Decision making and decision support in service systems

This thesis is a literature study that develops a conceptual model of decision making and decision support in service systems. The study is related to the Ä-Logi, Intelligent Service Logic for Welfare Sector Services research project, and the objective of the study is to develop the necessary theoretical framework to enable further research based on the research project results and material. The study first examines the concepts of service and service systems, focusing on understanding the characteristics of service systems and their implications for decision making and decision support to provide the basis for the development of the conceptual model. Based on the identified service system characteristics, an integrated model of service systems is proposed that views service systems through a number of interrelated perspectives that each offer different, but complementary, implications on the nature of decision making and the requirements for decision support in service systems. Based on the model, it is proposed that different types of decision making contexts can be identified in service systems that may be dominated by different types of decision making processes and where different types of decision support may be required, depending on the characteristics of the decision making context and its decision making processes. The proposed conceptual model of decision making and decision support in service systems examines the characteristics of decision making contexts and processes in service systems, and their typical requirements for decision support. First, a characterization of different types of decision making contexts in service systems is proposed based on the Cynefin framework and the identified service system characteristics. Second, the nature of decision making processes in service systems is proposed to be dual, with both rational and naturalistic decision making processes existing in service systems, and having an important and complementary role in decision making in service systems. Finally, a characterization of typical requirements for decision support in service systems is proposed that examines the decision support requirements associated with different types of decision making processes in characteristically different types of decision making contexts. It is proposed that decision support for the decision making processes that are based on rational decision making can be based on organizational decision support models, while decision support for the decision making processes that are based on naturalistic decision making should be based on supporting the decision makers’ situation awareness and facilitating the development of their tacit knowledge of the system and its tasks. Based on the proposed conceptual model a further research process is proposed. The study additionally provides a number of new perspectives on the characteristics of service systems, and the nature of decision making and requirements for decision support in service systems that can potentially provide a basis for further discussion and research, and support the practice alike.

Analyzing the Effects of the New Renewable Energy Policy in Russia on Investments into Wind, Solar and Small Hydro Power

This thesis presents an analysis of recently enacted Russian renewable energy policy based on capacity mechanism. Considering its novelty and poor coverage by academic literature, the aim of the thesis is to analyze capacity mechanism influence on investors’ decision-making process. The current research introduces a number of approaches to investment analysis. Firstly, classical financial model was built with Microsoft Excel® and crisp efficiency indicators such as net present value were determined. Secondly, sensitivity analysis was performed to understand different factors influence on project profitability. Thirdly, Datar-Mathews method was applied that by means of Monte Carlo simulation realized with Matlab Simulink®, disclosed all possible outcomes of investment project and enabled real option thinking. Fourthly, previous analysis was duplicated by fuzzy pay-off method with Microsoft Excel®. Finally, decision-making process under capacity mechanism was illustrated with decision tree. Capacity remuneration paid within 15 years is calculated individually for each RE project as variable annuity that guarantees a particular return on investment adjusted on changes in national interest rates. Analysis results indicate that capacity mechanism creates a real option to invest in renewable energy project by ensuring project profitability regardless of market conditions if project-internal factors are managed properly. The latter includes keeping capital expenditures within set limits, production performance higher than 75% of target indicators, and fulfilling localization requirement, implying producing equipment and services within the country. Occurrence of real option shapes decision-making process in the following way. Initially, investor should define appropriate location for a planned power plant where high production performance can be achieved, and lock in this location in case of competition. After, investor should wait until capital cost limit and localization requirement can be met, after that decision to invest can be made without any risk to project profitability. With respect to technology kind, investment into solar PV power plant is more attractive than into wind or small hydro power, since it has higher weighted net present value and lower standard deviation. However, it does not change decision-making strategy that remains the same for each technology type. Fuzzy pay-method proved its ability to disclose the same patterns of information as Monte Carlo simulation. Being effective in investment analysis under uncertainty and easy in use, it can be recommended as sufficient analytical tool to investors and researchers. Apart from described results, this thesis contributes to the academic literature by detailed description of capacity price calculation for renewable energy that was not available in English before. With respect to methodology novelty, such advanced approaches as Datar-Mathews method and fuzzy pay-off method are applied on the top of investment profitability model that incorporates capacity remuneration calculation as well. Comparison of effects of two different RE supporting schemes, namely Russian capacity mechanism and feed-in premium, contributes to policy comparative studies and exhibits useful inferences for researchers and policymakers. Limitations of this research are simplification of assumptions to country-average level that restricts our ability to analyze renewable energy investment region wise and existing limitation of the studying policy to the wholesale power market that leaves retail markets and remote areas without our attention, taking away medium and small investment into renewable energy from the research focus. Elimination of these limitations would allow creating the full picture of Russian renewable energy investment profile.

Advanced biofuel production: Engineering metabolic pathways for butanol and propane biosynthesis.

Greenhouse gases emitted from energy production and transportation are dramatically changing the climate of Planet Earth. As a consequence, global warming is affecting the living conditions of numerous plant and animal species, including ours. Thus the development of sustainable and renewable liquid fuels is an essential global challenge in order to combat the climate change. In the past decades many technologies have been developed as alternatives to currently used petroleum fuels, such as bioethanol and biodiesel. However, even with gradually increasing production, the market penetration of these first generation biofuels is still relatively small compared to fossil fuels. Researchers have long ago realized that there is a need for advanced biofuels with improved physical and chemical properties compared to bioethanol and with biomass raw materials not competing with food production. Several target molecules have been identified as potential fuel candidates, such as alkanes, fatty acids, long carbon‐chain alcohols and isoprenoids. The current study focuses on the biosynthesis of butanol and propane as possible biofuels. The scope of this research was to investigate novel heterologous metabolic pathways and to identify bottlenecks for alcohol and alkane generation using Escherichia coli as a model host microorganism. The first theme of the work studied the pathways generating butyraldehyde, the common denominator for butanol and propane biosynthesis. Two ways of generating butyraldehyde were described, one via the bacterial fatty acid elongation machinery and the other via partial overexpression of the acetone‐butanol‐ethanol fermentation pathway found in Clostridium acetobutylicum. The second theme of the experimental work studied the reduction of butyraldehyde to butanol catalysed by various bacterial aldehyde‐reductase enzymes, whereas the final part of the work investigated the in vivo kinetics of the cyanobacterial aldehyde deformylating oxygenase (ADO) for the generation of hydrocarbons. The results showed that the novel butanol pathway, based on fatty acid biosynthesis consisting of an acyl‐ACP thioesterase and a carboxylic acid reductase, is tolerant to oxygen, thus being an efficient alternative to the previous Clostridial pathways. It was also shown that butanol can be produced from acetyl‐CoA using acetoacetyl CoA synthase (NphT7) or acetyl‐CoA acetyltransferase (AtoB) enzymes. The study also demonstrated, for the first time, that bacterial biosynthesis of propane is possible. The efficiency of the system is clearly limited by the poor kinetic properties of the ADO enzyme, and for proper function in vivo, the catalytic machinery requires a coupled electron relay system.

Visual analytics for behavioral and niche market segmentation

Companies require information in order to gain an improved understanding of their customers. Data concerning customers, their interests and behavior are collected through different loyalty programs. The amount of data stored in company data bases has increased exponentially over the years and become difficult to handle. This research area is the subject of much current interest, not only in academia but also in practice, as is shown by several magazines and blogs that are covering topics on how to get to know your customers, Big Data, information visualization, and data warehousing. In this Ph.D. thesis, the Self-Organizing Map and two extensions of it – the Weighted Self-Organizing Map (WSOM) and the Self-Organizing Time Map (SOTM) – are used as data mining methods for extracting information from large amounts of customer data. The thesis focuses on how data mining methods can be used to model and analyze customer data in order to gain an overview of the customer base, as well as, for analyzing niche-markets. The thesis uses real world customer data to create models for customer profiling. Evaluation of the built models is performed by CRM experts from the retailing industry. The experts considered the information gained with help of the models to be valuable and useful for decision making and for making strategic planning for the future.

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.

Entry Modes of Finnish Food Enterprises in Chinese Market

China’s phenomenal economic growth and social development have brought along interesting opportunities for Finnish companies. One intriguing sector offering significant growth potential is the food industry. Due to the local food safety issues, rising disposable income level and changing consumer habits, the demand for foreign food is increasing. Finnish food companies have much to offer in terms of high quality, food safety in production, technological development and innovation. The purpose of this study is to examine how the Finnish food enterprises choose their entry modes in the Chinese market. This study increases understanding of entry modes the Finnish companies can use to successfully enter the unpredictable market of China in the food industry context. The study examines the industry specific challenges and the possible solutions to them. Qualitative research is selected as research methodology for this study because the intention is to understand the reasons behind the Finnish food enterprises’ entry mode choices in the Chinese market. The study is conducted as a qualitative case analysis. Six Finnish case companies operating in the food industry were interviewed. The results of the research indicate that most of the food industry companies use exporting as their entry mode to China; only one case company used an investment mode. This study illustrates the significance of the factors related to company’s background, mode concerns and Chinese market influences in the entry mode choice.

Sugarcane spirit market share simulation: an application of conjoint analysis

This study evaluated the influence of packaging and labeling attributes of sugarcane spirit on consumers' behavior by applying the results of conjoint analysis in sugarcane spirit market share simulation. Firstly, a conjoint analysis was performed aiming to estimate the part-worths of each consumer for some sugarcane spirit packaging and labeling attributes. These part-worths were used in the market share simulation using the maximum utility model. It was observed that some packaging and labeling attributes affected consumer's purchase intention and that most consumers showed a similar preference pattern regarding these attributes. These consumers showed preference for the Seleta brand, which was bottled in 700 mL clear glass bottles with a metal screw cap that bore a label illustration unrelated to sugarcane spirit production process and had the information "aged 36 months in oak barrels". This study also showed that conjoint analysis and the use of its results in the market share simulation proved important tools to better understand consumer behavior towards intention to purchase sugarcane spirit.

Monascus pigment production in bioreactor using a co-product of biodiesel as substrate

The study and use of natural pigments in food industries have increased in recent years due to the toxicity presented by artificial pigments. Monascus ruber is a filamentous fungus that produces red, orange, and yellow pigments under different growing conditions. The growth of health food market has increased in parallel with the growth in biofuels production, such as biodiesel, which generates a concomitant increase in the production of glycerin that can be used in bioprocesses. The objective of this study was to use glycerin and glucose as substrates in the production of natural pigments in a bioreactor. The culture of Monascus ruber was carried out in a Bioflo III reactor with 4 L of working volume and pH, temperature, aeration, and agitation control. The highest pigment production was observed after 60 hours of fungal culture with 8.28 UA510 of red pigment. The pH range remained from 5.45 to 6.23 favoring the release of red pigment in the medium. This study shows the feasibility of the production of natural pigments by Monascus ruber in a bioreactor using a co-product of biodiesel without previous treatment as a substrate.

Applying life cycle management of colombian cocoa production

The present research aims to evaluate the usefulness of the application of Life Cycle Management in the agricultural sector focusing on the environmental and socio-economic aspects of decision making in the Colombian cocoa production. Such appraisal is based on the application of two methodological tools: Life Cycle Assessment, which considers environmental impacts throughout the life cycle of the cocoa production system, and Taguchi Loss Function, which measures the economic impact of a process' deviation from production targets. Results show that appropriate improvements in farming practices and supply consumption can enhance decision-making in the agricultural cocoa sector towards sustainability. In terms of agri-business purposes, such qualitative shift allows not only meeting consumer demands for environmentally friendly products, but also increasing the productivity and competitiveness of cocoa production, all of which has helped Life Cycle Management gain global acceptance. Since farmers have an important role in improving social and economic indicators at the national level, more attention should be paid to the upgrading of their cropping practices. Finally, one fundamental aspect of national cocoa production is the institutional and governmental support available for farmers in face of socio-economic or technological needs.

Assessing environmental impacts using a comparative LCA of industrial and artisanal production processes: "Minas Cheese" case

This study uses the Life Cycle Assessment (LCA) methodology to evaluate and compare the environmental impacts caused by both the artisanal and the industrial manufacturing processes of "Minas cheese". This is a traditional cheese produced in the state of Minas Gerais (Brazil), and it is considered a "cultural patrimony" in the country. The high participation of artisanal producers in the market justifies this research, and this analysis can help the identification of opportunities to improve the environmental performance of several stages of the production system. The environmental impacts caused were also assessed and compared. The functional unit adopted was 1 kilogram (Kg) of cheese. The system boundaries considered were the production process, conservation of product (before sale), and transport to consumer market. The milk production process was considered similar in both cases, and therefore it was not included in the assessment. The data were collected through interviews with the producers, observation, and a literature review; they were ordered and processed using the SimaPro 7 LCA software. According to the impact categories analyzed, the artisanal production exerted lower environmental impacts. This can be justified mainly because the industrial process includes the pasteurization stage, which uses dry wood as an energy source and refrigeration.

Item-level life-cycle model for maintenance network – from cost to additional value

The importance of industrial maintenance has been emphasized during the last decades; it is no longer a mere cost item, but one of the mainstays of business. Market conditions have worsened lately, investments in production assets have decreased, and at the same time competition has changed from taking place between companies to competition between networks. Companies have focused on their core functions and outsourced support services, like maintenance, above all to decrease costs. This new phenomenon has led to increasing formation of business networks. As a result, a growing need for new kinds of tools for managing these networks effectively has arisen. Maintenance costs are usually a notable part of the life-cycle costs of an item, and it is important to be able to plan the future maintenance operations for the strategic period of the company or for the whole life-cycle period of the item. This thesis introduces an itemlevel life-cycle model (LCM) for industrial maintenance networks. The term item is used as a common definition for a part, a component, a piece of equipment etc. The constructed LCM is a working tool for a maintenance network (consisting of customer companies that buy maintenance services and various supplier companies). Each network member is able to input their own cost and profit data related to the maintenance services of one item. As a result, the model calculates the net present values of maintenance costs and profits and presents them from the points of view of all the network members. The thesis indicates that previous LCMs for calculating maintenance costs have often been very case-specific, suitable only for the item in question, and they have also been constructed for the needs of a single company, without the network perspective. The developed LCM is a proper tool for the decision making of maintenance services in the network environment; it enables analysing the past and making scenarios for the future, and offers choices between alternative maintenance operations. The LCM is also suitable for small companies in building active networks to offer outsourcing services for large companies. The research introduces also a five-step constructing process for designing a life-cycle costing model in the network environment. This five-step designing process defines model components and structure throughout the iteration and exploitation of user feedback. The same method can be followed to develop other models. The thesis contributes to the literature of value and value elements of maintenance services. It examines the value of maintenance services from the perspective of different maintenance network members and presents established value element lists for the customer and the service provider. These value element lists enable making value visible in the maintenance operations of a networked business. The LCM added with value thinking promotes the notion of maintenance from a “cost maker” towards a “value creator”.

Cross Listing of a Finnish Company on an Exchange in the United States of America

Finnish companies cross listing in the United States is an exceptional phenomenon. This study examines the cross listing decision, cross listing choice and cross listing process with associated challenges and critical factors. The aim is to create an in-depth understanding of the cross listing process and the required financial information. Based on that, the aim is to establish the process phases with the challenges and the critical factors that ought to be considered be- fore establishing the process plus re-evaluated and further considered at points in time during the process. The empirical part of this study is conducted as a qualitative study. The research data was collected through the adoption of two approaches, which are the interview approach and the textual data approach. The interviews were conducted with Finnish practitioners in the field of accounting and finance. The textual data was from publicly available publications of this phenomenon by the two BIG5 accounting companies worldwide. The results of this study demonstrate the benefits of cross listing in the U.S. are the better growth opportunities, the reduction of cost of capital and the production of higher quality financial information. In the decision making process companies should assess whether the benefits exceed the increased costs, the pressure for performance, the uncertainty of market recognition and the requirements of management. The exchange listing is seen as the most favourable cross listing choice for Finnish companies. The establishment of the processes for producing reliable, transparent and timely financial information was seen as both highly critical and very challenging. The critical success factors relating to the cross listing phases are the assessment and planning as well as the right mix of experiences and expertise. The timing plays important role in the process. The results mainly corroborate the literature concerning cross listing decision and choice. This study contributes to the literature on the cross listing process offering a useful model for the phases of the cross listing process.

Price movement in the Brazilian land market (1994-2010): an analysis in the light of post-Keynesian theory

ABSTRACT The present study aims to evaluate crop, pasture and forest land prices in Brazil, between 1994 and 2010, in the light of Post-Keynesian theory. The results provide evidence that land, more than just a simple factor of production, must be conceived of as an economic asset. In fact, the price of rural land is determined not only by the expected profitability deriving from agricultural activities but also by the agents' expectations about its future appreciation and liquidity in an economic environment permeated with uncertainty. In this context, as an object of speculation, land has been particularly important as a store of value.

Pk-yrityksen aurinkovoimalainvestointiin vaikuttavat tekijät

Tutkielman tavoitteena on selvittää pienten ja keskisuurten yritysten aurinkovoimalainvestointiin liittyviä tekijöitä sekä erityispiirteitä. Tutkielmassa pk-yritykset on rajattu alueellisesti Etelä-Suomeen ja tekijöitä tarkastellaan investoinnin sekä päätöksenteon näkökulmasta. Keskeisenä asiana tutkielmassa on aurinkosähkömarkkinoiden nykytila sekä mahdollisuudet. Osatavoitteena on tutkia aurinkosähkön hyödyntämistä ja käyttöönottoa Suomessa sekä luoda aurinkosähkön mahdollisuuksista selkeämpi kokonaiskuva. Tutkielman tutkimusmenetelmänä käytetään laadullista tutkimusta. Tutkielma koostuu teoreettisesta katsauksesta sekä empiirisestä osuudesta. Teoreettinen osuus tarkastelee investointeja ja rahoitusvaihtoehtoja. Empiirinen osuus pitää sisällään kolmen kohdeyrityksen haastattelut. Haastattelut toteutettiin marraskuussa 2015 aurinkosähkömarkkinoilla toimiville ratkaisuntarjoajille. Haastatteluiden avulla kartoitettiin alalla toteutettujen aurinkovoimalainvestointien taustatekijöitä ja erityispiirteitä. Tutkimustuloksina havaittiin selkeitä aurinkovoimalainvestointiin vaikuttavia tekijöitä sekä muutamia erityispiirteitä. Taloudellista kannattavuutta voidaan pitää investointien lähtökohtana. Tähän vaikuttaa uusiutuvan energian investointeihin saatavilla oleva energiatuki, jolla on merkittävä vaikutus pk-yrityksen päätöksentekoon. Lisäksi ekologinen sähkön tuotanto sekä omavaraisuus nousivat haastatteluissa esiin. Johtopäätöksinä voidaan todeta aurinkosähkön sisältävän useita tekijöitä ja erityispiirteitä, joita investoijien sekä ratkaisuntarjoajien tulee ottaa huomioon. Aurinkosähkömarkkinoiden suurta potentiaalia voidaan hyödyntää tehokkaammin kehittämällä alan tiedonjakoa esille nousseiden tekijöiden ja erityispiirteiden osalta.

POLITICAL RISK IN FOREIGN DIRECT INVESTMENT IN THE RUSSIAN ELECTRIC POWER SECTOR

Russia approved ambitious reform plan for the electricity sector in 2001 including privatisation of the country’s huge thermal generation assets. So far the sector had suffered from power shortages, aging infrastructure, substantial electricity losses, and weak productivity and profitability numbers. There was obvious need for foreign investments and technologies. The reform was rather successful; the generation assets were privatised in auctions in 2007-2008 and three European energy companies, E.On, Enel and Fortum, invested in and obtained together over 10% of the Russian production assets. The novelty of these foreign investments serves unique object for the study. The political risk is involved in the FDI due to the industry’s social and economic importance. The research’s objective was to identify and analyse the political risk that foreign investors face in the Russian electricity sector. The research had qualitative study method and the empirical data was collected by interviewing. The research’s theoretical framework was based on the existing political risk theories and it focused to understand the Russian government in relation to the country’s stability and define both macro-level and micro-level sources of political risk for the foreign direct investments in the sector. The research concludes that the centralised and obscure political decision-making, economic constriction, high level of governmental control in economy and corruption form the country’s internal macro-level risk sources for the foreign investors in the sector. Additionally the retribution due to the companies’ home country actions, possible violent confrontations at the Russian borders and the currency instability are externally originated risk sources. In the electricity industry there is risk of tightened governmental control and increased regulation and taxation. Similarly the company-level risk sources link to the unreformed heating sector, bargaining with the authorities, diplomatic stress between host and home countries and to companies and government’s divergent perspective for the profit-making. The research stresses the foreign companies’ ability to cope with the characteristics of Russian political environment. In addition to frequent political and market risk assessment, the companies need to focus on currency protection against rouble’s rate fluctuation and actively build good company-citizenship in the country. Good relationship is needed with the Russian political authorities. The political risk identification and the research’s conclusive framework also enable political risk study assessments for other industries in Russia