Magíster en Gestión de Operaciones / Ingeniero Civil Industrial / El presente trabajo se centra en la confección de distintas metodologías de creación de ratings, mediante técnicas estadísticas para el ordenamiento de las selecciones de fútbol internacionales con el fin de mejorar el ya existente y conocido mundialmente Ranking FIFA. Los métodos utilizados en este trabajo integran los datos de partidos de fútbol entre selecciones adultas desde el año 2005 al 2013 y que permitieron la asignación de los cabezas de serie para el Mundial de fútbol acontecido en Brasil durante los meses de Junio y Julio del 2014. Para el estudio de las variables más importantes que determinan el resultado de un encuentro se utilizaron 4 modelos predictivos. El principal enfoque utilizado fue el uso de modelos Logit Multinomiales. El modelo que permita explicar de mejor manera la data utilizando el mínimo número de variables será la primera metodología que se utilizará como propuesta al ranking FIFA actual. El modelo de predicción que mejor se ajustó a la data fue el basado en 2 atributos: Diferencia de ranking entre los equipos, y el factor localía. De esta manera variables como pertenecer a cierta confederación o la localía continental no fueron incluidas en las propuestas finales. Además de lo recién señalado se realizan modificaciones estructurales al modelo FIFA existente, que permiten corregir ciertos defectos. Luego de proponer metodologías diferentes a la actual, se evalúan los resultados de cada una de ellas bajo métricas de comparación. Primero que todo se debe notar que una metodología será evaluada de acuerdo al ranking que de ella se desprenda. Estos rankings serán comparados mediante la métrica "mean squared error" (MSE) a partir de Rankings de Referencias. En la segunda parte de esta tesis se propone un modelo lineal que sea capaz de generar propuestas para mundiales con fase de grupos mucho más equilibradas que los que se han visto en las últimas ediciones mundialistas, en las cuales la disparidad en el nivel de los equipos intergrupos ha sido tema recurrente.

Master of Science / Department of Agricultural Economics / Jeffrey M. Peterson / Understanding irrigation water demand is vital to policy decisions concerning water scarcity. This thesis evaluates irrigation water-use responses to changes in prices, while accounting for cross-sectional characteristics of irrigators’ resource settings. An irrigator’s profit-maximizing decision is modeled in two stages. In the first stage, he decides which crop to plant, and in the second stage he decides how much water to apply given the crop choice. This thesis employs an econometric modeling technique not previously used in the irrigation water demand literature, a multinomial logit selectivity model. This econometric technique allows the intensive (change in water use for each crop in the short run) and extensive (change in water use in the long run due to changes in crop-choice) margin effects to be computed in a simultaneous equation system. A multinomial logit selectivity model has applications to many resource issues in production agriculture where the two-stage decision process is common. The model is estimated from field-level data on water use and crop-choice for a 25-county region in western Kansas over the period 1991-2004. Water use was found to be highly inelastic to the price of natural gas, but becomes more elastic as the price increases. The intensive margin effect was significant for natural gas price. The extensive margin effect only comprised half the total effect under high natural gas prices and was negligible for low prices. However, the extensive margin effect under high natural gas prices declined over time due to more efficient irrigation systems and improved crop varieties. The intensive margin effect explained most of the water use response from changes in other variables, including corn price. An increase in corn price has a negligible extensive margin effect because corn is most often substituted with alfalfa, which has a similar water requirement. Inelastic demand implies that policies aiming to conserve the Ogallala Aquifer by increasing the price of water will not accomplish their purpose and will affect irrigators’ incomes. More effective policies would be voluntary or mandatory quantity restrictions. However, efficient restrictions would need to account for spatial variation in the rate of depletion and the remaining saturated thickness.

Different types of business incubators have been established worldwide in the last decade. As the latest generation of incubation models, the accelerator provides a mix of services including mentorship, office space, access to the latest technology and a network of investors, with an aim to help ventures survive in the market. Meanwhile, startups are important to the society because they help balance the labor market and make contributions to the economic growth. The aim of this paper is to find the factors which best predict the success of new ventures based on characteristics of entrepreneurs and ventures. This research utilizes a case study of TechStars Accelerator and includes 640 startups from all industries and geographical regions which participated in the programs between 2007 and 2015. The analysis employs two statistical models, namely the Logit Model and the Ordinary Least Squares (OLS) Model. This study finds that technology intensive ventures founded by a team of entrepreneurs are more likely to succeed. Also, other variables such as the amount of funding, previous industry experience and location have a positive effect on the success of accelerator backed startups.

Aim of this application-oriented master's thesis is to prove a benefits from using data analysis techniques connected with geodata processing to support business decisions. As a conclusion two solutions are given which are more attractive then starting situation. Since the first solution proposed is oriented on giving maximum success ratio while considering transactions, the second one is oriented on business value of each transaction. In this thesis R programming language is widely used together with ArcGIS Online in its final part.

Magíster en Gestión de Operaciones. Ingeniero Civil Industrial / Los principales antecedentes y la motivación del presente trabajo provienen de la teoría de Assortment, los modelos de elección discreta y los procesos de Social Learning. Se apunta a reunir parte de la vasta literatura en torno a estos temas, proponiendo un modelo matemático que incorpore el feedback de los consumidores en la elección del surtido de productos a ofrecer por parte de un vendedor. El modelo propuesto incluye un comerciante minorista quien se enfrenta a una secuencia finita de clientes, los que tienen la opción de escoger alguno de los productos ofrecidos por el vendedor. En caso de comprar alguno, descubren su calidad y la reportan de manera pública, siendo esta información utilizada por futuros consumidores en su proceso de decisión mediante actualización bayesiana de sus creencias. Estos reportes a la vez permiten al retailer - quien sólo puede ofrecer una cantidad limitada de productos - optimizar su oferta, escogiendo aquel conjunto de alternativas que le entregue un mayor beneficio esperado. La manera natural para abordar el problema de optimización de assortment enfrentado por el vendedor es mediante Programación Dinámica Estocástica, al tratarse de una situación en tiempo discreto donde período a período se debe tomar una decisión ante un determinado estado del sistema. Sin embargo, el número de estados posibles aumenta explosivamente en función de los parámetros considerados, volviéndose un problema virtualmente imposible de resolver en instancias realistas. Es por ello que se opta por Programación Dinámica Aproximada, proponiéndose 3 heurísticas que permiten obtener resultados en contextos en los cuales no es posible optimizar de manera exacta. A modo de referencia, se compara el rendimiento de las heurísticas con el de una estrategia bajo la cual el vendedor no considera las evaluaciones hechas por los clientes, ni la incidencia de sus decisiones en períodos futuros. La diferencia en los beneficios llega a ser enorme, observándose en los experimentos realizados aumentos superiores a 300% al utilizar alguno de los algoritmos sugeridos, en vez de obviar la información disponible. Esto no solo valida la calidad de los métodos heurísticos propuestos, sino que sobre todo ilustra la importancia de considerar el feedback de los consumidores. / Este trabajo ha sido parcialmente financiado por CONICYT

Wind energy is expanding rapidly in the United States as the nation\'s energy policy objectives increasingly focus on renewables. Public opinion polls show that a majority of Americans support wind energy development but actual wind farm projects often face intense local opposition. This dichotomy between general support for wind energy but opposition towards siting a project nearby is often attributed to the not-in-my-backyard (NIMBY) phenomenon. In this study we employ a discrete choice experiment to investigate public preferences for different characteristics of a local wind farm. We investigate NIMBY by first controlling for characteristics that might cause local opposition, such as seeing or hearing a wind farm from home, and then after considering these effects of a wind farm we examine whether people who favor wind energy display NIMBY resistance. Finally, we estimate compensation requirements for siting a wind farm within sight or sound of someone\'s home. Results show that people who somewhat favor wind energy do display NIMBY attitudes since they are predisposed to vote against local wind development even after controlling whether they would see and hear the wind farm from their homes. We do not detect NIMBY attitudes among people who strongly favor wind energy because they have a positive disposition towards local wind farms. Our results suggest that if an incentive program is in place from the onset of a wind development project it could offset NIMBY reactions to specific projects. / Master of Science

No description available.

This study analyzed preferences for wetland-loss prevention in coastal Louisiana. Data were obtained through a contingent-valuation mail survey of a random sample of Louisiana households. Results, based on 511 responses, indicate that respondents have a strong preference for a short-run program (72.41% chose this program over a long-run program or no action). Respondents that had higher incomes, were white, had prior knowledge of ongoing restoration efforts, and had confidence in government were more likely to support some program relative to no action, as were those citing hurricane, environmental, and/or climate-change protection as their primary concern. Older respondents and those with negative perceptions of climate change were more likely to prefer the short-run over the long-run program. Median net present value of willingness to pay (assuming 18.37% discount rate) was estimated at $17,491 per household for the multinomial logit model and $3,307 under the Turnbull lower-bound method.

Harvesting woody biomass for biofuel has become an important research topic. In Mississippi, feasibility of utilizing woody biomass for bioenergy lies in the willingness to harvest by non-industrial private forest (NIPF) landowners, who control 71% of forestlands. A mail survey of Mississippi NIPF landowners elicited preferences concerning utilizing logging residues for bioenergy. When presented with hypothetical situations that compared bioenergy utilization attributes along with those of standard harvesting practices, more landowners preferred the bioenergy scenarios, even when more money was offered for standard harvesting. Older landowners with larger landholdings were less likely to prefer bioenergy scenarios. Higher educated landowners who were financially motivated, concerned with climate change, and considered habitat management an important goal were more likely to prefer bioenergy scenarios over standard harvesting. Available markets for logging residues could increase NIPF harvest rates based solely on the different harvesting attributes, which should increase availability of feedstocks for producers.

The purpose of this thesis was to evaluate the impact of dynamic message signs (DMS) on the Orlando-Orange County Expressway Authority (OOCEA) toll road network using the Pre-Deployment DMS Survey (henceforth referred to as "pre-deployment survey"). DMS are electronic traffic signs used on roadways to give travelers information about travel times, traffic congestion, accidents, disabled vehicles, AMBER alerts, and special events. The particular DMS referred to in this study are large rectangular signs installed over the travel lanes and these are not the portable trailer mount signs. The OOCEA is currently in the process of adding several fixed DMS on their toll road network. Between January 2007 and February 2008, approximately 30 DMS are planned on their network. It is important to note that there was one DMS sign on the OOCEA network before this study started. Since most of the travelers on OOCEA toll roads are from Orange, Osceola and Seminole counties, this study is limited to these counties. This thesis documents the results of pre-deployment analysis. The instrument used to analyze the travelers' perception of DMS was a survey that utilized computer aided telephone interviews. The pre-deployment survey was conducted during early November of 2006. Questions pertaining to the acknowledgement of DMS on the OOCEA toll roads, satisfaction with travel information provided on the network, formatting of the messages, satisfaction with different types of messages, diversion questions (Revealed and Stated preferences), and classification/socioeconomic questions (such as age, education, most used toll road, and county of residence) were asked to the respondents. The results of the pre-deployment analysis showed that 54.4% of the OOCEA travelers recalled seeing DMS on the network. The respondents commonly agreed that the DMS are helpful for providing information about hazardous conditions, and that the DMS are easy to read. The majority of the travelers preferred DMS formats as a steady message for normal traffic conditions, and use of commonly recognized abbreviations such as I-Drive for International Drive. The results from the binary logit model for "satisfaction with travel information provided on OOCEA toll road network" display the significant variables that explain the likelihood of the traveler being satisfied. The results from the coefficients show that infrequent travelers are more likely to be satisfied with traveler information on OOCEA toll roads. In addition, the provision of hazard warnings, special event information, and accuracy of information on DMS are associated with higher levels of satisfaction with traveler information. The binary logit model for "Revealed Preference (RP)" diversion behavior showed that Seminole County travelers were likely to stay on the toll road, and SR 408 travelers were likely to divert off the toll road. The travelers who acknowledged DMS on the OOCEA network were also likely to divert off the toll road, but those who learned of the congestion by DMS were likely to stay on the toll road. Learning of congestion by DMS could encourage travelers to stay, since when they are on the toll roads, diversion at times could be difficult with no access to exits or little knowledge of alternate routes. But it is also possible that travelers stayed because their perception was that the toll roads are faster, especially when messages on DMS show travel times that confirm the travelers' belief. Travelers who were not satisfied with travel information on the network were more likely to divert off the toll road. The implications for implementation of these results are discussed in this thesis. DMS should be formatted as a steady message for normal traffic conditions. Commonly recognized abbreviations, such as I-Drive for International Drive, must be used for roadway identification when possible. DMS messages should be pertained to information on roadway hazards when necessary because it was found that travelers find it important to be informed on events that are related to their personal safety. Accuracy of information provided on DMS was important for traveler information satisfaction because if the travelers observe inaccurate travel times on DMS, they may not trust the validity of future messages. DMS information that led to the travelers canceling their intended stops led to a higher likelihood of them being dissatisfied with traveler information. It is important to meet the travelers' preferences and concerns for DMS.