Suomalaisten teollisuuden kunnossapitoyritysten investoinnit: analyysi ja skenaariot

Työn tavoitteena oli lisätä ymmärrystä teollisuuden kunnossapidon toimialasta ja sen tulevaisuudesta, tutkimalla teollisuuden kunnossapitoyritysten toteuttamia käyttöomaisuus- ja käyttöpääomainvestointeja vuosilta 2003–2007. Tutkimus toteutettiin tilinpää-tösanalyysin menetelmin suppealla, mutta edustavalla, 20 teollisuuden kunnossapitoyrityksen tilinpäätösaineistolla. Yritysjoukko jaettiin pk-yrityksiin ja suuriin yrityksiin, jolla pyrittiin kuvaamaan toimialan todellisempaa rakennetta. Analyysiosiossa tarkasteltiin toteutuneita investointiasteita, investointilogiikoita, yritysten kannattavuuksia sekä käyttöpääomainvestointien hallintaa. Toteutetun analyysin perusteella luotiin kolme tulevaisuuden skenaariota teollisuuden kunnossapidon toimi-alan kehitykselle. Eri skenaarioille laskettiin ennustemallilla keskimääräiset investointiasteet. Analyysin mukaan teollisuuden kunnossapitoyrityksien liikevaihto kasvoi tutkimusaikavälillä keskimäärin noin 8,5 prosenttia vuodessa. Kyseinen kasvu on vaatinut yrityksiltä noin 2,5 prosentin investointiasteen. Verratessa pk-yrityksiä ja isoja yrityksiä, havaittiin merkittäviä eroja toteutuneissa investointiasteissa sekä investointilogiikoissa. Yhteistä yritysjoukoille oli hyvä kannattavuus, johon eri investointiasteilla ei näyttäisi lyhyellä aikavälillä olevan vaikutusta. Tulevaisuuden investointitarve vaikuttaa maltillisemmalta kuin toteutunut taso, johtuen osaltaan taantuman vaikutuksista.

Financial integration and TARGET2-Securities – A stakeholder approach

The purpose of this study was to analyze how different stakeholders, such as the European Central Bank, the European Commission, the European Central Securities Depositories Association, the Bank of International Settlements and the International Monetary Fund, have influenced the European financial integration in the area of securities clearing and settlement since the introduction of the single currency. The results show that the contribution differs from stakeholder to another and can take the form of standards and recommendations, legislation, research and publications, risk analysis etc. The Eurosystem has been particularly active in this area by proving and planning central bank services, such as TARGET2, CCMB2 and T2S. Along the way the development has and continues to face challenges that need to be solved by European authorities. Coordination is a key factor for the future as we have seen during the recent financial turmoil.

Time-series forecasting of pollutant concentration levels using particle swarm optimization and artificial neural networks

This study evaluates the application of an intelligent hybrid system for time-series forecasting of atmospheric pollutant concentration levels. The proposed method consists of an artificial neural network combined with a particle swarm optimization algorithm. The method not only searches relevant time lags for the correct characterization of the time series, but also determines the best neural network architecture. An experimental analysis is performed using four real time series and the results are shown in terms of six performance measures. The experimental results demonstrate that the proposed methodology achieves a fair prediction of the presented pollutant time series by using compact networks.

Improving demand forecasting practices in the industrial context

Demand forecasting is one of the fundamental managerial tasks. Most companies do not know their future demands, so they have to make plans based on demand forecasts. The literature offers many methods and approaches for producing forecasts. When selecting the forecasting approach, companies need to estimate the benefits provided by particular methods, as well as the resources that applying the methods call for. Former literature points out that even though many forecasting methods are available, selecting a suitable approach and implementing and managing it is a complex cross-functional matter. However, research that focuses on the managerial side of forecasting is relatively rare. This thesis explores the managerial problems that are involved when demand forecasting methods are applied in a context where a company produces products for other manufacturing companies. Industrial companies have some characteristics that differ from consumer companies, e.g. typically a lower number of customers and closer relationships with customers than in consumer companies. The research questions of this thesis are: 1. What kind of challenges are there in organizing an adequate forecasting process in the industrial context? 2. What kind of tools of analysis can be utilized to support the improvement of the forecasting process? The main methodological approach in this study is design science, where the main objective is to develop tentative solutions to real-life problems. The research data has been collected from two organizations. Managerial problems in organizing demand forecasting can be found in four interlinked areas: 1. defining the operational environment for forecasting, 2. defining the forecasting methods, 3. defining the organizational responsibilities, and 4. defining the forecasting performance measurement process. In all these areas, examples of managerial problems are described, and approaches for mitigating these problems are outlined.

Financial and Environmental Impacts of a Dry Port to Facilitate Competitiveness of Two Major Transit Seaports of Finland

Environmental problems and issues have received more and more attention during the last decades. Reasons for this are different increased external costs such as congestion, CO2 emission, noise and accident costs. Transportation sector is the only sector with increasing external costs. The EU will increase its attention in decreasing the external costs of transport. Aim of this research was to find out if a dry port solution could decrease costs of transport, especially external costs. Dry port concept is an intermodal transport system, where inland transport between port and dry port is performed by rail transport instead of traditional road transport. In addition, dry ports offer similar services as ports. Research is conducted by performing a literature review about dry port concept and costs of transport, especially external costs of transport. Financial and environmental impacts of the dry port concept are studied by comparing costs of road and rail transport by cost accounting and with a simulation model. Location of dry port is researched with gravitational models. Results of the literature review are that rail transport is environmentally friendlier mode of transport than road transport. Cost model and simulation model show that if only costs of freight movement are considered, rail transport is more inexpensive transport mode than road transport in terms of internal and external costs. Because of that dry port concept could decrease costs of transport, especially external costs. Results of gravitational models are that city of Kouvola is in a good position to be a dry port. Russian transit traffic through Finland improves location of Kouvola to be a dry port.

The determination of EONIA rate: The impact of the financial crisis and the effects of the changes in the monetary policy implementation framework

EONIA is a market based overnight interest rate, whose role as the starting point of the yield curve makes it critical from the perspective of the implementation of European Central Bank´s common monetary policy in the euro area. The financial crisis that started in 2007 had a large impact on the determination mechanism of this interest rate, which is considered as the central bank´s operational target. This thesis examines the monetary policy implementation framework of the European Central Bank and changes made to it. Furthermore, we discuss the development of the recent turmoil in the money market. EONIA rate is modelled by means of a regression equation using variables related to liquidity conditions, refinancing need, auction results and calendar effects. Conditional volatility is captured by an EGARCH model, and autocorrelation is taken into account by employing an autoregressive structure. The results highlight how the tensions in the initial stage of the market turmoil were successfully countered by ECB´s liquidity policy. The subsequent response of EONIA to liquidity conditions under the full allotment liquidity provision procedure adopted after the demise of Lehman Brothers is also established. A clear distinction in the behavior of the interest rate between the sub-periods was evident. In the light of the results obtained, some of the challenges posed by the exit-strategy implementation will be addressed.

Determinants of credit default swap spread, the effect of the financial crisis in the us markets

The purpose of this study is to define what determinants affect the Credit spread. There are two theoretical frameworks to study this: structural models and reduced form models. Structural models indicate that the main determinants are company leverage, volatility and risk-free interest rate, and other market and firm-specific variables. The purpose is to determine which of these theoretical determinants can explain the CDS spread and also how these theoretical determinants are affected by the financial crisis in 2007. The data is collected from 30 companies in the US Markets, mainly S&P Large Cap. The sample time-frame is 31.1.2004 – 31.12.2009. Empirical studies indicate that structural models can explain the CDS spreads well. Also, there were significant differences between bear and bull markets. The main determinants explaining CDS spreads were leverage and volatility. The other determinants were significant, depending on the sample period. However, these other variables did not explain the spread consistently.

Determinants of cash holdings in Finnish industrial sector: measuring the impact of financial crisis 2007- 2010

This thesis studies cash and short term investments to net assets ratio of Finnish industrial companies during financial crisis, and how different firm specific and macro economical variables affect cash and short term investments. The data consists of quarter level interim reports. Regression analysis was used to find out the effects of different variables. Regression models were formed based on previous studies on cash holdings. It was found that firms studied held more cash during financial crisis than before it. Cash and short-term investments acted as substitute of net working capital. Leverage had a positive and significant relationship to cash and short term investment ratio. It was also found out that firms have a target cash and short term investments ratio.

Financial performance of segments in the intelligent home network

The goal of this study is to examine the intelligent home business network in order to determine which part of the network has the best financial abilities to produce new business models and products/services by using financial statement analysis. A group of 377 studied limited companies is divided into four examined segments based on their offering in producing intelligent homes. The segments are customer service providers, system integrators, subsystem suppliers and component suppliers. Eight different key figures are calculated from each of the companies to get a comprehensive view of their financial performances, after which each of the segments is studied statistically to determine the performances of the whole segments. The actual performance differences between the segments are calculated by using the multi-criteria decision analysis method in which the performances of the key figures are graded and each key figure is weighted according to its importance for the goal of the study. The results of this analysis showed that subsystem suppliers have the best financial performance. Second best are system integrators, third are customer service providers and fourth component suppliers. None of the segments were strikingly poor, but even component suppliers were rather reasonable in their performance; so, it can be said that no part of the intelligent home business network has remarkably inadequate financial abilities to develop new business models and products/services.

IT Financial Management In a Large Industrial Company

IT Service Management plays a key role in many IT organizations today. First IT Service Management principles founded in the early 1980s but the real adaption emerged in the end 2000s. IT Financial Management is one of IT Service Management’s processes. The main purpose of this thesis was study how IT Financial Management approach can be improved in a case company. Budgeting, accounting and charging are IT Financial Management functions. These functions are researched in this thesis. Thesis materials consist of both qualitative and quantitative material. The theoretical part consists mostly of IT Service Management literature while interviews and the case company’s information systems are researched in the empirical part. Thesis also reviews different kind of the systems which supports and automates IT Financial Management functions. The biggest challenge is the cost allocation with the current ERP system in the case company. It is worth to take group based system for allocation in use before there is a holistic system in a market. The case company should also develop its IT service processes forward.

Rullaava ennustaminen talousohjauksen välineenä

Kiinnostus rullaavaa ennustamista kohtaan on kasvanut 2000-luvulla sen tarjotessa vaihtoehdon perinteiselle budjetoinnille. Rullaavasta ennustamisesta ei ole kuitenkaan tehty viimeisimpiin tietoihin perustuvaa tutkielmaa, jossa yhdistetään analyyttisesti uusinta tutkimus- ja kirjallisuustietoa. Tämän lisäksi rullaavaan ennustamiseen liittyvä termistö ei ole vakiintunutta, eikä termistöä ole tutkittu tai vertailtu. Nopeasti muuttuvassa liiketoimintaympäristössä perinteinen budjetointi ei enää vastaa siihen tarpeeseen, mihin se on tarkoitettu. Kritiikki budjetointia kohtaan on kasvanut mutta edelleen suurin osa yrityksistä käyttää sitä talousohjauksessa. Perinteinen budjetointi koetaan kalliiksi, aikaa vieväksi sekä irralliseksi strategiasta. Lisäksi se ei ota huomioon muuttuvaa ympäristöä ja on usein vanhentunut jo käyttöönotettaessa. Näitä budjetoinnin heikkouksia voidaan poistaa ottamalla käyttöön rullaava ennustaminen talousohjauksen välineenä. Rullaavassa ennustamisessa on kyse siirtymisestä kiinteästä budjettivuodesta esimerkiksi neljännesvuosittain ylemmällä tasolla tapahtuvaan ennustamiseen ennusteajanjakson ulottuessa aina seuraavalle vuodelle. Rullaavaa ennustamista voidaan käyttää budjetoinnin ohella, mikä on tutkimusten mukaan selvästi suosituin menetelmä. Toinen vaihtoehto on korvata perinteinen budjetointi rullaavalla ennustamisella. Tällöin prosessia kutsutaan rullaavaksi budjetoinniksi tai suunnitteluksi. Kolmas vaihtoehto on budjetoinnin hylkääminen ja uusien taloudenohjauksen ja prosessien soveltaminen eli Beyond Budgeting. Tämä korostaa budjetoinnin hylkäämisen lisäksi suorituskyvyn mittaamista ja palkitsemista suhteellisiin tuloksiin ja ulkoiseen sekä sisäiseen vertailuun perustuen sekä vallan hajauttamista organisaatiossa tavoitteena asiakasarvon kasvattaminen.

From Fluid Dynamics to Human Psychology.What Drives Financial Markets Towards Extreme Events

For decades researchers have been trying to build models that would help understand price performance in financial markets and, therefore, to be able to forecast future prices. However, any econometric approaches have notoriously failed in predicting extreme events in markets. At the end of 20th century, market specialists started to admit that the reasons for economy meltdowns may originate as much in rational actions of traders as in human psychology. The latter forces have been described as trading biases, also known as animal spirits. This study aims at expressing in mathematical form some of the basic trading biases as well as the idea of market momentum and, therefore, reconstructing the dynamics of prices in financial markets. It is proposed through a novel family of models originating in population and fluid dynamics, applied to an electricity spot price time series. The main goal of this work is to investigate via numerical solutions how well theequations succeed in reproducing the real market time series properties, especially those that seemingly contradict standard assumptions of neoclassical economic theory, in particular the Efficient Market Hypothesis. The results show that the proposed model is able to generate price realizations that closely reproduce the behaviour and statistics of the original electricity spot price. That is achieved in all price levels, from small and medium-range variations to price spikes. The latter were generated from price dynamics and market momentum, without superimposing jump processes in the model. In the light of the presented results, it seems that the latest assumptions about human psychology and market momentum ruling market dynamics may be true. Therefore, other commodity markets should be analyzed with this model as well.

Financial losses in pork supply chain: a study of the pre-slaughter handling impacts

Brazil is amongst the world’s largest swine producers. However, its competitiveness has been vulnerable due to a lack of cooperation between the supply chain players. This condition makes the financial losses to be evaluated taking into account only an individual node, and most of the time, these damages are imputed by swine breeders. Living weight losses occur between the farm to slaughterhouses, and the main cause of these losses is the pre-slaughter handling, especially during animal transportation. In this research, we analyzed the pre-slaughter handling in a swine farm in Brasilândia, MS, Brazil. Analyzed data were provided by five slaughterhouses (farm clients) from the studied region, in which it was considered living weight losses, carcass bruising, animal injury, and death rate. The results indicated that total financial losses represent 160 thousand dollars per year, when taking into account the supply chain management.