Satisfaction in choice as a function of the number of alternatives: When "goods satiate" but "bads escalate"

Whereas people are typically thought to be better off with more choices, studiesshow that they often prefer to choose from small as opposed to large sets of alternatives.We propose that satisfaction from choice is an inverted U-shaped function of thenumber of alternatives. This proposition is derived theoretically by considering thebenefits and costs of different numbers of alternatives and is supported by fourexperimental studies. We also manipulate the perceptual costs of information processingand demonstrate how this affects the resulting satisfaction function. We furtherindicate that satisfaction when choosing from a given set is diminished if people aremade aware of the existence of other choice sets. The role of individual differences insatisfaction from choice is documented by noting effects due to gender and culture. Weconclude by emphasizing the need to have an explicit rationale for knowing how muchchoice is enough.

Ambiguity seeking as a result of the status quo bias

Several factors affect attitudes toward ambiguity. What happens, however, when peopleare asked to exchange an ambiguous alternative in their possession for an unambiguousone? We present three experiments in which individuals preferred to retain the former.This status quo bias emerged both within- and between-subjects, with and withoutincentives, with different outcome distributions, and with endowments determined byboth the experimenter and the participants themselves. Findings emphasize the need toaccount for the frames of reference under which evaluations of probabilistic informationtake place as well as modifications that should be incorporated into descriptive modelsof decision making.

The challenge of representative design in psychology and economics

The demands of representative design, as formulated by Egon Brunswik (1956), set a high methodological standard. Both experimental participants and the situations with which they are faced should be representative of the populations to which researchers claim to generalize results. Failure to observe the latter has led to notable experimental failures in psychology from which economics could learn. It also raises questions about the meaning of testing economic theories in abstract environments. Logically, abstract tests can only be generalized to abstract realities and these may or may not have anything to do with the empirical realities experienced by economic actors.

Deciding analytically or trusting your intuition? The advantadges and disadvantadges of analytic and intuitive thought

Recent research has highlighted the notion that people can make judgmentsand choices by means of two systems that are labeled here tacit(or intuitive) and deliberate (or analytic). Whereas most decisionstypically involve both systems, this chapter examines the conditions underwhich each system is liable to be more effective. This aims to illuminatethe age-old issue of whether and when people should trust intuition or analysis. To do this, a framework is presented to understand how thetacit and deliberate systems work in tandem. Distinctions are also madebetween the types of information typically used by both systems as wellas the characteristics of environments that facilitate or hinder accuratelearning by the tacit system. Next, several experiments that havecontrasted intuitive and analytic modes on the same tasks are reviewed.Together, the theoretical framework and experimental evidence leads tospecifying the trade-off that characterizes their relative effectiveness.Tacit system responses can be subject to biases. In making deliberate systemresponses, however, people might not be aware of the correct rule to dealwith the task they are facing and/or make errors in executing it. Whethertacit or deliberate responses are more valid in particular circumstancesrequires assessing this trade-off. In this, the probability of making errorsin deliberate thought is postulated to be a function of the analytical complexityof the task as perceived by the person. Thus the trade-off is one of bias (inimplicit responses) versus analytical complexity (when tasks are handled indeliberate mode). Finally, it is noted that whereas much attention has beenpaid in the past to helping people make decisions in deliberate mode, effortsshould also be directed toward improving ability to make decisions intacit mode since the effectiveness of decisions clearly depends on both. Thistherefore represents an important frontier for research.

What risks do people perceive in everyday life? A perspective gained from the experience sampling method (ESM)

The experiential sampling method (ESM) was used to collect data from 74 parttimestudents who described and assessed the risks involved in their current activitieswhen interrupted at random moments by text messages. The major categories ofperceived risk were short-term in nature and involved loss of time or materials relatedto work and physical damage (e.g., from transportation). Using techniques of multilevelanalysis, we demonstrate effects of gender, emotional state, and types of risk onassessments of risk. Specifically, females do not differ from males in assessing thepotential severity of risks but they see these as more likely to occur. Also, participantsassessed risks to be lower when in more positive self-reported emotional states. Wefurther demonstrate the potential of ESM by showing that risk assessments associatedwith current actions exceed those made retrospectively. We conclude by notingadvantages and disadvantages of ESM for collecting data about risk perceptions.

On ignoring scientific evidence: The bumpy road to enlightenment

It is well accepted that people resist evidence that contradicts their beliefs.Moreover, despite their training, many scientists reject results that are inconsistent withtheir theories. This phenomenon is discussed in relation to the field of judgment anddecision making by describing four case studies. These concern findings that clinical judgment is less predictive than actuarial models; simple methods have proven superiorto more theoretically correct methods in times series forecasting; equal weighting ofvariables is often more accurate than using differential weights; and decisions cansometimes be improved by discarding relevant information. All findings relate to theapparently difficult-to-accept idea that simple models can predict complex phenomenabetter than complex ones. It is true that there is a scientific market place for ideas.However, like its economic counterpart, it is subject to inefficiencies (e.g., thinness,asymmetric information, and speculative bubbles). Unfortunately, the market is only correct in the long-run. The road to enlightenment is bumpy.

On heuristic and linear models of judgment: Mapping the demand for knowledge

Research on judgment and decision making presents a confusing picture of human abilities. For example, much research has emphasized the dysfunctional aspects of judgmental heuristics, and yet, other findings suggest that these can be highly effective. A further line of research has modeled judgment as resulting from as if linear models. This paper illuminates the distinctions in these approaches by providing a common analytical framework based on the central theoretical premise that understanding human performance requires specifying how characteristics of the decision rules people use interact with the demands of the tasks they face. Our work synthesizes the analytical tools of lens model research with novel methodology developed to specify the effectiveness of heuristics in different environments and allows direct comparisons between the different approaches. We illustrate with both theoretical analyses and simulations. We further link our results to the empirical literature by a meta-analysis of lens model studies and estimate both human andheuristic performance in the same tasks. Our results highlight the trade-off betweenlinear models and heuristics. Whereas the former are cognitively demanding, the latterare simple to use. However, they require knowledge and thus maps of when andwhich heuristic to employ.

Ethical differentiation and market behavior: An experimental approach

Does ethical differentiation of products affect market behavior? We examined this issue in triopolistic experimental markets where producers set prices. One producer s costs were higher than the others. In two treatments, the additional costs were attributed tocompliance with ethical guidelines. In the third, no justification was provided. Manyparticipants playing the role of consumers reduced their experimental gains by purchasing the ethically differentiated product at a higher price whether or not they knew the amount of extra cost. Individual differences were important (students of business/economics paid smaller premia than others). Finally, we speculate about the observed demand function for ethics and emphasize the use of experimental methodology to complement empirical studies designed to assess the potential market for ethically differentiated products.

The role of incidental variables of time in mood assessment

Determining what influences mood is important for theories of emotion and research onsubjective well-being. We consider three sets of factors: activities in which people areengaged; individual differences; and incidental variables that capture when mood ismeasured, e.g., time-of-day. These three factors were investigated simultaneously in a studyinvolving 168 part-time students who each responded 30 times in an experience samplingstudy conducted over 10 working days. Respondents assessed mood on a simple bipolarscale from 1 (very negative) to 10 (very positive). Activities had significant effects but,with the possible exception of variability in the expression of mood, no systematicindividual differences were detected. Diurnal effects, similar to those already reported inthe literature, were found as was an overall Friday effect. However, these effects weresmall. Lastly, the weather had little or no influence. We conclude that simple measures ofoverall mood are not greatly affected by incidental variables.

When "hope springs eternal": The role of chance in risk taking

In most naturally occurring situations, success depends on both skill and chance. We contrastexperimental market entry decisions where payoffs depend on skill as opposed tocombinations of skill and chance. Our data show differential attitudes toward chance by thosewhose self-assessed skills are low and high. Making chance more important induces greateroptimism for the former who start taking more risk, while the latter maintain a belief that highlevels of skill are sufficient to overcome the vagaries of chance. Finally, although weobserved excess entry (i.e., too many participants entered markets), this could not beattributed to overconfidence.

The size and distribution of donations: Effects of numbers of potential recipients

Whereas much literature exists on choice overload, little is known about effects of numbers of alternatives in donation decisions. How do these affect both the size and distribution of donations? We hypothesize that donations are affected by the reputation of recipients and increase with their number, albeit at a decreasing rate. Allocations to recipients reflect different concepts of fairness equity and equality. Both may be employed but, since they differ in cognitive and emotional costs, numbers of recipients are important. Using a cognitive (emotional) argument, distributions become more uniform (skewed) as numbers increase. In a survey, respondents indicated how they would donate lottery winnings of 50 Euros. Results indicated that more was donated to NGO s that respondents knew better. Second, total donations increased with the number of recipients albeit at a decreasing rate. Third, distributions of donations became more skewed as numbers increased. We comment on theoretical and practical implications.

Insurance and safety after September 11, 2001: Coming to grips with the costs and threats of terrorism

This chapter, originally written as a consequence of the terrorist attacksof September 11, 2001, provides an elementary, everyday introduction tothe concepts of risk and insurance. Conceptually, risk has two dimensions:a potential loss, and the chance of that loss being realized. People can,however, transfer risk to insurance companies against the payment ofso-called premiums. In practice, however, one needs accurate assessmentsof both losses and probabilities to judge whether premiums are appropriate.For many risks, this poses little problem (e.g., life insurance); however,it is difficult to assess risks of many other kinds of events such as actsof terrorism. It is emphasized, that through evolution and learning, peopleare able to handle many of the common risks that they face in life. Butwhen people lack experience (e.g., new technologies, threats of terrorism),risk can only be assessed through imagination. Not surprisingly, insurancecompanies demand high prices when risks are poorly understood. In particular,the cost of insurance against possible acts of terrorism soared afterSeptember 11. How should people approach risk after the events of that day?Clearly, the world needs to protect itself from the acts of terrorists andother disturbed individuals. However, it is also important to address the root causes of such antisocial movements. It is, therefore, suggested thatprograms addressed at combatting ignorance, prejudice, and socialinequalities may be more effective premiums for reducing the risk ofterrosrtism than has been recognized to date.

Ignoring information in binary choice with continuous variables: When is less 'more'?

When can a single variable be more accurate in binary choice than multiple sources of information? We derive analytically the probability that a single variable (SV) will correctly predict one of two choices when both criterion and predictor are continuous variables. We further provide analogous derivations for multiple regression (MR) and equal weighting (EW) and specify the conditions under which the models differ in expected predictive ability. Key factors include variability in cue validities, intercorrelation between predictors, and the ratio of predictors to observations in MR. Theory and simulations are used to illustrate the differential effects of these factors. Results directly address why and when one-reason decision making can be more effective than analyses that use more information. We thus provide analytical backing to intriguing empirical results that, to date, have lacked theoretical justification. There are predictable conditions for which one should expect less to be more.

Gaia photometry for white dwarfs

Context. White dwarfs can be used to study the structure and evolution of the Galaxy by analysing their luminosity function and initial mass function. Among them, the very cool white dwarfs provide the information for the early ages of each population. Because white dwarfs are intrinsically faint only the nearby (~ 20 pc) sample is reasonably complete. The Gaia space mission will drastically increase the sample of known white dwarfs through its 5-6 years survey of the whole sky up to magnitude V = 20-25. Aims. We provide a characterisation of Gaia photometry for white dwarfs to better prepare for the analysis of the scientific output of the mission. Transformations between some of the most common photometric systems and Gaia passbands are derived. We also give estimates of the number of white dwarfs of the different galactic populations that will be observed. Methods. Using synthetic spectral energy distributions and the most recent Gaia transmission curves, we computed colours of three different types of white dwarfs (pure hydrogen, pure helium, and mixed composition with H/He = 0.1). With these colours we derived transformations to other common photometric systems (Johnson-Cousins, Sloan Digital Sky Survey, and 2MASS). We also present numbers of white dwarfs predicted to be observed by Gaia. Results. We provide relationships and colourcolour diagrams among different photometric systems to allow the prediction and/or study of the Gaia white dwarf colours. We also include estimates of the number of sources expected in every galactic population and with a maximum parallax error. Gaia will increase the sample of known white dwarfs tenfold to about 200 000. Gaia will be able to observe thousands of very cool white dwarfs for the first time, which will greatly improve our understanding of these stars and early phases of star formation in our Galaxy.