This dissertation consists of three essays in applied econometrics that analyze the strategic interactions between individuals and institutions. The first chapter examines the relationship between employee benefits and the performance of startups. Using national longitudinal data on startups, I find that an increase in the share of employee benefits in total compensation packages leads to increased productivity of startups. Results indicate that a 10 percent increase in the share of employee benefits leads to an increase ranging from 1.5 to 3.9 percent in productivity even if the returns to the employee benefits are heterogeneous across startups. I also find that an increase in the share of employee benefits increases the chance of survival of startups. The second chapter investigates the dynamics of employee screening and transitions from temporary to permanent employment. I analyze unique German data that contains specific information about the dynamics of the transition from temporary to permanent employment, I find that employers screen the abilities of employees only before they hire them. I find no evidence that employers screen the cognitive ability of employees during temporary employment. The third chapter examines the relationship between housing prices and the availability of curbside parking. Using a policy change in Istanbul as a quasi-experiment, this chapter explores the effect of Istanbul’s switch from informal and free curbside parking to formal and paid curbside parking on housing prices. In a differences-in-differences model coupled with a propensity score matching, we find that an exogenous change in the availability of parking leads to a statistically significant decrease in house prices. We estimate that house prices per square meter decrease by 13 percent in the neighborhoods where the city starts charging curbside parking spaces. However, rents stay the same compared to the other neighborhoods. / text

The time spent searching for a parking space increases air pollution, driver frustration, and safety problems impacting among other issues, traffic congestion and as consequence the environment. In the United States, parking represents a $20 billion industry (National Parking Association, 2005), and research shows that a car is parked on average 90 percent of the time. To alleviate this problem, more parking facilities should be built or intelligent models to better utilize current facilities should be explored. In this thesis, a general methodology is proposed to provide solutions to the parking problem. First, stated preference data is used to study drivers' choice/behavior. Parking choices are modeled as functions of arrival time, parking price, age, income and gender. The estimated values show that choice is relatively inelastic with respect to distance and more elastic with respect to price. The data is used to estimate the price elasticity that induces drivers to change their behavior. Second, neural networks are used to predict space availability using data provided by a parking facility. The model is compared with traditional forecasting models used in revenue management. Results show that neural networks are an effective tool to predict parking demand and perform better than traditional forecasting models. Third, the price elasticity that induces drivers to change their choice or behavior is determined. Finally, taking as an input the forecasting results obtained from the neural network and the price elasticity, parking spaces are optimally allocated at different price levels to optimize facility utilization and increase revenue. This research considers a parking facility network consisting of multiple parking lots with two, three and four fare classes and utilizes revenue management techniques as a mean to maximize revenue and to stimulate and diversify demand. The output indicates the number of parking spaces that should be made available for early booking to ensure full utilization of the parking lot, while at the same time attempting to secure as many full price parking spaces to ensure maximization of revenue.

published_or_final_version / Public Administration / Master / Master of Public Administration

Market research is becoming an increasingly important part of an airport's operational strategies as airport managers try to increase customer service and reach operational goals. This research applies conjoint analysis to investigate customer preferences for parking facilities and services at a major Canadian airport. This research will define and determine the relative importance of a set of attributes which influence business travelers' parking choice at the Vancouver International Airport. In addition, market segments for parking services will be identified. Sawtooth Software's Adaptive Conjoint Analysis and Ci2 were used in this study. A questionnaire was administered to a 36 employees among three local companies selected for data collection. Employees of these three companies represented potential local business travelers. This study was limited to the investigation of a subset of traveler (i.e. business traveler) preferences for parking at the Vancouver International Airport. More complete analysis would have to replicate the data collection procedures and target different users under different conditions (i.e. time of day, time of year, duration of stay). Results of the conjoint analysis indicated that price and distance to the terminal building account about equally for the majority of business travelers parking preference ratings (approximately two-thirds). The provision of video camera security was also an important determinant of customer preference. The provision of electronic signage providing guidance to available parking spaces did not contribute significantly to customer preference. In addition, the provision of a parkade rather than a surface lot contributed little to customer preference. Market share estimates were calculated for YVR's proposed Parkade, Main and Economy parking lots. Estimates of market shares suggested that a majority of business travelers taking an overnight journey in August preferred to park in the YVR Parkade. Market share estimates were also calculated for various service alternatives in the parkade. Comparing these additional estimates with the base service option revealed the trade-offs that business travelers were likely to make. Results anticipated approximately a 60 percent market share for the proposed parkade service despite charging a higher price ($6 per day higher than the alternative parking lots). Market share estimates predicted that the provision of video camera security and electronic signage in the parkade was significant in enabling a higher price. The predicted market share falls substantially to 28 percent if security and signage are not provided. Results also suggested that more travelers were willing to pay extra for the provision of video camera security than electronic signage in the parkade.

This dissertation formulates and develops models and solution approaches for plug-in electric vehicle (PEV) charging station installation. The models are formulated in the form of bilevel programming and stochastic programming problems, while a meta-heuristic method, genetic algorithm, and Monte Carlo bounding techniques are used to solve the problems. Demand for PEVs is increasing with the growing concerns about environment pollution, energy resources, and the economy. However, battery capacity in PEVs is still limited and represents one of the key barriers to a more widespread adoption of PEVs. It is expected that drivers who have long-distance commutes hesitate to replace their internal combustion engine vehicles with PEVs due to range anxiety. To address this concern, PEV infrastructure can be developed to provide re-fully status when they are needed. This dissertation is primarily focused on the development of mathematical models that can be used to support decisions regarding a charging station location and installation problem. The major parts of developing the models included identification of the problem, development of mathematical models in the form of bilevel and stochastic programming problems, and development of a solution approach using a meta-heuristic method. PEV parking building problem was formulated as a bilevel programming problem in order to consider interaction between transportation flow and a manager decisions, while the charging station installation problem was formulated as a stochastic programming problem in order to consider uncertainty in parameters. In order to find the best-quality solution, a genetic algorithm method was used because the formulation problems are NP-hard. In addition, the Monte Carlo bounding method was used to solve the stochastic program with continuous distributions. Managerial implications and recommendations for PEV parking building developers and managers were suggested in terms of sensitivity analysis. First, in the planning stage, the developer of the PEV parking building should consider long-term changes in future traffic flow and locate a PEV parking building closer to the node with the highest destination trip rate. Second, to attract more parking users, the operator needs to consider the walkability of walking links.

När en ny produkt lanseras på marknaden uppkommer det med stor sannolikhet brister som intetidigare upptäckts. Syftet med denna studie är att skapa en arbetsmodell för hur medelstora företagska hantera kvalitetsavvikelser som uppkommer inom produktion. För att skapa en realistisk modellför hur dessa kvalitetsavvikelser skall hanteras, baseras detta examensarbete på en fallstudie utfördpå ett tillverkande företag vid namn AQ ParkoPrint AB som är beläget i Gävle. Följande forskningsfrågor har besvarats för att understödja det huvudsakliga syftet: • Vilka kvalitetsavvikelser kan uppkomma inom medelstora företag? • Hur kan dessa kvalitetsavvikelser hanteras samt om möjligt reduceras? Metoderna som använts i studien är intervjuer och observationer. Fem intervjuer och tvåobservationer utfördes på AQ ParkoPrint AB. Den arbetsmodell som skapats kallas förfemstegsmodellen och innebär att processen för att hantera kvalitetsavvikelser delats upp i fem steg:dokumentera, utred, illustrera, forma åtgärdsförslag och genomför. Femstegsmodellen är utformadför medelstora tillverkande företag och inriktad på att skapa ett arbetssätt för systematiskt arbetemed hantering samt om möjligt reducering av kvalitetsbrister. Dessa steg är flexibla på det viset attvarje företag utformar egna åtgärdshanteringar och använder femstegsmodellen som grundstruktur idet fullständiga kvalitetsarbetet.Med hjälp av den utvecklade femstegsmodellen kan medelstora företag hantera och reducera sinakvalitetsbrister. Arbetsmodellen i sig kräver inga kostsamma verktyg utan det som styr kostnadernaär omfattningen av det arbete som läggs på samtliga steg.I denna studie presenteras även frågeställningar som företag kan arbeta utifrån för att reducerakvalitetsbrister som kan härledas till underleverantörer. Fallstudien påvisar att de kvalitetsavvikelsersom uppkommer troligtvis kan härledas till underleverantörerna. / When a new product is launched, product defects in various processes and process steps willprobably appear that were not previously known or detected. The purpose of this study is to create aworking model for how middle-sized companies should manage to handle defects in quality thatwill appear in manufacturing productions. To be able to create a realistic model, this thesis will bebased on a case study of a manufacturing company by the name of AQ ParkoPrint AB, located in Gävle, Sweden. The following research questions are answered in order to support the main purpose: • What defects in quality occur most often in middle-sized manufacturing companies? • How can these defects in quality be managed, and if possible, be reduced? The methods used in this study are interviews and observations. Five interviews and twoobservations were performed on AQ ParkoPrint AB. The working model that was created wasnamed “Five-step-model” and involves the process of managing defects in quality divided into fivesteps: document, investigate, illustrate, propose action and implement. The “Five-step model” isdesigned for middle-sized manufacturing companies focused on creating a way to worksystematically with how to managing quality defects and how to reduce them if possible. The stepsin this model are flexible because every single company should be able to customize each step tosuit their company needs, and only use the “Five-step model” that is created in this study as thebasic structure of the quality work. The case study shows that the suppliers are the majorcontributors of causing quality defects. Middle-sized companies can use the developed five stepmodel to handle and reduce their quality defects. The “Five-step model” itself requires no expensivetools. It is the extent of the work in every specific step that determines the costs.This study also presents some question formulations that companies can use to reduce their qualitydefects that can be traced back to the subcontractors.

Thesis (M.S.)--Texas State University--San Marcos, 2009. / Vita. Includes bibliographical references (leaves 52-54). Also available on microfilm.

L'environnement \textit{indoor} permet un grand nombre de services issus des technologies de l'information et de la communication. La localisation de l'utilisateur, via celle de son smartphone, est donc un élément-clé de cette réussite. Cette thèse s'intéresse au suivi des déplacements de l'utilisateur grâce aux capteurs de mouvement embarqués dans son smartphone. Elle repose sur la détermination du type de locomotion. Nous proposons une solution de navigation \textit{indoor} complète, permettant de proposer à l'utilisateur un chemin jusqu'à sa destination dans n'importe quel bâtiment tout en connaissant sa position à chaque instant, avec une précision de l'ordre du mètre. De façon analogue, nous avons également montré que nous pouvons déterminer le mode de transport d'un utilisateur pour une application de détection de places de parking libres. / Indoor environments present opportunities for a rich set of location-aware services in the information and communications technology (ICT) area. Therefore, accurately localizing a user indoors has become a key enabling technology. This thesis addresses the issue of tracking a user equipped with an off-the-shelf smartphone by exploiting its embedded motion sensors. Leveraging key characteristics of human locomotion, we propose a complete, infrastructure-free indoor navigation solution, allowing a user to navigate any unknown building with meter-level accuracy. Finally, extending our understanding of locomotion to outdoors areas where users are inside vehicles, we design and implement a smartphone application for smart on-street parking.

Parking a vehicle can often lead to frustration, air pollution and congestion due to limited availability of parking spaces. With increasing population density this problem can certainly increase unless addressed. Parking lots occupy large areas of scarce land resource therefore it is necessary to identify the driving behaviour in a parking lot to improve it further. This Paper tries study the driving behaviour in the parking lot and for this endeavours it conducted direct observation in three parking lots and used GPS data that was collected prior to this study by the University of Dalarna. To evaluate the driving behaviour in the parking lot direct observation was conducted to obtain overall indices of the parking lot vehicles movement. The parking route taken by the driver was compared with the optimal path to identify the driving behaviour in parking lot in terms of distance. The collected data was evaluated, filtered and analysed to identify the route, the distance and the time the vehicle takes to find a parking space. The outcome of the study shows that driving behaviour in the parking lots varies significantly among the parking user where most of the observed vehicles took unnecessary long time to complete their parking. The study shows that 56% of the 430 observed vehicles demonstrated inefficient driving behaviour as they took long driving path rather the than the optimal path. The study trace this behaviour to two factors, first, the absent of parking guidance in the parking lots and the second is the selectivity of the drivers when choosing the parking space. The study also shows that the ability of GPS data to identify the driving behaviour in the parking lots varies based on the time interval and the type of the device that is being used. The small the time interval the more accurate the GPS data in detecting the driving behaviour in the parking lots.

Kyoto University (京都大学) / 0048 / 新制・課程博士 / 博士(工学) / 甲第17536号 / 工博第3695号 / 新制||工||1562(附属図書館) / 30302 / 京都大学大学院工学研究科都市社会工学専攻 / (主査)教授 中川 大, 教授 藤井 聡, 准教授 松中 亮治 / 学位規則第4条第1項該当