Explore the vast range of titles available.

Multi-criteria decision analysis (MCDA) involves asking decision makers difficult questions, and can leave them thinking that their judgements are not as coherent as they might have thought. This experience can be distressing and may even lead to rejection of the analysis. The psychology of preference sheds light both on how people naturally make choices without decision analytic assistance, and on how people think about the MCDA elicitation questions. As such, it can help the analyst to respond helpfully to difficulties which decision makers may face. In this paper, we review research from Behavioural Decision Theory relevant to MCDA. Our review follows the MCDA process, discussing research relevant to the structuring, value elicitation, and weighting phases of the analysis, outlining relevant and important findings, and open questions for research and practice.

This review provides a critical survey of psychology-and-economics (\"behavioraleconomics\") research in contract theory. First, I introduce the theories of individual decision making most frequently used in behavioral contract theory, and formally illustrate some of their implications in contracting settings. Second, I provide a more comprehensive (but informal) survey of the psychology-and-economics work on classical contract-theoretic topics: moral hazard, screening, mechanism design, and incomplete contracts. I also summarize research on a new topic spawned by psychology and economics, exploitative contracting, that studies contracts designed primarily to take advantage of agent mistakes.

This article defines and analyzes a ‘‘sparse max’’ operator, which is a less than fully attentive and rational version of the traditional max operator. The agent builds (as economists do) a simplified model of the world which is sparse, considering only the variables of first-order importance. His stylized model and his resulting choices both derive from constrained optimization. Still, the sparse max remains tractable to compute. Moreover, the induced outcomes reflect basic psychological forces governing limited attention. The sparse max yields a behavioral version of basic chapters of the microeconomics textbook: consumer demand and competitive equilibrium. I obtain a behavioral version of Marshallian and Hicksian demand, Arrow-Debreu competitive equilibrium, the Slutsky matrix, the Edgeworth box, Roy’s identity, and so on. The Slutsky matrix is no longer symmetric: nonsalient prices are associated with anomalously small demand elasticities. Because the consumer exhibits nominal illusion, in the Edgeworth box, the offer curve is a two-dimensional surface rather than a one-dimensional curve. As a result, different aggregate price levels correspond to materially distinct competitive equilibria, in a similar spirit to a Phillips curve. The Arrow-Debreu welfare theorems typically do not hold. This framework provides a way to assess which parts of basic microeconomics are robust, and which are not, to the assumption of perfect maximization.

Consumers often encounter reminders of resource scarcity. However, relatively little is known about the psychological processes that such reminders instantiate. In this article, we posit that reminders of resource scarcity activate a competitive orientation, which guides consumers’ decision making towards advancing their own welfare. Further, we reveal that this tendency can manifest in behaviors that appear selfish, but also in behaviors that appear generous, in conditions where generosity allows for personal gains. The current research thus offers a more nuanced understanding of why resource scarcity may promote behaviors that appear either selfish or generous in different contexts, and provides one way to reconcile seemingly conflicting prior findings.

In this paper, we provide a perspective into the main ideas and findings emerging from the growing literature on motivated beliefs and reasoning. This perspective emphasizes that beliefs often fulfill important psychological and functional needs of the individual. Economically relevant examples include confidence in ones' abilities, moral self-esteem, hope and anxiety reduction, social identity, political ideology, and religious faith. People thus hold certain beliefs in part because they attach value to them, as a result of some (usually implicit) tradeoff between accuracy and desirability. In a sense, we propose to treat beliefs as regular economic goods and assets—which people consume, invest in, reap returns from, and produce, using the informational inputs they receive or have access to. Such beliefs will be resistant to many forms of evidence, with individuals displaying non-Bayesian behaviors such as not wanting to know, wishful thinking, and reality denial.

Theoretical models distinguish two decision-making strategies that have been formalized in reinforcement-learning theory. A model-based strategy leverages a cognitive model of potential actions and their consequences to make goaldirected choices, whereas a model-free strategy evaluates actions based solely on their reward history. Research in adults has begun to elucidate the psychological mechanisms and neural substrates underlying these learning processes and factors that influence their relative recruitment. However, the developmental trajectory of these evaluative strategies has not been well characterized. In this study, children, adolescents, and adults performed a sequential reinforcementlearning task that enabled estimation of model-based and model-free contributions to choice. Whereas a model-free strategy was apparent in choice behavior across all age groups, a model-based strategy was absent in children became evident in adolescents, and strengthened in adults. These results suggest that recruitment of model-based valuation systems represents a critical cognitive component underlying the gradual maturation of goal-directed behavior.

We examine the effect of trust in venture capital. Our theory predicts a positive relationship of trust with investment, but a negative relationship with success. Using a hand-collected dataset of European venture capital deals, we find that the Eurobarometer measure of trust among nations positively predicts venture capital firms' investment decisions, but that it has a negative correlation with successful exits. Our theory also predicts that earlier stage investments require higher trust, that syndication is more valuable in low-trust situations, and that higher trust investors use more contingent contracts. The empirical evidence supports these predictions.

We develop an equilibrium framework that relaxes the standard assumption that people have a correctly specified view of their environment. Each player is characterized by a (possibly misspecified) subjective model, which describes the set of feasible beliefs over payoff-relevant consequences as a function of actions. We introduce the notion of a Berk–Nash equilibrium: Each player follows a strategy that is optimal given her belief, and her belief is restricted to be the best fit among the set of beliefs she considers possible. The notion of best fit is formalized in terms of minimizing the Kullback–Leibler divergence, which is endogenous and depends on the equilibrium strategy profile. Standard solution concepts such as Nash equilibrium and self-confirming equilibrium constitute special cases where players have correctly specified models. We provide a learning foundation for Berk–Nash equilibrium by extending and combining results from the statistics literature on misspecified learning and the economics literature on learning in games.

Recommender systems are becoming a salient part of many e-commerce websites. Much research has focused on advancing recommendation technologies to improve accuracy of predictions, although behavioral aspects of using recommender systems are often overlooked. In our studies, we explore how consumer preferences at the time of consumption are impacted by predictions generated by recommender systems. We conducted three controlled laboratory experiments to explore the effects of system recommendations on preferences. Studies 1 and 2 investigated user preferences for television programs across a variety of conditions, which were surveyed immediately following program viewing. Study 3 investigated the granularity of the observed effects within individual participants. Results provide strong evidence that the rating presented by a recommender system serves as an anchor for the consumer's constructed preference. Viewers' preference ratings are malleable and can be significantly influenced by the recommendation received. The effect is sensitive to the perceived reliability of a recommender system and, thus, not a purely numerical or priming-based effect. Finally, the effect of anchoring is continuous and linear, operating over a range of perturbations of the system. These general findings have a number of important implications (e.g., on recommender systems performance metrics and design, preference bias, potential strategic behavior, and trust), which are discussed.

Intuitively, how you feel about potential outcomes will determine your decisions. Indeed, an implicit assumption in one of the most influential theories in psychology, prospect theory, is that feelings govern choice. Surprisingly, however, very little is known about the rules by which feelings are transformed into decisions. Here, we specified a computational model that used feelings to predict choices. We found that this model predicted choice better than existing value-based models, showing a unique contribution of feelings to decisions, over and above value. Similar to the value function in prospect theory, our feeling function showed diminished sensitivity to outcomes as value increased. However, loss aversion in choice was explained by an asymmetry in how feelings about losses and gains were weighted when making a decision, not by an asymmetry in the feelings themselves. The results provide new insights into how feelings are utilized to reach a decision.