978 resultados para Stated preference methods


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This research investigates whether a reconfiguration of maternity services, which collocates consultant- and midwifery-led care, reflects demand and value for money in Ireland. Qualitative and quantitative research is undertaken to investigate demand and an economic evaluation is performed to evaluate the costs and benefits of the different models of care. Qualitative research is undertaken to identify women’s motivations when choosing place of delivery. These data are further used to inform two stated preference techniques: a discrete choice experiment (DCE) and contingent valuation method (CVM). These are employed to identify women’s strengths of preferences for different features of care (DCE) and estimate women’s willingness to pay for maternity care (CVM), which is used to inform a cost-benefit analysis (CBA) on consultant- and midwifery-led care. The qualitative research suggests women do not have a clear preference for consultant or midwifery-led care, but rather a hybrid model of care which closely resembles the Domiciliary Care In and Out of Hospital (DOMINO) scheme. Women’s primary concern during care is safety, meaning women would only utilise midwifery-led care when co-located with consultant-led care. The DCE also finds women’s preferred package of care closely mirrors the DOMINO scheme with 39% of women expected to utilise this service. Consultant- and midwifery-led care would then be utilised by 34% and 27% of women, respectively. The CVM supports this hierarchy of preferences where consultant-led care is consistently valued more than midwifery-led care – women are willing to pay €956.03 for consultant-led care and €808.33 for midwifery-led care. A package of care for a woman availing of consultant- and midwifery-led care is estimated to cost €1,102.72 and €682.49, respectively. The CBA suggests both models of care are cost-beneficial and should be pursued in Ireland. This reconfiguration of maternity services would maximise women’s utility, while fulfilling important objectives of key government policy.

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This paper addresses the representation of landscape complexity in stated preferences research. It integrates landscape ecology and landscape economics and conducts the landscape analysis in a three-dimensional space to provide ecologically meaningful quantitative landscape indicators that are used as variables for the monetary valuation of landscape in a stated preferences study. Expected heterogeneity in taste intensity across respondents is addressed with a mixed logit model in Willingness to Pay space. Our methodology is applied to value, in monetary terms, the landscape of the Sorrento Peninsula in Italy, an area that has faced increasing pressure from urbanization affecting its traditional horticultural, herbaceous, and arboreal structure, with loss of biodiversity, and an increasing risk of landslides. We find that residents of the Sorrento Peninsula would prefer landscapes characterized by large open views and natural features. Residents also appear to dislike heterogeneous landscapes and the presence of lemon orchards and farmers' stewardship, which are associated with the current failure of protecting the traditional landscape. The outcomes suggest that the use of landscape ecology metrics in a stated preferences model may be an effective way to move forward integrated methodologies to better understand and represent landscape and its complexity.

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We present an experiment designed to investigate the presence and nature of ordering effects within repeat-response stated preference (SP) studies. Our experiment takes the form of a large sample, full-factorial, discrete choice SP exercise investigating preferences for tap water quality improvements. Our study simultaneously investigates a variety of different forms of position-dependent and precedent-dependent ordering effect in preferences for attributes and options and in response randomness. We also examine whether advanced disclosure of the choice tasks impacts on the probability of exhibiting ordering effects of those different types. We analyze our data both non-parametrically and parametrically and find robust evidence for ordering effects. We also find that the patterns of order effect in respondents' preferences are significantly changed but not eradicated by the advanced disclosure of choice tasks a finding that offers insights into the choice behaviors underpinning order effects. © 2011 Elsevier Inc.

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Using a choice experiment survey this study examines the UK public's willingness to pay to conserve insect pollinators in relation to the levels of two pollination service benefits: maintaining local produce supplies and the aesthetic benefits of diverse wildflower assemblages. Willingness to pay was estimated using a Bayesian mixed logit with two contrasting controls for attribute non-attendance, exclusion and shrinkage. The results suggest that the UK public have an extremely strong preference to avoid a status quo scenario where pollinator populations and pollination services decline. Total willingness to pay was high and did not significantly vary between the two pollination service outputs, producing a conservative total of £379M over a sample of the tax-paying population of the UK, equivalent to £13.4 per UK taxpayer. Using a basic production function approach, the marginal value of pollination services to these attributes is also extrapolated. The study discusses the implications of these findings and directions for related future research into the non-market value of pollination and other ecosystem services.

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The aim of this paper is to build the stated preference method into the social discount rate methodology. The first part of the paper presents the results of a survey about stated time preferences through pair-choice decision situations for various topics and time horizons. It is assumed that stated time preferences differ from calculated time preferences and that the extent of stated rates depends on the time period, and on how much respondents are financially and emotionally involved in the transactions. A significant question remains: how can the gap between the calculation and the results of surveys be resolved, and how can the real time preferences of individuals be interpreted using a social time preference rate. The second part of the paper estimates the social time preference rate for Hungary using the results of the survey, while paying special attention to the pure time preference component. The results suggest that the current method of calculation of the pure time preference rate does not reflect the real attitudes of individuals towards future generations.

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This paper describes the formalization and application of a methodology to evaluate the safety benefit of countermeasures in the face of uncertainty. To illustrate the methodology, 18 countermeasures for improving safety of at grade railroad crossings (AGRXs) in the Republic of Korea are considered. Akin to “stated preferencemethods in travel survey research, the methodology applies random selection and laws of large numbers to derive accident modification factor (AMF) densities from expert opinions. In a full Bayesian analysis framework, the collective opinions in the form of AMF densities (data likelihood) are combined with prior knowledge (AMF density priors) for the 18 countermeasures to obtain ‘best’ estimates of AMFs (AMF posterior credible intervals). The countermeasures are then compared and recommended based on the largest safety returns with minimum risk (uncertainty). To the author's knowledge the complete methodology is new and has not previously been applied or reported in the literature. The results demonstrate that the methodology is able to discern anticipated safety benefit differences across candidate countermeasures. For the 18 at grade railroad crossings considered in this analysis, it was found that the top three performing countermeasures for reducing crashes are in-vehicle warning systems, obstacle detection systems, and constant warning time systems.

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This study investigates potential demand for infrastructure investment for alternative fuel vehicles by applying stated preference methods to a Japanese sample. The potential demand is estimated on the basis of how much people are willing to pay for alternative fuel vehicles under various refueling scenarios. Using the estimated parameters, the economic efficiency of establishing battery-exchange stations for electric vehicles is examined. The results indicate that infrastructural development of battery-exchange stations can be efficient when electric vehicle sales exceed 5.63% of all new vehicle sales. Further, we find a complementary relationship between the cruising ranges of alternative fuel vehicles and the infrastructure established.

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Non-use values (i.e. economic values assigned by individuals to ecosystem goods and services unrelated to current or future uses) provide one of the most compelling incentives for the preservation of ecosystems and biodiversity. Assessing the non-use values of non-users is relatively straightforward using stated preference methods, but the standard approaches for estimating non-use values of users (stated decomposition) have substantial shortcomings which undermine the robustness of their results. In this paper, we propose a pragmatic interpretation of non-use values to derive estimates that capture their main dimensions, based on the identification of a willingness to pay for ecosystem protection beyond one's expected life. We empirically test our approach using a choice experiment conducted on coral reef ecosystem protection in two coastal areas in New Caledonia with different institutional, cultural, environmental and socio-economic contexts. We compute individual willingness to pay estimates, and derive individual non-use value estimates using our interpretation. We find that, a minima, estimates of non-use values may comprise between 25 and 40% of the mean willingness to pay for ecosystem preservation, less than has been found in most studies.

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Eutrophication of the Baltic Sea is a serious problem. This thesis estimates the benefit to Finns from reduced eutrophication in the Gulf of Finland, the most eutrophied part of the Baltic Sea, by applying the choice experiment method, which belongs to the family of stated preference methods. Because stated preference methods have been subject to criticism, e.g., due to their hypothetical survey context, this thesis contributes to the discussion by studying two anomalies that may lead to biased welfare estimates: respondent uncertainty and preference discontinuity. The former refers to the difficulty of stating one s preferences for an environmental good in a hypothetical context. The latter implies a departure from the continuity assumption of conventional consumer theory, which forms the basis for the method and the analysis. In the three essays of the thesis, discrete choice data are analyzed with the multinomial logit and mixed logit models. On average, Finns are willing to contribute to the water quality improvement. The probability for willingness increases with residential or recreational contact with the gulf, higher than average income, younger than average age, and the absence of dependent children in the household. On average, for Finns the relatively most important characteristic of water quality is water clarity followed by the desire for fewer occurrences of blue-green algae. For future nutrient reduction scenarios, the annual mean household willingness to pay estimates range from 271 to 448 and the aggregate welfare estimates for Finns range from 28 billion to 54 billion euros, depending on the model and the intensity of the reduction. Out of the respondents (N=726), 72.1% state in a follow-up question that they are either Certain or Quite certain about their answer when choosing the preferred alternative in the experiment. Based on the analysis of other follow-up questions and another sample (N=307), 10.4% of the respondents are identified as potentially having discontinuous preferences. In relation to both anomalies, the respondent- and questionnaire-specific variables are found among the underlying causes and a departure from standard analysis may improve the model fit and the efficiency of estimates, depending on the chosen modeling approach. The introduction of uncertainty about the future state of the Gulf increases the acceptance of the valuation scenario which may indicate an increased credibility of a proposed scenario. In conclusion, modeling preference heterogeneity is an essential part of the analysis of discrete choice data. The results regarding uncertainty in stating one s preferences and non-standard choice behavior are promising: accounting for these anomalies in the analysis may improve the precision of the estimates of benefit from reduced eutrophication in the Gulf of Finland.