Where do preferences come from?

Rational choice theory analyzes how an agent can rationally act, given his or her preferences, but says little about where those preferences come from. Preferences are usually assumed to be fixed and exogenously given. Building on related work on reasons and rational choice (Dietrich and List, Nous, forthcoming), we describe a framework for conceptualizing preference formation and preference change. In our model, an agent’s preferences are based on certain ‘motivationally salient’ properties of the alternatives over which the preferences are held. Preferences may change as new properties of the alternatives become salient or previously salient properties cease to be salient. Our approach captures endogenous preferences in various contexts and helps to illuminate the distinction between formal and substantive concepts of rationality, as well as the role of perception in rational choice.     

Confidence models of incomplete preferences

This paper introduces a new class of representations for incomplete preferences called confidence models. Confidence models describe decision makers who behave as if they have probabilistic uncertainty over their true preferences, and are only willing to express a binary preference if it is sufficiently likely to hold. Confidence models provide a natural way to connect incomplete preferences with stochastic choice. This connection is characterized by a simple joint condition on an incomplete preference relation and a random choice rule.     

Epistemic characterizations of iterated deletion of inferior strategy profiles in preference-based type spaces

Bonanno (Logics and the foundations of game and decision theory, Amsterdam University Press, Amsterdam, 2008) provides an epistemic characterization for the solution concept of iterated deletion of inferior strategy profiles (IDIP) by embedding strategic-form games with ordinal payoffs in non-probabilistic epistemic models which are built on Kripke frames. In this paper, we will follow the event-based approach to epistemic game theory and supplement strategic games with type space models, where each type is associated with a preference relation on the state space. In such a framework, IDIP can be characterized by the conditions that at least one player has correct beliefs about the state of the world and that there is common belief that every player is rational, has correct beliefs about the state of the world and has strictly monotone preferences. Moreover, we shall compare the epistemic motivations for IDIP and its mixed strategy variant known as strong rationalizability (SR). Presuppose the above conditions. Whenever there is also common belief that players’ preferences are representable by some expected utility function IDIP still applies. But if there is common belief that players’ preferences are representable by some expected payoff function, then SR results.     

Aggregation of preferences: a review

This paper presents a review and a classification of the main theoretical results obtained up to now in the important field of the aggregation of preferences. (Let us mention that multicriteria analysis is not considered here, as it essentially consists of methods for the aggregation of preferences).Section 1 describes a tableau, each square of which corresponds to a particular type of preference aggregation problem, and gives, for each of them, a list of references. The different types of problems are obtained by considering the various kinds of informations which can be obtained concerning the global preferences of a committee and the preferences of the individual members.Sections 2, 3 and 4 present some comments respectively on Arrow's problem (three first columns of the tableau), on the theory of choice functions (fourth column) and voting procedures (fifth column).In the bibliography, each reference is associated, in terms of its subject, to one particular square of the tableau.     

When conflict induces the expression of incomplete preferences

Multicriteria conflict arises in pairwise comparisons, where each alternative outperforms the other one on some criterion, which imposes a trade-off. Comparing two alternatives can be difficult if their respective advantages are of high magnitude (the attribute spread is large). In this paper, we investigate to which extent conflict in a comparison situation can lead decision makers to express incomplete preferences, that is, to refuse to compare the two alternatives, or to be unable to compare them with confidence. We report on an experiment in which subjects expressed preferences on pairs of alternatives involving varying conflicts. Results show that depending on whether the participants are allowed to express incomplete preferences or not, attribute spread has a different effect: a large attribute spread increases the frequency of incomparability statements, when available, while it increases the use of indifference statements when only indifference and preference answers are permitted. These results lead us to derive some implications for preference elicitation methods involving comparison tasks.     

Complexity of games and bounded rationality

An attempt is made to propose a concept of limited rationality for choice junctions based on computability theory in computer science.

Starting with the observation that it is possible to construct a machine simulating strategies of each individual in society, one machine for each individual's preference structure, we identify internal states of this machine with strategies or strategic preferences. Inputs are possible actions of other agents in society thus society is effectively operating as a game generated by machines. The main result states that effective realization of game strategies bound by the “complexity of computing machines'.     

Multicriterion analysis of preferences by means of pairwise actions and criterion comparisons (MAPPACC)

This paper presents a method for solving discrete choice problems characterized by multiple evaluative criteria. The proposed method, known as MAPPAC, is based on a pairwise comparison of alternatives relative to each pair of criteria, defining the two relations P (preference) and I (indifference), which constitute a complete preorder. Moreover, by aggregating these preferences, it is possible to obtain a variety of relations on a set of feasible actions.     

Value-based DEA models: application-driven developments

Data envelopment analysis (DEA) is an approach based on linear programming to assess the relative efficiency of peer decision-making units (DMUs). Typically, each DMU is free to choose the weights of the factors used in its evaluation. However, the evaluator's preferences may not warrant so much freedom. Several approaches have been proposed to allow the incorporation of managerial preferences in DEA, but few address the additive DEA model specifically. This paper presents additive DEA models that use multi-criteria decision analysis concepts to incorporate managerial preferences, and presents the corresponding preference elicitation protocols. The models developed allow the incorporation of preferences at different levels: on valuing performance improvements, on introducing weight restrictions, and on finding adequate targets. These were application-driven developments, resulting from discussing modelling options and preliminary results with the top-level management of a retail chain in the context of an assessment of stores’ performance, also described in this paper.     

A rational random behaviour model of choice

In this paper, a multinomial-Dirichlet-geometric model of consumer brand choice is developed. This individual-level stochastic choice model is derived as an extension of Theil's theory of rational random behaviour. These behavioural assumptions permit modelling of changes in likelihood of purchase as consumers are confronted with environmental factors whose occurrence and exact nature could not be anticipated at the planning stage of a shopping trip. Moreover, the model allows for uncertainties about future events which might affect actual choice to be built into the choice process alongside a traditional choice model which reflects preferences and/or utilities (and potential uncertainties surrounding them). Empirical results using consumer diary purchase panel data indicate a strong superiority of the model developed compared with previous models which assume stationary preference vectors.     

Mathematical programming models for revenue management under customer choice

We study a network airline revenue management problem with discrete customer choice behavior. We discuss a choice model based on the concept of preference orders, in which customers can be grouped according to a list of options in decreasing order of preference. If a customer’s preferred option is not available, the customer moves to the next choice on the list with some probability. If that option is not available, the customer moves to the third choice on the list with some probability, and so forth until either the customer has no other choice but to leave or his/her request is accepted. Using this choice model as an input, we propose some mathematical programs to determine seat allocations. We also propose a post-optimization heuristic to refine the allocation suggested by the optimization model. Simulation results are presented to illustrate the effectiveness of our method, including comparisons with other models.     

Restricted domains,arrow-social welfare functions and noncorruptible and non-manipulable social choice correspondences: The case of private alternatives

An n-person social choice problem is considered in which the alternatives are n dimensional vectors, with the ith component of such a vector being the part of the alternatives affecting individual i alone. Assuming that individuals are selfish (individual i must be indifferent between any two alternatives with the same components), that they may be indifferent among alternatives and that each individual may choose his preferences out of a different set of permissible preferences, we prove that any set of restricted domains of preferences admits an n person non-dictatorial Arrow-type social welfare function if and only if it admits a two-person Arrow-type social welfare function: we characterize all the sets of restricted domains of preferences which admit two-person Arrow-type social welfare functions (and therefore also admit n-person Arrow-type social welfare functions) and then we prove that we also characterized all the sets of restricted domains of preferences which admit nondictatorial, nonmanipulable, noncorruptible and rational social choice correspondences.     

基于偏好和动态直觉的产学研合作伙伴选择群决策分析

针对产学研合作伙伴选择的有限理性和偏好特性,基于直觉模糊多属性决策理论和相对熵理论,构建产学研合作伙伴选择群决策模型。运用动态直觉模糊加权几何算子(DIFWG)集成合作伙伴不同时段的个人准则决策矩阵,实现对产学研合作伙伴持续性的评价;运用直觉模糊有序加权平均算子(IFOWA)集成不同决策者的决策矩阵和偏好矩阵,并利用决策者对合作伙伴的主观偏好与对合作伙伴各准则的客观评价之间差距的极小化,基于加权平均思想,求取评价准则的客观权重;然后,引入相对熵求取评价对象理想的最优权重解,依据该解对各合作伙伴进行排序并选择;最终通过实证研究说明了该方法的有效性和可行性,充分利用直觉模糊理论,实现了产学研合作伙伴的“群偏好—多时段—群决策”的全面评价。     

Nothing else matters: Evolution of preference for social prestige

This paper seeks answers to two questions. First, if a greater social activity of an individual enhances oblique (i.e. to non-relatives) transmission of her cultural traits at the expense of vertical (i.e. to children) transmission as well as family size, which behavior is optimal from cultural evolution standpoint? I formalize a general model that characterizes evolutionarily stable social activity. The proposed model replicates the theory of Newson et al. (2007) that fertility decline is caused by increasing role of oblique cultural transmission. Second, if social activity is a rational choice rather than a culturally inherited trait, and if cultural transmission acts on preferences rather than behaviors, which preferences survive the process of cultural evolution? I arrive at a very simple yet powerful result: under mild assumptions on model structure, only preferences which emphasize exclusively the concern for social prestige, i.e. extent to which one’s cultural trait has been picked up by others, survive.     

Coevolution of role preference and fairness in the ultimatum game

Traditional economics assumes that humans are rational. However, it is known that humans behave fairly in the ultimatum game (UG). There are various explanations for this apparent paradox, such as the “inequity aversion.” However, the role preference (proposer or responder) of humans in the UG is obscure. I conducted a UG scenario experiment where subjects were asked their role preference in addition to their decision in the game. The results showed that the subjects prefer to be proposers rather than responders. In particular, it was found that rational subjects had a high preference for the proposer role. On the basis of these results, I conducted evolutionary simulations of the UG, where each individual has role preference intensity. A role is allocated to the individual proportional to the preference intensity. The results showed coevolution of role preference and fairness. The preference for the proposer role evolved when rational strategy evolved, whereas this preference weakened as rationality decreased. This indicates that fairness has a strong link with role preference; in other words, human fairness is always threatened by the “power and position” of some particular individuals. Hence, its equal distribution among individuals may be effective in maintaining a high level of fairness. © 2012 Wiley Periodicals, Inc. Complexity, 2012     

Core equivalences for equilibria supported by non-linear prices

The goal of this paper is to provide some new cooperative characterizations and optimality properties of competitive equilibria supported by non-linear prices. The general framework is that of economies whose commodity space is an ordered topological vector space which need not be a vector lattice. The central notion of equilibrium is the one of personalized equilibrium introduced by Aliprantis et al. (J Econ Theory 100:22–72, 2001). Following Herves-Beloso and Moreno-Garcia (J Math Econ 44:697–706, 2008), the veto power of the grand coalition is exploited in the original economy and in a suitable family of economies associated to the original one. The use of Aubin coalitions allows us to connect results with the arbitrage free condition due to non-linear supporting prices. The use of rational allocations allows us to dispense with Lyapunov convexity theorem. Applications are provided in connection with strategic market games and economies with asymmetric information.     

Experimental tour-based travel demand models

In this paper some experimental sequential models for the simulation of trip-chains are presented; the models have been calibrated on the basis of a survey made in a medium-sized town.This work is part of a research, effected by the Department of Regional Planning of the University of Calabria, to forecast travel demand and to analyze travel behavior of the transport system users (Festa et al., 2000).The travel choices of individuals have been reproduced simulating the decisional process in sequential steps, by models based on the random utility theory.The tour generation models, proposed by Festa et al. (2001), have been once again calibrated introducing a new set of variables in the systematic utility function of the alternatives of choice.Some models for the travel type choice simulation are also presented; the models have a Binomial Logit functional structure, with trip-tour and trip-chain as choice alternatives.     

Reasoning with various kinds of preferences: logic,non-monotonicity,and algorithms

As systems dealing with preferences become more sophisticated, it becomes essential to deal with various kinds of preference statements and their interaction. We introduce a non-monotonic logic distinguishing sixteen kinds of preferences, ranging from strict to loose and from careful to opportunistic, and two kinds of ways to deal with uncertainty, either optimistically or pessimistically. The classification of the various kinds of preferences is inspired by a hypothetical agent comparing the two alternatives of a preference statement. The optimistic and pessimistic way of dealing with uncertainty correspond on the one hand to considering either the best or the worst states in the comparison of the two alternatives of a preference statement, and on the other hand to the calculation of least or most specific “distinguished” preference orders from a set of preference statements. We show that each way to calculate distinguished preference orders is compatible with eight kinds of preferences, in the sense that it calculates a unique distinguished preference order for a set of such preference statements, and we provide efficient algorithms that calculate these unique distinguished preference orders. In general, optimistic kinds of preferences are compatible with optimism in calculating distinguished preference orders, and pessimistic kinds of preferences are compatible with pessimism in calculating distinguished preference orders. However, these two sets of eight kinds of preferences are not exclusive, such that some kinds of preferences can be used in both ways to calculate distinguished preference orders, and other kinds of preferences cannot be used in either of them. We also consider the merging of optimistically and pessimistically constructed distinguished preferences orders.     

Aggregation of ordinal data using ordered weighted averaging operator weights

In multi-criteria decision-making problems, ordinal data themselves provide a convenient instrument for articulating preferences but they impose some difficulty on the aggregation process since ambiguity prevails in the preference structure inherent in the ordinal data. One of the key concerns in the aggregation of ordinal data is to differentiate among the rank positions by reflecting decision-maker??s preferences. Since individual attitude is fairly different, it is presumable that each ranking position has different importance. In other words, the quantification schemes among the rank positions could vary depending on the individual preference structure. We find that, among others, the ordered weighted averaging (OWA) operator can help to take this concept into effect on several reasons. First, the OWA operator provides a means to take into account a discriminating factor by introducing the measure of attitudinal character. Second, it can produce appropriate ranking weights corresponding to each rank position by solving a mathematical program subject to the constraint of attitudinal character. To better understand the attitudinal character playing a role as a discriminating factor, we develop centered ranking weights from ordinal weak relations among the ranking positions and then investigate their properties to relate them with the OWA operator weights having the maximum entropy. Finally, we present a method for generating the OWA operator weights via rank-based weighting functions.     

Exact choice and fuzzy preferences

Agents often have to make exact choices on the basis of vague preferences. Therefore analysis of the way in which exact choices are induced by vague preferences is of considerable interest. In this paper we use the model of vague preferences as fuzzy orderings. One objective of this paper is conceptual in nature: we discuss several alternative notions of exact choice sets generated by a fuzzy preference ordering and corresponding notions of rationalizability of exact choices in terms of fuzzy preference orderings. The second objective of this paper is to explore conditions for rationalizability of exact choices in terms of a fuzzy preference ordering, under alternative definitions of such rationalizability.     

Multiple criteria linear programming model for portfolio selection

The portfolio selection problem is usually considered as a bicriteria optimization problem where a reasonable trade-off between expected rate of return and risk is sought. In the classical Markowitz model the risk is measured with variance, thus generating a quadratic programming model. The Markowitz model is frequently criticized as not consistent with axiomatic models of preferences for choice under risk. Models consistent with the preference axioms are based on the relation of stochastic dominance or on expected utility theory. The former is quite easy to implement for pairwise comparisons of given portfolios whereas it does not offer any computational tool to analyze the portfolio selection problem. The latter, when used for the portfolio selection problem, is restrictive in modeling preferences of investors. In this paper, a multiple criteria linear programming model of the portfolio selection problem is developed. The model is based on the preference axioms for choice under risk. Nevertheless, it allows one to employ the standard multiple criteria procedures to analyze the portfolio selection problem. It is shown that the classical mean-risk approaches resulting in linear programming models correspond to specific solution techniques applied to our multiple criteria model. This revised version was published online in June 2006 with corrections to the Cover Date.