Invoice process analysis and development. Case: Power and automation technology company

This master’s thesis studies the case company’s current purchase invoice process and the challenges that are related to it. Like most of other master’s thesis this study consists of both theoretical- and empirical parts. The purpose of this work is to combine theoretical and empirical parts together so that the theoretical part brings value to the empirical case study. The case company’s main business is frequency converters for both low voltage AC & DC drives and medium voltage AC Drives which are used across all industries and applications. The main focus of this study is on the current invoice process modelling. When modelling the existing process with discipline and care, current challenges can be understood better. Empirical study relays heavily on interviews and existing, yet fragmented, data. This, along with own calculations and analysis, creates the foundation for the empirical part of this master’s thesis.

Dynamic Competitor Analysis Model Of Welding Quality Management Software

Tämä diplomityö arvioi hitsauksen laadunhallintaohjelmistomarkkinoiden kilpailijoita. Kilpailukenttä on uusi ja ei ole tarkkaa tietoa siitä minkälaisia kilpailijoita on markkinoilla. Hitsauksen laadunhallintaohjelmisto auttaa yrityksiä takaamaan korkean laadun. Ohjelmisto takaa korkean laadun varmistamalla, että hitsaaja on pätevä, hän noudattaa hitsausohjeita ja annettuja parametreja. Sen lisäksi ohjelmisto kerää kaiken tiedon hitsausprosessista ja luo siitä vaadittavat dokumentit. Diplomityön teoriaosuus muodostuu kirjallisuuskatsauksesta ratkaisuliike-toimintaan, kilpailija-analyysin ja kilpailuvoimien teoriaan sekä hitsauksen laadunhallintaan. Työn empiriaosuus on laadullinen tutkimus, jossa tutkitaan kilpailevia hitsauksen laadunhallintaohjelmistoja ja haastatellaan ohjelmistojen käyttäjiä. Diplomityön tuloksena saadaan uusi kilpailija-analyysimalli hitsauksen laadunhallintaohjelmistoille. Mallin avulla voidaan arvostella ohjelmistot niiden tarjoamien primääri- ja sekundääriominaisuuksien perusteella. Toiseksi tässä diplomityössä analysoidaan nykyinen kilpailijatilanne hyödyntämällä juuri kehitettyä kilpailija-analyysimallia.

Spectral Analysis of Symmetric and Anti-Symmetric Pairwise Kernels

This work investigates theoretical properties of symmetric and anti-symmetric kernels. First chapters give an overview of the theory of kernels used in supervised machine learning. Central focus is on the regularized least squares algorithm, which is motivated as a problem of function reconstruction through an abstract inverse problem. Brief review of reproducing kernel Hilbert spaces shows how kernels define an implicit hypothesis space with multiple equivalent characterizations and how this space may be modified by incorporating prior knowledge. Mathematical results of the abstract inverse problem, in particular spectral properties, pseudoinverse and regularization are recollected and then specialized to kernels. Symmetric and anti-symmetric kernels are applied in relation learning problems which incorporate prior knowledge that the relation is symmetric or anti-symmetric, respectively. Theoretical properties of these kernels are proved in a draft this thesis is based on and comprehensively referenced here. These proofs show that these kernels can be guaranteed to learn only symmetric or anti-symmetric relations, and they can learn any relations relative to the original kernel modified to learn only symmetric or anti-symmetric parts. Further results prove spectral properties of these kernels, central result being a simple inequality for the the trace of the estimator, also called the effective dimension. This quantity is used in learning bounds to guarantee smaller variance.

PERFORMANCE ANALYSIS OF A TACTICAL ASSET ALLOCATION – Evidence from the Black–Litterman model based fixed income portfolio

Over time the demand for quantitative portfolio management has increased among financial institutions but there is still a lack of practical tools. In 2008 EDHEC Risk and Asset Management Research Centre conducted a survey of European investment practices. It revealed that the majority of asset or fund management companies, pension funds and institutional investors do not use more sophisticated models to compensate the flaws of the Markowitz mean-variance portfolio optimization. Furthermore, tactical asset allocation managers employ a variety of methods to estimate return and risk of assets, but also need sophisticated portfolio management models to outperform their benchmarks. Recent development in portfolio management suggests that new innovations are slowly gaining ground, but still need to be studied carefully. This thesis tries to provide a practical tactical asset allocation (TAA) application to the Black–Litterman (B–L) approach and unbiased evaluation of B–L models’ qualities. Mean-variance framework, issues related to asset allocation decisions and return forecasting are examined carefully to uncover issues effecting active portfolio management. European fixed income data is employed in an empirical study that tries to reveal whether a B–L model based TAA portfolio is able outperform its strategic benchmark. The tactical asset allocation utilizes Vector Autoregressive (VAR) model to create return forecasts from lagged values of asset classes as well as economic variables. Sample data (31.12.1999–31.12.2012) is divided into two. In-sample data is used for calibrating a strategic portfolio and the out-of-sample period is for testing the tactical portfolio against the strategic benchmark. Results show that B–L model based tactical asset allocation outperforms the benchmark portfolio in terms of risk-adjusted return and mean excess return. The VAR-model is able to pick up the change in investor sentiment and the B–L model adjusts portfolio weights in a controlled manner. TAA portfolio shows promise especially in moderately shifting allocation to more risky assets while market is turning bullish, but without overweighting investments with high beta. Based on findings in thesis, Black–Litterman model offers a good platform for active asset managers to quantify their views on investments and implement their strategies. B–L model shows potential and offers interesting research avenues. However, success of tactical asset allocation is still highly dependent on the quality of input estimates.

Power and Performance Management Strategies on NoC-Based Multicore Platforms, Using DVFS, Adaptive Algorithm and Task Parallelism

This work presents synopsis of efficient strategies used in power managements for achieving the most economical power and energy consumption in multicore systems, FPGA and NoC Platforms. In this work, a practical approach was taken, in an effort to validate the significance of the proposed Adaptive Power Management Algorithm (APMA), proposed for system developed, for this thesis project. This system comprise arithmetic and logic unit, up and down counters, adder, state machine and multiplexer. The essence of carrying this project firstly, is to develop a system that will be used for this power management project. Secondly, to perform area and power synopsis of the system on these various scalable technology platforms, UMC 90nm nanotechnology 1.2v, UMC 90nm nanotechnology 1.32v and UMC 0.18 μmNanotechnology 1.80v, in order to examine the difference in area and power consumption of the system on the platforms. Thirdly, to explore various strategies that can be used to reducing system’s power consumption and to propose an adaptive power management algorithm that can be used to reduce the power consumption of the system. The strategies introduced in this work comprise Dynamic Voltage Frequency Scaling (DVFS) and task parallelism. After the system development, it was run on FPGA board, basically NoC Platforms and on these various technology platforms UMC 90nm nanotechnology1.2v, UMC 90nm nanotechnology 1.32v and UMC180 nm nanotechnology 1.80v, the system synthesis was successfully accomplished, the simulated result analysis shows that the system meets all functional requirements, the power consumption and the area utilization were recorded and analyzed in chapter 7 of this work. This work extensively reviewed various strategies for managing power consumption which were quantitative research works by many researchers and companies, it's a mixture of study analysis and experimented lab works, it condensed and presents the whole basic concepts of power management strategy from quality technical papers.

Opportunity Analysis and Category Management as a Base for Effective Indirect Sourcing

Hankintojen johtamisen kirjallisuus korostaa tehokkaan hankinnan olevan käypä keino tehostaa organisaation tulosta kokonaisvaltaisesti. Myös kasvava tietoisuus erityisesti epäsuorista hankintamenetelmistä ja työkaluista toimivat kannustimina tälle tutkimukselle. Tämän Pro Gradu -tutkimuksen päätarkoituksena on rakentaa kokonaisvaltainen ymmärrys epäsuorasta hankinnasta sekä löytää keinoja sen tehostamiseksi. Tutkimuksen tavoitteena on selvittää, miten globaali, monikansal- linen organisaatio voi parantaa kannattavuuttaan epäsuorissa hankinnoissa, sekä mitkä tekijät hankintastrategiassa vaikuttavat siihen. Tutkimus toteutettiin yksittäisenä tapaustutkimuksena suuren globaalin, monikan- sallisen yrityksen työntekijän näkökulmasta, Pääosa datasta pohjautuu vuonna 2015 toteutettuun Opportunity -analyysi projektiin, joka toteutettiin yhteistyössä ulkoisen konsulttifirman kanssa. Osa datasta pohjautuu puolistrukturoituihin haas- tatteluihin organisaation hankintajohtajan kanssa. Datan keruussa hyödynnettiin lisäksi henkilökohtaista havainnointia ja sekundääristä aineistoa organisaatiosta. Tämä Pro Gradu tutkimus on toteutettu kvalitatiivisella otteella, sisältäen joitakin kvantitatiivisia metodin piirteitä.

Catching up with competitiveness in emerging markets – An analysis of the role of the firm’s technology management strategies

Emerging markets have experienced rapid economic growth, and manufacturing firms have had to face the effects of globalisation. Some of the major emerging economies have been able to create a supportive business environment that fosters innovation, and China is a good example of a country that has been able to increase value-added investments. Conversely, when we look at Russia, another big emerging market, we witness a situation in which domestic firms struggle more with global competitiveness. Innovation has proven to be one of the most essential ingredients for firms aiming to grow and become more competitive. In emerging markets, the business environment sets many constraints for innovation. However, open strategic choices in new product development enable companies in emerging markets to expand their resource base and capability building. Networking and close inter-firm cooperation are essential in this regard. In this dissertation, I argue that technology transfer is one of the key tools for these companies to become internationally networked and to improve their competitiveness. It forces companies to reach outside the company and national borders, which in many cases, is a major challenge for firms in emerging markets. This dissertation focuses on how companies can catch up with competitiveness in emerging markets. The empirical studies included in the dissertation are based on analyses of survey data mainly of firms and their strategies in the Russian manufacturing industry. The dissertation contributes to the current strategic management literature by further investigating technology management strategies in manufacturing firms in emerging markets and the benefits of more open approaches to new product development and innovation.