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We review the experimental evidence on risk aversion in controlled laboratory settings. We review the strengths and weaknesses of alternative elicitation procedures, the strengths and weaknesses of alternative estimation procedures, and finally the effect of controlling for risk attitudes on inferences in experiments.

Evaluation of energy and climate policy interactions is a complex issue, whereas stakeholders' preferences incorporation has not been addressed systematically. The purpose of this paper is to present an integrated weighting methodology that has been developed in order to incorporate weighting preferences into an ex ante evaluation of climate and energy policy interactions.

A multi‐criteria analysis (MCA) weighting methodology which combines pair‐wise comparisons and ratio importance weighting methods has been elaborated. It initially introduces the users to the evaluation process through a warming up holistic approach for an initial rank of the criteria and then facilitates them to express their ratio relative importance in pair‐wise comparisons of criteria by providing them an interactive mean with verbal, numerical and visual representation of their preferences. Moreover, it provides a ranking consistency test where users can see the degree of (in)consistency of their preferences.

Stakeholders and experts in the energy policy field who tested the methodology stated their approval and satisfaction for the combination of both ranking and pair‐wise comparison techniques, since it allows the gradual approach to the evaluation problem. In addition, main difficulties in MCA weights elicitation processes were overcome.

The methodology is tested by a small sample of stakeholders, whereas a larger sample, a broader range of stakeholders and applications on different climate policy evaluation cases merit further research.

The novel aspect of the developed methodology consists of the combination of ranking and pair‐wise comparison techniques for the elicitation of stakeholders' preferences.

Emergency situations may differ in many ways but they share some common characteristics, such as the sudden onset and the need to transparently evaluate various usually conflicting objectives. In nuclear power generation, however, emergency situations constitute a special challenge. The focus of this paper is to highlight the role of multi‐criteria decision analysis (MCDA) in nuclear emergency and recovery management on the basis of a hypothetical case study.

Multi‐attribute value theory as one field of research within MCDA is introduced. Special emphasis is placed on the modelling of the decision makers' preferences which is a crucial part in any multi‐criteria analysis. A central aim is to facilitate the preference elicitation in group decision processes.

The management of emergency situations in nuclear power generation necessitates the consideration of technical, economic, environmental, socio‐psychological and political aspects. Furthermore, various stakeholder and expert groups with diverse background knowledge and different views, responsibilities and interests are involved in such a decision‐making process. MCDA can help to take into account various incommensurable aspects and the subjective preferences of the decision makers and thus contribute to transparency and traceability of decision‐making processes. Since the preference parameters are inherently afflicted with uncertainties, thorough sensitivity analyses are important to visualise the impact of the uncertainties in an understandable way.

A new approach to sensitivity analysis is proposed, allowing one to comprehensibly visualise and communicate the impact of the uncertainties associated with the subjective preference parameters on the results of the decision analysis.

Therapeutic communities (TCs) assume that residents are capable of working together to overcome substance abuse and criminal behavior. Economic games allow us to study the potential of cooperative behavior in TC residents. The paper aims to discuss this issue.

The authors analyze results from a sample of 85 corrections-based TC residents and a comparison group of 45 individuals drawn from the general population who participated in five well-known economic experiments – the dictator game, the ultimatum game, the trust game, risk attitude elicitation and time preference elicitation.

TC residents keep less money in the dictator game and return more in the trust game, and prefer short-term rewards in the time preference elicitation. In the ultimatum game, nearly half of all residents refuse offers that are either too low or too high.

While the study involves a sample from one TC and a comparison group, the results suggest that residents are at least comparable to the general public in generosity and appear willing on average to repay trust. A substantial minority may have difficulty accepting help.

Rapid peer feedback is of value. Residents will be willing to offer help to peers. The TC environment may explain residents’ tendency to return money in the trust game. Residents who refuse to accept offers that are either too low or too high in the ultimatum game may also have difficulty in accepting help from peers.

Economic games may help to clarify guidelines for TC clinical practice.

This is the first use of economic games with TC residents.

Behavioral economics poses a challenge for the welfare evaluation of choices, particularly those that involve risk. It demands that we recognize that the descriptive account of behavior toward those choices might not be the ones we were all taught, and still teach, and that subjective risk perceptions might not accord with expert assessments of probabilities. In addition to these challenges, we are faced with the need to jettison naive notions of revealed preferences, according to which every choice by a subject expresses her objective function, as behavioral evidence forces us to confront pervasive inconsistencies and noise in a typical individual’s choice data. A principled account of errant choice must be built into models used for identification and estimation. These challenges demand close attention to the methodological claims often used to justify policy interventions. They also require, we argue, closer attention by economists to relevant contributions from cognitive science. We propose that a quantitative application of the “intentional stance” of Dennett provides a coherent, attractive and general approach to behavioral welfare economics.

This paper aims to develop an algorithm to pretest an industrial portfolio on a new scale. Portfolios include complex and uncertain projects at the front-end phase. The study, therefore, proposes a procedure that helps decision-makers to handle various complex projects and defines a common scale applicable to various kinds of industrial projects.

Decision-makers can employ the preference algorithm to reach a common understanding. To this end, the current paper posits the organization of criteria in various project sets. A sexagesimal scale is developed based on project complexity and its ability to achieve broad impact, both these factors being gauged on a five-point scale of user-friendly numberings.

The proposed algorithm shows the equivalence of industrial projects in different fields. Also, the algorithm articulates the status in terms of uncertainty, complexity, risk, and value of projects. The connections between decision-makers and criteria operate on the basis of the foreseen complexity, risk, and value. It can be said that this study exemplifies and visualizes the portfolio and criteria relationship.

The procedure covers contingency exercises at the front-end phase of a portfolio and supports decisions. However, updated information can change support positions.

The paper presents original scoring guidance for portfolio complexity on a new scale. The scaling and scoring are adjustable and calibrated using the proposed sexagesimal system. It presents an original classification of project risk and value. The main contribution is the presented algorithm which can be used to pretest industrial portfolios composed of projects that vary in both size and context.

The behavior of tourists strongly depends on the availability and quality of information. Too little information as well as too much can be disorienting and forces many tourists to join the majority visiting major sights. This causes a few crowded places in contrast to many which are under‐utilized. A Destination Management Organization has the goal to spread tourists more evenly, whereas the tourists would like to enjoy the destination to its full potential according to their personal interests. The paper aims to focus on the issues surrounding the creation of a mobile tourist guide.

A field trial was conducted in the summer of 2005 to study the following questions as a precondition for the development: Is it possible to seed generic interest profiles in the mobile context that allow the accurate prediction of actual rankings? Are the interest profiles sufficiently diverse to base personalized tours on individual interest profiles instead of interest prototypes? How do personalized tours affect the spatial behavior of tourist? Three methods to elicit the generic preferences of tourist in the mobile context are compared with actual rankings using Spearman's rank order coefficient.

The diversity of the interest profiles is analyzed in various ways leading to the conclusion that personalized interest profiles are necessary. For the gathered profiles tours are computed and simulated in order to gain a first insight into the effect on the spatial behavior of tourists.

The dynamic tour guide is supporting both goals by means of pervasive computing based on the actual context which is defined by personal interests, location and schedule of a tourist. It enables a personalized, spontaneous and guided tour.

The purpose of this paper is to verify the consumer preference and choice behavior; also determine the speculative low loyalty behavior of consumers belonging to generation Y sub segment – adults (age 19‐28) and their perceptions regarding various brands.

Data were collected from 100 university students in Pakistan belonging to the age group 19‐28 years old. The research was concentrated in the mobile phone service sector. Data analysis was conducted using statistical analysis software SPSS.

The results indicate that stated preference set and actual choice behavior are dissimilar. The generation Y adults sub group contra‐indicates loyalty characteristics as high in a developing market context against the established wisdom of low loyalty found in developed countries. The perceptual maps of brands indicate no distinct personality characteristics necessitating marketers to rethink their strategies in this service industry. Finally, this research reconciles the gap between loyalty, stated preference and distinctiveness of brand personalities.

One limitation pertains to the target segment of 19‐28 years old. Future research could be expanded to other demographic segments and use other products and brands.

The major contribution of this paper is that it will advance theory regarding generation‐based characteristics to a less developed economy context by verifying theoretical proposition with regard to brand preferences and revealed brand choices. Second, marketers would be able to focus their promotions keeping in mind the perception and loyalty factors.

The author presents new estimates of the probability weighting functions found in rank-dependent theories of choice under risk. These estimates are unusual in two senses. First, they are free of functional form assumptions about both utility and weighting functions, and they are entirely based on binary discrete choices and not on matching or valuation tasks, though they depend on assumptions concerning the nature of probabilistic choice under risk. Second, estimated weighting functions contradict widely held priors of an inverse-s shape with fixed point well in the interior of the (0,1) interval: Instead the author usually finds populations dominated by “optimists” who uniformly overweight best outcomes in risky options. The choice pairs used here mostly do not provoke similarity-based simplifications. In a third experiment, the author shows that the presence of choice pairs that provoke similarity-based computational shortcuts does indeed flatten estimated probability weighting functions.

The purpose of this paper is to propose a model to guide organizations according to the relative importance of customer's satisfaction about six quality service dimensions: reliability, empathy, assurance, tangibility, responsiveness (Parasuraman et al., 1985) and price.

The present study uses SERVPERF customer requirements and weights of ELECTRE TRI multicriteria method to provide guidance on an appropriated action plan. Subsequently, it was demonstrated how the proposed model applied to the Inn.

SERVPERF is based on the subjective and cognitive perception of customer's service analyses. ELECTRE TRI decreases the deviation of subjectivity and develops manager's energy flow, focussed on enterprise resources.

Measuring quality is hard work and usually the customer perceptions are not well understood, because it changes many times. In addition SERVPERF and ELECTRE TRI weights do not order the quality importance.

Together, SERVPERF and ELECTRE TRI allow managers to prioritize the service level desired by the customer.

The importance of this analysis follows the competitiveness approach: productivity, quality and flexibility (Boljwin and Kumpe, 1990). The paper develops an approach to lead organizational quality performance based on the customer view. It provides a sustainable competitive advantage.