Incomparability and Incommensurability in Choice: No Common Currency of Value?

Models of decision-making typically assume the existence of some common currency of value, such as utility, happiness, or inclusive fitness. This common currency is taken to allow comparison of options and to underpin everyday choice. Here we suggest instead that there is no universal value scale, that incommensurable values pervade everyday choice, and hence that most existing models of decision-making in both economics and psychology are fundamentally limited. We propose that choice objects can be compared only with reference to specific but nonuniversal "covering values." These covering values may reflect decision-makers' goals, motivations, or current states. A complete model of choice must accommodate the range of possible covering values. We show that abandoning the common-currency assumption in models of judgment and decision-making necessitates rank-based and "simple heuristics" models that contrast radically with conventional utility-based approaches. We note that if there is no universal value scale, then Arrow's impossibility theorem places severe bounds on the rationality of individual decision-making and hence that there is a deep link between the incommensurability of value, inconsistencies in human decision-making, and rank-based coding of value. More generally, incommensurability raises the question of whether it will ever be possible to develop single-quantity-maximizing models of decision-making.

Context-effect bias in capuchin monkeys (Sapajus spp.): exploring decoy influences in a value-based food choice task

Decision making is known to be liable to several context effects. In particular, adding a seemingly irrelevant alternative (decoy) to a set of options can modify preferences: typically, by increasing choices towards whatever option clearly dominates the decoy (attraction effect), but occasionally also decreasing its appeal and generating a shift in the opposite direction (repulsion effect). Both types of decoy effects violate rational choice theory axioms and suggest dynamic processes of preference-formation, in which the value of each alternative is not determined a priori, but it is instead constructed by comparing options during the decision process. These effects are well documented, both in humans and in other species: e.g., amoebas, ants, honeybees, frogs, birds, cats, dogs. However, evidence of decoy effects in non-human primates remains surprisingly mixed. This study investigates decoy effects in capuchin monkeys (Sapajus spp.), manipulating time pressure across different conditions, to test whether such effects require time-consuming comparative processes among available alternatives. Whereas the time-dependent nature of decoy effects is a robust finding in the human literature, this is its first investigation in non-human animals. Our results show that capuchins exhibit an attraction effect with decoys targeting their preferred food, and that this effect disappears under time pressure; moreover, we observe preliminary evidence of a repulsion effect when decoys target instead the less-preferred food, possibly due to the larger distance between decoy and target in the attribute space. Taken together, these results provide valuable insight on the evolutionary roots of comparative decision making.

A robust Bayesian test for identifying context effects in multiattribute decision-making

Research on multiattribute decision-making has repeatedly shown that people's preferences for options depend on the set of other options they are presented with, that is, the choice context. As a result, recent years have seen the development of a number of psychological theories explaining context effects. However, much less attention has been given to the statistical analyses of context effects. Traditionally, context effects are measured as a change in preference for a target option across two different choice sets (the so-called relative choice share of the target, or RST). We first show that the frequently used definition of the RST measure has some weaknesses and should be replaced by a more appropriate definition that we provide. We then show through a large-scale simulation that the RST measure as previously defined can lead to biased inferences. As an alternative, we suggest a Bayesian approach to estimating an accurate RST measure that is robust to various circumstances. We applied the two approaches to the data of five published studies (total participants, N = 738), some of which used the biased approach. Additionally, we introduce the absolute choice share of the target (or AST) as the appropriate measure for the attraction effect. Our approach is an example of evaluating and proposing proper statistical tests for axiomatic principles of decision-making. After applying the AST and the robust RST to published studies, we found qualitatively different results in at least one-fourth of the cases. These results highlight the importance of utilizing robust statistical tests as a foundation for the development of new psychological theories.

Deviations of rational choice: an integrative explanation of the endowment and several context effects

People's choices are often found to be inconsistent with the assumptions of rational choice theory. Over time, several probabilistic models have been proposed that account for such deviations from rationality. However, these models have become increasingly complex and are often limited to particular choice phenomena. Here we introduce a network approach that explains a broad set of choice phenomena. We demonstrate that this approach can be used to compare different choice theories and integrates several choice mechanisms from established models. A basic setup implements bounded rationality, loss aversion, and inhibition in a natural fashion, which allows us to predict the occurrence of well-known choice phenomena, such as the endowment effect and the similarity, attraction, compromise, and phantom context effects. Our results show that this network approach provides a simple representation of complex choice behaviour, and can be used to gain a better understanding of how the many choice phenomena and key theoretical principles from different types of decision-making are connected.