Exploring Different Assumptions about Outcome-Related Risk Perceptions in Discrete Choice Experiments

AbstractEnvironmental outcomes are often affected by the stochastic nature of the environment and ecosystem, as well as the effectiveness of governmental policy in combination with human activities. Incorporating information about risk in discrete choice experiments has been suggested to enhance survey credibility. Although some studies have incorporated risk in the design and treated it as either the weights of the corresponding environmental outcomes or as a stand-alone factor, little research has discussed the implications of those behavioural assumptions under risk and explored individuals’ outcome-related risk perceptions in a context where environmental outcomes can be either described as improvement or deterioration. This paper investigates outcome-related risk perceptions for environmental outcomes in the gain and loss domains together and examines differences in choices about air quality changes in China using a discrete choice experiment. Results suggest that respondents consider the information of risk in both domains, and their elicited behavioural patterns are best described by direct risk aversion, which states that individuals obtain disutility directly from the increasing risk regardless of the associated environmental outcomes. We discuss the implication of our results and provide recommendations on the choice of model specification when incorporating risk.

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Design of Discrete Choice Experiments

Oxford Research Encyclopedia of Economics and Finance ◽

10.1093/acrefore/9780190625979.013.91 ◽

2019 ◽

Cited By ~ 1

Author(s):

Deborah J. Street ◽

Rosalie Viney

Keyword(s):

Discrete Choice ◽

Choice Experiment ◽

Stated Preference ◽

Choice Experiments ◽

Individual Characteristics ◽

Discrete Choice Experiments ◽

Random Component ◽

Choice Sets ◽

Attribute Levels ◽

Choice Set

Discrete choice experiments are a popular stated preference tool in health economics and have been used to address policy questions, establish consumer preferences for health and healthcare, and value health states, among other applications. They are particularly useful when revealed preference data are not available. Most commonly in choice experiments respondents are presented with a situation in which a choice must be made and with a a set of possible options. The options are described by a number of attributes, each of which takes a particular level for each option. The set of possible options is called a “choice set,” and a set of choice sets comprises the choice experiment. The attributes and levels are chosen by the analyst to allow modeling of the underlying preferences of respondents. Respondents are assumed to make utility-maximizing decisions, and the goal of the choice experiment is to estimate how the attribute levels affect the utility of the individual. Utility is assumed to have a systematic component (related to the attributes and levels) and a random component (which may relate to unobserved determinants of utility, individual characteristics or random variation in choices), and an assumption must be made about the distribution of the random component. The structure of the set of choice sets, from the universe of possible choice sets represented by the attributes and levels, that is shown to respondents determines which models can be fitted to the observed choice data and how accurately the effect of the attribute levels can be estimated. Important structural issues include the number of options in each choice set and whether or not options in the same choice set have common attribute levels. Two broad approaches to constructing the set of choice sets that make up a DCE exist—theoretical and algorithmic—and no consensus exists about which approach consistently delivers better designs, although simulation studies and in-field comparisons of designs constructed by both approaches exist.

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Präferenzen von Patienten, pflegenden Angehörigen, Leistungserbringern, Kostenträgern und politischen Entscheidungsträgern bei der integrierten Versorgung in Deutschland: Ein Discrete Choice Experiment

Das Gesundheitswesen ◽

10.1055/a-1547-6898 ◽

2021 ◽

Author(s):

Verena Struckmann ◽

Verena Vogt ◽

Julia Köppen ◽

Theresa Meier ◽

Maaike Hoedemakers ◽

...

Keyword(s):

Discrete Choice Experiment ◽

Discrete Choice ◽

Choice Experiment ◽

Choice Experiments ◽

Discrete Choice Experiments ◽

Pflegende Angehörige ◽

Triple Aim ◽

Körperliche Funktionsfähigkeit

Zusammenfassung Ziel Ziel dieser Studie ist Präferenzen zu erheben, die multimorbide Patienten, pflegende Angehörige, Leistungserbringer, Kostenträger oder politische Entscheidungsträger verschiedenen Endpunkten von integrierten Versorgungsprogrammen (IV-Programmen) in Deutschland beimessen und diese zu vergleichen. Methodik Mit Hilfe eines Discrete Choice Experiments (DCE) wurden die Präferenzen der Befragten für die Endpunkte von zwei IV-Programmen ermittelt. Jedes IV-Programm wurde anhand von Attributen, bzw.Endpunkten präsentiert, die das „Triple Aim“ abbilden. Sie waren in die Endpunkte Wohlbefinden, Erfahrung mit Versorgung und Kosten unterteilt, mit insgesamt acht Attributen und jeweils drei Ausprägungen. Ergebnisse Die Ergebnisse von 676 Fragebögen zeigen, dass die Attribute „Lebensfreude“ und „Kontinuität der Versorgung“ interessengruppenübergreifend die höchsten Bewertungen erhalten. Am geringsten blieben die relativen Bewertungen für alle Interessengruppen bei dem Attribut „Kosten“. Die Präferenzen der Leistungserbringer und pflegenden Angehörigen unterschieden sich am deutlichsten von denen der Patienten. Diese Unterschiede betrafen meist die „körperliche Funktionsfähigkeit“, die von Patienten am höchsten bewertet wurde, die „Personenzentrierung“ und „Kontinuität der Versorgung“, die die höchsten Bewertungen von den Leistungserbringern erhielten. Schlussfolgerung Die identifizierten Präferenzheterogenitäten in Bezug auf die Endpunkte von IV-Programmen zwischen den Interessengruppen verdeutlichen, wie wichtig es für eine optimale Ausgestaltung von IV-Programmen ist, Vertreter der Praxis und politische Entscheidungsträger über die unterschiedlichen Perspektiven zu informieren. Die Ergebnisse unterstreichen zudem die Relevanz von gemeinsamen Entscheidungsfindungs- und Abstimmungsprozessen zwischen Leistungserbringern, pflegenden Angehörigen und Patienten.

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Scope Elasticity of Willingness to pay in Discrete Choice Experiments

Environmental and Resource Economics ◽

10.1007/s10640-021-00577-7 ◽

2021 ◽

Author(s):

Anders Dugstad ◽

Kristine M. Grimsrud ◽

Gorm Kipperberg ◽

Henrik Lindhjem ◽

Ståle Navrud

Keyword(s):

Willingness To Pay ◽

Discrete Choice ◽

Stated Preference ◽

Choice Experiments ◽

Discrete Choice Experiments ◽

Model Specification ◽

Economic Significance ◽

Scope Sensitivity ◽

Order Of Magnitude ◽

Unit Of Measurement

AbstractSensitivity to scope in nonmarket valuation refers to the property that people are willing to pay more for a higher quality or quantity of a nonmarket public good. Establishing significant scope sensitivity has been an important check of validity and a point of contention for decades in stated preference research, primarily in contingent valuation. Recently, researchers have begun to differentiate between statistical and economic significance. This paper contributes to this line of research by studying the significance of scope effects in discrete choice experiments (DCEs) using the scope elasticity of willingness to pay concept. We first formalize scope elasticity in a DCE context and relate it to economic significance. Next, we review a selection of DCE studies from the environmental valuation literature and derive their implied scope elasticity estimates. We find that scope sensitivity analysis as validity diagnostics is uncommon in the DCE literature and many studies assume unitary elastic scope sensitivity by employing a restrictive functional form in estimation. When more flexible specifications are employed, the tendency is towards inelastic scope sensitivity. Then, we apply the scope elasticity concept to primary DCE data on people’s preferences for expanding the production of renewable energy in Norway. We find that the estimated scope elasticities vary between 0.13 and 0.58, depending on the attribute analyzed, model specification, geographic subsample, and the unit of measurement for a key attribute. While there is no strict and universally applicable benchmark for determining whether scope effects are economically significant, we deem these estimates to be of an adequate and plausible order of magnitude. Implications of the results for future DCE research are provided.

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How discrete choice experiments contribute to person-centered healthcare. A commentary on Kaltoft et al. (2015): ”Can a Discrete Choice Experiment contribute to person-centred healthcare?”

European Journal for Person Centered Healthcare ◽

10.5750/ejpch.v3i4.1049 ◽

2015 ◽

Vol 3 (4) ◽

pp. 438

Author(s):

Line Bjørnskov Pedersen ◽

Mickael Bech ◽

Mirja Kløgaard ◽

Rikke Søgaard ◽

Jorien Veldwijk ◽

...

Keyword(s):

Discrete Choice Experiment ◽

Discrete Choice ◽

Choice Experiment ◽

Choice Experiments ◽

Discrete Choice Experiments

No abstract

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The impact of health vs. non-health goals on individuals’ lifestyle program choices: a discrete choice experiment approach

BMC Public Health ◽

10.1186/s12889-020-8416-3 ◽

2020 ◽

Vol 20 (1) ◽

Cited By ~ 1

Author(s):

Tim M. Benning ◽

Benedict G. C. Dellaert ◽

Theo A. Arentze

Keyword(s):

Discrete Choice Experiment ◽

Discrete Choice ◽

Choice Experiment ◽

Choice Experiments ◽

Discrete Choice Experiments ◽

Experimental Conditions ◽

Health Goals ◽

Health Goal ◽

Lifestyle Program ◽

The Impact

Abstract Background Goals play an important role in the choices that individuals make. Yet, there is no clear approach of how to incorporate goals in discrete choice experiments. In this paper, we present such an approach and illustrate it in the context of lifestyle programs. Furthermore, we investigate how non-health vs. health goals affect individuals’ choices via non-goal attributes. Methods We used an unlabeled discrete choice experiment about lifestyle programs based on two experimental conditions in which either a non-health goal (i.e., looking better) or a health goal (i.e., increasing life expectancy) was presented to respondents as a fixed attribute level for the goal attribute. Respondents were randomly distributed over the experimental conditions. Eventually, we used data from 407 Dutch adults who reported to be overweight (n = 212 for the non-health goal, and n = 195 for the health goal). Results Random parameter logit model estimates show that the type of goal significantly (p < 0.05) moderates the effect that the attribute diet has on lifestyle program choice, but that this is not the case for the attributes exercise per week and expected weight loss. Conclusions A flexible diet is more important for individuals with a non-health goal than for individuals with a health goal. Therefore, we advise policy makers to use information on goal interactions for developing new policies and communication strategies to target population segments that have different goals. Furthermore, we recommend researchers to consider the impact of goals when designing discrete choice experiments.

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A query theory account of a discrete choice experiment under oath

European Review of Agricultural Economics ◽

10.1093/erae/jbz026 ◽

2019 ◽

Vol 47 (3) ◽

pp. 1133-1172

Author(s):

Nathan P Kemper ◽

Jennie S Popp ◽

Rodolfo M Nayga

Keyword(s):

Discrete Choice Experiment ◽

Discrete Choice ◽

Choice Experiment ◽

Stated Preference ◽

Choice Experiments ◽

Hypothetical Bias ◽

Discrete Choice Experiments ◽

Thought Processes ◽

Stated Preference Methods ◽

Ex Ante

Abstract One limitation of stated-preference methods is the formation of hypothetical bias. To address this, the honesty oath has been used as an ex ante technique to reduce hypothetical bias. Our study provides a query account of the honesty oath in a discrete-choice experiment setting by using Query Theory to examine the mechanism behind the effectiveness of the honesty oath. Our results show that the honesty oath can change the content and order of queries; potentially reducing hypothetical bias in discrete choice experiments. The study suggests the potential usefulness of Query Theory in examining thought processes of respondents in valuation studies.

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Sample-based longitudinal discrete choice experiments: preferences for electric vehicles over time

Journal of the Academy of Marketing Science ◽

10.1007/s11747-020-00758-8 ◽

2021 ◽

Author(s):

Katharina Keller ◽

Christian Schlereth ◽

Oliver Hinz

Keyword(s):

Discrete Choice ◽

Electric Vehicles ◽

Choice Experiment ◽

State Of The Art ◽

Statistical Significance ◽

Choice Experiments ◽

Hierarchical Bayes ◽

Discrete Choice Experiments ◽

Cross Sectional ◽

Over Time

AbstractDiscrete choice experiments have emerged as the state-of-the-art method for measuring preferences, but they are mostly used in cross-sectional studies. In seeking to make them applicable for longitudinal studies, our study addresses two common challenges: working with different respondents and handling altering attributes. We propose a sample-based longitudinal discrete choice experiment in combination with a covariate-extended hierarchical Bayes logit estimator that allows one to test the statistical significance of changes. We showcase this method’s use in studies about preferences for electric vehicles over six years and empirically observe that preferences develop in an unpredictable, non-monotonous way. We also find that inspecting only the absolute differences in preferences between samples may result in misleading inferences. Moreover, surveying a new sample produced similar results as asking the same sample of respondents over time. Finally, we experimentally test how adding or removing an attribute affects preferences for the other attributes.

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