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Boccara, Bruno 1956. "Modelling choice set formation in discrete choice models." Thesis, Massachusetts Institute of Technology, 1989. http://hdl.handle.net/1721.1/14324.
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Bonnet, Odran. "Individual housing choices and aggregate housing prices : discrete choice models revisited with matching models." Thesis, Paris, Institut d'études politiques, 2018. http://www.theses.fr/2018IEPP0010.
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Le premier chapitre, écrit conjointement avec Alfred Galichon, Keith O'Hara et Matthew Shum, montre l'équivalence entre les modèles de choix discrets et les modèles d'appariements. Cette équivalence permet l'estimation efficace, par des algorithmes d'appariement, de modèles qui étaient jusqu'à présent réputés comme difficile à estimer dans la littérature. Le deuxième chapitre, écrit conjointement avec Mathilde Poulhès, s'appuie sur les résultats du premier pour estimer le consentement marginal à payer des agents pour différentes caractéristiques du logement et du quartier à Paris. Il introduit une nouvelle procédure d'estimation basée sur le modèle de pures caractéristiques. Grâce à un riche jeu de données sur les achats de logements à Paris, nous montrons que le revenu moyen du voisinage et le niveau de criminalité sont de puissants déterminants du choix du quartier pour tous les types d'acheteurs, que l'accessibilité à l'emploi est également un facteur déterminant pour les ménages comptant plus d'une personne, et que la qualité de l'école du secteur joue un rôle primordial pour les ménages avec enfants. Le troisième chapitre, écrit conjointement avec Guillaume Chapelle, Alain Trannoy et Etienne Wasmer, montre que la croissance récente du ratio patrimoine sur revenu est due uniquement à l'augmentation du prix des logements, et plus précisément à l'augmentation du prix d'un facteur fixe de production: la terre. Nous montrons ensuite qu'un système de taxation du patrimoine doit taxer le facteur fixe qu'est la terre à des fins de redistribution et non le capital productif pour ne pas décourager l'investissementThe first two of the three chapters of this thesis examine the identification and the estimation of discrete choice models. The first chapter proves the equivalence between matching models and discrete choice models, and draws the consequences in terms of identification and estimation. The second chapter builds on the results of the first, and uses matching algorithms to estimate the marginal willingness to pay of households for various housing and neighborhood characteristics in Paris (such as school performance, crime level, distance to employment areas). The third chapter deals with another topic: it first shows that the recent rise in the capital-income ratio highlighted by Thomas Piketty in his book is due to the rise in housing prices, and it then explores the consequences in terms of wealth distribution
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Lindberg, Per Olov. "Contributions to Probabilistic Discrete Choice." Doctoral thesis, KTH, Transport- och lokaliseringsanalys, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-95402.
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Han, Bijun. "Analyzing car ownership and route choices using discrete choice models." Doctoral thesis, KTH, Infrastructure and Planning, 2001. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-3215.
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This thesis consists of two parts. The first part analyzesthe accessibility, generation and license holding effects incar ownership models. The second part develops a route choicemodeling framework with an attempt to address the differencesin drivers' route choice behavior. These two parts of work areboth based on the discrete choice theory - the car ownershipmodels are built up on the standard logit model, whereas theroute choice models are formulated in a mixed logit form.
The study result of the first part shows that measuring theaccessibility by the monetary inclusive value reasonably wellcaptures the mechanism of the accessibility impact. Otheraccessibility proxies such as the parking costs, parking typeand house type are correlated with the accessibility but not toa great extent. Both young and old households are less likelyto have a car. The reduction of the propensity to own a car issignificant for households with average birth year before 1920,whereas this reduction is moderate for households with birthyear between 1920 and 1945. It is also demonstrated thatdriving license holding choice is conditional on the carownership level choice, and that these two choices need to bemodeled in a dynamic framework.
The second part of the work investigates the performance ofthe mixed logit model using both simulated data and empiricalroute switching data. The empirical study mainly focused on theimpacts of information and incident related factors on drivers'route switching behavior.
The result shows that using mixed logit gives a significantimprovement in model performance as well as a more sensitiveexplanation of drivers' decision-making behavior. For apopulation with greatly varying tastes, simply using thestandard logit model to analyze its behavior can yield veryunrealistic results. However, care must be taken when settingthe number of random draws for simulating the choiceprobability of the mixed logit model in order to get reliableestimates.
The empirical results demonstrate that incident relatedfactors such as delay and information reliability havesignificant impacts on drivers' route switching, where themagnitude of the response to the change in the delay is shownto vary significantly between individuals. Other factors, suchas confidence in the estimated delay, gender, frequency of cardriving and attitude towards congestion, also make majorcontributions. In addition, it is found that individual's routeswitching behavior may differ depending on the purpose of thetrip and when the choice is made, i.e. pre-trip oren-route.
Keywords: car ownership, accessibility, logit model,route choice, heterogeneity, mixed logit model
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Tapley, Nigel. "Nonlinearities in discrete choice attributes : a study of transport-related choices." Thesis, University of Leeds, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.496518.
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Lukban, Albert. "Discrete choice modelling in conjoint analysis." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape11/PQDD_0005/MQ44211.pdf.
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Lukban, Albert. "Discrete choice modelling in conjoint analysis." Thesis, McGill University, 1997. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=20582.
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Strategic planning is not only necessary in today's global economy where markets are becoming more susceptible to international competition, it is vital. The foresight of market reactions can lead to a competitive advantage. Market share losses can be minimized (and market share gains maximized) with the knowledge obtained from primary marketing research involving a stated preference study to examine consumer behaviour. Before launching a new product or providing a service, discrete choice analysis can empower strategic planners, managers and marketers with a tool which aids in optimizing products and services for a potential market with the end of maximizing sales and services.Discrete choice analysis is a tool to understand human choice behaviour. It is employed for statistical inference on a model of choice behaviour from data obtained by sampling from a population of decision makers. This thesis gives an overview of the basic concepts of conjoint analysis which addresses discrete choice analysis for strategic product and service planning. The statistical model specification, the multinomial logit, is derived assuming that decision makers follow a choice rule called utility maximization, where these random utilities are Gumbel distributed. The model is applied to a stated preference study in which environmentally friendly vehicles are presented as possible vehicle choices.
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Nagel, Herbert, and Reinhold Hatzinger. "Diagnostics in some Discrete Choice Models." Department of Statistics and Mathematics, WU Vienna University of Economics and Business, 1990. http://epub.wu.ac.at/506/1/document.pdf.
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Discrete choice models form a class of models widely used in econometrics for modelling the individual choice from a finite set of alternatives. The most widely used model is the multinomial logit model, implicitly assuming independence of irrelevant alternatives. A generalization is the nested multinomial logit model, relaxing this strong assurnp tion. Viewing both models as nonlinear regression models a set of diagnostics is derived. This includes a hat matrix, measures of leverage, influence and residuals and an approximation to the parameters for case deletion. In an example for the multinomid logit model a good performance of these diagnostics is observed and the parameter approximation by the proposed formula is better than a one step Newton-Raphson procedure. In an example for the nested logit model a constructed outlier with high influence is revealed by the measures of leverage and residual, but the parameter approximation is insufficient. (author's abstract)Series: Forschungsberichte / Institut für Statistik
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Meginnis, Keila. "Strategic bias in discrete choice experiments." Thesis, University of Manchester, 2018. https://www.research.manchester.ac.uk/portal/en/theses/strategic-bias-in-discrete-choice-experiments(1a1407ed-c026-4d27-b336-3dfc69dba8d9).html.
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This thesis investigates the problem of strategic bias in discrete choice experiments using three approaches: simulations, a laboratory experiment, and a field experiment. Carson et al. (2007) state that choice experiments must be seen as consequential by respondents in order to provide useful information about preferences. To meet this requirement, surveys must exhibit two characteristics. First, the survey must be seen as influencing the provision of the good/service and second, the respondent must care about that provision outcome. However, the notion that the survey must be consequential, may also induce respondents to misrepresent their preferences in order to influence the decision making process. This is known as strategic bias. Using simulations, laboratory experiments and field studies, this thesis will investigate strategic bias in discrete choice experiments. To do so, we must assume that the discrete choice experiment will be used to influence a provisioning decision. Strategic behaviour is conceptualised as changes in choice behaviour that occurs when respondents have information on the relative likelihood of the provision outcomes. This information causes changes in choice strategies. In Chapter 1 we create a simulated environment that replicates when respondents may have incentive to bias their choice strategies. We explore the ramifications of biased choices through simulations. In Chapter 2 we replicate that environment in an induced value laboratory experiment. We present respondents with three possible `provision' outcomes, each of which was defined in terms of levels of arbitrary attributes. Each possible provision outcome was associated with a monetary payout to the respondent, therefore we know a respondents preference ordering over the possible outcomes. The monetary payouts varied such that there was a clear ranking between possible outcomes, such that respondents had a first, second and worst provision outcome. Respondents then completed a discrete choice experiment (DCE) that would decide which provision outcome is paid out. A respondent's payout was determined by which of the competing provision outcomes had the highest choice probability, based on their individual choice behaviour. As this was an unlabelled choice experiment, participants had to use choice strategies based on attributes in order to influence the provision outcome they hoped would get paid out. To introduce strategic bias, respondents were given information on the likelihood of the provision contenders being implemented. This information would affect which provision outcome would be chosen and hence paid out. In this respect, a respondent has incentive to act strategically if they believe (i) their first best outcome will lose in the final provision decision; (ii) their worst outcome is most likely to be paid out; and (iii) their choices can influence the provision to deliver the second best outcome. Strategic respondents are therefore those who chose to target their second best outcome to avoid worst outcome, which respondents are told is the most likely. We find approximately 27% of respondents exhibit strategic behaviour in the laboratory choice experiment. In Chapter 3 we implement the approach in the field. We administered a choice experiment about tidal energy development in Puget Sound, Washington. Local opposition to tidal energy has been strong in the past, with no project ever coming to fruition. As a result, we envision respondents to have strong sentiments towards the location of tidal energy development and potentially have incentives to behave strategically when location is a factor in their decision making process. We presented respondents with three possible site locations for tidal energy development in Puget Sound. Respondents can use the choice experiment as a means to reveal which site location they prefer (if any). As this was an unlabelled experiment, respondents must use choice strategies based on the attributes of tidal development in order to reveal preference for location. In order to identify strategic behaviour, rather than simply differences in preferences, half way through the DCE, we provide respondents with additional information on the likelihood of each of the tidal energy sites being chosen. Respondents whose first best location is revealed as the site least likely to be chosen, may seek to secure their second best location. Strategic bias is when respondents are trying to push preference away from their worst location site, when the set of provision outcomes has gone from three to two possible sites. Despite the complexity of the task, there is evidence of behavioural changes when the final set of possible locations changes. We find that 25% of respondents exhibit signs of strategic behaviour. These respondents are more likely to 1) believe their survey responses will affect future policy; and, 2) prefer the site which was revealed to be the unlikely site location and thus have strong motive to push development away from their worst location, and towards a second best site.
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Graham, Justin W. "School choice : a discrete optimization approach." Thesis, Massachusetts Institute of Technology, 2020. https://hdl.handle.net/1721.1/127294.
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Thesis: S.M., Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, May, 2020Cataloged from PDF version of thesis.
Includes bibliographical references (pages 32-34).
An equitable and flexible mechanism for assigning students to schools is a major concern for many school districts. The school a student attends dramatically impacts the quality of education, access to resources, family and neighborhood cohesion, and transportation costs. Facing this intricate optimization problem, school districts often utilize to stable-matching techniques which only produce stable matchings that do not incorporate these different objectives; this can be expensive and inequitable. We present a new optimization model for the Stable Matching (SM) school choice problem which relies on an algorithm we call Price-Costs-Flexibility-and- Fairness (PCF2). Our model leverages techniques to balance competing objectives using mixed-integer optimization methods. We explore the trade-offs between stability, costs, and preferences and show that, surprisingly, there are stable solutions that decrease transportation costs by 8-17% over the Gale-Shapley solution.
by Justin W. Graham.
S.M.
S.M. Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center
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Beville, S. T. "Modelling differences in angler choice behaviour with advanced discrete choice models." Lincoln University, 2009. http://hdl.handle.net/10182/2332.
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New Zealand is internationally renowned for having some of the finest and most challenging trout fishing in the world. However, due to continuing development and angling pressure many fishing sites are showing signs of environmental degradation and over fishing. This trend is almost certain to continue into the future given continued population and economic growth. Understanding the determinants of site choice, preference heterogeneity and anglers’ substitution patterns is fundamentally important to fishery managers who have the difficult task of maintaining quality angling experiences on a number of fishing sites, managing angling pressure and maintaining license sales. Recent advances in simulation techniques and computational power have improved the capability of discrete choice models to reveal preference heterogeneity and complex substitution patterns among individuals. This thesis applies and evaluates a number of state-of-the-art discrete choice models to study angler site choice in New Zealand. Recreation specialisation theory is integrated into the analysis to enhance the behavioural representation of the statistical models. A suite of models is presented throughout the empirical portion of this thesis. These models demonstrate different ways and degrees of explaining preference heterogeneity as well as identifying anglers’ substitution patterns. The results show that North Canterbury anglers’ preferences vary considerably. Resource disturbances such as riparian margin erosion, reduced water visibility and declines in catch rates can cause significant declines in angler use of affected sites, and at the same time non-proportional increases in the use of unaffected sites. Recreation specialisation is found to be closely related to the types of fishing site conditions, experiences and regulations preferred by anglers. Anglers’ preference intensities for fishing site attributes, such as catch rates, vary across different types of fishing sites. This location specific preference heterogeneity is found to be related to specialisation. Overall, the empirical findings indicate that conventional approaches to modelling angler site choice which do not incorporate a strong understanding of angler preference heterogeneity can lead to poorly representative models and suboptimal management and policy outcomes.
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Norets, Andriy. "Bayesian inference in dynamic discrete choice models." Diss., University of Iowa, 2007. http://ir.uiowa.edu/etd/148.
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Zhu, Liyu. "Discrete Brand Choice Models: Analysis and Applications." Diss., Available online, Georgia Institute of Technology, 2007, 2007. http://etd.gatech.edu/theses/available/etd-07102007-142035/.
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Thesis (Ph. D.)--Industrial and Systems Engineering, Georgia Institute of Technology, 2008.Esogbue, Augustine, Committee Chair ; Griffin, Paul, Committee Member ; Lu, Jye-Chyi (JC), Committee Member ; Li, MinQiang, Committee Member ; McCarthy, Patrick, Committee Member.
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Martinez-Cruz, Adan L. "Implications of heterogeneity in discrete choice analysis." Thesis, University of Maryland, College Park, 2013. http://pqdtopen.proquest.com/#viewpdf?dispub=3587273.
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This dissertation carries out a series of Monte Carlo simulations seeking the implications for welfare estimates from three research practices commonly implemented in empirical applications of mixed logit and latent class logit.
Chapter 3 compares welfare measures across conditional logit, mixed logit, and latent class logit. The practice of comparing welfare estimates is widely used in the field. However, this chapter shows comparisons of welfare estimates seem unable to provide reliable information about the differences in welfare estimates that result from controlling for unobserved heterogeneity. The reason is that estimates from mixed logit and latent class logit are inherently inecient and inaccurate.
Researchers tend to use their own judgement to select the number of classes of a latent class logit. Chapter 4 studies the reliability of welfare estimates obtained under two scenarios for which an empirical researcher using his/her judgement would arguably choose less classes than the true number of classes. Results show that models with a number of classes smaller than the true number tend to yield down- ward biased and inaccurate estimates. The latent class logit with the true number of classes always yield unbiased estimates but their accuracy may be worse than models with the smaller number of classes.
Studies implementing discrete choice experiments commonly obtain estimates of preference parameters from latent class logit models. This practice, however, implies a mismatch: discrete choice experiments are designed under the assumption of homogeneity in preferences, and latent class logit search for heterogeneous preferences. Chapter 5 studies whether welfare estimates are robust to this mismatch. This chapter checks whether the number of choice tasks impact the reliability of welfare estimates. The findings show welfare estimates are unbiased regardless the number of choice tasks, and their accuracy increases with the number of choice tasks. However, some of the welfare estimates are inefficient to the point that cannot be statistically distinguished from zero, regardless the number of choice tasks.
Implications from these findings for the empirical literature are discussed.
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Ammar, Ammar (Ammar T. ). "Ranked personalized recommendations using discrete choice models." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/101564.
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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2015.Cataloged from PDF version of thesis.
Includes bibliographical references (pages 79-82).
Personalized recommendation modules have become an integral part of most consumer information systems. Whether you are looking for a movie to watch, a restaurant to dine, or a news article to read, the number of available option has exploded significantly. Furthermore, the commensurate growth in data collection and processing has created a unique opportunity, where the successful identification of a relevant/desired item in a timely and efficient manner can have serious ramifications for the underlying business in terms of consumer satisfaction, operational efficiency, or both. Taken together, these developments create a need for a principled, scalable, and efficient approach for distilling the available consumer data into compact and accurate representations that can be utilized for making inference about future behavior and preference. In this work, we address the problem of providing such recommendations using ranked data, both as system input and output . In particular, we consider two concrete, and interrelated, scenarios, that capture a large number of applications in a variety of domains. In the first scenario, we consider a set-up where the desired goal is to identify a single global ranking, as we would in a tournament. This setup is analogous to the problem of rank aggregation, historically studied in political science and economics, and more recently in computer science and operations research. In the second scenario, we extend the setup to include multiple 'prominent' rankings. Taken together, these rankings reflect the intrinsic heterogeneity of the population, where each ranking can be viewed as a profile for a subset of said population. In both scenarios, the goal is to (i) devise a model to explain and compress the data, (ii) provide efficient algorithms to identify the relevant ranking for a given user, and (iii) provide a theoretical characterization of the difficulty of this task together with conditions under which this difficulty can be avoided. To that end, and drawing on ideas from econometrics and computer science, we propose a model for the single ranking problem where the data is assumed to be generated from a Multi-Nomial Logit (MNL) model, a parametric probability distribution over permutations used in applications ranging from the ranking of players in online gaming platforms to the pricing of airline tickets. We then devise a simple algorithm for learning the underlying ranking directly from data, and show that this algorithm is consistent for a large subset of the so called Random Utility Models (RUM). Building on the insight from the single ranking case, we handle the multiple ranking scenario using a mixture of Multi-Nomial Logit models. We then provide a theoretical illustration of the difficulty in learning models from this class, which is not surprising given the richness of the model class, and the notorious difficulties inherent in dealing with ranked data. Finally, we devise a simple algorithm for estimating the model under plausible realistic conditions, together with theoretical guarantees on the performance together with an experimental evaluation.
by Ammar Ammar.
Ph. D.
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Chaptini, Bassam H. 1978. "Use of discrete choice models with recommender systems." Thesis, Massachusetts Institute of Technology, 2005. http://hdl.handle.net/1721.1/31137.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2005.Includes bibliographical references (leaves 130-133).
Recommender systems, also known as personalization systems, are a popular technique for reducing information overload and finding items that are of interest to the user. Increasingly, people are turning to these systems to help them find the information that is most valuable to them. A variety of techniques have been proposed for performing recommendation, including content-based, collaborative, knowledge-based and other techniques. All of the known recommendation techniques have strengths and weaknesses, and many researchers have chosen to combine techniques in different ways. In this dissertation, we investigate the use of discrete choice models as a radically new technique for giving personalized recommendations. Discrete choice modeling allows the integration of item and user specific data as well as contextual information that may be crucial in some applications. By giving a general multidimensional model that depends on a range of inputs, discrete choice subsumes other techniques used in the literature. We present a software package that allows the adaptation of generalized discrete choice models to the recommendation task. Using a generalized framework that integrates recent advances and extensions of discrete choice allows the estimation of complex models that give a realistic representation of the behavior inherent in the choice process, and consequently a better understanding of behavior and improvements in predictions. Statistical learning, an important part of personalization, is realized using Bayesian procedures to update the model as more observations are collected.
(cont.) As a test bed for investigating the effectiveness of this approach, we explore the application of discrete choice as a solution to the problem of recommending academic courses to students. The goal is to facilitate the course selection task by recommending subjects that would satisfy students' personal preferences and suit their abilities and interests. A generalized mixed logit model is used to analyze survey and course evaluation data. The resulting model identifies factors that make an academic subject "recommendable". It is used as the backbone for the recommender system application. The dissertation finally presents the software architecture of this system to highlight the software package's adaptability and extensibility to other applications.
by Bassam H. Chaptini.
Ph.D.
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Keller, Philipp W. (Philipp Wilhelm) 1982. "Tractable multi-product pricing under discrete choice models." Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/82871.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2013.Cataloged from PDF version of thesis.
Includes bibliographical references (pages 199-204).
We consider a retailer offering an assortment of differentiated substitutable products to price-sensitive customers. Prices are chosen to maximize profit, subject to inventory/ capacity constraints, as well as more general constraints. The profit is not even a quasi-concave function of the prices under the basic multinomial logit (MNL) demand model. Linear constraints can induce a non-convex feasible region. Nevertheless, we show how to efficiently solve the pricing problem under three important, more general families of demand models. Generalized attraction (GA) models broaden the range of nonlinear responses to changes in price. We propose a reformulation of the pricing problem over demands (instead of prices) which is convex. We show that the constrained problem under MNL models can be solved in a polynomial number of Newton iterations. In experiments, our reformulation is solved in seconds rather than days by commercial software. For nested-logit (NL) demand models, we show that the profit is concave in the demands (market shares) when all the price-sensitivity parameters are sufficiently close. The closed-form expressions for the Hessian of the profit that we derive can be used with general-purpose nonlinear solvers. For the special (unconstrained) case already considered in the literature, we devise an algorithm that requires no assumptions on the problem parameters. The class of generalized extreme value (GEV) models includes the NL as well as the cross-nested logit (CNL) model. There is generally no closed form expression for the profit in terms of the demands. We nevertheless how the gradient and Hessian can be computed for use with general-purpose solvers. We show that the objective of a transformed problem is nearly concave when all the price sensitivities are close. For the unconstrained case, we develop a simple and surprisingly efficient first-order method. Our experiments suggest that it always finds a global optimum, for any model parameters. We apply the method to mixed logit (MMNL) models, by showing that they can be approximated with CNL models. With an appropriate sequence of parameter scalings, we conjecture that the solution found is also globally optimal.
by Philipp Wilhelm Keller.
Ph.D.
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Gong, Sheng. "Essays on conservation adoption and discrete choice modeling." Diss., Kansas State University, 2016. http://hdl.handle.net/2097/32785.
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Doctor of PhilosophyDepartment of Agricultural Economics
Jason S. Bergtold
This dissertation examines advances in applied discrete choice econometrics in applied settings and conservation practice adoptions by Kansas farmers. The research contributes to the literature by examining the use of discrete choice models to more deeply examine adoption of conservation practices and the choice of crop rotations in Kansas. In addition, a method for examining the proper functional specification of logistic regression models is explored. The first essay aims to examine landscape, climatic, socio-economic and farm factors affecting choice of crop rotations by farm managers in dryland cropping systems. A particular emphasis is place on the role, insurance products (such as RA-CRC (Revenue Assurance/Crop Revenue Coverage) and ACRE (Average Crop Revenue Election)), as well as marketing options, and characteristics of farming operations. This paper models the joint adoption of crop rotations using a multinomial modeling framework which is used to estimate the probabilities of adopting different crop rotations. The data used for this paper was obtained from a mail survey in 2011 examining Kansas farmers’ land use decisions and consisted of an eight-page survey with 46 questions, leading to more than 400 distinct variables. The purpose of the second essay is to examine and analyze the adoption of conservation practices, no-till, cover crops and use of crediting of nutrients from manure, by Kansas farmers from both a joint and conditional perspective. This study develops a modeling framework that can analyze conditional adoption and examine farmers’ joint and conditional adoption decisions. Estimates calculated from the model will allow for an assessment of the linkages between the adoption of different conservation practices, as well as the socio-economic factors that affect the likelihood of adopting conservation practices given other conservation practices have already been adopted on-farm. The third essay aims to develop a robust test to examine the functional form of predictor/ index function in the logistic regression models as misspecified models can lead to biased and inconsistent estimates, and consequently inappropriate inferences. An Orthogonal Polynomial RESET test is developed to assess proper functional form for different functional form assumptions of the predictor/ index function, as well as provide guidance on the use of the test in applied logistic regression modeling. Monte Carlo Simulations are used to assess the viability of the test and compare it to similar tests found in the literature.
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Zhang, Shanshan. "Discrete choice analysis of preferences for dental prostheses." Thesis, University of Edinburgh, 2014. http://hdl.handle.net/1842/18747.
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Background: Tooth loss has a negative impact on patients’ general health and wellbeing. Dental prostheses can restore oral function, aesthetics and improve oral health related quality of life. Preferences for dental prostheses cannot be fully captured using existing clinical studies and questionnaires. Discrete choice experiment (DCE) is a novel method in health economics to elicit people’s preference for treatments and it allows the researcher to integrate all aspects relevant to treatment into evaluation and measurement of interrelationship between factors. The aim of this PhD thesis is to use a mixed method of DCE and qualitative interviews to analyse dentists and patient’s preferences for dental prosthesis choices in replacing missing teeth. Methods: Discrete choice experiment questionnaires were developed, describing dental prosthdontic treatments in multi-dimensions, including outcome, process and economic factors. Survey and analysis using the questionnaires were conducted with dentists and patients in Edinburgh. Qualitative interviews with Edinburgh dentists and patients were carried out to derive factors to aid the DCE questionnaire design and provide in-depth understanding of DCE results. Systematic reviews were performed to summarise existing evidence on prosthesis evaluation in traditional quantitative studies and perception of prostheses in qualitative interviews. The current application of DCEs in dentistry was also systematically reviewed. Results: Treatment longevity was identified as the most important factor for dentists and patients’ treatment decisions of anterior missing tooth replacements, followed by appearance and chewing function. Dentists put more value on fixation/comfort and treatment procedure than patients. Patients cared about cost of treatment whereas dentists were relatively insensitive. Gender, age and treatment experience significantly influenced patients’ preference for treatment characteristics. Dental implant supported crown was preferred by dentists, whereas patients gave higher utility to traditional prosthodontic treatments. The monetary benefit of fixed dental prostheses ranged from £1856 -£3848 for patients, far exceeding their willingness-to-pay (WTP), which was £120 - £240. Dentists were willing to pay £600-£3000, more than the perceived benefit £503 to £1649. Qualitative study identified the above factors and provided interpretation of DCE results. Problems in the dental care system related to referral and training for dental implant treatments were raised. Discussion: This thesis is the first DCE application in dentistry evaluating and comparing dentists and patients preferences for missing tooth replacements. Dentists and patients’ preferences were elicited qualitatively and qualitatively integrating multidimensional factors. Patients’ preference for treatments, monetary benefit and WTP were demonstrated to be different from dentists’. Treatment benefits exceeded patients WTP for fixed dental prostheses.
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Danaf, Mazen(Mazen Salah). "Online discrete choice models : applications in smart mobility." Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/123227.
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Thesis: Ph. D. in Transportation, Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2019Cataloged from PDF version of thesis.
Includes bibliographical references (pages 100-108).
Discrete choice models have been widely applied in different fields to better understand behavior and forecast market shares. Because of their ability to capture taste heterogeneity, logit mixture models have gained increasing interest among researchers and practitioners. However, since the estimation of these models is computationally expensive, their applications have been limited to offline contexts. On the other hand, online applications (such as recommender systems) require users' preferences to be updated frequently and dynamically. The objective of this dissertation is to develop a methodology for estimating discrete choice models online, while accounting for inter- and intra-consumer heterogeneity. An offline-online framework is proposed to update individual-specific parameters after each choice using Bayesian estimation.
The online estimator is computationally efficient, as it uses the data of the individual making the choice only in updating his/her individual preferences. Periodically, data from multiple individuals are pooled, and population parameters are updated offline. Online estimation allows for new and innovative applications of discrete choice models such as personalized recommendations, dynamic personalized pricing, and real-time individual forecasting. This methodology subsumes the utility-based advantages of discrete choice models and the personalization capabilities of common recommendation techniques by making use of all the available data including user-specific, item specific, and contextual variables. In order to enhance online learning, two extensions are proposed to the logit mixture model with inter- and intra-consumer heterogeneity.
In the first extension, socio-demographic variables and contextual variables are used to model systematic inter- and intra-consumer taste heterogeneity respectively. In the second extension, a latent class model is used to allow for more flexibility in modeling the inter- and intra-consumer mixing distributions. Finally, the online estimation methodology is applied to Tripod, an app-based travel advisor that aims to incentivize and shift travelers' behavior towards more sustainable alternatives. Stated preferences data are collected in the Greater Boston Area and used to estimate the population parameters, which are then used by the app in online estimation. Using the collected data, a large number of synthetic users is simulated, and the recommendation system is tested over several days, and under different scenarios. The results show that the average hit-rate generally increases over time as we learn individual preferences and population parameters.
"funding from the Advanced Research Projects Agency-Energy (ARPA-E), Ford, the Civil and Environmental Engineering Department at MIT, and the MIT-Singapore Alliance for Research and Technology (SMART)"--Page 5
by Mazen Danaf.
Ph. D. in Transportation
Ph.D.inTransportation Massachusetts Institute of Technology, Department of Civil and Environmental Engineering
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Hosoda, Takamichi 1965. "Incorporating unobservable heterogeneity in discrete choice model : mode choice model for shopping trips." Thesis, Massachusetts Institute of Technology, 1999. http://hdl.handle.net/1721.1/9498.
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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 1999.Includes bibliographical references (leaves 90-95).
In this thesis, we propose a methodology for incorporating attitudinal data in a choice model to capture unobservable heterogeneity across the population. The key features of this approach are, 1) the concept of latent attitudes, and the assumption that 2) the respondent's answers to psychometric attitudinal questions relating to the importance of attributes are manifestations of these attitudes and that 3) those attitudinal data bring sufficient information to capture unobservable heterogeneity across the population in the context of choice behavior. Each individual is probabilistically assigned to a finite number of segments according to his/her own value of latent attitudinal variable(s) as well as to threshold parameter(s) common to the population. Segment-specific parameters are estimated simultaneously. An empirical case study on shopping trip mode choice demonstrates the effectiveness of the methodology.
by Takamichi Hosoda.
S.M.
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Bouscasse, Hélène. "Essays on travel mode choice modeling : a discrete choice approach of the interactions between economic and behavioral theories." Thesis, Lyon, 2017. http://www.theses.fr/2017LYSE2106/document.
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Cette thèse a pour objectif d’incorporer des éléments de théories de psychologie et d’économie comportementale dans des modèles de choix discret afin d’améliorer la compréhension du choix modal réalisé à l’échelle régionale. Les estimations se basent sur une enquête de type choice experiment présentée en première partie. Une deuxième partie s’intéresse à l’incorporation de variables latentes pour expliquer le choix modal. Après une revue de littérature sur les modèles de choix hybrides, c’est-à-dire des modèles combinant modèle d’équations structurelles et modèle de choix discret, un tel modèle est estimé pour montrer comment l’hétérogénéité d’outputs économiques (ici, la valeur du temps) peut être expliquée à l’aide de variables latentes (ici, le confort perçu dans les transports en commun) et de variables observables (ici, la garantie d’une place assise). La simulation de scénarios montre cependant que le gain économique (diminution de la valeur du temps) est plus élevé lorsque les politiques agissent sur des dimensions palpables que sur des dimensions latentes. S’appuyant sur un modèle de médiation, l’estimation d’un modèle d’équations structurelles montre par ailleurs que l’effet de la conscience environnementale sur les habitudes de choix modal est partiellement médié par l’utilité indirecte retirée de l’usage des transports en commun. Une troisième partie s’intéresse à deux formalisations de l’utilité issues de l’économie comportementale : 1) l’utilité dépendante au rang en situation de risque et 2) l’utilité dépendante à la référence. Dans un premier temps, un modèle d’utilité dépendante au rang est inséré dans des modèles de choix discret et, en particulier, un modèle à classes latentes, afin d’analyser l’hétérogénéité intra- et inter-individuelle lorsque le temps de déplacement n’est pas fiable. La probabilité de survenue d’un retard est sur-évaluée pour les déplacements en train et sous-évaluée pour les déplacements en voiture, en particulier pour les automobilistes, les usagers du train prenant d’avantage en compte l’espérance du temps de déplacement. Dans les modèles prenant en compte l’aversion au risque, les fonctions d’utilité sont convexes, ce qui implique une décroissance,de la valeur du temps. Dans un deuxième temps, une nouvelle famille de modèles de choix discret généralisant le modèle logit multinomial, les modèles de référence, est estimée. Sur mes données, ces modèles permettent une meilleure sélection des variables explicatives que le logit multinomial et l’estimation d’outputs économiques plus robustes, notamment en cas de forte hétérogénéité inobservée. La traduction économique des modèles de référence montre que les meilleurs modèles empiriques sont également les plus compatibles avec le modèle de dépendance à la référence de Tversky et KahnemanThe objective of this thesis is to incorporate aspects of psychology and behavioral economics theories in discrete choice models to promote a better understanding of mode choice at regional level. Part II examines the inclusion of latent variables to explain mode choice. A literature review of integrated choice and latent variable models – that is, models combining a structural equation model and a discrete choice model – is followed by the estimation of an integrated choice and latent variable model to show how the heterogeneity of economic outputs (here, value of time) can be explained with latent variables (here, perceived comfort in public transport) and observable variables (here, the guarantee of a seat). The simulation of scenarios shows, however, that the economic gain (decrease in value of time) is higher when policies address tangible factors than when they address latent factors. On the basis of a mediation model, the estimation of a structural equation model furthermore implies that the influence of environmental concern on mode choice habits is partially mediated by the indirect utility derived frompublic transport use. Part III examines two utility formulations taken from behavioral economics: 1) rankdependent utility to model risky choices, and 2) reference-dependent utility. Firstly, a rank-dependent utility model is included in discrete choice models and, in particular, a latent-class model, in order to analyze intra- and inter-individual heterogeneity when the travel time is subject to variability. The results show that the probability of a delay is over-estimated for train travel and under-estimated for car travel, especially for car users, as train users are more likely to take into account the expected travel time. In the models that account for risk aversion, the utility functions are convex, which implies a decrease in value of time. Secondly, a new family of discrete choice models generalizing the multinomial logit model, the reference models, is estimated. On my data, these models allow for a better selection of explanatory variables than the multinomial logit model and a more robust estimation of economic outputs, particularly in cases of high unobserved heterogeneity. The economic formulation of reference models shows thatthe best empirical models are also more compatible with Tversky et Kahneman’s reference-dependent model
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Bayoh, Isaac Moussa. "Estimating the determinants of household residential location choice using a multinomial, discrete choice model." The Ohio State University, 2001. http://rave.ohiolink.edu/etdc/view?acc_num=osu1374586719.
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Hess, Stephane. "Advanced discrete choice models with applications to transport demand." Thesis, Imperial College London, 2005. http://hdl.handle.net/10044/1/11357.
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The area of discrete choice modelling has, over recent years, witnessed the development of ever more flexible model structures that allow for an increasingly realistic representation of travel behaviour. With these developments have also come important issues of specification, estimation and interpretation, some of which are addressed in this thesis, mainly in the context of models allowing for random taste heterogeneity across respondents. As such, it is shown that severe risks of misinterpretation arise when relying on the commonly used Normal distribution, and the advantages of several alternative distributions are illustrated, while also discussing the benefits of a discrete mixture approach. The thesis also highlights risks of confounding between different components of the error structure, and discusses the development of approaches that can lead to computational savings in simulation-based model estimation and application. Finally, a framework is developed for the representation of random variations in a model’s covariance structure. With the pace of theoretical developments, the gap between theory and practice in the use of discrete choice models has widened. The applied part of the thesis aims to partly bridge this gap in one area of travel-behaviour research, looking at the modelling of choices made by air-passengers departing from multi-airport regions, with applications to Greater London and the San Francisco Bay area. The case-studies show the benefits of using advanced model approaches, in this case cross-nesting and random coefficients structures. At the same time however, the work shows that the appeal of such models in largescale analyses is reduced by heightened data requirements, and the significant rise in estimation cost. Finally, the case-studies show that, while the issues discussed in the theoretical part of the thesis need to be taken into account in interpretation, for practical purposes, the guidelines in terms of specification often need to be violated.
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Telser, Harald. "Nutzenmessung im Gesundheitswesen : die Methode der Discrete-Choice-Experimente /." Hamburg : Kovač, 2002. http://www.gbv.de/dms/zbw/35199016X.pdf.
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Nunes, Letícia Faria de Carvalho. "Practice location of physicians: a discrete choice model approach." reponame:Repositório Institucional do FGV, 2015. http://hdl.handle.net/10438/13827.
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Economists and policymakers have long been concerned with increasing the supply of health professionals in rural and remote areas. This work seeks to understand which factors influence physicians’ choice of practice location right after completing residency. Differently from previous papers, we analyse the Brazilian missalocation and assess the particularities of developing countries. We use a discrete choice model approach with a multinomial logit specification. Two rich databases are employed containing the location and wage of formally employed physicians as well as details from their post-graduation. Our main findings are that amenities matter, physicians have a strong tendency to remain in the region they completed residency and salaries are significant in the choice of urban, but not rural, communities. We conjecture this is due to attachments built during training and infrastructure concerns.
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Sagebiel, Julian. "Valuing improvements in electricity supply using discrete choice experiments." Doctoral thesis, Humboldt-Universität zu Berlin, Lebenswissenschaftliche Fakultät, 2017. http://dx.doi.org/10.18452/17754.
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Um Strommärkte so zu konzipieren damit sie sowohl zur Verringerung der Nutzung fossiler Brennstoffe als auch zur Deckung des steigenden Energiebedarfes beitragen, ist Wissen über die Präferenzen der Konsumenten notwendig. Die vorliegende kumulative Dissertation untersucht Präferenzen für Elektrizitätsattribute von privaten Haushalten und trägt zu einem tieferen Verständnis dieser in unterschiedlichen Kontextsituationen bei. Der erste Artikel betrachtet statistische Methoden um die zwei am häufigsten angewandten Modelle – das Random Parameter Logit und das Latent Class Logit Modell – zu vergleichen. Der Artikel trägt dazu bei, den Prozess der Modellwahl zu verbessern und für die angewandte Forschung im Energiebereich anzupassen. Basierend auf den empirischen Ergebnissen des ersten Artikels untersucht der zweite Artikel die Präferenzen von privaten Haushalten in Hyderabad, Indien mit besonderem Fokus auf die physische Qualität der Energieversorgung. Die Ergebnisse deuten auf eine geringe Zahlungsbereitschaft der Konsumenten hin. Jedoch unterscheiden sich die Präferenzen der Haushalte. Die Artikel 3 und 4 basieren auf Datenerhebungen in Deutschland. Im dritten Artikel werden die Präferenzen privater Haushalte hinsichtlich der Organisationsform von Stromanbietern untersucht. Die Ergebnisse zeigen, dass die Kunden bereit sind mehr zu zahlen, wenn die Stromversorgung von Genossenschaften oder Stadtwerken übernommen wird. Der vierte Artikel betrachtet die Erfolgsfaktoren von Energiegenossenschaften in Deutschland. Die Ergebnisse zeigen, dass die Governance des Stromanbieters die Zahlungsbereitschaft für Strom beeinflussen. Insbesondere Genossenschaften werden den großen Privatunternehmen und Aktiengesellschaften vorgezogen.In order to design electricity markets to simultaneously reduce the share of fossil fuels in energy production and meet the increasing demand for electricity, knowledge on consumer preferences is necessary. The goal of this cumulative dissertation is to contribute to the understanding of preferences of private households for electricity supply attributes in different contexts. In Paper 1 I review statistical methods to compare two frequently applied models, the random parameters logit and the latent class logit. The methods presented here can be readily used by other researchers and practitioners to better understand model performance which ultimately contributes to improving model choice in applied energy research. Based on the empirical findings of Paper 1, Paper 2 identifies preferences of private households in Hyderabad in India for electricity supply quality. The results indicate that willingness to pay for improvements are, on average, rather low. However, the preferences strongly vary between subjects. Papers 3 and 4 investigate preferences of German private households. In \textbf{Paper 3}, the respondents stated their preferences for the organization of the electricity distribution company under different renewable energy scenarios. It turned out that most people are willing to pay more for electricity supplied by municipally-owned companies and cooperatives. This additional willingness to pay increases disproportionally when the share of renewable energy is high. The paper identifies non-profit orientated distribution companies as potential drivers of the energy transition. Paper 4 investigates the determinants for the success of energy cooperatives in Germany. The results indicate that the governance of distribution companies impacts the choices of private households for electricity supply contracts. Especially, people preferred cooperative-like governance attributes.
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Ramsey, Steven M. "Advances in land-use and stated-choice modeling using neural networks and discrete-choice models." Diss., Kansas State University, 2017. http://hdl.handle.net/2097/35802.
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Doctor of PhilosophyDepartment of Agricultural Economics
Jason S. Bergtold
Jessica L. Heier Stamm
Applied research in agricultural economics often involves a discrete process. Most commonly, these applications entail a conceptual framework, such as random utility, that describes a discrete-variable data-generating process. Assumptions in the conceptual framework then imply a particular empirical model. Common approaches include the binary logit and probit models and the multinomial logit when more than two outcomes are possible. Conceptual frameworks based on a discrete choice process have also been used even when the dependent variable of interest is continuous. In any case, the standard models may not be well suited to the problem at hand, as a result of either the assumptions they require or the assumptions they impose. The general theme of this dissertation is to adopt seldom-used empirical models to standard research areas in the field through applied studies. A common motivation in each paper is to lessen the exposure to specification concerns associated with more traditional models. The first paper is an attempt to provide insights into what --- if any --- weather patterns farmers respond to with respect to cropping decisions. The study region is a subset of 11 north-central Kansas counties. Empirically, this study adopts a dynamic multinomial logit with random effects approach, which may be the first use of this model with respect to farmer land-use decisions. Results suggest that field-level land-use decisions are significantly influenced by past weather, at least up to ten years. Results also suggest, however, that that short-term deviations from the longer trend can also influence land-use decisions. The second paper proposes multiple-output artificial neural networks (ANNs) as an alternative to more traditional approaches to estimating a system of acreage-share equations. To assess their viability as an alternative to traditional estimation, ANN results are compared to a linear-in-explanatory variables and parameters heteroskedastic and time-wise autoregressive seemingly unrelated regression model. Specifically, the two approaches are compared with respect to model fit and acre elasticities. Results suggest that the ANN is a viable alternative to a simple traditional model that is misspecified, as it produced plausible acre-response elasticities and outperformed the traditional model in terms of model fit. The third paper proposes ANNs as an alternative to the traditional logit model for contingent valuation analysis. With the correct network specifications, ANNs can be viewed as a traditional logistic regression where the index function has been replaced by a flexible functional form. The paper presents methods for obtaining marginal effect and willingness-to-pay (WTP) measures from ANNs, which has not been provided by the existing literature. To assess the viability of this approach, it is compared with the traditional logit and probit models as well an additional semi-nonparametric estimator with respect to model fit, marginal effects, and WTP estimates. Results suggest ANNs are viable alternative and may be preferable if misspecification of the index function is a concern.
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Shen, Yu. "Car fleet modelling : Data processing and discrete choice model estimation." Thesis, KTH, Transportvetenskap, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-43719.
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This thesis deals with the modelling of the choice of new car based on the registration data of the whole Sweden car fleet for 2005 to 2010. It is divided into two parts. In the first part, to obtain the observations of new car choices for the discrete choice modelling, a subset based on the first registration date of each car is extracted. Then, a descriptive analysis based on the new car choice data is presented to find the variances of the attributes for the modelling. Specifically, two major issues are paid attention to. One is the change of market share of each car make in these years and the other is the incremental demand of diesel and hybrid fuel cars. The second part of the thesis deals with the discrete choice modelling. In order to designate the alternatives, another dataset showing the new car supply in Sweden is introduced. In the supply data, the alternatives are shown in the car version level, whereas the registration data only contain the names of car models. Additionally, the supply data also have some attributes that are unavailable in the registration, e.g. price. Thus, this thesis presents various matching methods to match the supply and the registration to define the alternatives for the modelling and also to obtain a higher precision of each attribute than that in matching with model names only. Finally, we choose to match the data by the same model name with the same maximum power, which is defined as the “model-engine” level. Therefore, based on these model-engine level alternatives, 18 MNL models are estimated from 2005 to 2010, with 3 different ownerships, namely private owned, company owned and company owned but leasing to its employee which is named as “leasing users”. The results show the slump of the brand constants of Saab among these years in private owners and leasing users due to the close-down crisis when the coefficient of Volvo is fixed to zero. By contrast, the brand value of Kia for private owners and the value of VW for leasing users go up. Meanwhile, this thesis analyses a shift of car buyers’ attitude to the alternative fuel car from negative in 2006 to positive in 2007 when a “clean car” compensation policy is implemented from Jan. 2007 to Jul. 2009. And in 2010, the coefficient of the alternative fuel remains positive. These results indicate that this policy was quite successful.
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Li, Ji. "Essays on discrete choice under social interaction methodology and applications /." Columbus, Ohio : Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1180499711.
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Gopinath, Dinesh A. (Dinesh Ambat). "Modeling heterogeneity in discrete choice proceses : application to travel demand." Thesis, Massachusetts Institute of Technology, 1995. http://hdl.handle.net/1721.1/11734.
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Rosa, Andrea. "Probit based methods in traffic assignment and discrete choice modelling." Thesis, Edinburgh Napier University, 2003. http://researchrepository.napier.ac.uk/Output/4168.
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Sukhin, David A. "Dynamic, personalized discrete choice incentive allocation to optimize system performance." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/113170.
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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017Cataloged from PDF version of thesis.
Includes bibliographical references (pages 37-38).
Incentivization is a powerful way to get independent agents to make choices that drive a system to a desired optimum. Simply offering compensation for making a certain choice is enough to change the behavior of some people. If you incentivize the right choices, you can get closer to your desired choice-dependent goal. Ways to optimize these choices in an environment with many choices and many users is essential for achieving goals for the least cost. I examine how a model that is aware of the utility function of each choice and for each user in a system can optimally allocate incentives in real time while considering opportunity cost, personalized incentive response behavior, and maximizing marginal results. This method is useful in systems that have direct and private communication with each user but are limited by having users enter the system at different times. The method must offer a menu of choices and incentives on demand while still considering users that are yet to come. I discuss several solutions and benchmark them on the TRIPOD traffic optimization system which aims to incentivize users to make energy efficient daily commute choices. The final model incorporates user personalized incentives and opportunity cost of each incentive to achieve the optimal incentive allocation on an ad-hoc basis.
by David A. Sukhin.
M. Eng.
M.Eng. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science
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Zivanovic, Sanja. "Attractors in Dynamics with Choice." Scholarly Repository, 2009. http://scholarlyrepository.miami.edu/oa_dissertations/210.
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Dynamics with choice is a generalization of discrete-time dynamics where instead of the same evolution operator at every time step there is a choice of operators to transform the current state of the system. Many real life processes studied in chemical physics, engineering, biology and medicine, from autocatalytic reaction systems to switched systems to cellular biochemical processes to malaria transmission in urban environments, exhibit the properties described by dynamics with choice. We study the long-term behavior in dynamics with choice. We prove very general results on the existence and properties of global compact attractors in dynamics with choice. In addition, we study the dynamics with restricted choice when the allowed sequences of operators correspond to subshifts of the full shift. One of practical consequences of our results is that when the parameters of a discrete-time system are not known exactly and/or are subject to change due to internal instability, or a strategy, or Nature's intervention, the long term behavior of the system may not be correctly described by a system with "averaged" values for the parameters. There may be a Gestalt effect.
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Lancsar, Emily. "New methods to estimate individual level choice models and Hicksian welfare measure from discrete choice experiments." Thesis, University of Newcastle Upon Tyne, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.506557.
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Espinoza, García Juan Carlos. "Robust optimization for discrete structures and non-linear impact of uncertainty." Thesis, Cergy-Pontoise, Ecole supérieure des sciences économiques et commerciales, 2017. http://www.theses.fr/2017ESEC0004/document.
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L’objectif de cette thèse est de proposer des solutions efficaces à des problèmes de décision qui ont un impact sur la vie des citoyens, et qui reposent sur des données incertaines. Au niveau des applications, nous nous intéressons à deux problèmes de localisation qui ont un impact sur l’espace public, notamment la localisation de nouveaux logements, et la localisation de vendeurs mobiles dans l’espace urbain. Les problèmes de localisation ne sont pas un sujet récent dans la littérature, toutefois, pour ces deux problèmes qui reposent sur des modèles de choix pour le comportement d’achat des consommateurs, l’incertitude dans le modèle génère un cas spécial qui permet d’étendre la littérature sur l’Optimisation Robuste. Les contributions de cette thèse peuvent s’appliquer à divers problèmes génériques d’optimisationWe address decision problems under uncertain information with non-linear structures of parameter variation, and devise solution methods in the spirit of Bertsimas and Sim’s Γ-Robustness approach. Furthermore, although the non-linear impact of uncertainty often introduces discrete structures to the problem, for tractability, we provide the conditions under which the complexity class of the nominal model is preserved for the robust counterpart. We extend the Γ-Robustness approach in three avenues. First, we propose a generic case of non-linear impact of parameter variation, and model it with a piecewise linear approximation of the impact function. We show that the subproblem of determining the worst-case variation can be dualized despite the discrete structure of the piece-wise function. Next, we built a robust model for the location of new housing where the non-linearity is introduced by a choice model, and propose a solution combining Γ-Robustness with a scenario-based approach. We show that the subproblem is tractable and leads to a linear formulation of the robust problem. Finally, we model the demand in a Location Problem through a Poisson Process inducing, when demands are uncertain, non-linear structures of parameter variation. We propose the concept of Nested Uncertainty Budgets to manage uncertainty in a tractable way through a hierarchical structure and, under this framework, obtain a subproblem that includes both continuous and discrete deviation variables
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Bilala, Nikita. "Estimating mode choice: A discrete choice analysis of a park and ride system for Florida road, Durban." Master's thesis, Faculty of Engineering and the Built Environment, 2018. http://hdl.handle.net/11427/30069.
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The majority of roads in Southern Africa have been designed primarily for private vehicle usage, with alternative modes such as public transport and non- motorised transport being largely neglected, and this is also true of Florida Road. Florida Road is located in Morningside, Durban, and has become an iconic landmark street known for its buzzing day and night life. However, due to the lack of adequate parking provision, coupled with increased traffic volumes, this street is plagued by traffic congestion, drivers performing unsafe vehicle manoeuvres as well as illegal parking, contributing to increased driver frustration and the increased possibility of car accidents. In this study, the feasibility of introducing a Park and Ride (P&R) system to Florida Road (from Greyville Racecourse) was investigated. Previous studies have shown that P&R systems can have a positive impact on traffic congestion on the local road network, however, there are not many studies that document the travel impacts and demand for P&R systems of this type – smaller P&R that do not link to major bus or rail public transport systems, but rather operate as “express bus” systems. This dissertation investigated the predicted travel behaviour responses of car users to the introduction of a P&R system to Florida Road from Greyville Racecourse. By doing so, the demand for the service, in terms of choice probabilities, was forecast. Another interest in this study was to examine the influence of current travel behaviour patterns as well as socio demographic characteristics on the predicted demand for the service. A stated preference survey was designed and implemented, which presented respondents with hypothetical choice scenarios involving three modes considered available – car, P&R and Uber with varying levels of service attributes i.e. travel cost, time spent parking, security and headway. A questionnaire asking respondents about their current travel patterns and personal characteristics was also administered. A discrete choice experiment was then carried out. A discrete choice experiment models the stated choices of respondents and provides a relative evaluation on the attributes presented, based on their responses. A multinomial logit model was then used in this experiment, to estimate the results. The results of the discrete choice experiment show that travel cost is one of the most important factors in mode choice evaluation by users of Florida Road. In particular to the P&R system, the service headway as well as presence of car guards/ security at the P&R facility were critical determinants of choice. Employment status was found to have a significant impact on the perceived costs of a trip, particularly trips made by respondent’s private vehicle. Respondents also displayed a preference for P&R for social trips, and work trips, over other modes. The time users spent parking at Florida Road was found to not be a significant deterrent to car usage. Socio – demographic variables such as age and gender were not found to have a significant bearing on mode choice probabilities. To ensure a sustainable demand for the P&R system, P&R service characteristics should be optimised, and the utility of using the P&R service should be higher than that of the other modes considered. From the data analysis, it was evident that for a higher patronage, the cost of using the P&R service should be low, or ideally, the service should be free. Shorter headways between pick – ups/ drop – offs should be maintained. Another important aspect is that, to promote the service, adequate advertising on social media is recommended. Aspects such as parking facility location, bus schedules, costs etc should be highly publicised. A high - quality shuttle bus service should also be provided, to further attract prospective users to the service. For the P&R system to be truly successful, P&R should be also introduced with measures to discourage use of parking bays on Florida, and encourage the use of the P&R service. An option considered is to start charging parking costs for the bays on Florida Road, thereby discouraging the use of this parking. The promotion of public transport, coupled with measures that actively discourage private vehicle usage would add to the attraction of the P&R system.
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Blom, Västberg Oskar. "Five papers on large scale dynamic discrete choice models of transportation." Doctoral thesis, KTH, Systemanalys och ekonomi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-219882.
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Travel demand models have long been used as tools by decision makers and researchers to analyse the effects of policies and infrastructure investments. The purpose of this thesis is to develop a travel demand model which is: sensitive to policies affecting timing of trips and time-space constraints; is consistent with microeconomics; and consistently treats the joint choice of the number of trips to perform during day as well as departure time, destination and mode for all trips. This is achieved using a dynamic discrete choice model (DDCM) of travel demand. The model further allows for a joint treatment of within-day travelling and between-day activity scheduling assuming that individuals are influenced by the past and considers the future when deciding what to do on a certain day. Paper I develops and provides estimation techniques for the daily component of the proposed travel demand model and present simulation results provides within sample validation of the model. Paper II extends the model to allow for correlation in preferences over the course of a day using a mixed-logit specification. Paper III introduces a day-to-day connection by using an infinite horizon DDCM. To allow for estimation of the combined model, Paper III develops conditions under which sequential estimation can be used to estimate very large scale DDCM models in situations where: the discrete state variable is partly latent but transitions are observed; the model repeatedly returns to a small set of states; and between these states there is no discounting, random error terms are i.i.d Gumble and transitions in the discrete state variable is deterministic given a decision. Paper IV develops a dynamic discrete continuous choice model for a household deciding on the number of cars to own, their fuel type and the yearly mileage for each car. It thus contributes to bridging the gap between discrete continuous choice models and DDCMs of car ownership. Infinite horizon DDCMs are commonly found in the literature and are used in, e.g., Paper III and IV in this thesis. It has been well established that the discount factor must be strictly less than one for such models to be well defined.Paper V show that it is possible to extend the framework to discount factors greater than one, allowing DDCM's to describe agents that: maximize the average utility per stage (when there is no discounting); value the future greater than the present and thus prefers improving sequences of outcomes implying that they take high costs early and reach a potential terminal state sooner than optimal.Modeller för reseefterfrågan har länge använts av besultsfattare såväl somforskare för att analysera effekterna av transportpolitiska åtgärder. Avhandlingenshuvudsakliga syfte har varit att bidra till utvecklandet av modellerför reseefterfrågan som är: känsliga för åtgärder som påverkar tidsvalför resor eller tids-rums begränsningar; och konsistent behandlar valet avantalet resor, avresetid, destination och färdmedel för en individ. Dettauppnås genom användandet av en dynamisk diskret valmodell (DDCM) förreseefterfrågan. Modellen klarar vidare av att gemensamt modellera bådedagligt resande med hänsyn till hur det påverkar behovet av andra resoröver en längre tidshorisont, där individer antas ta hänsyn till både när desenaste utfört olika aktiviteter samt framtida effekter av sina besult. Papper I utvecklar den dagliga komponenten i den föreslagna modellenför reseefterfrågan, presenterar en estimeringsteknik samt resultat från simuleringarmed valideringsresultat. Papper II förbättrar modellen genom attinkludera korrelation i preferenser under dagen med hjälp av en mixed-logitspecifikation. Papper III introducerar en koppling mellan dagar genom enDDCM med oändlig tidshorisont. För att den kombinerade modellen skullevara möjlig att estimera härleddes vilkor under vilka sekvensiell estimeringvar möjlig. Dessa vilkor möjligör därmed estimering av en specific typ avstorskaliga DDCM modeller i situationer när: den diskreta tillståndsvariabelnär delvis latent men där val observeras; där modellen återkommer tillett mindre tillståndrum; och där det mellan återkomsten till detta mindretillståndrum inte sker någon diskontering, nyttofunktionernas feltermer gesav i.i.d Gumble termer och övergångarna mellan disrekta tillståndsvariablerär deterministisk givet valet. Papper IV utvecklar en dynamiskt diskret-kontinuerlig valmodell för etthushålls beslut gällande antalet bilar att äga, deras bränsletyp samt årligamiltal för varje bil. Det därmed till att komibinera dynamiska och diskretkontinulerligavalmodeller för bilägande. DDCM med oändliga tidshorisonter är vanligt förekommande och användsi bland annat Papper III och IV i den här avhandlingen. Det harvarit väl etablerat att diskonteringsfaktorn måste vara strikt mindre än ettför att sådana modeller ska vara väldefinerade. Papper V visar hur det ärmöjligt tillåta diskonteringsfaktorer större än eller lika med ett, och därmedbeskriva agenter som: maximerar den genomsnittliga nyttan per steg (närdet inte sker någon diskontering); värderar framtiden högre än nutiden ochdärmed föredrar förbättrande sekvenser vilket också implicerar att de tarhöga kostnader så tidigt som möjligt och når ett potentiellt sluttillståndtidigare än optimalt.
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Tinelli, Michela. "Developing and applying Discrete Choice Experiments (DCEs) to inform pharmacy policy." Thesis, University of Aberdeen, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.485814.
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Introduction. In the United Kingdom (UK), recent policy developments include an increased role for the community phannacist in the management of drug therapy in primary care. When embarking on such service redesign, it is recognised that. patient preferences must be considered. The quality adjusted life years (QALY) approach is the common economic approach ~o 1'. considering preferences in economic evaluations. However, it is limited to consideration of - ·only health outcomes. Other approaches widely used in health services research, such as · satisfaction surveys, do not find a place in the economic eval~tion framework because they' do not incorporate any notion of opportunity cost or strength of preference. Another measure of benefit is required to go beyond the scope of the QALY and pla~e a value on non-health outcomes (e.g. information, reassurance, regret, anxiety) and process attributes (e.g. waiting · time at the ~ealth care centre, staff involyed, waiting time for test res!llts), as well as estimate trade-offs between such aspects ofcare. . . One technique adopted over the past decade in health economics to go beyond health outcome is Discrete Choice Experiment (DCEs). This is an attribute-based technique for eliciting preferenc~s. ~en a price proxy is included, willingness to pay (WTP), a monetary measure of benefit, can be estimated for both marginal changes in service characteristics and changes in the overall service. Whilst the last 15 years has seen an increased uSe of DeEs in health care, there has been limited application in pharmacy. The Community Pharmacy Medicines Management Project (Medman study) constituted the perfect platfonn for this PhD thesis. It was a large, randomised, controlled trial (ReT) to evaluate the introduction of a pharmacy-led medicines management service for patients with 'cQronary- heart -disease-(CHD): It- allowed comparison of results between traditional outcome measures (such as clinical outcomes, QALYs and satisfaction) and a broader measure of benefit llsing the DCE. As well as considering the relevance of DCE ·to policy making, methodological issues in their development were also considered. Aim and ·objectives. The aims of this PhD programme are: to consider the implications of ..taking a .broader patient centred approach (which goes beyond he~th outcomes) to ev~luating ' . a proposed policy change in community pharmacy; and to develop' and apply the DCE '. ' ~ . methodology to pharmacy. The specific objectives ofthe thesis are: • to conduct a review ofthe literature relating to benefit evaluation and its application to the economic evaluation framework in pharmacy; ' • to apply traditional benefit evaluation approaches, including' clinical outcomes, - . QALYs and a satisfaction survey to a' pharmacy setting;. jI ' i .J I' • to develop an alternative approach, DCEs, to value benefits, looking at different design appr?ache~ \\,~en defining multiple choice· DCEs and addressing welfare . estimation issJles when.analysing the data; • to apply DCE to phaimacy within the Medman .study and to compare the results with _these ofclinical and QALY approaches within an economic evaluation framework; • to consider the impact on policy when different approaches are applied. Methods. A fully comprehensive review of the health care literature was conducted to . identify possible methods for valuing community pharmacy-based services and their integration into economic evaluation.
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Maier, Gunther, and Peter Rogerson. "Discrete Choice, Optimal Search and Spatial Interaction Models: Some Fundamental Relationships." WU Vienna University of Economics and Business, 1986. http://epub.wu.ac.at/6231/1/IIR_Disc_31.PDF.
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Haaf, Christine Grace. "Vehicle Demand Forecasting with Discrete Choice Models: 2 Logit 2 Quit." Research Showcase @ CMU, 2014. http://repository.cmu.edu/dissertations/491.
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Discrete choice models (DCMs) are used to forecast demand in a variety of engineering, marketing, and policy contexts, and understanding the uncertainty associated with model forecasts is crucial to inform decision-making. This thesis evaluates the suitability of DCMs for forecasting automotive demand. The entire scope of this investigation is too broad to be covered here, but I explore several elements with a focus on three themes: defining how to measure forecast accuracy, comparing model specifications and forecasting methods in terms of prediction accuracy, and comparing the implications of model specifications and forecasting methods on vehicle design. Specifically I address several questions regarding the accuracy and uncertainty of market share predictions resulting from choice of utility function and structural specification, estimation method, and data structure assumptions. I1 compare more than 9,000 models based on those used in peer-reviewed literature and academic and government studies. Firstly, I find that including more model covariates generally improves predictive accuracy, but that the form those covariates take in the utility function is less important. Secondly, better model fit correlates well with better predictive accuracy; however, the models I construct— representative of those in extant literature— exhibit substantial prediction error stemming largely from limited model fit due to unobserved attributes. Lastly, accuracy of predictions in existing markets is neither a necessary nor sufficient condition for use in design. Much of the econometrics literature on vehicle market modeling has presumed that biased coefficients make for bad models. For purely predictive purposes, the drawbacks of potentially mitigating bias using generalized method of moments estimation coupled with instrumental variables outweigh the expected benefits in the experiments conducted in this dissertation. The risk of specifying invalid instruments is high, and my results suggest that the instruments frequently used in the automotive demand literature are likely invalid. Furthermore, biased coefficients are not necessarily bad for maximizing the predictive power of the model. Bias can even aid predictions by implicitly capturing persistent unobserved effects in some circumstances. Including alternative specific constants (ASCs) in DCM utility functions improves model fit but not necessarily forecast accuracy. For frequentist estimated models all tested methods of forecasting ASCs improved share predictions of the whole midsize sedan market over excluding ASC in predictions, but only one method results in improved long term new vehicle, or entrant, forecasts. As seen in a synthetic data study, assuming an incorrect relationship between observed attributes and the ASC for forecasting risks making worse forecasts than would be made by a model that excludes ASCs entirely. Treating the ASCs as model parameters with full distributions of uncertainty via Bayesian estimation is more robust to selection of ASC forecasting method and less reliant on persistent market structures, however it comes at increased computational cost. Additionally, the best long term forecasts are made by the frequentist model that treats ASCs as calibration constants fit to the model post estimation of other parameters.
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Korfmann, Frauke [Verfasser], and Knut [Akademischer Betreuer] Haase. "Essays on Advanced Discrete Choice Applications / Frauke Korfmann ; Betreuer: Knut Haase." Hamburg : Staats- und Universitätsbibliothek Hamburg, 2018. http://d-nb.info/1155304179/34.
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McIntosh, Emma Sarah. "Using discrete choice experiments to value the benefits of health care." Thesis, University of Aberdeen, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.401379.
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The aim of this thesis is to broaden work in the area of discrete choice experiments (DCEs) in health economics by focusing on the development of some key areas which have to date received relatively little attention. By firstly outlining the background, theory and context of DCEs in health economics, areas are identified that deserve further exploration due to their particular relevance to health economics. Specific contributions of the thesis are in three main areas: modelling the participation decision in DCEs in health care; the use of strength of preference choice modelling approaches; and the applicability of a new approach, best attribute scaling (BSc), to health economics. The contributions of the thesis are to the design, analysis and interpretation of DCE studies. The seven key recommendations for the conduct of DCE surveys arising from this thesis have been made on the basis of the best available knowledge gleaned from empirical analysis carried out. They are as follows: (1) Researchers conducting DCE studies in health care should carefully consider the participation decision when designing and analysing a DCE and where appropriate pay particular attention to describing the opt-out or status quo option as realistically as possible (2) When incorporating status quo or opt-out scenarios within a DCE design researchers should check that the statistical properties of the resulting design are still valid (3) Strength of preference models appear to improve the statistical efficiency of models and produce more accurate estimates of welfare however this may come at the expense of the predictive ability of the model and consistency rates (4) Where possible DCE surveys should provide respondents with the most realistic range of preference ‘capture’ mechanisms as possible, this includes providing opting out, status quo and indifference options where appropriate. (5) As shown in the environmental economics literature strength of preference models facilitates the elicitation of preferences in health economics (6) BSc methods can be used to predict choices in health care preference surveys (7) BSc has the ability to separate scale and weight in choice experiments and hence place all attribute levels on a common scale, unlike traditional choice experiments however future work with larger samples should clarify this result.
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Hashemi, Ali. "Empirical Studies of Discrete Choice Models in Health, Fertility, and Voting." Diss., Virginia Tech, 2011. http://hdl.handle.net/10919/77336.
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Almost everything that we do involves a choice. In recent years there has been a growing interest in the development and application of quantitative statistical methods to study choices made by individuals with the purpose of gaining a better understanding of how choices are made and also to predict future choice responses. In many fields, the choices made by individuals will determine the effectiveness of policy. Understanding what drives people's choices and how these choices may change is critical for developing successful policy. Discrete choice modeling provides an analytical framework with which to analyze and predict how people's choices are influenced by their personal characteristics and by the different attributes of the alternatives available to them.
In an ideal situation we would build discrete choice models using information from choices that people are observed to make, i.e., revealed preference (RP) information. From these data we can quantify the influence of particular variables in the real choice context; for example, how important is price in the decision to travel by train? There are, however, potential problems with these data. There might not be enough variation of the explanatory attributes; for example little price variation across alternatives. Furthermore, several attributes might be highly correlated e.g. price and quality. But the most important of all is the fact that it is not possible to observe choices for alternatives that do not yet exist; for example new programs and technologies. In cases where the data limits the information provided by real choices it may be appropriate to collect stated preference (SP) data, which is information on preferences provided from hypothetical choice situations.
This dissertation provides several applications of discrete choice modeling using both raveled preferences and stated preference. Unlike the last two chapters which deal with the revealed preference, the first Chapter, uses stated preference data. This Chapter evaluates the impact of several attributes of monetary incentives on the decision of patients to participate in a new weight loss program. Since this program does not exist yet, revealed preference data were not available and stated preference data were collected. The attributes of interest in this study include magnitude, timing and form of payment. The goal is to see what level and what combination of these attributes provides greater impact on the reach of the program. We also account for preference heterogeneity by using a random parameter framework.
Chapter 2 discusses another application of discrete choice models in event history models (also called survival analysis). In these type of models, the main goal is to use the history of happening an event to learn more about the effect of different factors on the probability of occurrence. The event of interest in our case is the birth. We use the birth history of rural women and try to model their decision to give birth over time. The ultimate goal is to evaluate the effect of health clinics and family planning program on this decision.
The final Chapter considers the application of discrete choice modeling in an electoral framework. The 2005 presidential election in Iran is used to model the decisions of Iranian voters. Using this revealed preference data we try to learn more about the main factors evolved in both participation and in the candidate selection.Ph. D.
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Xu, Yuanquan. "A discrete choice based facility location model for inland container depots." Morgantown, W. Va. : [West Virginia University Libraries], 1999. http://etd.wvu.edu/templates/showETD.cfm?recnum=1113.
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Thesis (Ph. D.)--West Virginia University, 1999.Title from document title page. Document formatted into pages; contains x, 126 p. : ill. (some col.), maps (some col.). Includes abstract. Includes bibliographical references (p. 98-103).
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Aloef, Fatimah. "Bayesian design of discrete choice experiments for valuing health state utilities." Thesis, University of Sheffield, 2015. http://etheses.whiterose.ac.uk/9446/.
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This thesis concerns about using discrete choice experiment for valuing health state utilities within the QALY framework. Therefore, it discusses the main issues with generating choice design for valuing health state utilities, and then presents an efficient methodology to construct an optimal choice design for valuing health state utilities using the most recent theoretical development in Bayesian optimal design literature. The use of the new design algorithm and the effect of the prior in the Bayesian design are demonstrated in this thesis by constructing Bayesian choice design for asthma quality of life classification system (AQL-5D).
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Schulz, Norbert [Verfasser]. "Discrete Choice Experimente zur Prognose des Entscheidungsverhaltens von Landwirten / Norbert Schulz." Kiel : Universitätsbibliothek Kiel, 2013. http://d-nb.info/104560402X/34.
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Chiu, Yih-wan Danny. "Convergence of discrete-vortex induced-flow calculations by optimum choice of mesh." Diss., Georgia Institute of Technology, 1988. http://hdl.handle.net/1853/12390.
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Takama, Takeshi. "Stochastic agent-based modelling for reality : dynamic discrete choice analysis with interaction." Thesis, University of Oxford, 2005. http://ora.ox.ac.uk/objects/uuid:07a643ed-c98a-4e66-936b-e8b558dbc1e3.
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This D.Phil. thesis develops a new agent-based simulation model to improve the results of analysis, which solely uses discrete choice modelling, as well as to analyse the effects of a road user charging scheme for the Upper Derwent Valley in the Peak District National Park. The advantages of discrete choice analysis are well known. However, results with these conventional conventional approaches, which conduct analysis solely with discrete choice models, can be biased if interaction and learning effects are significant. The Minority Game, in which agents try to choose the option of the minority side, is an appropriate tool to deal with these problems. The situation in the Upper Derwent Valley can be explained with economic game theories and the Minority Game. The two approaches mutually help to analyse the situation in the Upper Derwent Valley leading to the development of a stochastic Minority Game. The stochastic Minority Game was tested with an online game (questionnaire), which was played 3,886 times by response in all around the world. The practical part of this thesis examines the components of the stochastic Minority Game with the data collected around the Upper Derwent Valley. The main data was collected using a stated preference survey. Overall, 700 questionnaires were distributed and 323 of them were returned (i.e. a return rate of 46.1 %). In the practical part, the agent-based model has four sub modules: 1) Multinomial mixed logit model for mode choice, 2) Binary logit model for parking location choice, 3) Markov queue model for parking network, and 4) the Minority Game for parking congestion and learning. This simulation model produces comprehensive outputs including mode choices, congestion levels, and user utilities. The results show that the road user charging scheme reduces car demand in the Upper Derwent Valley and ensures a reduction in congestion at the parking areas. The model also shows that an exemption will increase the utilities of elderly visitors without substantially sacrificing those of younger visitors. In conclusion, the simulation model demonstrated that oversimplification in conventional approaches solely using discrete choice models gave significant biases when real world problems were analysed.
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Campbell, D. "Discrete choice experiments applied to the valuation of rural environmental landscape improvements." Thesis, Queen's University Belfast, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.438155.
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