The Pay-Off Method as a Tool for Evaluating the Risk and Profitability of Public Real Estate Investments

Real option valuation, in particular the fuzzy pay-off method, has proven to be useful in defining risk and visualizing imprecision of investments in various industry applications. This study examines whether the evaluation of risk and profitability for public real estate investments can be improved by using real option methodology. Firstly, the context of real option valuation in the real estate industry is examined. Further, an empirical case study is performed on 30 real estate investments of a Finnish government enterprise in order to determine whether the presently used investment analysis system can be complemented by the pay-off method. Despite challenges in the application of the pay-off method to the case company’s large investment base, real option valuation is found to create additional value and facilitate more robust risk analysis in public real estate applications.

A simple model for the estimation of congenital malformation frequency in racially mixed populations

A simple model is proposed, using the method of maximum likelihood to estimate malformation frequencies in racial groups based on data obtained from hospital services. This model uses the proportions of racial admixture, and the observed malformation frequency. It was applied to two defects: postaxial polydactyly and cleft lip, the frequencies of which are recognizedly heterogeneous among racial groups. The frequencies estimated in each racial group were those expected for these malformations, which proves the applicability of the method.

Sähkönsiirtoprojektien kustannuslaskennan kehittäminen

Tämän tutkimuksen tarkoituksena oli lisätä tietoa asiakasyrityksen voimajohto- ja sähköasemaliiketoimintayksiköiden tarjouslaskennan nykytilasta, etsiä ongelmakohtia ja kehittää ratkaisuja ongelmiin. Työn tuloksena saatu tieto on kyseisille liiketoimintayksiköille tärkeää tulevaisuuden kannattavuuden ja jatkuvuuden kannalta. Työn alun teoriaosuudessa esitellään Suomen sähkönsiirtojärjestelmä, käydään läpi voimajohto- ja sähköasemarakentamisen perusteet sekä esitellään kirjallisuuskatsaus projektiliiketoiminnasta. Teoriaosuutta hyödynnetään myöhemmissä tarkasteluissa joissa pyrittiin löytämään kustannuslaskennan ongelmia. Tutkimuksen tärkein tavoite oli löytää tämän hetkisen kustannuslaskennan ongelmakohdat. Tutkimukseen sisältyy tarjouslaskentaohjelmiston koekäyttö sekä sen analysointi. Työn lopputuloksena todetaan, ettei tarkasteltu ohjelma ole sopiva voimajohto- tai sähköasematarjouslaskennan toteutukseen. Ohjelma on laskentatarkkuudeltaan hyvä, mutta ohjelman käyttö hidastaa ja vaikeuttaa sekä laskennan että projektin talouden seurannan suorittamista. Lopputuloksissa todetaan myös erinäisiä pienempiä kehityskohteita tarjouslaskennan sujuvoittamiseksi ja sen tarkkuuden parantamiseksi. 

A priori estimation of accuracy and of the number of wells to be employed in limiting dilution assays

The use of limiting dilution assay (LDA) for assessing the frequency of responders in a cell population is a method extensively used by immunologists. A series of studies addressing the statistical method of choice in an LDA have been published. However, none of these studies has addressed the point of how many wells should be employed in a given assay. The objective of this study was to demonstrate how a researcher can predict the number of wells that should be employed in order to obtain results with a given accuracy, and, therefore, to help in choosing a better experimental design to fulfill one's expectations. We present the rationale underlying the expected relative error computation based on simple binomial distributions. A series of simulated in machina experiments were performed to test the validity of the a priori computation of expected errors, thus confirming the predictions. The step-by-step procedure of the relative error estimation is given. We also discuss the constraints under which an LDA must be performed.

The estimation of tuberculosis transmission parameters using ABC and MCMC methods

The aim of this work is to apply approximate Bayesian computation in combination with Marcov chain Monte Carlo methods in order to estimate the parameters of tuberculosis transmission. The methods are applied to San Francisco data and the results are compared with the outcomes of previous works. Moreover, a methodological idea with the aim to reduce computational time is also described. Despite the fact that this approach is proved to work in an appropriate way, further analysis is needed to understand and test its behaviour in different cases. Some related suggestions to its further enhancement are described in the corresponding chapter.

Profitability differences between online and offline retailers -An empirical study on European SMEs

Tämän pro gradu tutkielman tarkoituksena oli selvittää jos ja miten kannattavuus eroaa verkko- ja kivijalkakauppojen välillä. Lisäksi pyrittiin selvittämään onko näiden erojen syitä mahdollista selvittää yritysten taloudellisten tunnuslukujen avulla. Tutkielma koostuu kirjallisuuskatsauksesta ja kvantitatiivisesta tutkimuksesta. Kirjallisuuskatsaus antaa yleiskuvan siitä miten verkkokaupan toiminta eroaa kivijalkaliikkeen toiminnasta ja mitkä ovat näistä eroista koituvat hyödyt ja yleisimmät sudenkuopat. Kvantitatiivisessa tutkimuksessa käytetään Amadeus tietokannasta kerättyjä taloudellisia tietoja Eurooppalaisista verkko- ja kivijalkakaupoista. Tutkimuksessa löydettiin tilastollisesti merkitseviä eroja verkko- ja kivijalkakauppojen kannattavuudessa. Verkkokauppojen todettiin olevan kivijalkakauppoja kannattavampia, mutta taloudellisten tunnuslukujen tilastollisella analysoinnilla ei kyetty löytämään yksittäisiä selittäviä tekijöitä näille eroille.

Net working capital estimation model in project business

The objective of this Master’s thesis is to develop a model which estimates net working capital (NWC) monthly in a year period. The study is conducted by a constructive research which uses a case study. The estimation model is designed in the need of one case company which operates in project business. Net working capital components should be linked together by an automatic model and estimated individually, including advanced components of NWC for example POC receivables. Net working capital estimation model of this study contains three parts: output template, input template and calculation model. The output template gets estimate values automatically from the input template and the calculation model. Into the input template estimate values of more stable NWC components are inputted manually. The calculate model gets estimate values for major affecting components automatically from the systems of a company by using a historical data and made plans. As a precondition for the functionality of the estimation calculation is that sales are estimated in one year period because the sales are linked to all NWC components.

Power efficiency estimation and simulation of different control methods for the rotary screw compressor

Nowadays the energy efficiency has become one of the most concerned topics. Compressors are the equipment, which is very common in industry. Moreover, they tend to operate during long cycles and therefore even small decrease in power consumption can significantly reduce electricity costs during the year. And therefore it is important to investigate ways of increasing the energy efficiency of the compressors. In the thesis rotary screw compressor alongside with different control approaches is described. Simulation models for various control types of rotary screw compressor are developed. Analysis of laboratory equipment is conducted and results are compared with simulation. Suggestions of the real laboratory equipment improvement are given.

Effects of life cycle profits on the profitability of industrial heavy duty cranes

The goal of the thesis was to investigate how much after-sales profits a crane sale generates over the life cycle of the crane and the effects of these after-sales profits on the overall profitability of the crane. The thesis utilizes theories about life cycle costing from an equipment and service supplier’s point of view. However, instead of costs, the thesis is focused on the life cycle after-sales profits from maintenance services and spare parts provided for the sold crane. The case study approach was chosen and a total of five cranes from three different segments were investigated. An eight-step life cycle profit calculation model was developed in order to analyze the chosen cases’ life cycle profits systematically. The results of the investigation suggest that the life cycle after-sales profits are significant in value. In the case analyses they accounted for between 20% and 44% of the overall life cycle profits of the case cranes. The after-sales profits should be taken into account already in the pricing when offering a crane to a customer.

Fuzzy real option analysis in patent related decision making and patent valuation

The shift towards a knowledge-based economy has inevitably prompted the evolution of patent exploitation. Nowadays, patent is more than just a prevention tool for a company to block its competitors from developing rival technologies, but lies at the very heart of its strategy for value creation and is therefore strategically exploited for economic pro t and competitive advantage. Along with the evolution of patent exploitation, the demand for reliable and systematic patent valuation has also reached an unprecedented level. However, most of the quantitative approaches in use to assess patent could arguably fall into four categories and they are based solely on the conventional discounted cash flow analysis, whose usability and reliability in the context of patent valuation are greatly limited by five practical issues: the market illiquidity, the poor data availability, discriminatory cash-flow estimations, and its incapability to account for changing risk and managerial flexibility. This dissertation attempts to overcome these impeding barriers by rationalizing the use of two techniques, namely fuzzy set theory (aiming at the first three issues) and real option analysis (aiming at the last two). It commences with an investigation into the nature of the uncertainties inherent in patent cash flow estimation and claims that two levels of uncertainties must be properly accounted for. Further investigation reveals that both levels of uncertainties fall under the categorization of subjective uncertainty, which differs from objective uncertainty originating from inherent randomness in that uncertainties labelled as subjective are highly related to the behavioural aspects of decision making and are usually witnessed whenever human judgement, evaluation or reasoning is crucial to the system under consideration and there exists a lack of complete knowledge on its variables. Having clarified their nature, the application of fuzzy set theory in modelling patent-related uncertain quantities is effortlessly justified. The application of real option analysis to patent valuation is prompted by the fact that both patent application process and the subsequent patent exploitation (or commercialization) are subject to a wide range of decisions at multiple successive stages. In other words, both patent applicants and patentees are faced with a large variety of courses of action as to how their patent applications and granted patents can be managed. Since they have the right to run their projects actively, this flexibility has value and thus must be properly accounted for. Accordingly, an explicit identification of the types of managerial flexibility inherent in patent-related decision making problems and in patent valuation, and a discussion on how they could be interpreted in terms of real options are provided in this dissertation. Additionally, the use of the proposed techniques in practical applications is demonstrated by three fuzzy real option analysis based models. In particular, the pay-of method and the extended fuzzy Black-Scholes model are employed to investigate the profitability of a patent application project for a new process for the preparation of a gypsum-fibre composite and to justify the subsequent patent commercialization decision, respectively; a fuzzy binomial model is designed to reveal the economic potential of a patent licensing opportunity.

Estimation procedures affect the center of pressure frequency analysis

Even though frequency analysis of body sway is widely applied in clinical studies, the lack of standardized procedures concerning power spectrum estimation may provide unreliable descriptors. Stabilometric tests were applied to 35 subjects (20-51 years, 54-95 kg, 1.6-1.9 m) and the power spectral density function was estimated for the anterior-posterior center of pressure time series. The median frequency was compared between power spectra estimated according to signal partitioning, sampling rate, test duration, and detrending methods. The median frequency reliability for different test durations was assessed using the intraclass correlation coefficient. When increasing number of segments, shortening test duration or applying linear detrending, the median frequency values increased significantly up to 137%. Even the shortest test duration provided reliable estimates as observed with the intraclass coefficient (0.74-0.89 confidence interval for a single 20-s test). Clinical assessment of balance may benefit from a standardized protocol for center of pressure spectral analysis that provides an adequate relationship between resolution and variance. An algorithm to estimate center of pressure power density spectrum is also proposed.

A simple test of muscle coactivation estimation using electromyography

In numerous motor tasks, muscles around a joint act coactively to generate opposite torques. A variety of indexes based on electromyography signals have been presented in the literature to quantify muscle coactivation. However, it is not known how to estimate it reliably using such indexes. The goal of this study was to test the reliability of the estimation of muscle coactivation using electromyography. Isometric coactivation was obtained at various muscle activation levels. For this task, any coactivation measurement/index should present the maximal score (100% of coactivation). Two coactivation indexes were applied. In the first, the antagonistic muscle activity (the lower electromyographic signal between two muscles that generate opposite joint torques) is divided by the mean between the agonistic and antagonistic muscle activations. In the second, the ratio between antagonistic and agonistic muscle activation is calculated. Moreover, we computed these indexes considering different electromyographic amplitude normalization procedures. It was found that the first algorithm, with all signals normalized by their respective maximal voluntary coactivation, generates the index closest to the true value (100%), reaching 92 ± 6%. In contrast, the coactivation index value was 82 ± 12% when the second algorithm was applied and the electromyographic signal was not normalized (P < 0.04). The new finding of the present study is that muscle coactivation is more reliably estimated if the EMG signals are normalized by their respective maximal voluntary contraction obtained during maximal coactivation prior to dividing the antagonistic muscle activity by the mean between the agonistic and antagonistic muscle activations.

Comparison of Model-Based Flow Rate Estimation Methods in Frequency-Converter-Driven Pumps and Fans

Fluid handling systems such as pump and fan systems are found to have a significant potential for energy efficiency improvements. To deliver the energy saving potential, there is a need for easily implementable methods to monitor the system output. This is because information is needed to identify inefficient operation of the fluid handling system and to control the output of the pumping system according to process needs. Model-based pump or fan monitoring methods implemented in variable speed drives have proven to be able to give information on the system output without additional metering; however, the current model-based methods may not be usable or sufficiently accurate in the whole operation range of the fluid handling device. To apply model-based system monitoring in a wider selection of systems and to improve the accuracy of the monitoring, this paper proposes a new method for pump and fan output monitoring with variable-speed drives. The method uses a combination of already known operating point estimation methods. Laboratory measurements are used to verify the benefits and applicability of the improved estimation method, and the new method is compared with five previously introduced model-based estimation methods. According to the laboratory measurements, the new estimation method is the most accurate and reliable of the model-based estimation methods.