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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.

Choice under risk has a large stochastic (unpredictable) component. This chapter examines five stochastic models for binary discrete choice under risk and how they combine with “structural” theories of choice under risk. Stochastic models are substantive theoretical hypotheses that are frequently testable in and of themselves, and also identifying restrictions for hypothesis tests, estimation and prediction. Econometric comparisons suggest that for the purpose of prediction (as opposed to explanation), choices of stochastic models may be far more consequential than choices of structures such as expected utility or rank-dependent utility.

This article addresses simultaneously two important features in random utility maximisation (RUM) choice modelling: choice set generation and unobserved taste heterogeneity. It is proposed to develop and to compare definitions and properties of econometric specifications that are based on mixed logit (MXL) and latent class logit (LCL) RUM models in the additional presence of prior compensatory screening decision rules. The latter allow for continuous latent bounds that determine choice alternatives to be or not to be considered for decision making. It is also proposed to evaluate and to test each against the other ones in an application to home-to-work mode choice in the Paris region of France using 2002 data.

We take Cumulative Prospect Theory (CPT) seriously by rigorously estimating structural models using the full set of CPT parameters. Much of the literature only estimates a subset of CPT parameters, or more simply assumes CPT parameter values from prior studies. Our data are from laboratory experiments with undergraduate students and MBA students facing substantial real incentives and losses. We also estimate structural models from Expected Utility Theory (EUT), Dual Theory (DT), Rank-Dependent Utility (RDU), and Disappointment Aversion (DA) for comparison. Our major finding is that a majority of individuals in our sample locally asset integrate. That is, they see a loss frame for what it is, a frame, and behave as if they evaluate the net payment rather than the gross loss when one is presented to them. This finding is devastating to the direct application of CPT to these data for those subjects. Support for CPT is greater when losses are covered out of an earned endowment rather than house money, but RDU is still the best single characterization of individual and pooled choices. Defenders of the CPT model claim, correctly, that the CPT model exists “because the data says it should.” In other words, the CPT model was borne from a wide range of stylized facts culled from parts of the cognitive psychology literature. If one is to take the CPT model seriously and rigorously then it needs to do a much better job of explaining the data than we see here.

Research on strategic choices available to the firm are often modeled as a limited number of possible decision outcomes and leads to a discrete limited dependent variable. A limited dependent variable can also arise when values of a continuous dependent variable are partially or wholly unobserved. This chapter discusses the methodological issues associated with such phenomena and the appropriate statistical methods developed to allow for consistent and efficient estimation of models that involve a limited dependent variable. The chapter also provides a road map for selecting the appropriate statistical technique and it offers guidelines for consistent interpretation and reporting of the statistical results.

The purpose of this paper is to introduce the concept of robust design in retail service literature.

Using a Taguchi design comprising of inner L₈ (2⁷) and outer 2² arrays, a discrete choice task was designed for 233 students respond to. Signal‐to‐noise (S/N) ratio was used to test design robustness.

Negative effects of uncontrollable design factors on service choice were minimized through the use of inner and outer Taguchi arrays. The single composite measure of consumer choice called S/N ratio accounted both for mean and variance of choice probabilities.

Use of student sample was a major limitation. Also, the interaction between design factors was not tested as it required the use of more complicated designs.

This method can be used to improve design robustness by minimizing the impact of uncontrollable noise factors. Use of S/N ratio can help to select the design that simultaneously maximized the choice probabilities and minimized performance variation.

The paper makes important methodological and operational contributions to the retail service design literature. First, the concept of controllable and uncontrollable factors in choice‐based designs is introduced. Second, the use of S/N ratio as a single, composite measure of design robustness was incorporated. Operationally, this study highlights the impact of less‐studied concepts of wayfinding and customer incompatibility on satisfaction of retail customers.

This research measures the causal effects of pertinent agricultural credit policy attributes on farmers' participation probability and their willingness to pay (WTP) for agricultural credit and its associated services.

A randomized conjoint field experiment is conducted in three districts of Nangarhar Province, Afghanistan, capturing stated-preference data of 300 farmers. Each survey participant was provided with two hypothetical choices and one opt-out option to generate rankings based on their preferences. The levels of six attributes—namely, the credit service provider's location, the time required to obtain credit, the frequency of installments, the type of loan security, the provider of the credit services and the annual membership fee to participate in the proposed policy—are randomly assigned to produce the alternative choices.

The results reveal that farmers support the suggested agricultural credit services policy (ACSP), and the lower bound of their WTP for participation in the policy is as high as 5% of their average annual income.

This study provides evidence-based policy input for designing effective agricultural credit policies in Afghanistan, which can be extended to other countries with a similar context.

This is the first study estimating the causal effects of formal agricultural credit policy attributes on farmers' participation probability. Further, this study nonparametrically measures farmers' WTP for participation in the proposed policy.

This paper aims to extend the work by Vafeas and Lie and Lie by developing an empirical model of choice among four alternative mechanisms for distributing cash from corporations to shareholders: a fixed‐price self‐tender offer, a Dutch auction self‐tender offer, an open market share repurchase, and a special dividend.

A multinomial logit (MNL) model adapted for choice‐based sampling is used to examine the factors that influence a firm's choice among the four methods.

Firms with a high degree of heterogeneity in shareholder valuations tend to select an open market repurchase, while firms with low levels of heterogeneity choose a special dividend. Firms already paying high dividends are more likely to issue a special dividend than institute an open market repurchase. A firm with poor stock performance prior to the announcement is more likely to choose a fixed‐price self‐tender offer or open market share repurchase. On the other hand, firms are more likely to follow strong performance with a special dividend. Contrary to Persons' model, it is found that firms facing a takeover threat are more likely to choose a fixed‐price tender offer than a Dutch auction.

It is shown that the ownership structure, current payout level; the size of the distribution, and the degree of stock undervaluation are among the most important determinants of a firm's choice among alternative payout methods.

This study adds to the existing literature by developing the first empirical model of choice among all four one‐time (or infrequent) corporate cash disbursement methods. It is also the first to adjust the MNL estimates for the choice‐based sampling method used to collect the data.

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.

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.

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.

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.