Storm surge risk mitigation under ambiguity by coupled tropical cyclone and decision model

Even as storm surge risks are increasing, the projections of such risks have an element of ambiguity. Consequently, policymakers find it extremely difficult to design policies to deal with storm surge risks. Therefore, in this study, we have linked the tropical cyclone models and stated preference experiments with decision models to provide a fresh perspective on households’ preferences for storm surge risk mitigation under ambiguity. We have validated households’ choices under the average and worst projections of storm surges and estimated the expected loss reduction, risk premium, and ambiguity premium for storm surge risk mitigation. Our study reveals that households pay disproportionately more attention to the worst case and that the ambiguity premium is not negligible. This leads to an important conclusion that policymakers should factor in the ambiguity premium to formulate risk mitigation policies.

Exploring Individual Preferences and Willingness to Pay for Mobility as a Service

This paper discusses demand and willingness to pay for mobility as a service (MaaS) plans. Given the rising popularity of the MaaS concept, research exploring preferences and demand for such services is valuable to researchers and policy makers as well as other involved stakeholders and mobility operators. This research investigates individual preferences for MaaS utilizing data collected via questionnaire surveys from Greater Manchester, United Kingdom. The surveys collected socio-demographic data and data in relation to individuals’ attitudes and typical mode use patterns, while stated preference data were also obtained by designing menu-based stated preference experiments where the respondents were able to create their ideal MaaS plan. A hybrid choice model is developed to explore user choices toward MaaS, while distributed willingness to pay values are estimated. A latent variable that captures the latent predisposition of people toward using multiple modes of transport is constructed. The results indicate that individuals who are more prone to using multimodal mobility options are willing to pay more for being offered both traditional and emerging mobility services as part of a monthly MaaS plan. Considering that the implementation of MaaS is still at an immature phase, while research efforts in relation to the demand for MaaS are limited, the results of this paper provide significant insights into individuals’ preferences toward MaaS and the heterogeneity between different user segments, and could be exploited to formulate valuable plans and contribute to the successful implementation of MaaS.

Virtual Immersive Reality for Stated Preference Travel Behavior Experiments: A Case Study of Autonomous Vehicles on Urban Roads

Stated preference experiments have been criticized for lack of realism. This issue is particularly visible when the scenario does not have a well understood prior reference, as in the case of research into demand for autonomous vehicles. The paper presents Virtual Immersive Reality Environment (VIRE), which is capable of developing highly realistic, immersive, and interactive choice scenarios. We demonstrate the use of VIRE in researching pedestrian preferences related to autonomous vehicles and associated infrastructure changes on urban streets in Montréal, Canada. The results are compared with predominantly used approaches: text-only and visual aid. We show that VIRE results in respondents having better understanding of the scenario and it yields more consistent results.

Eliciting Preferences in Dentistry with Multiattribute Stated Preference Methods: A Systematic Review

Background: Preference experiments are used to understand how patients and stakeholders value aspects of health care. These methods are gaining popularity in dentistry, but quality and breadth of use have not been evaluated. Objectives: To describe multiattribute stated preference experiment use in dentistry through illustration and critique of existing studies. Data Sources: Systematic literature search of PubMed, Econlit and Ovid for Medline, Embase, PsychINFO, PsychARTICLES, and All EBM Reviews, as well as gray literature. Study Eligibility: Multiattribute stated preference experiments eliciting preferences for dental service delivery, treatments, and oral health states from the perspective of patients, the public, and dental professionals. Outcomes of interest were preference weights and marginal rates of substitution. Study selection was independently performed by 2 reviewers. Appraisal: Ten-point checklist published by the International Society of Pharmacoeconomics and Outcomes Research was used for quality assessment. Synthesis: Descriptive analysis. Results: Searches identified 12 records published between 1999 and 2015, mostly in nondental academic journals. Studies were undertaken in high-income countries in Europe and the United States. The studies aimed to elicit preference for service delivery, treatment, or oral health states from the perspective of the patients, dentists, or the public via discrete choice experiment methods. The quality scores for the studies ranged from 53% to 100%. Limitations: A detailed description and critique of stated preference methods are provided, but it was not possible to provide synthesized preference data. Conclusions: Multiattribute stated preference experiments are increasingly popular, but understanding the methods and outputs is essential for designing and interpreting preference studies to improve patient care. Patient preferences highlight important considerations for decision making during treatment planning. Valuation of health states and estimation of willingness-to-pay are important for resource planning and allocation and economic evaluation. Preference estimates and relative value of attributes for interventions and service delivery inform development and selection of treatments and services (PROSPERO 21.3.17: CRD42017059859). Knowledge Transfer Statement: Understanding patient, professional, and public preferences is fundamental for evidence-based decision making and treatment delivery. Preference elicitation methods can be used to estimate the value given to health states, service delivery, individual treatments, and health outcomes. By describing and appraising the methodology and application of multiattribute stated preference experiments in dentistry, this review provides an essential first step to wider use of well-designed, high-quality preference elicitation methods.

Causal Inference in Conjoint Analysis: Understanding Multidimensional Choices via Stated Preference Experiments

Survey experiments are a core tool for causal inference. Yet, the design of classical survey experiments prevents them from identifying which components of a multidimensional treatment are influential. Here, we show howconjoint analysis, an experimental design yet to be widely applied in political science, enables researchers to estimate the causal effects of multiple treatment components and assess several causal hypotheses simultaneously. In conjoint analysis, respondents score a set of alternatives, where each has randomly varied attributes. Here, we undertake a formal identification analysis to integrate conjoint analysis with the potential outcomes framework for causal inference. We propose a new causal estimand and show that it can be nonparametrically identified and easily estimated from conjoint data using a fully randomized design. The analysis enables us to propose diagnostic checks for the identification assumptions. We then demonstrate the value of these techniques through empirical applications to voter decision making and attitudes toward immigrants.