Asiantuntijan suorituskykyyn vaikuttavien tekijöiden mittaaminen

Tutkimuksen tavoitteena oli tutkia asiantuntijaorganisaation henkilöstön työmotivaatioon vaikuttavia tekijöitä. Konkreettisena tavoitteena oli kehittää asiantuntijaorganisaation olemassa olevaan suorituskykymittaristoon uusia mittareita, joiden avulla yrityksessä pyritään luomaan asiantuntijoille mahdollisimman motivoiva työskentelyilmapiiri. Tutkimus toteutettiin kvalitatiivisena tapaustutkimuksena. Tutkimuksen teoreettisessa osuudessa tutkittiin asiantuntijan työmotivaatioon vaikuttavia tekijöitä sekä aineettoman pääoman mittaamista. Empiirisessä osuudessa tutkittiin pienen asiantuntijaorganisaation työskentelyolosuhteita. Aineistonkeruumenetelmänä toimi vanha tutkimustieto, puolistrukturoidun haastattelun piirteitä omaavat teemahaastattelut sekä tutkijan oma havainnointi. Asiantuntijan motivaatioon vaikuttaa erityisen paljon henkilökohtainen kasvu, autonomisuus, merkityksellinen työ, haasteelliset ja vaihtelevat työtehtävät sekä työstä saatu palaute. Vähemmän merkittäviä motivaattoreita ovat raha, työsuhteen jatkuvuus, ystävälliset työtoverit, kunnioitus ja oikeudenmukainen kohtelu. Urakehitystä asiantuntija ei koe erityisen motivoivana asiana. Tutkimuksen kohdeyrityksen haasteiksi ilmeni erityisesti palautteen antaminen, osaamisen ja koulutuksen johtaminen, autonomian vähyys projektin käyttöönotto vaiheessa sekä työn kuormittavuuden jakautuminen. Uudet mittarisuoritukset kohdeyrityksessä ovat: projektipalautteen antaminen, positiivisen palautteen määrä, projektien edistymispalaverit, projektikatselmukset, suunnittelun tuntiarviot, sisäisten kehitysideoiden toteutuminen, työntekijöiden kuormituksen jakautuminen sekä koulutuksen ja osaamisen jakautuminen.

Electrical Machine Product Development; Transmission to Lean Approach

The requirements set by the market for electrical machines become increasingly demanding requiring more sophisticated technological solutions. Companies producing electrical ma-chines are challenged to develop machines that provide competitive edge for the customer for example through increased efficiency, reliability or some customer specific special requirement. The objective of this thesis is to derive a proposal for the first steps to transform the electrical machine product development process of a manufacturing company towards lean product development. The current product development process in the company is presented together with the processes of four other companies interviewed for the thesis. On the basis of current processes of the electrical machine industry and the related literature, a generalized electrical machine product development process is derived. The management isms and –tools utilized by the companies are analyzed. Adoption of lean Pull-Event –reviews, Oobeya –management and Knowledge based product development are suggested as the initial steps of implementing lean product development paradigm in the manufacturing company. Proposals for refining the cur-rent product development process and increasing the stakeholder involvement in the development projects are made. Lean product development is finding its way to Finnish electrical machine industry, but the results will be available only after the methods have been implemented and adopted by the companies. There is some enthusiasm about the benefits of lean approach and if executed successfully it will provide competitive edge for the Finnish electrical machine industry.

Finnish cleantech SMEs in China: Challenges and solutions

The rapid economic growth in China has resulted in environmental challenges ranging from air pollution to water-related issues. Thus supporting clean technology, or cleantech, that encompasses industries that focus on alternative energy, pollution and recycling, power supplies and conservation has become one of the focal points in the Chinese economic policy for the next decade. Simultaneously, the Finnish government has initiated programs to support the internationalisation of domestic cleantech companies in an attempt to spiral the industry into one of the pillars of Finnish economic growth. This study concentrates on the conjunction of these two themes and studies the challenges faced by Finnish cleantech SMEs in the Chinese market. Consequently, the study answers the following sub questions: 1. What human and financial resource-based challenges do Finnish cleantech SMEs face in the Chinese market and what are their solutions? 2. What knowledge-based challenges do Finnish cleantech SMEs face in the Chinese market and how can these difficulties be resolved? 3. What network-based challenges do Finnish cleantech SMEs face in the Chinese market, how do they relate to the resource- and knowledge-based challenges, and how can these difficulties be resolved? This qualitative study is conducted by analysing four semi structured interviews collected from four Finnish SMEs that operate in China. The findings of the study indicate that in human resources the most important challenges are related to the hiring and retaining of employees. In contrast to extant academic literature results distinguish salary and social status as the main solutions to this challenge. Regarding financial resources it is discovered that cleantech companies enjoy a benign business environment in China and benefit from the Chinese government’s support for cleantech industry. Challenges related to knowledge resources can be grouped into categories with the most interesting knowledge flows being the stream of local market knowledge into to the foreign parent company and the outward flow of manufacturing and business practice information into the target venture. The challenge related to the first flow is gathering relevant information and the main solutions are clustering at the foreign location and hiring knowledge prior to internationalisation. Regarding the second flow the main challenge is related to intellectual property rights and the most interesting solution is the purposeful transformation of explicit knowledge into tacit knowledge. Finally, it is discovered that networks, called guanxi in China, greatly affect the business processes. Within the guanxi system there is the concept of face which was found to affect employee propensity to stay as well as, as a novel academic result, employees’ knowledge sharing intention.

Kokemusperäisen tiedon jakaminen työkierrossa

Kokemusperäinen tieto on käytäntöihin sitoutunutta ja siirtyy pitkälti vuorovaikutuksen kautta. Organisaation toiminnalle keskeisenä osatekijänä sen jakamisen tulee olla suunnitelmallista. Tämä tutkimus keskittyy tarkastelemaan kokemusperäisen tiedon jakamista työkierron avulla. Työkierto osaamisen kehittämisen menetelmänä on laajalti organisaatioiden käyttämä, mutta sen tutkiminen kokemusperäisen tiedon osalta on ollut vähäistä. Tutkimuksen teoriaosuus tarkastelee tiedon jakamista ja omaksumista yksilön ja organisaation tasoilla hyödyntäen tietoperustaisen näkemyksen ja organisaation oppimisen teorioita, joiden kautta tutkimuksen viitekehys muotoutui. Tutkimuksen empiriaosuus toteutettiin kvalitatiivisina teemahaastatteluina, joissa haastateltiin kuutta työkierron mentori-oppija –paria. Tutkimuksen tulokset osoittivat työkierron olevan toimiva keino siirtää kokemusperäistä tietoa, johon merkittävimpinä keinoina vaikuttivat vuorovaikutuksellinen yhdessä työskenteleminen, sekä toiminnan organisoinnin suunnitelmallisuus. Tutkimuksen johtopäätöksenä esitettiin yhdenmukaisen työkierron suunnitelman rakentamista, sekä työkierron toteutumisen sitouttamista osaksi työn arviointia.

Semantic and fuzzy modelling for human behaviour recognition in smart spaces : a case study on ambient assisted living.

Human activity recognition in everyday environments is a critical, but challenging task in Ambient Intelligence applications to achieve proper Ambient Assisted Living, and key challenges still remain to be dealt with to realize robust methods. One of the major limitations of the Ambient Intelligence systems today is the lack of semantic models of those activities on the environment, so that the system can recognize the speci c activity being performed by the user(s) and act accordingly. In this context, this thesis addresses the general problem of knowledge representation in Smart Spaces. The main objective is to develop knowledge-based models, equipped with semantics to learn, infer and monitor human behaviours in Smart Spaces. Moreover, it is easy to recognize that some aspects of this problem have a high degree of uncertainty, and therefore, the developed models must be equipped with mechanisms to manage this type of information. A fuzzy ontology and a semantic hybrid system are presented to allow modelling and recognition of a set of complex real-life scenarios where vagueness and uncertainty are inherent to the human nature of the users that perform it. The handling of uncertain, incomplete and vague data (i.e., missing sensor readings and activity execution variations, since human behaviour is non-deterministic) is approached for the rst time through a fuzzy ontology validated on real-time settings within a hybrid data-driven and knowledgebased architecture. The semantics of activities, sub-activities and real-time object interaction are taken into consideration. The proposed framework consists of two main modules: the low-level sub-activity recognizer and the high-level activity recognizer. The rst module detects sub-activities (i.e., actions or basic activities) that take input data directly from a depth sensor (Kinect). The main contribution of this thesis tackles the second component of the hybrid system, which lays on top of the previous one, in a superior level of abstraction, and acquires the input data from the rst module's output, and executes ontological inference to provide users, activities and their in uence in the environment, with semantics. This component is thus knowledge-based, and a fuzzy ontology was designed to model the high-level activities. Since activity recognition requires context-awareness and the ability to discriminate among activities in di erent environments, the semantic framework allows for modelling common-sense knowledge in the form of a rule-based system that supports expressions close to natural language in the form of fuzzy linguistic labels. The framework advantages have been evaluated with a challenging and new public dataset, CAD-120, achieving an accuracy of 90.1% and 91.1% respectively for low and high-level activities. This entails an improvement over both, entirely data-driven approaches, and merely ontology-based approaches. As an added value, for the system to be su ciently simple and exible to be managed by non-expert users, and thus, facilitate the transfer of research to industry, a development framework composed by a programming toolbox, a hybrid crisp and fuzzy architecture, and graphical models to represent and con gure human behaviour in Smart Spaces, were developed in order to provide the framework with more usability in the nal application. As a result, human behaviour recognition can help assisting people with special needs such as in healthcare, independent elderly living, in remote rehabilitation monitoring, industrial process guideline control, and many other cases. This thesis shows use cases in these areas.

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.

The nature and role of trust in temporary virtual problem-solving teams

The objective of this study is to increase understanding of the nature and role of trust in temporary virtual problem-solving teams engaged in real-life co-creation activities, while much of previous research has been conducted in student settings. The different forms and bases of trust, possible trust barriers and trust building actions, and perceived role of trust in knowledge sharing and collaboration are analyzed. The study is conducted as a qualitative case study in case company. Data includes interviews from 24 people: 13 from 3 different project teams that were going on during the study, 8 from already finalized project teams, and 3 founders of case company. Additional data consists of communication archives from three current teams. The results indicate that there were both knowledge-based and swift trust present, former being based on work-related personal experiences about leaders or other team members, and latter especially on references, disposition to trust and institution-based factors such as norms and rules, as well as leader and expert action. The findings suggest that possible barriers of trust might be related to lack of adaptation to virtual work, unclear roles and safety issues, and nature of virtual communication. Actions that could be applied to enhance trust are for example active behavior in discussions, work-related introductions communicating competence, managerial actions and face-to-face interaction. Finally, results also suggest that trust has a focal role as an enabler of action and knowledge sharing, and coordinator of effective collaboration and performance in temporary virtual problem-solving teams.

Evaluation of Machine Learning Classifiers for Mobile Network Intrusion Detection Systems

Mobile malwares are increasing with the growing number of Mobile users. Mobile malwares can perform several operations which lead to cybersecurity threats such as, stealing financial or personal information, installing malicious applications, sending premium SMS, creating backdoors, keylogging and crypto-ransomware attacks. Knowing the fact that there are many illegitimate Applications available on the App stores, most of the mobile users remain careless about the security of their Mobile devices and become the potential victim of these threats. Previous studies have shown that not every antivirus is capable of detecting all the threats; due to the fact that Mobile malwares use advance techniques to avoid detection. A Network-based IDS at the operator side will bring an extra layer of security to the subscribers and can detect many advanced threats by analyzing their traffic patterns. Machine Learning(ML) will provide the ability to these systems to detect unknown threats for which signatures are not yet known. This research is focused on the evaluation of Machine Learning classifiers in Network-based Intrusion detection systems for Mobile Networks. In this study, different techniques of Network-based intrusion detection with their advantages, disadvantages and state of the art in Hybrid solutions are discussed. Finally, a ML based NIDS is proposed which will work as a subsystem, to Network-based IDS deployed by Mobile Operators, that can help in detecting unknown threats and reducing false positives. In this research, several ML classifiers were implemented and evaluated. This study is focused on Android-based malwares, as Android is the most popular OS among users, hence most targeted by cyber criminals. Supervised ML algorithms based classifiers were built using the dataset which contained the labeled instances of relevant features. These features were extracted from the traffic generated by samples of several malware families and benign applications. These classifiers were able to detect malicious traffic patterns with the TPR upto 99.6% during Cross-validation test. Also, several experiments were conducted to detect unknown malware traffic and to detect false positives. These classifiers were able to detect unknown threats with the Accuracy of 97.5%. These classifiers could be integrated with current NIDS', which use signatures, statistical or knowledge-based techniques to detect malicious traffic. Technique to integrate the output from ML classifier with traditional NIDS is discussed and proposed for future work.

Tietoperustaisten HRM-käytäntöjen, luottamuksen ja suorituskyvyn suhde suomalaisessa organisaatiokontekstissa

Henkilöstöjohtamisen käytännöillä on merkittävä vaikutus organisaation johtamiseen ja tätä kautta menestymiseen. Hyvin suunnitellut ja toteutetut käytännöt ovat osaltaan vaikuttamassa yrityksessä vallitsevaan luottamukseen. Hyvä sisäinen luottamustaso puolestaan heijastuu myös organisaation ulkoiseen luottamukseen. Tietoperustaiset HRM-käytännöt ovat keskeisessä roolissa juuri nyt, koska työelämä ja työn tekeminen ovat murrosvaiheessa ja muutosten nopeus kiihtyy entisestään tietointensiivisten työtehtävien lisääntyessä. HRM-käytäntöjä on tutkittu paljon aiempien vuosikymmenten aikana. Tietoperustaisten henkilöstöjohtamisen käytäntöjen tutkimusta on ollut jonkin verran 2000-luvun alun jälkeen. Henkilöstöjohtamisen käytäntöjen suhdetta luottamukseen ja suorituskykyyn on myös tutkittu. Sen sijaan vielä ei ollut tehty tutkimusta, jossa yhdistetään tietoperustaisten henkilöstöjohtamisen käytäntöjen, luottamuksen ja suorituskyvyn suhde. Tämän tutkimuksen tarkoitus on selvittää tietoperustaisten HRM-käytäntöjen, luottamuksen ja suorituskyvyn yhteyttä. Tutkimuksen pääpaino on tietoperustaisten henkilöstökäytäntöjen suhde luottamukseen. Tutkittavat tietoperustaiset henkilöstöjohtaminen käytännöt liittyvät rekrytointiin, osaamisen kehittämiseen, suoritusarviointiin ja palkitsemiseen. Tutkimukseen osallistui 246 Suomessa toimivaa yritystä. Kyselytutkimuksen lisäksi tutkimuksessa käytettiin taloudellisia tietokantoja yritysten suorituskykyä kuvaavien tunnuslukujen määrittämisessä. Tutkimus on määrällinen ja se perustuu tilastollisten menetelmien ja analyysien käyttöön. Tutkimuksessa saatiin selville, että tietoperustaisilla osaamisen kehittämisen ja suoritusarviointien HRM-käytännöillä on positiivinen vaikutus luottamukseen. Tietoon pohjautuvilla henkilöstöjohtamisen käytännöillä voidaan siis rakentaa parempaa luottamustasoa organisaatioissa.

Tietämyksenhallinta kirurgiassa

Tässä kandidaatin työssä tavoitteena oli selvittää tietämyksenhallinnan ongelmia Etelä-Karjalan keskussairaalan kirurgisella osastolla empiirisen case-tutkimuksen avulla. Tutkimuksessa haastateltiin kolmea Etelä-Karjalan keskussairaalan kirurgia, joiden vastausten avulla pyrittiin luomaan ankkuroitua teoria-tutkimusmenetelmää hyväksi käyttäen keskeisimpiä vastauksia tutkimusongelmiin. Kirurgisen osaston tietämyksenhallinnan ongelmat perustuivat pääosin tietojärjestelmien hajanaisuuteen, hitauteen sekä käyttäjäystävällisyyteen. Lisäksi hiljaisen tiedon vaikuttavuus tietämyksenhallinnassa nähtiin ongelmana, koska se lisää epävarmuutta hoitopäätöksissä sekä uuden tiedon luomisessa. Tuloksista voidaan todeta, että tietojärjestelmiä täytyisi parantaa lääkäreiden työn nopeuttamiseksi sekä laadun parantamiseksi. Lisäksi työssä tehtiin kirjallisuuskatsaus tietämyksenhallinnasta terveydenhuollon näkökulmasta.

Adaptability, Transformation and Complex Changes in Namibia and Tanzania: Resilience and Innovation System Development in Local Communities

This thesis is a research about the recent complex spatial changes in Namibia and Tanzania and local communities’ capacity to cope with, adapt to and transform the unpredictability engaged to these processes. I scrutinise the concept of resilience and its potential application to explaining the development of local communities in Southern Africa when facing various social, economic and environmental changes. My research is based on three distinct but overlapping research questions: what are the main spatial changes and their impact on the study areas in Namibia and Tanzania? What are the adaptation, transformation and resilience processes of the studied local communities in Namibia and Tanzania? How are innovation systems developed, and what is their impact on the resilience of the studied local communities in Namibia and Tanzania? I use four ethnographic case studies concerning environmental change, global tourism and innovation system development in Namibia and Tanzania, as well as mixed-methodological approaches, to study these issues. The results of my empirical investigation demonstrate that the spatial changes in the localities within Namibia and Tanzania are unique, loose assemblages, a result of the complex, multisided, relational and evolutional development of human and non-human elements that do not necessarily have linear causalities. Several changes co-exist and are interconnected though uncertain and unstructured and, together with the multiple stressors related to poverty, have made communities more vulnerable to different changes. The communities’ adaptation and transformation measures have been mostly reactive, based on contingency and post hoc learning. Despite various anticipation techniques, coping measures, adaptive learning and self-organisation processes occurring in the localities, the local communities are constrained by their uneven power relationships within the larger assemblages. Thus, communities’ own opportunities to increase their resilience are limited without changing the relations in these multiform entities. Therefore, larger cooperation models are needed, like an innovation system, based on the interactions of different actors to foster cooperation, which require collaboration among and input from a diverse set of stakeholders to combine different sources of knowledge, innovation and learning. Accordingly, both Namibia and Tanzania are developing an innovation system as their key policy to foster transformation towards knowledge-based societies. Finally, the development of an innovation system needs novel bottom-up approaches to increase the resilience of local communities and embed it into local communities. Therefore, innovation policies in Namibia have emphasised the role of indigenous knowledge, and Tanzania has established the Living Lab network.

Managing Human Factor in Accounting Change - Introducing Activity Based Costing System to Organization

Tutkimuksen tavoitteena on identifioida yleisimmät toimintolaskennan implementointiin liittyvät ongelmat ja muutosprojektin onnistumiseen vaikuttavat tekijät. Tavoitteena on myös saada kokonaisvaltainen kuva siitä, miksi laskentatoimen muutokset ovat vaikeita implementoida ja miten ihmisten käyttäytyminen vaikuttaa muutosprosessin onnistumiseen. Sekä laskentatoimen että muutosjohtamisen teorioita tarkastellaan laaja-alaisen kuvan saamiseksi siitä, miten ihmisiin ja heidän käyttäytymiseensä liittyvät tekijät vaikuttavat muutosprojektin onnistumiseen tai epäonnistumiseen. Tutkielma käyttää empiirisiä tutkimustuloksia pohjana aiheen tarkastelulle. Tutkielma tarjoaa ehdotuksia tulevaisuuden tutkimukselle liittyen laskentatoimen muutoksen kriittisiin tekijöihin. Kiinnostavimpia alueita tulevaisuuden tutkimukselle on pohtia tarkemmin, miten työntekijöiden oletukset johtajien motiiveista muutoksen takana vaikuttavat muutosvastarintaan sekä miten organisaation rakenne ja muutosvastarintavaikuttavat muutoksen institutionaalistamiseen.

Competitor Information andCompetitive Knowledge Management in a Large Industrial Organization

Thisthesis supplements the systematic approach to competitive intelligence and competitor analysis by introducing an information-processing perspective on management of the competitive environment and competitors therein. The cognitive questions connected to the intelligence process and also the means that organizational actors use in sharing information are discussed. The ultimate aim has been to deepen knowledge of the different intraorganizational processes that are used in acorporate organization to manage and exploit the vast amount of competitor information that is received from the environment. Competitor information and competitive knowledge management is examined as a process, where organizational actorsidentify and perceive the competitive environment by using cognitive simplification, make interpretations resulting in learning and finally utilize competitor information and competitive knowledge in their work processes. The sharing of competitive information and competitive knowledge is facilitated by intraorganizational networks that evolve as a means of developing a shared, organizational level knowledge structure and ensuring that the right information is in the right place at the right time. This thesis approaches competitor information and competitive knowledge management both theoretically and empirically. Based on the conceptual framework developed by theoretical elaboration, further understanding of the studied phenomena is sought by an empirical study. The empirical research was carried out in a multinationally operating forest industry company. This thesis makes some preliminary suggestions of improving the competitive intelligence process. It is concluded that managing competitor information and competitive knowledge is not simply a question of managing information flow or improving sophistication of competitor analysis, but the crucial question to be solved is rather, how to improve the cognitive capabilities connected to identifying and making interpretations of the competitive environment and how to increase learning. It is claimed that competitive intelligence can not be treated like an organizational function or assigned solely to a specialized intelligence unit.

The governmental organization's role in railway freight market's liberalization -building knowledge through Swedish and Polish operators' experiences

Globalization has increased transport aggregates’ demand. Whilst transport volumes increase, ecological values’im portance has sharpened: carbon footprint has become a measure known world widely. European Union together with other communities emphasizes friendliness to the environment: same trend has extended to transports. As a potential substitute for road transport is noted railway transport, which decreases the congestions and lowers the emission levels. Railway freight market was liberalized in the European Union 2007, which enabled new operators to enter the markets. This research had two main objectives. Firstly, it examined the main market entry strategies utilized and the barriers to entry confronted by the operators who entered the markets after the liberalization. Secondly, the aim was to find ways the governmental organization could enhance its service towards potential railway freight operators. Research is a qualitative case study, utilizing descriptive analytical research method with a normative shade. Empirical data was gathered by interviewing Swedish and Polish railway freight operators by using a semi-structured theme-interview. This research provided novel information by using first-hand data; topic has been researched previously by utilizing second-hand data and literature analyses. Based on this research, rolling stock acquisition, needed investments and bureaucracy generate the main barriers to entry. The research results show that the mostly utilized market entry strategies are start-up and vertical integration. The governmental organization could enhance the market entry process by organizing courses, paying extra attention on flexibility, internal know-how and educating the staff.

Developing A Knowledge Management Process Model for Internal IT Organization, Case: Stora Enso Oyj, Corporate IT

The objectives of this Master’s Thesis were to find out what kind of knowledge management strategy would fit best an IT organization that uses ITIL (Information Technology Infrastructure Library) framework for IT Service Management and to create a knowledge management process model to support chosen strategy. The empirical material for this research was collected through qualitative semi-structured interviews of a case organization Stora Enso Corporate IT. The results of the qualitative interviews indicate that codification knowledge management strategy would fit best for the case organization. The knowledge management process model was created based on earlier studies and a literature of knowledge management. The model was evaluated in the interview research and the results showed that the created process model is realistic, useful, and it responds to a real life phenomenon.