Bestimmung von Präferenzen bei der Studiengangs- und Studienortwahl aus Sicht von Studierenden mittels Choice-Based Conjointanalyse

Diese Bachelorarbeit gliedert sich in einen theoretischen und einen praktischen Abschnitt. Zunächst werden Studien- und Berufswahlmodelle aus theoretischer Sicht betrachtet. Dabei ist festzuhalten, dass kein Ansatz existiert, der den komplexen Studienwahlprozess vollständig abbildet und erklärt. Jedoch ergänzen sich verschiedene Modelle, sodass alle bedeutenden Einflussfaktoren berücksichtigt sind. Ebenso die Conjointanalyse wird einer theoretischen Betrachtung unterzogen. Als eine Methode der Präferenzmessung wird dieses Analyseverfahren häufig eingesetzt, um die Vorziehenswürdigkeit von Produkten zu ermitteln. Sowohl im Bereich der Neuproduktentwicklung, als auch bei der Marktsegmentierung und der Preisfindung findet die Analyse Verwendung. Sehr charakteristisch für die Methodik ist, dass die Präferenzbeurteilung ganzheitlich für das Produkt erfolgt und nicht direkt einzelne Produkteigenschaften bei der Auskunftsperson abgefragt werden. Besonders relevant für diese Arbeit ist die Choice-Based Conjointanalyse. Die Vorziehenswürdigkeit von Konzepten werden basierend auf Auswahlentscheidungen von Probanden erfasst. Die Beweggründe bei der Studienortwahl aus Sicht der Studierenden an der Hochschule Anhalt werden im praktischen Abschnitt dieser Ausarbeitung mit Hilfe der Choice-Based Conjointanalyse untersucht. Dafür wurde ein Fragebogen entwickelt. Es konnte ermittelt werden, dass sowohl der Ruf der Hochschule, als auch die Heimatnähe und die Höhe des Semesterbeitrages bedeutende Einflussfaktoren bei der Studiengangwahl darstellen. Darüber hinaus werden Motive der Studiengangwahl analysiert. Festzuhalten ist, dass sowohl intrinsische Motive, aber auch extrinsische Motive von hoher Wichtigkeit sind.

New microfluidic-based sampling procedure for overcoming the hematocrit problem associated with dried blood spot analysis.

Hematocrit (Hct) is one of the most critical issues associated with the bioanalytical methods used for dried blood spot (DBS) sample analysis. Because Hct determines the viscosity of blood, it may affect the spreading of blood onto the filter paper. Hence, accurate quantitative data can only be obtained if the size of the paper filter extracted contains a fixed blood volume. We describe for the first time a microfluidic-based sampling procedure to enable accurate blood volume collection on commercially available DBS cards. The system allows the collection of a controlled volume of blood (e.g., 5 or 10 μL) within several seconds. Reproducibility of the sampling volume was examined in vivo on capillary blood by quantifying caffeine and paraxanthine on 5 different extracted DBS spots at two different time points and in vitro with a test compound, Mavoglurant, on 10 different spots at two Hct levels. Entire spots were extracted. In addition, the accuracy and precision (n = 3) data for the Mavoglurant quantitation in blood with Hct levels between 26% and 62% were evaluated. The interspot precision data were below 9.0%, which was equivalent to that of a manually spotted volume with a pipet. No Hct effect was observed in the quantitative results obtained for Hct levels from 26% to 62%. These data indicate that our microfluidic-based sampling procedure is accurate and precise and that the analysis of Mavoglurant is not affected by the Hct values. This provides a simple procedure for DBS sampling with a fixed volume of capillary blood, which could eliminate the recurrent Hct issue linked to DBS sample analysis.

Test result-based sampling: an efficient design for estimating the accuracy of patient safety indicators.

OBJECTIVE: Accuracy studies of Patient Safety Indicators (PSIs) are critical but limited by the large samples required due to low occurrence of most events. We tested a sampling design based on test results (verification-biased sampling [VBS]) that minimizes the number of subjects to be verified. METHODS: We considered 3 real PSIs, whose rates were calculated using 3 years of discharge data from a university hospital and a hypothetical screen of very rare events. Sample size estimates, based on the expected sensitivity and precision, were compared across 4 study designs: random and VBS, with and without constraints on the size of the population to be screened. RESULTS: Over sensitivities ranging from 0.3 to 0.7 and PSI prevalence levels ranging from 0.02 to 0.2, the optimal VBS strategy makes it possible to reduce sample size by up to 60% in comparison with simple random sampling. For PSI prevalence levels below 1%, the minimal sample size required was still over 5000. CONCLUSIONS: Verification-biased sampling permits substantial savings in the required sample size for PSI validation studies. However, sample sizes still need to be very large for many of the rarer PSIs.

Analysing the factors that influence tag choice based on semiotic analysis and activity theory

Social tagging has become very popular around the Internet as well as in research. The main idea behind tagging is to allow users to provide metadata to the web content from their perspective to facilitate categorization and retrieval. There are many factors that influence users' tag choice. Many studies have been conducted to reveal these factors by analysing tagging data. This paper uses two theories to identify these factors, namely the semiotics theory and activity theory. The former treats tags as signs and the latter treats tagging as an activity. The paper uses both theories to analyse tagging behaviour by explaining all aspects of a tagging system, including tags, tagging system components and the tagging activity. The theoretical analysis produced a framework that was used to identify a number of factors. These factors can be considered as categories that can be consulted to redirect user tagging choice in order to support particular tagging behaviour, such as cross-lingual tagging.

Aerosol inorganic composition at a tropical site: Discrepancies between filter-based sampling and a semi-continuous method

The concentrations of the water-soluble inorganic aerosol species, ammonium (NH4+), nitrate (NO3-), chloride (Cl-), and sulfate (SO42-), were measured from September to November 2002 at a pasture site in the Amazon Basin (Rondnia, Brazil) (LBA-SMOCC). Measurements were conducted using a semi-continuous technique (Wet-annular denuder/Steam-Jet Aerosol Collector: WAD/SJAC) and three integrating filter-based methods, namely (1) a denuder-filter pack (DFP: Teflon and impregnated Whatman filters), (2) a stacked-filter unit (SFU: polycarbonate filters), and (3) a High Volume dichotomous sampler (HiVol: quartz fiber filters). Measurements covered the late dry season (biomass burning), a transition period, and the onset of the wet season (clean conditions). Analyses of the particles collected on filters were performed using ion chromatography (IC) and Particle-Induced X-ray Emission spectrometry (PIXE). Season-dependent discrepancies were observed between the WAD/SJAC system and the filter-based samplers. During the dry season, when PM2.5 (D-p <= 2.5 mu m) concentrations were similar to 100 mu g m(-3), aerosol NH4+ and SO42- measured by the filter-based samplers were on average two times higher than those determined by the WAD/SJAC. Concentrations of aerosol NO3- and Cl- measured with the HiVol during daytime, and with the DFP during day- and nighttime also exceeded those of the WAD/SJAC by a factor of two. In contrast, aerosol NO3- and Cl- measured with the SFU during the dry season were nearly two times lower than those measured by the WAD/SJAC. These differences declined markedly during the transition period and towards the cleaner conditions during the onset of the wet season (PM2.5 similar to 5 mu g m(-3)); when filter-based samplers measured on average 40-90% less than the WAD/SJAC. The differences were not due to consistent systematic biases of the analytical techniques, but were apparently a result of prevailing environmental conditions and different sampling procedures. For the transition period and wet season, the significance of our results is reduced by a low number of data points. We argue that the observed differences are mainly attributable to (a) positive and negative filter sampling artifacts, (b) presence of organic compounds and organosulfates on filter substrates, and (c) a SJAC sampling efficiency of less than 100%.

Spatial methods for plot-based sampling of wildlife populations

Classical sampling methods can be used to estimate the mean of a finite or infinite population. Block kriging also estimates the mean, but of an infinite population in a continuous spatial domain. In this paper, I consider a finite population version of block kriging (FPBK) for plot-based sampling. The data are assumed to come from a spatial stochastic process. Minimizing mean-squared-prediction errors yields best linear unbiased predictions that are a finite population version of block kriging. FPBK has versions comparable to simple random sampling and stratified sampling, and includes the general linear model. This method has been tested for several years for moose surveys in Alaska, and an example is given where results are compared to stratified random sampling. In general, assuming a spatial model gives three main advantages over classical sampling: (1) FPBK is usually more precise than simple or stratified random sampling, (2) FPBK allows small area estimation, and (3) FPBK allows nonrandom sampling designs.

UNDERSTANDING CUSTOMER CHOICES IN SERVICE OUTSOURCING AND REVENUE MANAGEMENT

This dissertation investigates customer behavior modeling in service outsourcing and revenue management in the service sector (i.e., airline and hotel industries). In particular, it focuses on a common theme of improving firms’ strategic decisions through the understanding of customer preferences. Decisions concerning degrees of outsourcing, such as firms’ capacity choices, are important to performance outcomes. These choices are especially important in high-customer-contact services (e.g., airline industry) because of the characteristics of services: simultaneity of consumption and production, and intangibility and perishability of the offering. Essay 1 estimates how outsourcing affects customer choices and market share in the airline industry, and consequently the revenue implications from outsourcing. However, outsourcing decisions are typically endogenous. A firm may choose whether to outsource or not based on what a firm expects to be the best outcome. Essay 2 contributes to the literature by proposing a structural model which could capture a firm’s profit-maximizing decision-making behavior in a market. This makes possible the prediction of consequences (i.e., performance outcomes) of future strategic moves. Another emerging area in service operations management is revenue management. Choice-based revenue systems incorporate discrete choice models into traditional revenue management algorithms. To successfully implement a choice-based revenue system, it is necessary to estimate customer preferences as a valid input to optimization algorithms. The third essay investigates how to estimate customer preferences when part of the market is consistently unobserved. This issue is especially prominent in choice-based revenue management systems. Normally a firm only has its own observed purchases, while those customers who purchase from competitors or do not make purchases are unobserved. Most current estimation procedures depend on unrealistic assumptions about customer arriving. This study proposes a new estimation methodology, which does not require any prior knowledge about the customer arrival process and allows for arbitrary demand distributions. Compared with previous methods, this model performs superior when the true demand is highly variable.

The influence of sampling design on tree-ring-based quantification of forest growth

Tree-rings offer one of the few possibilities to empirically quantify and reconstruct forest growth dynamics over years to millennia. Contemporaneously with the growing scientific community employing tree-ring parameters, recent research has suggested that commonly applied sampling designs (i.e. how and which trees are selected for dendrochronological sampling) may introduce considerable biases in quantifications of forest responses to environmental change. To date, a systematic assessment of the consequences of sampling design on dendroecological and-climatological conclusions has not yet been performed. Here, we investigate potential biases by sampling a large population of trees and replicating diverse sampling designs. This is achieved by retroactively subsetting the population and specifically testing for biases emerging for climate reconstruction, growth response to climate variability, long-term growth trends, and quantification of forest productivity. We find that commonly applied sampling designs can impart systematic biases of varying magnitude to any type of tree-ring-based investigations, independent of the total number of samples considered. Quantifications of forest growth and productivity are particularly susceptible to biases, whereas growth responses to short-term climate variability are less affected by the choice of sampling design. The world's most frequently applied sampling design, focusing on dominant trees only, can bias absolute growth rates by up to 459% and trends in excess of 200%. Our findings challenge paradigms, where a subset of samples is typically considered to be representative for the entire population. The only two sampling strategies meeting the requirements for all types of investigations are the (i) sampling of all individuals within a fixed area; and (ii) fully randomized selection of trees. This result advertises the consistent implementation of a widely applicable sampling design to simultaneously reduce uncertainties in tree-ring-based quantifications of forest growth and increase the comparability of datasets beyond individual studies, investigators, laboratories, and geographical boundaries.

Prospective sampling based on model ensembles improves the detection of rare species

Identifying the geographic distribution of populations is a basic, yet crucial step in many fundamental and applied ecological projects, as it provides key information on which many subsequent analyses depend. However, this task is often costly and time consuming, especially where rare species are concerned and where most sampling designs generally prove inefficient. At the same time, rare species are those for which distribution data are most needed for their conservation to be effective. To enhance fieldwork sampling, model-based sampling (MBS) uses predictions from species distribution models: when looking for the species in areas of high habitat suitability, chances should be higher to find them. We thoroughly tested the efficiency of MBS by conducting an important survey in the Swiss Alps, assessing the detection rate of three rare and five common plant species. For each species, habitat suitability maps were produced following an ensemble modeling framework combining two spatial resolutions and two modeling techniques. We tested the efficiency of MBS and the accuracy of our models by sampling 240 sites in the field (30 sitesx8 species). Across all species, the MBS approach proved to be effective. In particular, the MBS design strictly led to the discovery of six sites of presence of one rare plant, increasing chances to find this species from 0 to 50%. For common species, MBS doubled the new population discovery rates as compared to random sampling. Habitat suitability maps coming from the combination of four individual modeling methods predicted well the species' distribution and more accurately than the individual models. As a conclusion, using MBS for fieldwork could efficiently help in increasing our knowledge of rare species distribution. More generally, we recommend using habitat suitability models to support conservation plans.

Efficiency of risk-based vs . random sampling for the monitoring of tetracycline residues in slaughtered calves in Switzerland

In all European Union countries, chemical residues are required to be routinely monitored in meat. Good farming and veterinary practice can prevent the contamination of meat with pharmaceutical substances, resulting in a low detection of drug residues through random sampling. An alternative approach is to target-monitor farms suspected of treating their animals with antimicrobials. The objective of this project was to assess, using a stochastic model, the efficiency of these two sampling strategies. The model integrated data on Swiss livestock as well as expert opinion and results from studies conducted in Switzerland. Risk-based sampling showed an increase in detection efficiency of up to 100% depending on the prevalence of contaminated herds. Sensitivity analysis of this model showed the importance of the accuracy of prior assumptions for conducting risk-based sampling. The resources gained by changing from random to risk-based sampling should be transferred to improving the quality of prior information.

Cuticular hydrocarbons of Drosophila birchii and D-serrata: Identification and role in mate choice in D-serrata

The cuticular hydrocarbon compositions of two sympatric species of Australian Drosophila in the montium subgroup of the melanogaster group that use cuticular hydrocarbons in mate recognition have been characterized. Drosophila birchii has 34 components in greater than trace amounts, with a carbon number range of C-20 to C-33. Drosophila serrata has 21 components above trace level and a carbon number range of C-24 to C-31. These two species share eight hydrocarbon components, with all but two of them being monoenes. For both species, the (Z)-9-monoenes are the predominant positional isomer. The hydrocarbons of D. birchii are n-alkanes, n-alkenes (Z)-5-, (Z)-7-, (Z)-9-, and (Z)-11-), low to trace levels of homologous (Z,Z)-7,11- and (Z,Z)-9,13-dienes; and trace amounts of (Z,Z)-5,9- C-25:2, a major component of D. serrata. Only one methyl branched hydrocarbon was detected (2-methyl C-28), and it occurred at very low levels. The hydrocarbons of D. serrata are dominated by a homologous series of (Z,Z)-5,9-dienes, and notably, are characterized by the apparent absence of n-alkanes. Homologous series of (Z)-5-, (Z)-7-, and (Z)-9- alkenes are also present in D. serrata as well as 2-methyl alkanes. Drosophila serrata females display strong directional mate choice based on male cuticular hydrocarbons and prefer D. serrata males with higher relative abundances of the 2-methyl alkanes, but lower relative abundances of (Z,Z)-5,9- C-24:2 and (Z)-9-C-25:1.

Anàlisi de la qualitat de l'aigua: estudi dels impactes humans sobre la qualitat de l'aigua en pous i basses del Parc del Garraf i rodalies

Amb la finalitat de conèixer l’estat de qualitat de les aigües de les basses i pous del Parc del Garraf, s’analitzen una sèrie de paràmetres fisico-químics en 17 estacions de mostreig prèviament seleccionades, distribuïdes en zones amb diferents tipologies d’ús del sòl. La base de l’anàlisi ha estat la integració d’informació provinent de diferents fonts. Mitjançant l’elaboració de taules i gràfics, la generació de cartografia i el tractament estadístic de les dades, s’ha procedit a la tria de punts de mostreig i s’ha obtingut un inventari que ha permès la interpretació global dels resultats, facilitant la diagnosi. El procés de tractament de dades inclou la confecció d’un índex de qualitat de les aigües (ICA) propi, no vinculant, a partir de fórmules genèriques de normalització i ponderació de valors. Durant la realització de la diagnosi s’han detectat pertorbacions puntuals en determinats paràmetres corresponents a contaminacions locals, en diferents estacions de mostreig. Aquestes pertorbacions s’han relacionat amb la situació dels pous i les basses al Garraf i les tipologies d’ús del sòl de cada zona. El diagnòstic de pertorbacions ha orientat les propostes de millora aplicables que s’han dividit en tres classes segons el nivell d’actuació. Aquestes incideixen principalment, en la millora de la informació disponible, l’aplicació de l’agricultura ecològica, l’explotació sostenible dels aqüífers i la realització d’estudis globals i/o locals, més complets i exhaustius.

Revenue management under general discrete choice model of consumer behavior

Customer choice behavior, such as 'buy-up' and 'buy-down', is an importantphe-nomenon in a wide range of industries. Yet there are few models ormethodologies available to exploit this phenomenon within yield managementsystems. We make some progress on filling this void. Specifically, wedevelop a model of yield management in which the buyers' behavior ismodeled explicitly using a multi-nomial logit model of demand. Thecontrol problem is to decide which subset of fare classes to offer ateach point in time. The set of open fare classes then affects the purchaseprobabilities for each class. We formulate a dynamic program todetermine the optimal control policy and show that it reduces to a dynamicnested allocation policy. Thus, the optimal choice-based policy caneasily be implemented in reservation systems that use nested allocationcontrols. We also develop an estimation procedure for our model based onthe expectation-maximization (EM) method that jointly estimates arrivalrates and choice model parameters when no-purchase outcomes areunobservable. Numerical results show that this combined optimization-estimation approach may significantly improve revenue performancerelative to traditional leg-based models that do not account for choicebehavior.

Portfolio choice beyond the traditional approach

This paper surveys asset allocation methods that extend the traditional approach. An important feature of the the traditional approach is that measures the risk and return tradeoff in terms of mean and variance of final wealth. However, there are also other important features that are not always made explicit in terms of investor s wealth, information, and horizon: The investor makes a single portfolio choice based only on the mean and variance of her final financial wealth and she knows the relevant parameters in that computation. First, the paper describes traditional portfolio choice based on four basic assumptions, while the rest of the sections extend those assumptions. Each section will describe the corresponding equilibrium implications in terms of portfolio advice and asset pricing.

School Choice and Student Screening in the Chilean Educational System: Who Chooses Whom?. The Case of the Catholic Education

The student´s screening made by schools corresponds to a regulatory mechanism for school inclusion and exclusion that normally overlaps the parental expectations of school choice. Based in "Parents survey 2006" data (n=188.073) generated by the Chilean Educational Ministry, this paper describe the parents reasons for choosing their children's school, and school´s criteria for screening students. It concludes that the catholic schools are the most selective institutions and usually exceed the capacity of parental choice. One of the reasons to select students would be the direct relationship between this practice and increasing the average score on the test of the Chilean Educational Quality Measurement System (SIMCE).