Place of Residence and Cost Attribute Non-Attendance in a Stated Preference Choice Experiment Involving a Marine Endangered Species

2019 ◽  
Vol 34 (3) ◽  
pp. 225-245 ◽  
Author(s):  
Daniel K. Lew
Keyword(s):  
Endangered Species ◽  
Choice Experiment ◽  
Stated Preference ◽  
Place Of Residence ◽  
Cost Attribute ◽  
Marine Endangered Species

Using a stated preference discrete choice experiment to assess societal value from the perspective of decision-makers in Europe. Does it work for rare diseases?

Health Policy ◽  
2019 ◽  
Vol 123 (2) ◽  
pp. 152-158 ◽  
Author(s):  
J. López-Bastida ◽  
J.M. Ramos-Goñi ◽  
I. Aranda-Reneo ◽  
M. Trapero-Bertran ◽  
P. Kanavos ◽  
...  
Keyword(s):  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Rare Diseases ◽  
Choice Experiment ◽  
Stated Preference ◽  
Decision Makers ◽  
Societal Value

scholarly journals Understanding uptake of digital health products: Methodology tutorial for a Discrete Choice Experiment using a Bayesian efficient design (Preprint)

2021 ◽  
Author(s):  
Dorothy Szinay ◽  
Rory Cameron ◽  
Felix Naughton ◽  
Jennifer A. Whitty ◽  
Jamie Brown ◽  
...  
Keyword(s):  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Choice Experiment ◽  
Stated Preference ◽  
Digital Health ◽  
Revealed Preferences ◽  
Quantitative Methodology ◽  
Efficient Design ◽  
Trade Offs ◽  
Health Products

UNSTRUCTURED Understanding the preferences of potential users of digital health products is beneficial for digital health policy and planning. Stated preference methods could help elicit individuals’ preferences in the absence of observational data. A discrete choice experiment (DCE) is a commonly used stated preference method; a quantitative methodology that argues that individuals make trade-offs when engaging in a decision by choosing an alternative of a product or service that offers the greatest utility, or benefit. This methodology is widely used in health economics in situations where revealed preferences are difficult to collect but is much less used in the field of digital health. This article outlines the stages involved in developing a discrete choice experiment. As a case study, it uses the application of a DCE for revealing preferences in targeting the uptake of smoking cessation apps. It describes the establishment of attributes, the construction of choice tasks of two or more alternatives, and the development of the experimental design. This tutorial offers a guide for researchers with no prior knowledge of this research technique.

A Stated Preference Binary Choice Experiment to Explore NICE Decision Making

2007 ◽  
Vol 25 (8) ◽  
pp. 685-693 ◽  
Author(s):  
Paul Tappenden ◽  
John Brazier ◽  
Julie Ratcliffe ◽  
James Chilcott
Keyword(s):  
Decision Making ◽  
Choice Experiment ◽  
Stated Preference ◽  
Binary Choice

Economics and the Endangered Species Act

2021 ◽  
Author(s):  
Joe Kerkvliet
Keyword(s):  
Endangered Species ◽  
Economic Analysis ◽  
Stated Preference ◽  
Species Conservation ◽  
Endangered Species Act ◽  
Future Research ◽  
Economic Science ◽  
Economic Costs ◽  
Cost Estimates ◽  
Stated Preference Methods

Economics plays strong roles in the design, implementation, and evaluation of the Endangered Species Act (ESA). First, the ESA’s language allows for economic analysis of critical habitat designations, recovery plan implementations, listing postponements, and the design of habitat-conservation plans. Extensive administrative changes to the ESA in the 1990s were designed to reduce economic costs and to elicit landowners’ cooperation. These reforms were partly motivated and guided by economic analysis. Second, economic analysis plays a role in providing credible estimates of the economic costs of ESA implementation. Cost estimates are highly variable and likely to depend on species’ characteristics and the effectiveness of recovery programs. Emerging evidence suggests that the 1990 reforms are reducing costs and increasing effectiveness. Third, economic science contributes to estimation of benefits. Because of the “public goods” nature of nearly all ecosystem and species conservation efforts, estimates must be based on stated preference methods. This use leads to difficulties in establishing the authenticity of benefits estimates. Also, research suggests that benefits estimates are highly sensitive to the spatial nature of the market (beneficiaries’ geographic locations). Future research needs to tackle both authenticity and spatial issues. Fourth, benefit–cost analysis (BCA) is required by law to inform many resource decisions affecting ecosystem and species conservation. Four illustrative BCAs show that whether benefits exceed costs is highly dependent on the authenticity of benefits based on stated preference methods and assumptions about the spatial nature of the market. Substantial uncertainty accompanies both benefit and cost estimates.

scholarly journals Understanding Midwives’ Preferences for Providing Information About Newborn Bloodspot Screening

2018 ◽  
Vol 3 (1) ◽  
pp. 238146831774617 ◽  
Author(s):  
Stuart James Wright ◽  
Fiona Ulph ◽  
Tina Lavender ◽  
Nimarta Dharni ◽  
Katherine Payne
Keyword(s):  
Conjoint Analysis ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Choice Experiment ◽  
Screening Program ◽  
Stated Preference ◽  
Information Provision ◽  
Stated Preference Survey ◽  
Newborn Bloodspot Screening ◽  
Types Of Information

Background: Understanding preferences for information provision in the context of health care service provision is challenging because of the number of potential attributes that may influence preferences. This study aimed to identify midwives’ preferences for the process and outcomes of information provision in an expanded national newborn bloodspot screening program. Design: A sample of practicing midwives completed a hybrid-stated preference survey including a conjoint analysis (CA) and discrete choice experiment to quantify preferences for the types of, and way in which, information should be provided in a newborn bloodspot screening program. Six conjoint analysis questions captured the impact of different types of information on parents’ ability to make a decision, and 10 discrete choice experiment questions identified preferences for four process attributes (including parents’ ability to make a decision). Results: Midwives employed by the UK National Health Service (n = 134) completed the survey. All types of information content were perceived to improve parents’ ability to make a decision except for the possibility of false-positive results. Late pregnancy was seen to be the best time to provide information, followed by day 3 postbirth. Information before 20 weeks of pregnancy was viewed as reducing parents’ ability to make a decision. Midwives preferred information to be provided by an individual discussion and did not think parents should receive information on the Internet. Conclusion: A hybrid stated preference survey design identified that a wide variety of information should be provided to maximize parents’ ability to make a decision ideally provided late in pregnancy or on day 3 postbirth.

Estimating US federal wildland fire managers’ preferences toward competing strategic suppression objectives

2013 ◽  
Vol 22 (2) ◽  
pp. 212 ◽  
Author(s):  
David E. Calkin ◽  
Tyron Venn ◽  
Matthew Wibbenmeyer ◽  
Matthew P. Thompson
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Cost Containment ◽  
Choice Experiment ◽  
Management Practices ◽  
Stated Preference ◽  
Wildland Fire ◽  
Ceteris Paribus ◽  
Current Management ◽  
Wildfire Management

Wildfire management involves significant complexity and uncertainty, requiring simultaneous consideration of multiple, non-commensurate objectives. This paper investigates the tradeoffs fire managers are willing to make among these objectives using a choice experiment methodology that provides three key advancements relative to previous stated-preference studies directed at understanding fire manager preferences: (1) a more immediate relationship between the instrument employed in measuring preferences and current management practices and operational decision-support systems; (2) an explicit exploration of how sociopolitical expectations may influence decision-making and (3) consideration of fire managers’ relative prioritisation of cost-containment objectives. Results indicate that in the current management environment, choices among potential suppression strategies are driven largely by consideration of risk to homes and high-value watersheds and potential fire duration, and are relatively insensitive to increases in cost and personnel exposure. Indeed, when asked to choose the strategy they would expect to choose under current social and political constraints, managers favoured higher-cost suppression strategies, ceteris paribus. However, managers indicated they would personally prefer to pursue strategies that were more cost-conscious and proportionate with values at risk. These results confirm earlier studies that highlight the challenges managerial incentives and sociopolitical pressures create in achieving cost-containment objectives.

Moving beyond the Contingent Valuation versus Choice Experiment Debate: Presentation Effects in Stated Preference

2020 ◽  
Vol 96 (1) ◽  
pp. 1-24
Author(s):  
Patrick Lloyd-Smith ◽  
Ewa Zawojska ◽  
Wiktor Adamowicz
Keyword(s):  
Contingent Valuation ◽  
Choice Experiment ◽  
Stated Preference

Investigating demand for biofortified seeds in developing countries

2015 ◽  
Vol 5 (1) ◽  
pp. 24-43 ◽  
Author(s):  
Ekin Birol ◽  
Dorene Asare-Marfo ◽  
Bhushana Karandikar ◽  
Devesh Roy ◽  
Michael Tedla Diressie
Keyword(s):  
Developing Countries ◽  
Pearl Millet ◽  
Choice Experiment ◽  
Latent Class ◽  
Stated Preference ◽  
Significant Heterogeneity ◽  
Content Type ◽  
High Iron ◽  
First Choice ◽  
Experiment Method

Purpose – The purpose of this paper is to explore farmer acceptance of a biofortified staple food crop in a developing country prior to its commercialization. The paper focuses on the hypothetical introduction of a high-iron pearl millet variety in Maharashtra, India, where pearl millet is among the most important staple crops. Design/methodology/approach – A choice experiment is used to investigate farmer preferences for and trade-offs among various production and consumption attributes of pearl millet. The key pearl millet attributes studied include days it takes pearl millet to mature, color of the roti (flat bread) the grain produces, the presence of high-iron content (nutritional attribute), and the price of the pearl millet seed. Choice data come from 630 pearl millet-producing households from three purposefully selected districts of Maharashtra. A latent class model is used to investigate the heterogeneity in farmers’ preferences for pearl millet attributes and to profile farmers who are more or less likely to choose high-iron varieties of pearl millet. Findings – The results reveal that there are three distinct segments in the sample, and there is significant heterogeneity in farmer preferences across these segments. High-iron pearl millet is valued the most by larger households that produce mainly for household consumption and currently have lower quality diets. Households that mainly produce for market sales, on the other hand, derive lower benefits from consumption characteristics such as color and nutrition. Research limitations/implications – The main limitation of the study is that it uses a stated preference choice experiment method, which suffers from hypothetical bias. At the time of implementing this study biofortified high-iron pearl millet varieties were not yet developed, therefore the authors could not have implemented revealed preference elicitation methods with real products and payment. Originality/value – The method used (stated preference choice experiment method) is commonly used to value non-market goods such as environmental goods and products that are not yet in the market. It’s application to agriculture and in developing countries is increasing. As far as the authors know this is the first choice experiment implemented to investigate farmer/consumer preferences for biofortified crops. The study presents valuable information for development and delivery of biofortified crops for reducing micronutrient deficiencies.

Design of Discrete Choice Experiments

2019 ◽  
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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