Does uncertainty cause inertia in decision making? An experimental study of the role of regret aversion and indecisiveness

Previous research has shown that often there is clear inertia in individual decision making---that is, a tendency for decision makers to choose a status quo option. I conduct a laboratory experiment to investigate two potential determinants of inertia in uncertain environments: (i) regret aversion and (ii) ambiguity-driven indecisiveness. I use a between-subjects design with varying conditions to identify the effects of these two mechanisms on choice behavior. In each condition, participants choose between two simple real gambles, one of which is the status quo option. I find that inertia is quite large and that both mechanisms are equally important.

Risk, ambiguity, and diversification

Attitudes toward risk influence the decision to diversify among uncertain options. Yet, because in most situations the options are ambiguous, attitudes toward ambiguity may also play an important role. I conduct a laboratory experiment to investigate the effect of ambiguity on the decision to diversify. I find that diversification is more prevalent and more persistent under ambiguity than under risk. Moreover, excess diversification under ambiguity is driven by participants who stick with a status quo gamble when diversification among gambles is not feasible. This behavioral pattern cannot be accommodated by major theories of choice under ambiguity.

Applications of behavioural economics to tax evasion

The paper reviews recent models that have applied the techniques of behavioural economics to the analysis of the tax compliance choice of an individual taxpayer. The construction of these models is motivated by the failure of the Yitzhaki version of the Allingham–Sandmo model to predict correctly the proportion of taxpayers who will evade and the effect of an increase in the tax rate upon the chosen level of evasion. Recent approaches have applied non-expected utility theory to the compliance decision and have addressed social interaction. The models we describe are able to match the observed extent of evasion and correctly predict the tax effect but do not have the parsimony or precision of the Yitzhaki model.

Sobre la toma de decisiones economicas bajo incertidumbre

In this article we review the evolution of economic theory on decision making under uncertainty. After a brief reference to Expected Utility Theory, we refer to behavioural paradoxes, forcing the theorists to adopt less restrictive approaches, allowing us to explain a broader spectrum of phenomena. The complexity entailed in the new theories requires a multidimensional description of human attitudes towards risk. Nevertheless, measurement of this attitudes has not followed the desired path, with most elicitation methods remaining uni-dimensional.

Leilões eletrônicos reversos multiatributo : uma abordagem de decisão multicritério como instrumento de agregação de valor aos processos de compras do setor público brasileiro

Leilões são instituições seculares utilizadas nas relações comerciais entre indivíduos e organizações. Provêem maior flexibilidade aos processos de determinação de preços e alocação de bens, aumentando o espaço para negociações entre compradores e vendedores. Na Internet, têm sido empregados, de maneira crescente, em atividades de comércio eletrônico B2B e G2B, em sua maioria, através da modalidade de leilão reverso. No entanto, seu aspecto unidimensional reduz as negociações à variável preço, produzindo, muitas vezes, resultados aquém do desejado. No caso brasileiro, o Governo Federal instituiu o Portal Comprasnet, através do qual, as organizações públicas adquirem bens e serviços de fornecedores cadastrados. Dentre as modalidades de licitação disponíveis, destaca-se o Pregão Eletrônico, um mecanismo de leilão eletrônico reverso baseado no atributo preço, através do qual, fornecedores submetem lances decrescentes, na disputa por contratos do setor público. No presente trabalho, o autor propõe uma abordagem de decisão multicritério, baseada na Teoria da Utilidade Multiatributo, como uma alternativa para a adoção de leilões reversos baseados em múltiplos atributos e, consequentemente, para uma maior agregação de valor pelas organizações compradoras do setor público brasileiro.

MoSAC: um módulo para seleção de configurações arquiteturais baseado em critérios de QoS no contexto de sistema distribuídos autoadaptativos

The process for choosing the best components to build systems has become increasingly complex. It becomes more critical if it was need to consider many combinations of components in the context of an architectural configuration. These circumstances occur, mainly, when we have to deal with systems involving critical requirements, such as the timing constraints in distributed multimedia systems, the network bandwidth in mobile applications or even the reliability in real-time systems. This work proposes a process of dynamic selection of architectural configurations based on non-functional requirements criteria of the system, which can be used during a dynamic adaptation. This proposal uses the MAUT theory (Multi-Attribute Utility Theory) for decision making from a finite set of possibilities, which involve multiple criteria to be analyzed. Additionally, it was proposed a metamodel which can be used to describe the application s requirements in terms of the non-functional requirements criteria and their expected values, to express them in order to make the selection of the desired configuration. As a proof of concept, it was implemented a module that performs the dynamic choice of configurations, the MoSAC. This module was implemented using a component-based development approach (CBD), performing a selection of architectural configurations based on the proposed selection process involving multiple criteria. This work also presents a case study where an application was developed in the context of Digital TV to evaluate the time spent on the module to return a valid configuration to be used in a middleware with autoadaptative features, the middleware AdaptTV

Dominance Measuring Method Performance under Incomplete Information about Weights.

In multi-attribute utility theory, it is often not easy to elicit precise values for the scaling weights representing the relative importance of criteria. A very widespread approach is to gather incomplete information. A recent approach for dealing with such situations is to use information about each alternative?s intensity of dominance, known as dominance measuring methods. Different dominancemeasuring methods have been proposed, and simulation studies have been carried out to compare these methods with each other and with other approaches but only when ordinal information about weights is available. In this paper, we useMonte Carlo simulation techniques to analyse the performance of and adapt such methods to deal with weight intervals, weights fitting independent normal probability distributions orweights represented by fuzzy numbers.Moreover, dominance measuringmethod performance is also compared with a widely used methodology dealing with incomplete information on weights, the stochastic multicriteria acceptability analysis (SMAA). SMAA is based on exploring the weight space to describe the evaluations that would make each alternative the preferred one.

Dominance intensity measure within fuzzy weight oriented MAUT: an application

We introduce a dominance intensity measuring method to derive a ranking of alternatives to deal with incomplete information in multi-criteria decision-making problems on the basis of multi-attribute utility theory (MAUT) and fuzzy sets theory. We consider the situation where there is imprecision concerning decision-makers’ preferences, and imprecise weights are represented by trapezoidal fuzzy weights.The proposed method is based on the dominance values between pairs of alternatives. These values can be computed by linear programming, as an additive multi-attribute utility model is used to rate the alternatives. Dominance values are then transformed into dominance intensity measures, used to rank the alternatives under consideration. Distances between fuzzy numbers based on the generalization of the left and right fuzzy numbers are utilized to account for fuzzy weights. An example concerning the selection of intervention strategies to restore an aquatic ecosystem contaminated by radionuclides illustrates the approach. Monte Carlo simulation techniques have been used to show that the proposed method performs well for different imprecision levels in terms of a hit ratio and a rank-order correlation measure.

Dominance measuring methods within MAVT/MAUT with imprecise information concerning decision-makers'preferences

Dominance measuring methods are an approach for dealing with complex decision-making problems with imprecise information within multi-attribute value/utility theory. These methods are based on the computation of pairwise dominance values and exploit the information in the dominance matrix in different ways to derive measures of dominance intensity and rank the alternatives under consideration. In this paper we review dominance measuring methods proposed in the literature for dealing with imprecise information (intervals, ordinal information or fuzzy numbers) about decision-makers? preferences and their performance in comparison with other existing approaches, like SMAA and SMAA-II or Sarabando and Dias? method.

Veto values in Group Decision Making within MAUT: aggregating complete rankings derived from dominance intensity measures

We consider a groupdecision-making problem within multi-attribute utility theory, in which the relative importance of decisionmakers (DMs) is known and their preferences are represented by means of an additive function. We allow DMs to provide veto values for the attribute under consideration and build veto and adjust functions that are incorporated into the additive model. Veto functions check whether alternative performances are within the respective veto intervals, making the overall utility of the alternative equal to 0, where as adjust functions reduce the utilty of the alternative performance to match the preferences of other DMs. Dominance measuring methods are used to account for imprecise information in the decision-making scenario and to derive a ranking of alternatives for each DM. Specifically, ordinal information about the relative importance of criteria is provided by each DM. Finally, an extension of Kemeny's method is used to aggregate the alternative rankings from the DMs accounting for the irrelative importance.

Toma de decisiones en grupo con información parcial y veto basada en medidas de la intensidad de dominancia

En la mayoría de problemas de decisión a los que nos enfrentamos no hay evidencia sobre cuál es la mejor elección debido a la complejidad de los mismos. Esta complejidad está asociada a la existencia de múltiples objetivos conflictivos y a que en muchos casos solo se dispone de información incompleta o imprecisa sobre los distintos parámetros del modelo de decisión. Por otro lado, el proceso de toma de decisiones se puede realizar en grupo, debiendo incorporar al modelo las preferencias individuales de cada uno de los decisores y, posteriormente, agregarlas para alcanzar un consenso final, lo que dificulta más todavía el proceso de decisión. La metodología del Análisis de Decisiones (AD) es un procedimiento sistemático y lógico que permite estructurar y simplificar la tarea de tomar decisiones. Utiliza la información existente, datos recogidos, modelos y opiniones profesionales para cuantificar la probabilidad de los valores o impactos de las alternativas y la Teoría de la Utilidad para cuantificar las preferencias de los decisores sobre los posibles valores de las alternativas. Esta tesis doctoral se centra en el desarrollo de extensiones del modelo multicriterio en utilidad aditivo para toma de decisiones en grupo con veto en base al AD y al concepto de la intensidad de la dominancia, que permite explotar la información incompleta o imprecisa asociada a los parámetros del modelo. Se considera la posibilidad de que la importancia relativa que tienen los criterios del problema para los decisores se representa mediante intervalos de valores o información ordinal o mediante números borrosos trapezoidales. Adicionalmente, se considera que los decisores tienen derecho a veto sobre los valores de los criterios bajo consideración, pero solo un subconjunto de ellos es efectivo, teniéndose el resto solo en cuenta de manera parcial. ABSTRACT In most decision-making problems, the best choice is unclear because of their complexity. This complexity is mainly associated with the existence of multiple conflicting objectives. Besides, there is, in many cases, only incomplete or inaccurate information on the various decision model parameters. Alternatively, the decision-making process may be performed by a group. Consequently, the model must account for individual preferences for each decision-maker (DM), which have to be aggregated to reach a final consensus. This makes the decision process even more difficult. The decision analysis (DA) methodology is a systematic and logical procedure for structuring and simplifying the decision-making task. It takes advantage of existing information, collected data, models and professional opinions to quantify the probability of the alternative values or impacts and utility theory to quantify the DM’s preferences concerning the possible alternative values. This PhD. thesis focuses on developing extensions for a multicriteria additive utility model for group decision-making accounting for vetoes based on DA and on the concept of dominance intensity in order to exploit incomplete or imprecise information associated with the parameters of the decision-making model. We consider the possibility of the relative importance of criteria for DMs being represented by intervals or ordinal information, or by trapezoidal fuzzy numbers. Additionally, we consider that DMs are allowed to provide veto values for the criteria under consideration, of which only a subset are effective, whereas the remainder are only partially taken into account.

Contribution of individual to collective brands

Traditionally, literature estimates the equity of a brand or its extension but it pays little attention to collective brand equity even though collective branding is increasingly used to differentiate the homogenous products of different firms or organizations. We propose an approach that estimates the incremental effect of individual brands (or the contribution of individual brands) on collective brand equity through the various stages of a consumer hierarchical buying choice process in which decisions are nested: “whether to buy”, “what collective brand to buy” and “what individual brand to buy”. This proposal follows the approach of the Random Utility Theory, and it is theoretically argued through the Associative Networks Theory and the cybernetic model of decision making. The empirical analysis carried out in the area of collective brands in Spanish tourism finds a three-stage hierarchical sequence, and estimates the contribution of individual brands to the equity of the collective brands of “Sun, Sea and Sand” and of “World Heritage Cities”.

The effects of government disability benefits, accessibility laws and rehabilitation on employment choices by individuals with spinal cord injuries

Greater inclusion of individuals with disabilities into mainstream society is an important goal for society. One of the best ways to include individuals is to actively promote and encourage their participation in the labor force. Of all disabilities, it is feasible to assume that individual with spinal cord injuries can be among the most easily mainstreamed into the labor force. However, less that fifty percent of individuals with spinal cord injuries work. ^ This study focuses on how disability benefit programs, such as Social Security Disability Insurance, and Worker's Compensation, the Americans with Disabilities Act and rehabilitation programs affect employment decisions. The questions were modeled using utility theory with an augmented expenditure function and indifference theory. Statically, Probit, Logit, predicted probability, and linear regressions were used to analyze these questions. Statistical analysis was done on the probability of working, ever attempting to work after injury, and on the number of years after injury that work was first attempted and the number of hours worked per week. The data utilized were from the National Spinal Cord Injury Database and the Spinal Cord Injuries and Labor Database. The Spinal Cord Injuries and Labor Database was created specifically for this study by the author. Receiving disability benefits decreased the probability of working, of ever attempting to work, increased the number of years after injury before the first work attempt was made, and decreased the number of hours worked per week for those individuals working. These results were all statistically significant. The Americans with Disabilities Act decrease the number of years before an individual made a work attempt. The decrease is statistically significant. The amount of rehabilitation had a significant positive effect for male individuals with low paraplegia, and significant negative effect for individuals with high tetraplegia. For women, there were significant negative effects for high tetraplegia and high paraplegia. ^ This study finds that the financial disincentives of receiving benefits are the major determinants of whether an individual with a spinal cord injury returns to the labor force. Policies are recommended that would decrease the disincentive. ^

A decision support framework for infrastructure maintenance investment decision-making

Infrastructure management agencies are facing multiple challenges, including aging infrastructure, reduction in capacity of existing infrastructure, and availability of limited funds. Therefore, decision makers are required to think innovatively and develop inventive ways of using available funds. Maintenance investment decisions are generally made based on physical condition only. It is important to understand that spending money on public infrastructure is synonymous with spending money on people themselves. This also requires consideration of decision parameters, in addition to physical condition, such as strategic importance, socioeconomic contribution and infrastructure utilization. Consideration of multiple decision parameters for infrastructure maintenance investments can be beneficial in case of limited funding. Given this motivation, this dissertation presents a prototype decision support framework to evaluate trade-off, among competing infrastructures, that are candidates for infrastructure maintenance, repair and rehabilitation investments. Decision parameters' performances measured through various factors are combined to determine the integrated state of an infrastructure using Multi-Attribute Utility Theory (MAUT). The integrated state, cost and benefit estimates of probable maintenance actions are utilized alongside expert opinion to develop transition probability and reward matrices for each probable maintenance action for a particular candidate infrastructure. These matrices are then used as an input to the Markov Decision Process (MDP) for the finite-stage dynamic programming model to perform project (candidate)-level analysis to determine optimized maintenance strategies based on reward maximization. The outcomes of project (candidate)-level analysis are then utilized to perform network-level analysis taking the portfolio management approach to determine a suitable portfolio under budgetary constraints. The major decision support outcomes of the prototype framework include performance trend curves, decision logic maps, and a network-level maintenance investment plan for the upcoming years. The framework has been implemented with a set of bridges considered as a network with the assistance of the Pima County DOT, AZ. It is expected that the concept of this prototype framework can help infrastructure management agencies better manage their available funds for maintenance.