950 resultados para Discrete choice experiments
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Purpose – In 2012, the European food industry was hit by a food fraud: horsemeat was found in
pre-prepared foods, without any declaration on the package. This is commonly referred to as the
“horsemeat scandal”. The purpose of this paper is to investigate consumers’ preferences across
Europe for a selected ready meal, ready to heat (RTH) fresh lasagne, to consider whether the effects of
potential food frauds on consumers’ choices can be mitigated by introducing enhanced standards of
RTH products.
Design/methodology/approach – An online survey was administered to 4,598 consumers of RTH
lasagne in six European countries (Republic of Ireland, France, Italy, Spain, Germany and Norway),
applying discrete choice experiments to estimate consumers’ willingness to pay for enhanced food
safety standards and highlight differences between countries.
Findings – Many similarities across countries emerged, as well as some differences. Consumers in
Europe are highly concerned with the authenticity of the meat in ready meals and strongly prefer to
know that ingredients are nationally sourced. Strong regional differences in price premiums exist for
enhanced food safety standards.
Originality/value – This research adds relevant insights in the analysis of consumers’ reaction to
food fraud, providing practical guidelines on the most appropriate practices that producers should
adopt and on the information to reduce food risk perception among consumers. This would prove
beneficial for the food processing industry and the European Union. The survey is based on a
representative sample of European consumers making this the largest cross-country study of this kind.
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We conduct the first empirical economic investigation of the decision to cheat by University students. We investigate student demand for essays, using hypothetical discrete choice experiments in conjunction with consequential Holt-Laury gambles to derive subjects risk preferences. Students stated willingness to participate in the essay market, and their valuation of purchased essays, vary with the characteristics of student and institutional environment. Risk preferring students, those working in a non-native language, and those believing they will attain a lower grade are willing to pay more. Purchase likelihoods and essay valuations decline as the probability of detection and associated penalty increase.
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This research examines the role of social context in ethical consumption, specifically, the extent to which anonymity and social control influence individuals' decisions to purchase organic and Fair Trade coffee. Our research design overcomes biases of prior research by combining framing and discrete choice experiments in a survey. We systematically vary coffee growing method (organic or not), import status (Fair Trade or not), flavor, and price across four social contexts that vary in degree of anonymity and normative social control. The social contexts are buying coffee online, in a large grocery store, in a small neighborhood shop, and for a meeting of a human rights group. Subjects comprise 1,103 German and American undergraduate students. We find that social context indeed influences subjects' ethical consumer decisions, especially in situations with low anonymity and high social control. In addition, gender, coffee buying, and subjective social norms trigger heterogeneity regarding stated ethical consumption and the effects of social context. These results suggest previous research has underestimated the relevance of social context for ethical consumption and overestimated altruistic motives of ethical consumers. Our study demonstrates the great potential of discrete choice experiments for the study of social action and decision making processes in sociology.
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En general, el análisis socioeconómico de los sistemas naturales no se contempla en los dominios de la ciencia natural. En este trabajo, sin embargo, se estima el cambio en el bienestar social por los efectos de la presión antrópica sobre el piedemonte mendocino vía la menor provisión de servicios ambientales. Para ello, se utiliza el método de los experimentos de elección discreta para inferir el valor social de tres servicios ambientales generados en las cuencas ubicadas al oeste del Gran Mendoza (riesgo aluvional, cobertura vegetal y recreación) y los costos de programas diseñados para mitigar la intensidad de dichos efectos. Un incremento del riesgo aluvional es el efecto de origen antrópico sobre el piedemonte mendocino que más preocupa a la población, seguido de una disminución de la cobertura vegetal y de la recreación. Se estimó que un incremento del riesgo aluvional en 1% equivale en pérdida de bienestar individual a un gasto, en promedio, de 24,13 pesos, en moneda de 2013, al año, cifra que es equivalente en términos de bienestar a una disminución de 6% de cobertura vegetal. Esta información puede ayudar a los hacedores de políticas, gestores de territorio y ecologistas a tener en cuenta las preferencias sociales en el diseño de sus programas y actividades.
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La sostenibilidad de los sistemas olivareros situados en zonas de pendiente y montaña (SMOPS) en Andalucía se encuentra actualmente amenazada por las elevadas tasas de abandono que afectan a estos sistemas productivos. Así, la consumación de este proceso de abandono, no sólo pondría en peligro a las propias explotaciones, sino a todo el conjunto de bienes y servicios no productivos y al patrimonio cultural generado por este sistema productivo. En este contexto, la búsqueda de alternativas políticas enfocadas a revertir este proceso se erige como una necesidad categórica en aras de garantizar en el largo plazo la sostenibilidad de los olivares de montaña. Esta tesis pretende hacer frente a esta necesidad a través de la construcción de un marco político alternativo para los SMOPS, que permita la integración simultánea de todas las dimensiones que pueden influir en su desarrollo; esto es: el marco político actual, principalmente determinado por la Política Agraria Común (PAC) de la Unión Europea (UE); las preferencias de la sociedad hacia la oferta de bienes y servicios públicos generados por los SMOPS; y las preferencias y voluntad de innovación hacia nuevos manejos y sistemas de gestión de los agricultores y propietarios de las explotaciones. Para ello, se emplea una metodología de investigación mixta, que abarca la realización de cuatro encuestas (personales y online) llevadas a cabo a los agentes o grupos de interés involucrados directa o indirectamente en la gestión de los SMOPS –ciudadanos, agricultores y propietarios y expertos-; una profunda revisión de las herramientas de política agroambiental actuales y posibles alternativas a las mismas; y el desarrollo de nuevas estrategias metodológicas para dotar de mayor precisión y fiabilidad las estimaciones obtenidas a partir del Método del Experimento de Elección (MEE) en el campo de la valoración medioambiental. En general, los resultados muestran que una estrategia de política agroambiental basada en la combinación de los Contratos Territoriales de Zona Rural (CTZR) y el manejo ecológico supondría una mejora en la sostenibilidad de los sistemas olivareros de montaña andaluces, que, al mismo tiempo, propiciaría una mejor consideración de las necesidades y demandas de los agentes implicados en su gestión. Asimismo, los hallazgos obtenidos en esta investigación demandan un cambio de paradigma en los actuales pagos agroambientales, que han de pasar de una estrategia basada en la implementación de acciones, a otra enfocada al logro de objetivos, la cual, en el caso del olivar, se podría centrar en el aumento del secuestro de carbono en el suelo. Desde un punto de vista metodológico, los resultados han contribuido notablemente a mejorar la fiabilidad y precisión de las conclusiones estimadas a partir del MEE, mediante el diseño de un novedoso proceso iterativo para detectar posibles comportamientos inconsistentes por parte de los entrevistados con respecto a su máxima Disposición al Pago (DAP) para lograr la situación considerada como “óptima” en los olivares ecológicos de montaña andaluces. En líneas generales, el actual marco institucional favorece la puesta en práctica de la mayoría de las estrategias propuestas en esta tesis; sin embargo son necesarios mayores esfuerzos para reconducir los actuales Pagos Agroambientales y Climáticos de la PAC, hacia una estrategia de política agroambiental adaptada a las necesidades y requisitos del territorio en el que se aplica, enfocada al logro de objetivos y que sea capaz de integrar y coordinar al conjunto de agentes y grupos de interés involucrados -directa o indirectamente- en la gestión de los olivares de montaña. En este contexto, se espera que la puesta en práctica de nuevas estructuras y acuerdos de gobernanza territorial juegue un importante papel en el desarrollo de una política agroambiental realmente adaptada a las necesidades de los sistemas olivareros de montaña andaluces. ABSTRACT The long-term sustainability of Andalusian sloping and mountainous olive production systems (SMOPS) is currently threatened by the high abandonment rates that affect these production systems. The effective occurrence of this abandonment process is indeed menacing not only farms themselves, but also the wide array of public goods and services provided by SMOPS and the cultural heritage held by this production system. The search of policy alternatives aimed at tackling this process is thus a central necessity. This thesis aims to undertake this necessity by building an alternative policy framework for SMOPS that simultaneously integrates the several dimensions that are susceptible to influence it, namely: the current policy framework, mainly determined by the European Union’s (EU) Common Agricultural Policy (CAP); the social preferences toward the supply of SMOPS’ public goods and services; and farmers’ preferences and willingness to innovate toward new management practices in their farms. For this purpose, we put into practice a mixed-method strategy that combines four face-to-face and online surveys carried out with SMOPS’ stakeholders -including citizens, farmers and experts-; in-depth analysis of current and alternative agrienvironmental policy (AEP) instruments; and the development of novel methodological approaches to advance toward more reliable Discrete Choice Experiment’s (DCE) outcomes in the field of environmental valuation. Overall, results show that a policy strategy based on the combination of Territorial Management Contracts (TMC) and organic management would further enhance Andalusian SMOPS’ sustainability by simultaneously taking into account stakeholders’ demands and needs. Findings also call for paradigm shift of the current action-oriented design of Agri-Environmental-Climate Schemes (AECS), toward a result-based approach, that in the case of olive orchards should particularly be focused on enhancing soil carbon sequestration. From a methodological perspective, results have contributed to improve the accuracy and feasibility of DCE outcomes by designing a novel and iterative procedure focused in ascertaining respondents’ inconsistent behaviour with respect to their stated maximum WTP for the attainment of an ideal situation to be achieved in organic Andalusian SMOPS. Generally, the present institutional framework favours the implementation of the main policy strategies proposed in this thesis, albeit further efforts are required to better conduct current CAP’s agri-environmental instruments toward a territorially targeted result-oriented strategy capable to integrate and coordinate the whole set of stakeholders involved in the management of SMOPS. In this regard, alternative governance structures and arrangements are expected to play a major role on the process of tackling SMOPS’ agri-environmental policy challenge.
GPs' implicit prioritization through clinical choices – evidence from three national health services
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Acknowledgments The authors are grateful for valuable comments and inputs from participants at a series of seminars and conferences as well as to our three anonymous referees.
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In the quest for a descriptive theory of decision-making, the rational actor model in economics imposes rather unrealistic expectations and abilities on human decision makers. The further we move from idealized scenarios, such as perfectly competitive markets, and ambitiously extend the reach of the theory to describe everyday decision making situations, the less sense these assumptions make. Behavioural economics has instead proposed models based on assumptions that are more psychologically realistic, with the aim of gaining more precision and descriptive power. Increased psychological realism, however, comes at the cost of a greater number of parameters and model complexity. Now there are a plethora of models, based on different assumptions, applicable in differing contextual settings, and selecting the right model to use tends to be an ad-hoc process. In this thesis, we develop optimal experimental design methods and evaluate different behavioral theories against evidence from lab and field experiments.
We look at evidence from controlled laboratory experiments. Subjects are presented with choices between monetary gambles or lotteries. Different decision-making theories evaluate the choices differently and would make distinct predictions about the subjects' choices. Theories whose predictions are inconsistent with the actual choices can be systematically eliminated. Behavioural theories can have multiple parameters requiring complex experimental designs with a very large number of possible choice tests. This imposes computational and economic constraints on using classical experimental design methods. We develop a methodology of adaptive tests: Bayesian Rapid Optimal Adaptive Designs (BROAD) that sequentially chooses the "most informative" test at each stage, and based on the response updates its posterior beliefs over the theories, which informs the next most informative test to run. BROAD utilizes the Equivalent Class Edge Cutting (EC2) criteria to select tests. We prove that the EC2 criteria is adaptively submodular, which allows us to prove theoretical guarantees against the Bayes-optimal testing sequence even in the presence of noisy responses. In simulated ground-truth experiments, we find that the EC2 criteria recovers the true hypotheses with significantly fewer tests than more widely used criteria such as Information Gain and Generalized Binary Search. We show, theoretically as well as experimentally, that surprisingly these popular criteria can perform poorly in the presence of noise, or subject errors. Furthermore, we use the adaptive submodular property of EC2 to implement an accelerated greedy version of BROAD which leads to orders of magnitude speedup over other methods.
We use BROAD to perform two experiments. First, we compare the main classes of theories for decision-making under risk, namely: expected value, prospect theory, constant relative risk aversion (CRRA) and moments models. Subjects are given an initial endowment, and sequentially presented choices between two lotteries, with the possibility of losses. The lotteries are selected using BROAD, and 57 subjects from Caltech and UCLA are incentivized by randomly realizing one of the lotteries chosen. Aggregate posterior probabilities over the theories show limited evidence in favour of CRRA and moments' models. Classifying the subjects into types showed that most subjects are described by prospect theory, followed by expected value. Adaptive experimental design raises the possibility that subjects could engage in strategic manipulation, i.e. subjects could mask their true preferences and choose differently in order to obtain more favourable tests in later rounds thereby increasing their payoffs. We pay close attention to this problem; strategic manipulation is ruled out since it is infeasible in practice, and also since we do not find any signatures of it in our data.
In the second experiment, we compare the main theories of time preference: exponential discounting, hyperbolic discounting, "present bias" models: quasi-hyperbolic (α, β) discounting and fixed cost discounting, and generalized-hyperbolic discounting. 40 subjects from UCLA were given choices between 2 options: a smaller but more immediate payoff versus a larger but later payoff. We found very limited evidence for present bias models and hyperbolic discounting, and most subjects were classified as generalized hyperbolic discounting types, followed by exponential discounting.
In these models the passage of time is linear. We instead consider a psychological model where the perception of time is subjective. We prove that when the biological (subjective) time is positively dependent, it gives rise to hyperbolic discounting and temporal choice inconsistency.
We also test the predictions of behavioral theories in the "wild". We pay attention to prospect theory, which emerged as the dominant theory in our lab experiments of risky choice. Loss aversion and reference dependence predicts that consumers will behave in a uniquely distinct way than the standard rational model predicts. Specifically, loss aversion predicts that when an item is being offered at a discount, the demand for it will be greater than that explained by its price elasticity. Even more importantly, when the item is no longer discounted, demand for its close substitute would increase excessively. We tested this prediction using a discrete choice model with loss-averse utility function on data from a large eCommerce retailer. Not only did we identify loss aversion, but we also found that the effect decreased with consumers' experience. We outline the policy implications that consumer loss aversion entails, and strategies for competitive pricing.
In future work, BROAD can be widely applicable for testing different behavioural models, e.g. in social preference and game theory, and in different contextual settings. Additional measurements beyond choice data, including biological measurements such as skin conductance, can be used to more rapidly eliminate hypothesis and speed up model comparison. Discrete choice models also provide a framework for testing behavioural models with field data, and encourage combined lab-field experiments.
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We estimate a carbon mitigation cost curve for the U.S. commercial sector based on econometric estimation of the responsiveness of fuel demand and equipment choices to energy price changes. The model econometrically estimates fuel demand conditional on fuel choice, which is characterized by a multinomial logit model. Separate estimation of end uses (e.g., heating, cooking) using the U.S. Commercial Buildings Energy Consumption Survey allows for exceptionally detailed estimation of price responsiveness disaggregated by end use and fuel type. We then construct aggregate long-run elasticities, by fuel type, through a series of simulations; own-price elasticities range from -0.9 for district heat services to -2.9 for fuel oil. The simulations form the basis of a marginal cost curve for carbon mitigation, which suggests that a price of $20 per ton of carbon would result in an 8% reduction in commercial carbon emissions, and a price of $100 per ton would result in a 28% reduction. © 2008 Elsevier B.V. All rights reserved.
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This paper reviews the main development of approaches to modelling urban public transit users’ route choice behaviour from 1960s to the present. The approaches reviewed include the early heuristic studies on finding the least cost transit route and all-or-nothing transit assignment, the bus common line problem and corresponding network representation methods, the disaggregate discrete choice models which are based on random utility maximization assumptions, the deterministic use equilibrium and stochastic user equilibrium transit assignment models, and the recent dynamic transit assignment models using either frequency or schedule based network formulation. In addition to reviewing past outcomes, this paper also gives an outlook into the possible future directions of modelling transit users’ route choice behaviour. Based on the comparison with the development of models for motorists’ route choice and traffic assignment problems in an urban road area, this paper points out that it is rewarding for transit route choice research to draw inspiration from the intellectual outcomes out of the road area. Particularly, in light of the recent advancement of modelling motorists’ complex road route choice behaviour, this paper advocates that the modelling practice of transit users’ route choice should further explore the complexities of the problem.
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Public transport is one of the key promoters of sustainable urban transport. To encourage and increase public transport patronage it is important to investigate the route choice behaviours of urban public transit users. This chapter reviews the main developments of modelling urban public transit users’ route choice behaviours in a historical perspective, from the 1960s to the present time. The approaches re- viewed for this study include the early heuristic studies on finding the least-cost transit route and all-or- nothing transit assignment, the bus common lines problem, the disaggregate discrete choice models, the deterministic and stochastic user equilibrium transit assignment models, and the recent dynamic transit assignment models. This chapter also provides an outlook for the future directions of modelling transit users’ route choice behaviours. Through the comparison with the development of models for motorists’ route choice and traffic assignment problems, this chapter advocates that transit route choice research should draw inspiration from the research outcomes from the road area, and that the modelling practice of transit users’ route choice should further explore the behavioural complexities.
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Statisticians along with other scientists have made significant computational advances that enable the estimation of formerly complex statistical models. The Bayesian inference framework combined with Markov chain Monte Carlo estimation methods such as the Gibbs sampler enable the estimation of discrete choice models such as the multinomial logit (MNL) model. MNL models are frequently applied in transportation research to model choice outcomes such as mode, destination, or route choices or to model categorical outcomes such as crash outcomes. Recent developments allow for the modification of the potentially limiting assumptions of MNL such as the independence from irrelevant alternatives (IIA) property. However, relatively little transportation-related research has focused on Bayesian MNL models, the tractability of which is of great value to researchers and practitioners alike. This paper addresses MNL model specification issues in the Bayesian framework, such as the value of including prior information on parameters, allowing for nonlinear covariate effects, and extensions to random parameter models, so changing the usual limiting IIA assumption. This paper also provides an example that demonstrates, using route-choice data, the considerable potential of the Bayesian MNL approach with many transportation applications. This paper then concludes with a discussion of the pros and cons of this Bayesian approach and identifies when its application is worthwhile
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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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This research improved the measurement of public transport accessibility by capturing; travellers' behaviour; diversity of public transport mode; and the subjectivity of travellers' decision in the complex transport networks. The results of this research not only highlighted the importance of considering public transport network characteristics but also, revealed the impact of public transport diversity in the modelling of public transport accessibility. The research developed a hybrid discrete choice model with a nested logit structure to treat the correlation among the public transport mode choices and, a logit correction factor to rectify the correlation among the stop choices.
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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.
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This paper introduces the discrete choice model-paradigm of Random Regret Minimization (RRM) to the field of environmental and resource economics. The RRM-approach has been very recently developed in the context of travel demand modelling and presents a tractable, regret-based alternative to the dominant choice-modelling paradigm based on Random Utility Maximization-theory (RUM-theory). We highlight how RRM-based models provide closed form, logit-type formulations for choice probabilities that allow for capturing semi-compensatory behaviour and choice set-composition effects while being equally parsimonious as their utilitarian counterparts. Using data from a Stated Choice-experiment aimed at identifying valuations of characteristics of nature parks, we compare RRM-based models and RUM-based models in terms of parameter estimates, goodness of fit, elasticities and consequential policy implications.