Utility Functions

Utility functions are an important component of normative decision analysis, in that they characterize the nature of peoples risk-taking attitudes. In this paper we examine various factors that make it difficult to speak of the utility function for a given person. Similarly we show that it is questionable to pool risk-propensity data across studies (for descriptive purposes) that differ in the elicitation methods employed. The following five sources of bias or indeterminacy are hypothesized and demonstrated. First, certainty equivalence methods generally yield greater risk-seeking than probability equivalence methods. Second, the probability and outcome levels used in reference lotteries induce systematic bias. Third, combining gain and loss domains yields different utility measures than separate examinations of the two domains. Fourth, whether a risk is assumed or transferred away exerts a significant influence on peoples preferences in ways counter to expected utility theory. Finally, context or framing differences strongly affect choice in a nonnormative manner. The above five factors are first discussed as essential choices to be made by the decision scientist in constructing Von Neumann-Morgenstern utility functions. Next, each is examined separately in view of existing literature, and demonstrated via experiments. The emerging picture is that basic preferences under uncertainty exhibit serious incompatibilities with traditional expected utility theory. An important implication of this paper is to commence development of a systematic theory of utility encoding which incorporates the many information processing effects that influence peoples expressed risk preferences.

Risk Taking and Problem Context in the Domain of Losses: An Expected Utility Analysis

This paper presents an experimental investigation of risk taking in the domain of losses. The results are partly compatible with expected utility theory, assuming an inflection point in the utility function over losses. However, overweighting of low probabilities and underweighting of high ones was observed, which runs counter to the expected utility model. Additionally, a strong context effect was observed in which choices presented in an insurance context were judged with greater risk aversion than mathematically identical choices presented as standard gambles. Both the normative and descriptive implications for expected utility theory are discussed. This article examines two related issues regarding decision-making under conditions of objective or known risk. The first one concerns the nature of peoples risk preferences for losses, and its compatibility with expected utility theory; the second concerns the extent to which such risk preferences are influenced by problem context.

Prospect theory's reflection hypothesis: A critical examination

Abstract In a recent new theory of decision making under risk (called prospect theory), Kahneman and Tversky suggest that peoples preferences among lotteries on the loss side are a mirror image of those on the gain side. This article examines the reflection hypothesis at both an across-subject and within-subject level. Since significant reflection at either level does not necessarily imply significant reflection at the other, upper and lower bounds are computed for each. Four types of within-subject reflectivity are distinguished and analyzed. Relationships among these types are examined theoretically as well as empirically. Experimental results from three separate studies are presented, which seriously question the generality of prospect theorys reflection hypothesis.

Avoiding the Pitfalls of Emerging Technologies

Despite their superior resources, incumbents have a poor track record in developing and managing emerging technologies. Established firms are prone to delay participation and stick with the familiar too long. Even if these pitfalls are sidestepped, incumbents are often unwilling to make a full-fledged commitment and find it difficult to persist in the face of uncertainty and adversity. Some established firms have been able to avoid these pitfalls by: attending closely to signals from the periphery of their markets; investing in a learning capacity so there is a diversity of viewpoints that challenge prevailing mind-sets and myopic views of new ventures; maintaining their flexibility by adopting a real options perspective, which lets the firm make informed investments when the time is right; and organizationally separating the fledging initiative pursuing the emerging technology from the mainstream activities.

An Experimental Study of Insurance Decisons

This chapter describes an insurance study that was aimed at a better understanding of people’s preferences for so-called pure risk alternatives (Williams, 1966). Unlike speculative risk choices, pure risk alternatives offer no chance of gain. The present study ran parallel to another research effort, also based at the Wharton School of the University of Pennsylvania. This other effort consisted of field studies (Kunreuther et al., 1978) and laboratory experiments (Slovic et al., 1977) on insurance behavior, particularly decisions involving low-probability, high-loss events. Relationships with this parallel research will be highlighted later in this chapter.

Determinants of Risk-Taking: Behavioral and Economic Views

The concept of risk-taking is examined from various perspectives: economic, decision theoretic, and psychological. Multiple factors are discussed as complicating the extraction of any presumed risk-taking propensity from a persons real-world behavior.Problem structuring, beliefs, andvalues (defined here as riskless as opposed to risky utility) may of course underlie differences in risk behavior. In addition,context andprocess factors can induce variance in risk-bearing. Also,portfolio effects (including cross-sectional, multiattribute, and longitudinal) may greatly complicate the measurement of risk-taking propensity. Lastly, the presence of incompletemarkets (via which risks can be partially diversified and traded) may further mask the link between intrinsic and observed risk-taking. This article examines each of these measurement obstacles and sources of variance.

A Pyramid of Decision Approaches

Under increasing pressure to make better decisions in less time, managers often use the quickest and easiest decision-making method: going on ” gut feel.” But recent decision research shows that intuition is much less reliable than most people believe. Managers need to use more sophisticated methods. We describe a series of increasingly accurate (and demanding) decision-making approaches. We start with purely intuitive choices, which are quickest and least accurate, and then examine heuristic short-cuts and rules-of-thumb. Thereafter, we discuss more demanding and reliable methods, such as bootstrapping and value analysis. We examine the strengths and weaknesses of each approach in terms of speed, accuracy and justifiability. Each approach is described in step-by-step detail, with illustrative applications to managerial practice. Finally, we offer pragmatic advice on incorporating the more sophisticated techniques into your organization.

The Future Challenges of Business: Rethinking Management Education

he traditional paradigm of business schools, with its strong focus onanalytical models and reductionism, is not well suited to handle theambiguity and high rate of change facing many industries today.Business educators have always faced the dilemma of academicrigor pitted against practical relevance (notwithstanding Kurt Lewin’s astuteobservation that nothing is as practical as good theory). The dilemma stems fromtwo seemingly conflicting notions. On one hand, universities must hold true tothe time-honored tradition of scholarship and the associated principles of scien-tific inquiry. On the other hand, whatever universities teach and explore withintheir professional schools must be relevant to the clinical art that defines thatprofession at the time. Unlike such professions as law, medicine, engineering, or architecture, business has yet to develop a unifying professional identity or a standard for professional certification (which the MBA presently is not).The need to balance the competing demands of rigor and relevance wasscrutinized in a provocative 2005

Utility measurement: Signal, noise, and bias

Abstract Recent research has documented various violations of procedural invariance, ranging from preference reversals to discrepancies among theoretically equivalent utility encoding methods. This paper explores multiple causes for such discrepancies, focusing on the effects and possible interactions of (1) random noise, (2) insufficient adjustment due to anchoring, and (3) refraining. The case of certainty-equivalence (CE) versus probability-equivalence (PE) judgments is used to model and study the above effects. First, a random noise model is developed. Second, anchoring and insufficient adjustment are formalized, including the notion of variable anchors. Third, our earlier PE-reframing hypothesis (Hershey and Schoemaker, 1985) is examined for the mixed as well as the gain and loss domains. Finally, the effects are combined to yield aggregate predictions for different domains and response sequences. The second part of the paper reports an experiment aimed at testing the component and composite predictions. Some evidence is found for each main effect, although none of the three alone can explain the results. Our data suggest that multiple effects are operative, specifically PE reframing and random noise. We briefly discuss the challenges this poses for both utility encoding and psychological theories concerning violations of procedural invariance.

The role of statistical knowledge in gambling decisions: Moment vs risk dimension approaches☆

Abstract This study examines whether statistically trained and untrained subjects differ in their strategies for risk assessment and if so, in what ways they differ, and whether these differences can be understood from an information processing perspective. Recent research on decision making under risk has focused on the moment vs risk dimension approach. Experimental evidence exists for either model even though they are theoretically incompatible, one being multiplicative, the other additive. This study suggests that the conflicting findings of previous studies can be partly explained by controlling for the confounding effects of statistical training. It is suggested that statistical knowledge (1) reduces the cognitive complexity of assessing duplex bets, (2) improves the quality of risk-assessment, and (3) increases the propensity that subjects will follow a moment model. The findings were corroborated by regression analyses, although note was made of the methodological difficulties inherent in this approach.