948 resultados para Discrete Choice Experiment
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In order to achieve to minimize car-based trips, transport planners have been particularly interested in understanding the factors that explain modal choices. In the transport modelling literature there has been an increasing awareness that socioeconomic attributes and quantitative variables are not sufficient to characterize travelers and forecast their travel behavior. Recent studies have also recognized that users? social interactions and land use patterns influence travel behavior, especially when changes to transport systems are introduced, but links between international and Spanish perspectives are rarely deal. In this paper, factorial and path analyses through a Multiple-Indicator Multiple-Cause (MIMIC) model are used to understand and describe the relationship between the different psychological and environmental constructs with social influence and socioeconomic variables. The MIMIC model generates Latent Variables (LVs) to be incorporated sequentially into Discrete Choice Models (DCM) where the levels of service and cost attributes of travel modes are also included directly to measure the effect of the transport policies that have been introduced in Madrid during the last three years in the context of the economic crisis. The data used for this paper are collected from a two panel smartphone-based survey (n=255 and 190 respondents, respectively) of Madrid.
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In order to minimize car-based trips, transport planners have been particularly interested in understanding the factors that explain modal choices. Transport modelling literature has been increasingly aware that socioeconomic attributes and quantitative variables are not sufficient to characterize travelers and forecast their travel behavior. Recent studies have also recognized that users’ social interactions and land use patterns influence travel behavior, especially when changes to transport systems are introduced; but links between international and Spanish perspectives are rarely dealt with. The overall objective of the thesis is to develop a stepped methodology that integrate diverse perspectives to evaluate the willingness to change patterns of urban mobility in Madrid, based on four steps: (1st) analysis of causal relationships between both objective and subjective personal variables, and travel behavior to capture pro-car and pro-public transport intentions; (2nd) exploring the potential influence of individual trip characteristics and social influence variables on transport mode choice; (3rd) identifying built environment dimensions on travel behavior; and (4th) exploring the potential influence on transport mode choice of extrinsic characteristics of individual trip using panel data, land use variables using spatial characteristics and social influence variables. The data used for this thesis have been collected from a two panel smartphone-based survey (n=255 and 190 respondents, respectively) carried out in Madrid. Although the steps above are mainly methodological, the application to the area of Madrid allows deriving important results that can be directly used to forecast travel demand and to evaluate the benefits of specific policies that might be implemented in the area. The results demonstrated, respectively: (1st) transport policy actions are more likely to be effective when pro-car intention has been disrupted first; (2nd) the consideration of “helped” and “voluntary” users as tested here could have a positive and negative impact, respectively, on the use of public transport; (3rd) the importance of density, design, diversity and accessibility underlying dimensions responsible for land use variables; and (4th) there are clearly different types of combinations of social interactions, land use and time frame on travel behavior studies. Finally, with the objective to study the impact of demand measures to change urban mobility behavior, those previous results have been considered in a unique way, a hybrid discrete choice model has been used on a 5th step. Then it can be concluded that urban mobility behavior is not only ruled by the maximum utility criterion, but also by a strong psychological-environment concept, developed without the mediation of cognitive processes during choice, i.e., many people using public transport on their way to work do not do it for utilitarian reasons, but because no other choice is available. Regarding built environment dimensions, the more diversity place of residence, the more difficult the use of public transport or walking.
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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.
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El papel del precio en el sector turístico es especialmente complejo debido a la heterogeneidad existente entre los turistas y, por tanto, a las distintas sensibilidades al precio que muestran. En este sentido, el presente trabajo propone la utilización de modelos de elección discreta para identificar las sensibilidades individuales, turista a turista, y, a continuación, utilizar dichas estimaciones como punto de partida para detectar grupos de turistas con una respuesta similar a los precios. La aplicación empírica realizada en el contexto de la Comunidad Valenciana permite detectar tres segmentos: turistas de precio bajo, turistas indiferentes al precio y turistas de precio alto.
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We model and test the relationship between social and commercial entrepreneurship drawing on social capital theory. We propose that the country prevalence rate of social entrepreneurship is an indicator of constructible nation-level social capital and enhances the likelihood of individual commercial entry. We further posit that both social and commercial entrepreneurial entry is facilitated by certain formal institutions, namely strong property rights and (low) government activism, albeit the latter impacts each of these types of entrepreneurship differently. We apply bivariate discrete choice multilevel modeling to population-representative samples in 47 countries and find support for these hypotheses. © 2013 Baylor University.
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Expected damages of environmental risks depend both on their intensities and probabilities. There is very little control over probabilities of climate related disasters such as hurricanes. Therefore, researchers of social science are interested identifying preparation and mitigation measures that build human resilience to disasters and avoid serious loss. Conversely, environmental degradation, which is a process through which the natural environment is compromised in some way, has been accelerated by human activities. As scientists are finding effective ways on how to prevent and reduce pollution, the society often fails to adopt these effective preventive methods. Researchers of psychological and contextual characterization offer specific lessons for policy interventions that encourage human efforts to reduce pollution. This dissertation addresses four discussions of effective policy regimes encouraging pro-environmental preference in consumption and production, and promoting risk mitigation behavior in the face of natural hazards. The first essay describes how the speed of adoption of environment friendly technologies is driven largely by consumers' preferences and their learning dynamics rather than producers' choice. The second essay is an empirical analysis of a choice experiment to understand preferences for energy efficient investments. The empirical analysis suggests that subjects tend to increase energy efficient investment when they pay a pollution tax proportional to the total expenditure on energy consumption. However, investments in energy efficiency seem to be crowded out when subjects have the option to buy health insurance to cover pollution related health risks. In context of hurricane risk mitigation and in evidence of recently adopted My Safe Florida Home (MSFH) program by the State of Florida, the third essay shows that households with home insurance, prior experience with damages, and with a higher sense of vulnerability to be affected by hurricanes are more likely to allow home inspection to seek mitigation information. The fourth essay evaluates the impact of utility disruption on household well being based on the responses of a household-level phone survey in the wake of hurricane Wilma. Findings highlight the need for significant investment to enhance the capacity of rapid utility restoration after a hurricane event in the context of South Florida.
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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This dissertation consists of three separate essays on job search and labor market dynamics. In the first essay, “The Impact of Labor Market Conditions on Job Creation: Evidence from Firm Level Data”, I study how much changes in labor market conditions reduce employment fluctuations over the business cycle. Changes in labor market conditions make hiring more expensive during expansions and cheaper during recessions, creating counter-cyclical incentives for job creation. I estimate firm level elasticities of labor demand with respect to changes in labor market conditions, considering two margins: changes in labor market tightness and changes in wages. Using employer-employee matched data from Brazil, I find that all firms are more sensitive to changes in wages rather than labor market tightness, and there is substantial heterogeneity in labor demand elasticity across regions. Based on these results, I demonstrate that changes in labor market conditions reduce the variance of employment growth over the business cycle by 20% in a median region, and this effect is equally driven by changes along each margin. Moreover, I show that the magnitude of the effect of labor market conditions on employment growth can be significantly affected by economic policy. In particular, I document that the rapid growth of the national minimum wages in Brazil in 1997-2010 amplified the impact of the change in labor market conditions during local expansions and diminished this impact during local recessions.
In the second essay, “A Framework for Estimating Persistence of Local Labor
Demand Shocks”, I propose a decomposition which allows me to study the persistence of local labor demand shocks. Persistence of labor demand shocks varies across industries, and the incidence of shocks in a region depends on the regional industrial composition. As a result, less diverse regions are more likely to experience deeper shocks, but not necessarily more long lasting shocks. Building on this idea, I propose a decomposition of local labor demand shocks into idiosyncratic location shocks and nationwide industry shocks and estimate the variance and the persistence of these shocks using the Quarterly Census of Employment and Wages (QCEW) in 1990-2013.
In the third essay, “Conditional Choice Probability Estimation of Continuous- Time Job Search Models”, co-authored with Peter Arcidiacono and Arnaud Maurel, we propose a novel, computationally feasible method of estimating non-stationary job search models. Non-stationary job search models arise in many applications, where policy change can be anticipated by the workers. The most prominent example of such policy is the expiration of unemployment benefits. However, estimating these models still poses a considerable computational challenge, because of the need to solve a differential equation numerically at each step of the optimization routine. We overcome this challenge by adopting conditional choice probability methods, widely used in dynamic discrete choice literature, to job search models and show how the hazard rate out of unemployment and the distribution of the accepted wages, which can be estimated in many datasets, can be used to infer the value of unemployment. We demonstrate how to apply our method by analyzing the effect of the unemployment benefit expiration on duration of unemployment using the data from the Survey of Income and Program Participation (SIPP) in 1996-2007.
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My dissertation has three chapters which develop and apply microeconometric tech- niques to empirically relevant problems. All the chapters examines the robustness issues (e.g., measurement error and model misspecification) in the econometric anal- ysis. The first chapter studies the identifying power of an instrumental variable in the nonparametric heterogeneous treatment effect framework when a binary treat- ment variable is mismeasured and endogenous. I characterize the sharp identified set for the local average treatment effect under the following two assumptions: (1) the exclusion restriction of an instrument and (2) deterministic monotonicity of the true treatment variable in the instrument. The identification strategy allows for general measurement error. Notably, (i) the measurement error is nonclassical, (ii) it can be endogenous, and (iii) no assumptions are imposed on the marginal distribution of the measurement error, so that I do not need to assume the accuracy of the measure- ment. Based on the partial identification result, I provide a consistent confidence interval for the local average treatment effect with uniformly valid size control. I also show that the identification strategy can incorporate repeated measurements to narrow the identified set, even if the repeated measurements themselves are endoge- nous. Using the the National Longitudinal Study of the High School Class of 1972, I demonstrate that my new methodology can produce nontrivial bounds for the return to college attendance when attendance is mismeasured and endogenous.
The second chapter, which is a part of a coauthored project with Federico Bugni, considers the problem of inference in dynamic discrete choice problems when the structural model is locally misspecified. We consider two popular classes of estimators for dynamic discrete choice models: K-step maximum likelihood estimators (K-ML) and K-step minimum distance estimators (K-MD), where K denotes the number of policy iterations employed in the estimation problem. These estimator classes include popular estimators such as Rust (1987)’s nested fixed point estimator, Hotz and Miller (1993)’s conditional choice probability estimator, Aguirregabiria and Mira (2002)’s nested algorithm estimator, and Pesendorfer and Schmidt-Dengler (2008)’s least squares estimator. We derive and compare the asymptotic distributions of K- ML and K-MD estimators when the model is arbitrarily locally misspecified and we obtain three main results. In the absence of misspecification, Aguirregabiria and Mira (2002) show that all K-ML estimators are asymptotically equivalent regardless of the choice of K. Our first result shows that this finding extends to a locally misspecified model, regardless of the degree of local misspecification. As a second result, we show that an analogous result holds for all K-MD estimators, i.e., all K- MD estimator are asymptotically equivalent regardless of the choice of K. Our third and final result is to compare K-MD and K-ML estimators in terms of asymptotic mean squared error. Under local misspecification, the optimally weighted K-MD estimator depends on the unknown asymptotic bias and is no longer feasible. In turn, feasible K-MD estimators could have an asymptotic mean squared error that is higher or lower than that of the K-ML estimators. To demonstrate the relevance of our asymptotic analysis, we illustrate our findings using in a simulation exercise based on a misspecified version of Rust (1987) bus engine problem.
The last chapter investigates the causal effect of the Omnibus Budget Reconcil- iation Act of 1993, which caused the biggest change to the EITC in its history, on unemployment and labor force participation among single mothers. Unemployment and labor force participation are difficult to define for a few reasons, for example, be- cause of marginally attached workers. Instead of searching for the unique definition for each of these two concepts, this chapter bounds unemployment and labor force participation by observable variables and, as a result, considers various competing definitions of these two concepts simultaneously. This bounding strategy leads to partial identification of the treatment effect. The inference results depend on the construction of the bounds, but they imply positive effect on labor force participa- tion and negligible effect on unemployment. The results imply that the difference- in-difference result based on the BLS definition of unemployment can be misleading
due to misclassification of unemployment.
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In dieser Studie geht es darum, ein umfassendes Bild bezüglich der Konsumenteneinstellungen, Präferenzen und Zahlungsbereitschaften für ökologisch produzierte Lebensmittel und Lebensmittel verschiedener Herkünfte in Deutschland zu erhalten. Obwohl die regionale Herkunft von Lebensmitteln nicht offiziell und einheitlich geregelt ist und keiner Zertifizierung unterliegt wie die ökologische Produktion von Lebensmitteln, zeigen nationale und internationale Studien gleichermaßen, dass Konsumenten bereit sind, mehr für regionale als für ökologisch produzierte Lebensmittel zu bezahlen. Zur Erreichung des Forschungsziels wurde ein Kaufexperiment in Kombination mit einer Konsumentenbefragung, bestehend aus Fragen zum generellen Einkaufsverhalten, zu Einstellungen gegenüber regionalen und ökologisch produzierten Lebensmitteln und zu soziodemographischen Informationen durchgeführt. Im Kaufexperiment wurden die Attribute Produktherkunft, Produktionsweise und Preis anhand vier verschiedener Produkte (Äpfel, Butter, Mehl und Steaks) untersucht. Die Befragung, einschließlich des Experimentes, war durch Interviewer eines Marktforschungsinstituts initiiert, computergestützt und von den Konsumenten selbständig zu erledigen. Das Ziel war es 80 Konsumenten in jedem der acht Befragungsorte in verschiedenen Regionen Deutschlands zu befragen. Zur Auswertung des Experiments wurden RPL-Modell geschätzt, die die Konsumentenpräferenzen für die zu untersuchenden Produktattribute aufzeigen und die Berechnung von Zahlungsbereitschaften ermöglichen. Für die Gesamtheit der Konsumenten war die regionale Herkunft von Lebensmitteln wichtiger als die ökologische Produktion. Außerdem wurden Produktalternativen, die aus der Region stammen, immer stärker präferiert als Produkte aus Deutschland, aus einem Nachbarland und einem außereuropäischen Land. Weiterhin zeigte die Studie, dass Konsumentenpräferenzen produkt- und regionsspezifisch sind. Folglich wird empfohlen, in zukünftigen Studien unterschiedlich Produkte bzw. Produktgruppen und Konsumenten verschiedener Regionen einzubeziehen. Die zunehmenden Präferenzen und Zahlungsbereitschaften der Konsumenten für regionale Lebensmittel deuteten sowohl in dieser Dissertation als auch in vielen anderen nationalen und internationalen Studien darauf hin, dass es ein großes Potential für einen regionalen Lebensmittelmarkt gibt. Aus diesem Grund wird Produzenten und Vermarktern von ökologischen sowie konventionellen Produkten empfohlen, verstärkt in die Entwicklung von regionalen Versorgungsketten zu investieren.
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Este artículo de investigación científica y tecnológica estudia la percepción de seguridad en el uso de puentes peatonales, empleando un enfoque sustentado en dos campos principales: el microeconómico y el psicológico. El trabajo hace la estimación simultánea de un modelo híbrido de elección y variables latentes con datos de una encuesta de preferencias declaradas, encontrando mejor ajuste que un modelo mixto de referencia, lo que indica que la percepción de seguridad determina el comportamiento de los peatones cuando se enfrentan a la decisión de usar o no un puente peatonal. Se encontró que el sexo, la edad y el nivel de estudios son atributos que inciden en la percepción de seguridad. El modelo calibrado sugiere varias estrategias para aumentar el uso de puentes peatonales que son discutidas, encontrando que el uso de barreras ocasiona una pérdida de utilidad, en los peatones, que debería ser estudiada como extensión del presente trabajo.
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This dissertation proposes statistical methods to formulate, estimate and apply complex transportation models. Two main problems are part of the analyses conducted and presented in this dissertation. The first method solves an econometric problem and is concerned with the joint estimation of models that contain both discrete and continuous decision variables. The use of ordered models along with a regression is proposed and their effectiveness is evaluated with respect to unordered models. Procedure to calculate and optimize the log-likelihood functions of both discrete-continuous approaches are derived, and difficulties associated with the estimation of unordered models explained. Numerical approximation methods based on the Genz algortithm are implemented in order to solve the multidimensional integral associated with the unordered modeling structure. The problems deriving from the lack of smoothness of the probit model around the maximum of the log-likelihood function, which makes the optimization and the calculation of standard deviations very difficult, are carefully analyzed. A methodology to perform out-of-sample validation in the context of a joint model is proposed. Comprehensive numerical experiments have been conducted on both simulated and real data. In particular, the discrete-continuous models are estimated and applied to vehicle ownership and use models on data extracted from the 2009 National Household Travel Survey. The second part of this work offers a comprehensive statistical analysis of free-flow speed distribution; the method is applied to data collected on a sample of roads in Italy. A linear mixed model that includes speed quantiles in its predictors is estimated. Results show that there is no road effect in the analysis of free-flow speeds, which is particularly important for model transferability. A very general framework to predict random effects with few observations and incomplete access to model covariates is formulated and applied to predict the distribution of free-flow speed quantiles. The speed distribution of most road sections is successfully predicted; jack-knife estimates are calculated and used to explain why some sections are poorly predicted. Eventually, this work contributes to the literature in transportation modeling by proposing econometric model formulations for discrete-continuous variables, more efficient methods for the calculation of multivariate normal probabilities, and random effects models for free-flow speed estimation that takes into account the survey design. All methods are rigorously validated on both real and simulated data.
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This dissertation investigates customer behavior modeling in service outsourcing and revenue management in the service sector (i.e., airline and hotel industries). In particular, it focuses on a common theme of improving firms’ strategic decisions through the understanding of customer preferences. Decisions concerning degrees of outsourcing, such as firms’ capacity choices, are important to performance outcomes. These choices are especially important in high-customer-contact services (e.g., airline industry) because of the characteristics of services: simultaneity of consumption and production, and intangibility and perishability of the offering. Essay 1 estimates how outsourcing affects customer choices and market share in the airline industry, and consequently the revenue implications from outsourcing. However, outsourcing decisions are typically endogenous. A firm may choose whether to outsource or not based on what a firm expects to be the best outcome. Essay 2 contributes to the literature by proposing a structural model which could capture a firm’s profit-maximizing decision-making behavior in a market. This makes possible the prediction of consequences (i.e., performance outcomes) of future strategic moves. Another emerging area in service operations management is revenue management. Choice-based revenue systems incorporate discrete choice models into traditional revenue management algorithms. To successfully implement a choice-based revenue system, it is necessary to estimate customer preferences as a valid input to optimization algorithms. The third essay investigates how to estimate customer preferences when part of the market is consistently unobserved. This issue is especially prominent in choice-based revenue management systems. Normally a firm only has its own observed purchases, while those customers who purchase from competitors or do not make purchases are unobserved. Most current estimation procedures depend on unrealistic assumptions about customer arriving. This study proposes a new estimation methodology, which does not require any prior knowledge about the customer arrival process and allows for arbitrary demand distributions. Compared with previous methods, this model performs superior when the true demand is highly variable.
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Tese (doutorado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Civil e Ambiental, 2016.
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Doutoramento em Engenharia Agronómica - Instituto Superior de Agronomia - UL