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Book part
Publication date: 31 January 2015

Soora Rasouli and Harry Timmermans

This chapter reviews models of decision-making and choice under conditions of certainty. It allows readers to position the contribution of the other chapters in this book…

Abstract

Purpose

This chapter reviews models of decision-making and choice under conditions of certainty. It allows readers to position the contribution of the other chapters in this book in the historical development of the topic area.

Theory

Bounded rationality is defined in terms of a strategy to simplify the decision-making process. Based on this definition, different models are reviewed. These models have assumed that individuals simplify the decision-making process by considering a subset of attributes, and/or a subset of choice alternatives and/or by disregarding small differences between attribute differences.

Findings

A body of empirical evidence has accumulated showing that under some circumstances the principle of bounded rationality better explains observed choices than the principle of utility maximization. Differences in predictive performance with utility-maximizing models are however small.

Originality and value

The chapter provides a detailed account of the different models, based on the principle of bounded rationality, that have been suggested over the years in travel behaviour analysis. The potential relevance of these models is articulated, model specifications are discussed and a selection of empirical evidence is presented. Aspects of an agenda of future research are identified.

Details

Bounded Rational Choice Behaviour: Applications in Transport
Type: Book
ISBN: 978-1-78441-071-1

Keywords

Content available
Book part
Publication date: 31 January 2015

Abstract

Details

Bounded Rational Choice Behaviour: Applications in Transport
Type: Book
ISBN: 978-1-78441-071-1

Content available
Book part
Publication date: 31 January 2015

Abstract

Details

Bounded Rational Choice Behaviour: Applications in Transport
Type: Book
ISBN: 978-1-78441-071-1

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Book part
Publication date: 31 January 2015

Stephane Hess and Caspar G. Chorus

This chapter proposes a new mixture model which allows for heterogeneity in sensitivities and decision rules across decision makers and attributes.

Abstract

Purpose

This chapter proposes a new mixture model which allows for heterogeneity in sensitivities and decision rules across decision makers and attributes.

Theory

A new mixture model is put forward in which the different latent classes make use of different decision rules, where the use of generalised random regret minimisation kernel allows for within class heterogeneity in the decision rules applied across attributes.

Findings

Our theoretical developments are supported by the findings of an empirical application using data from a typical stated choice survey.

Originality and value

Existing work has looked at heterogeneity in decision rules and sensitivities across respondents. Other work has focused on the possibility that different decision rules apply to different attributes. This chapter puts forward a model that combines these two directions of research and does so in a way that lets the optimal specification be driven by the data rather than being imposed by the analyst.

Details

Bounded Rational Choice Behaviour: Applications in Transport
Type: Book
ISBN: 978-1-78441-071-1

Keywords

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Article
Publication date: 7 June 2011

Lisa J. Abendroth

Prior to e‐commerce, tourists could only purchase souvenirs at a destination. The goal of this research is to develop and test a theory to explain how adding a retail web…

Abstract

Purpose

Prior to e‐commerce, tourists could only purchase souvenirs at a destination. The goal of this research is to develop and test a theory to explain how adding a retail web site affects tourists' decision‐making for souvenir purchases.

Design/methodology/approach

The researcher conducts two experiments using scenarios to simulate a souvenir purchase. The researcher manipulates item type and web site availability, and then measures purchase intent, attitudes toward the souvenir, and regret.

Findings

Purchase limitation increases initial purchase intent by increasing the souvenir's reminder value, regardless of item type. Non‐purchase regrets are greater than purchase regrets, which in turn increases purchase intent at a later time.

Research limitations

The stimuli are necklaces, and although the findings do not show gender effects, the stimuli could limit the generalizability to other souvenir types. The research tests hypotheses using scenarios and less‐experienced travelers. Future research should examine different types of souvenirs in a naturalistic setting.

Practical implications

Retailers should not mention web sites until after a tourist decides not to buy in‐store and should do so subtly.

Originality/value

This research contributes to souvenir research by identifying a purchase limitation, available in‐store only, as a new determinant of a souvenir's reminder value. The research also contributes to scarcity research by identifying reminder value as a new and qualitatively different type of valuation affected by scarcity. Lastly, the research extends the regret literature by reversing inaction inertia at a later purchase opportunity while maintaining a regret minimization goal.

Details

International Journal of Culture, Tourism and Hospitality Research, vol. 5 no. 2
Type: Research Article
ISSN: 1750-6182

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Article
Publication date: 1 January 2001

Helmut Mausser and Dan Rosen

Standard market risk optimization tools, based on assumptions of normality, are ineffective for evaluating credit risk. In this article, the authors develop three scenario…

Abstract

Standard market risk optimization tools, based on assumptions of normality, are ineffective for evaluating credit risk. In this article, the authors develop three scenario optimization models for portfolio credit risk. They first create the trading risk profile and find the best hedge position for a single asset or obligor. The second model adjusts all positions simultaneously to minimize the regret of the portfolio subject to general linear restrictions. Finally, a credit risk‐return efficient frontier is constructed using parametric programming. While scenario optimization of quantile‐based credit risk measures leads to problems that are not generally tractable, regret is a relevant and tractable measure that can be optimized using linear programming. The three models are applied to optimizing the risk‐return profile of a portfolio of emerging market bonds.

Details

The Journal of Risk Finance, vol. 2 no. 2
Type: Research Article
ISSN: 1526-5943

Content available
Article
Publication date: 27 August 2020

Dieter Koemle and Xiaohua Yu

This paper reviews the current literature on theoretical and methodological issues in discrete choice experiments, which have been widely used in non-market value…

Abstract

Purpose

This paper reviews the current literature on theoretical and methodological issues in discrete choice experiments, which have been widely used in non-market value analysis, such as elicitation of residents' attitudes toward recreation or biodiversity conservation of forests.

Design/methodology/approach

We review the literature, and attribute the possible biases in choice experiments to theoretical and empirical aspects. Particularly, we introduce regret minimization as an alternative to random utility theory and sheds light on incentive compatibility, status quo, attributes non-attendance, cognitive load, experimental design, survey methods, estimation strategies and other issues.

Findings

The practitioners should pay attention to many issues when carrying out choice experiments in order to avoid possible biases. Many alternatives in theoretical foundations, experimental designs, estimation strategies and even explanations should be taken into account in practice in order to obtain robust results.

Originality/value

The paper summarizes the recent developments in methodological and empirical issues of choice experiments and points out the pitfalls and future directions both theoretically and empirically.

Details

Forestry Economics Review, vol. 2 no. 1
Type: Research Article
ISSN: 2631-3030

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Article
Publication date: 17 June 2008

Jerzy Józefczyk

In many decision‐making problems under parameter uncertainty, the most popular stochastic approach is not used because of its serious drawbacks. The purpose of this paper…

Abstract

Purpose

In many decision‐making problems under parameter uncertainty, the most popular stochastic approach is not used because of its serious drawbacks. The purpose of this paper is to present another approach, which copes with the uncertainty of parameters. It uses a precise criterion evaluating a decision with respect to uncertain parameters. This precision by the maximum operator is performed on a term based on the criterion and called the relative regret. The approach is applied to the allocation problems in a complex of operations.

Design/methodology/approach

The resource allocation problems in a complex of operations of independent and dependent structures to minimize a total execution time of all operations are investigated. Then, the results are extended for the problem of a task allocation in the complex of independent operations. The case is considered when the parameters in the functional models of the operations are uncertain, and their values belong to the intervals of known bounds. The solution algorithms for the uncertain problems are based on known solution algorithms for the corresponding deterministic problems. The solution algorithms for the latter problems are outlined in the paper.

Findings

The main contribution of the paper consists in presenting the property that it is possible for the uncertain problems considered to replace the solution of the uncertain allocation problems by solving a number of corresponding deterministic problems.

Research limitations/implications

The useful and interesting property of the solution algorithm for the allocation problems, in general, cannot be applied to the other decision‐making problems under uncertainty. As an example of such a problem, a simple routing‐scheduling problem is presented for which, however, a number of possible parameter scenarios can be substantially limited.

Practical implications

The allocation problems addressed in the paper have a variety of applications in computer systems and in manufacturing systems. Moreover, a lack of crisp values for the parameters in models of individual operations is rather common.

Originality/value

The paper extends previous results for the allocation problems in a complex of operations.

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Book part
Publication date: 31 January 2015

Junyi Zhang

The chapter outlines the principles underlying relative utility models, discusses the results of empirical applications and critically assesses the usefulness of this…

Abstract

Purpose

The chapter outlines the principles underlying relative utility models, discusses the results of empirical applications and critically assesses the usefulness of this specification against commonly used random utility models and other context dependence models. It also discusses how relative utility can be viewed as a generalisation of context dependency.

Theory

In contrast to the conventional concept of random utility, relative utility assumes that decision-makers derive utility from their choices relative to some threshold(s) or reference points. Relative utility models thus systematically specify the utility against such thresholds or reference points.

Findings

Examples in the chapter show that relative utility model perform well in comparison to conventional utility-maximising models in some circumstances.

Originality and value

Examples of relative utility models are rare in transportation research. The chapter shows that several recent models can be viewed as special cases of relative utility models.

Details

Bounded Rational Choice Behaviour: Applications in Transport
Type: Book
ISBN: 978-1-78441-071-1

Keywords

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Book part
Publication date: 1 December 2008

Luke J. Chang and Alan G. Sanfey

Purpose – Initial explorations in the burgeoning field of neuroeconomics have highlighted evidence supporting a potential dissociation between a fast automatic system and…

Abstract

Purpose – Initial explorations in the burgeoning field of neuroeconomics have highlighted evidence supporting a potential dissociation between a fast automatic system and a slow deliberative controlled system. Growing research in the role of emotion in decision-making has attempted to draw parallels to the automatic system. This chapter will discuss a theoretical framework for understanding the role of emotion in decision-making and evidence supporting the underlying neural substrates.

Design/Methodology/Approach – This chapter applies a conceptual framework to understanding the role of emotion in decision-making, and emphasizes a distinction between expected and immediate emotions. Expected emotions refer to anticipated emotional states associated with a given decision that are never actually experienced. Immediate emotions, however, are experienced at the time of decision, and either can occur in response to a particular decision or merely as a result of a transitory fluctuation. This chapter will review research from the neuroeconomics literature that supports a neural dissociation between these two classes of emotion and also discuss a few interpretive caveats.

Findings – Several lines of research including regret, uncertainty, social decision-making, and moral decision-making have yielded evidence consistent with our formulization – expected and immediate emotions may invoke dissociable neural systems.

Originality/value – This chapter provides a more specific conceptualization of the mediating role of emotions in the decision-making process, which has important implications for understanding the interacting neural systems underlying the interface between emotion and cognition – a topic of immediate value to anyone investigating topics within the context of social-cognitive-affective-neuroscience.

Details

Neuroeconomics
Type: Book
ISBN: 978-1-84855-304-0

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