100 resultados para case study research method


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Laser additive manufacturing (LAM), known also as 3D printing, is a powder bed fusion (PBF) type of additive manufacturing (AM) technology used to manufacture metal parts layer by layer by assist of laser beam. The development of the technology from building just prototype parts to functional parts is due to design flexibility. And also possibility to manufacture tailored and optimised components in terms of performance and strength to weight ratio of final parts. The study of energy and raw material consumption in LAM is essential as it might facilitate the adoption and usage of the technique in manufacturing industries. The objective this thesis was find the impact of LAM on environmental and economic aspects and to conduct life cycle inventory of CNC machining and LAM in terms of energy and raw material consumption at production phases. Literature overview in this thesis include sustainability issues in manufacturing industries with focus on environmental and economic aspects. Also life cycle assessment and its applicability in manufacturing industry were studied. UPLCI-CO2PE! Initiative was identified as mostly applied exiting methodology to conduct LCI analysis in discrete manufacturing process like LAM. Many of the reviewed literature had focused to PBF of polymeric material and only few had considered metallic materials. The studies that had included metallic materials had only measured input and output energy or materials of the process and compared to different AM systems without comparing to any competitive process. Neither did any include effect of process variation when building metallic parts with LAM. Experimental testing were carried out to make dissimilar samples with CNC machining and LAM in this thesis. Test samples were designed to include part complexity and weight reductions. PUMA 2500Y lathe machine was used in the CNC machining whereas a modified research machine representing EOSINT M-series was used for the LAM. The raw material used for making the test pieces were stainless steel 316L bar (CNC machined parts) and stainless steel 316L powder (LAM built parts). An analysis of power, time, and the energy consumed in each of the manufacturing processes on production phase showed that LAM utilises more energy than CNC machining. The high energy consumption was as result of duration of production. Energy consumption profiles in CNC machining showed fluctuations with high and low power ranges. LAM energy usage within specific mode (standby, heating, process, sawing) remained relatively constant through the production. CNC machining was limited in terms of manufacturing freedom as it was not possible to manufacture all the designed sample by machining. And the one which was possible was aided with large amount of material removed as waste. Planning phase in LAM was shorter than in CNC machining as the latter required many preparation steps. Specific energy consumption (SEC) were estimated in LAM based on the practical results and assumed platform utilisation. The estimated platform utilisation showed SEC could reduce when more parts were placed in one build than it was in with the empirical results in this thesis (six parts).

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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.

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Several companies are trying to improve their operation efficiency by implementing an enterprise resource planning (ERP) system that makes it possible to control the resources of the company in real time. However, the success of the implementation project is not a foregone conclusion; a significant part of these projects end in a failure, one way or another. Therefore it is important to investigate ERP system implementation more closely in order to increase understanding about factors influencing ERP system success and to improve the probability of a successful ERP implementation project. Consequently, this study was initiated because a manufacturing case company wanted to review the success of their ERP implementation project. To be exact, the case company hoped to gain both information about the success of the project and insight for future implementation improvement. This study investigated ERP success specifically by examining factors that influence ERP key-user satisfaction. User satisfaction is one of the most commonly applied indicators of information system success. The research data was mainly collected by conducting theme interviews. The subjects of the interviews were six key-users of the newly implemented ERP system. The interviewees were closely involved in the implementation project. Furthermore, they act as representative users that utilize the new system in everyday business processes. The collected data was analyzed by thematizing. Both data collection and analysis were guided by a theoretical frame of reference. This frame was based on previous research on the subject. The results of the study aligned with the theoretical framework to large extent. The four principal factors influencing key-user satisfaction were change management, contractor service, key-user’s system knowledge and characteristics of the ERP product itself. One of the most significant contributions of the research is that it confirmed the existence of a connection between change management and ERP key-user satisfaction. Furthermore, it discovered two new sub-factors influencing contractor service related key-user satisfaction. In addition, the research findings indicated that in order to improve the current level of key-user satisfaction, the case company should pay special attention to system functionality improvement and enhancement of the key-users’ knowledge. During similar implementation projects in the future, it would be important to assure the success of change management and contractor service related processes.

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The main objective of this study was to find out the bases for innovation model formulation in an existing organization based on cases. Innovation processes can be analyzed based on their needs and based on their emphasis on the business model development or R&D. The research was conducted in energy sector within one company by utilizing its projects as cases for the study. It is typical for the field of business that development is slow, although the case company has put emphasis on its innovation efforts. Analysis was done by identifying the cases’ needs and comparing them. The results were that because of the variances in the needs of the cases, the applicability of innovation process models varies. It was discovered that by dividing the process into two phases, a uniform model could be composed. This model would fulfill the needs of the cases and potential future projects as well.

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The aim of this study is to investigate value added service concept for an asset and real estate management case company. The initial purpose was to recognize the most value adding key performance indicators (KPIs) information delivered for its customers, real estate investors with value added service. The multiple case study strategy included two focus group interviews with five case interviews in total. Additionally, quality function deployment (QFD) was used in order to form up the service process. The study starts with introduction and methodology explaining the demand for the thesis study. The subsequent chapter presents the theoretical background on real estate management KPIs in four main points of views and quality function deployment from the service development point of view. The chapter also defines research gap for the case study. According to the case study interviews, the most favored KPIs to deliver for the clients are income maturity of lease agreements and leasing activity. These KPIs and quality characteristics are translated into the QFD. In total, the service QFD explains the service planning, process control, and action plan phases.

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This research is looking to find out what benefits employees expect the organization of data governance gains for an organization and how it benefits implementing automated marketing capabilities. Quality and usability of the data are crucial for organizations to meet various business needs. Organizations have more data and technology available what can be utilized for example in automated marketing. Data governance addresses the organization of decision rights and accountabilities for the management of an organization’s data assets. With automated marketing it is meant sending a right message, to a right person, at a right time, automatically. The research is a single case study conducted in Finnish ICT-company. The case company was starting to organize data governance and implementing automated marketing capabilities at the time of the research. Empirical material is interviews of the employees of the case company. Content analysis is used to interpret the interviews in order to find the answers to the research questions. Theoretical framework of the research is derived from the morphology of data governance. Findings of the research indicate that the employees expect the organization of data governance among others to improve customer experience, to improve sales, to provide abilities to identify individual customer’s life-situation, ensure that the handling of the data is according to the regulations and improve operational efficiency. The organization of data governance is expected to solve problems in customer data quality that are currently hindering implementation of automated marketing capabilities.

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The literature on agency suggests different implications for the use of export intermediaries. However, only few studies provide a view on import intermediaries. This thesis tries for its part to fill this research gap by studying the import intermediaries in the EU–Russia trade from a Russian industrial company’s point of view. The aim is to describe import intermediation and explain the need for import intermediary companies in the EU–Russia trade. The theoretical framework of this thesis originates from an article by Peng and York (2001), in which they study the performance of export intermediaries. This thesis applies resource-based theory, transaction cost theory and agency cost theory, following the idea of Peng and York. The resource-based theory approach is utilised for describing an ideal import intermediary company, and transaction cost theory provides a basis for understanding the benefits of using the services of import intermediary companies, while agency cost theory is applied in order to understand the risks the Russian industrial company faces when it decides to use the services of import intermediaries. The study is performed in the form of a case interview with a representative of a major Russian metallurgy company. The results of the study suggest that an ideal intermediary has the skills required specifically for the imports process, in order to save time and money of the principal company. The intermediary company helps reducing the amount of time the managers and the staff of the principal company use to make imports possible, thus reducing the salary costs and providing the possibility to concentrate on the company’s core competencies. The benefits of using the services of import intermediary companies are the reduced transaction costs, especially salary costs that are minimised because of the effectiveness and specialisation of import intermediaries. Intermediaries are specialised in the imports process and thus need less time and resources to organise the imports. They also help to reduce the fixed salary costs, because their services can be used only when needed. The risks of being misled by intermediaries are minimised by the competition on the import intermediary market. In case an intermediary attempts fraud, it gets replaced by its rival.

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The thesis explores how the business ecosystem of financial services has changed and what its drivers of change are. Existing literature in the field of financial industry is concerned with financial innovations and their features, determinants and factors, but also with how to organize innovation activities such as open innovation principles. Thus, there is a clear need for understanding changes in financial service ecosystem. First, the comprehensive theory framework is conducted in order to serve the reader’s necessary understanding of basic theoretical concepts that are related to ecosystem changes. Second, the research is carried out by using qualitative research methods; the data is collected by interviewing 11 experts from the field of financial services in Finland. According to the results of this thesis, the most significant changes in the financial service ecosystem are the new market players. They have increased competition, created new courses of action, set new requirements for financial services, and first and foremost, they have shifted customers into the heart of the whole ecosystem. These new market players have a willingness to cooperate with external partners, which means a shift towards the world of open innovation. In addition, the economic environment has changed which has resulted in tighter regulation for incumbents making them even unyielding. Technology change, together with digitalization, has lead new financial innovations and new digital service channels, which have challenged the traditional business models in the financial industry. They have improved transparency, openness and efficiency, but also lead to the fragmentation of financial services. Thus, customers search for financial services from different sources and different service providers, and finally combine them into a coherent whole, which meets their own needs. The change of customers’ behavior and social environment has enabled and boosted these changes in the financial ecosystem. All in all, the change of the financial ecosystem is not a result of one or a few change forces, but instead it is a combination of many different factors.

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Business intelligence (BI) is an information process that includes the activities and applications used to transform business data into valuable business information. Today’s enterprises are collecting detailed data which has increased the available business data drastically. In order to meet changing customer needs and gain competitive advantage businesses try to leverage this information. However, IT departments are struggling to meet the increased amount of reporting needs. Therefore, recent shift in the BI market has been towards empowering business users with self-service BI capabilities. The purpose of this study was to understand how self-service BI could help businesses to meet increased reporting demands. The research problem was approached with an empirical single case study. Qualitative data was gathered with a semi-structured, theme-based interview. The study found out that case company’s BI system was mostly used for group performance reporting. Ad-hoc and business user-driven information needs were mostly fulfilled with self-made tools and manual work. It was felt that necessary business information was not easily available. The concept of self-service BI was perceived to be helpful to meet such reporting needs. However, it was found out that the available data is often too complex for an average user to fully understand. The respondents felt that in order to self-service BI to work, the data has to be simplified and described in a way that it can be understood by the average business user. The results of the study suggest that BI programs struggle in meeting all the information needs of today’s businesses. The concept of self-service BI tries to resolve this problem by allowing users easy self-service access to necessary business information. However, business data is often complex and hard to understand. Self-serviced BI has to overcome this challenge before it can reach its potential benefits.

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In any manufacturing system, there are many factors that are affecting and limiting the capacity of the entire system. This thesis addressed a study on how to improve the production capacity in a Finnish company (Viljavuuspalvelu Oy) through different methods like bottleneck analysis, Overall Equipment Effectiveness (OEE), and Just in Time production. Four analyzing methods have been studied in order to detect the bottleneck machine in Viljavuuspalvelu Oy. The results shows that the bottleneck machine in the industrial area that constraint the production is the grinding machine while the bottleneck machine in the laboratory section is the photometry machine. In addition, the Overall Equipment Effectiveness (OEE) of the entire system of the studied case was calculated and it has been found that the OEE of the Viljavuuspalvelu Oy is 35.75%. Moreover, two methods on how to increase the OEE were studied and it was shown that either the total output of the company should be 1254 samples/shift in order to have an OEE around 85% which is considered as a world class or the Ideal run rate should be 1.45 pieces/minute. In addition, some realistic methods are applied based on the finding in this thesis to increase the OEE factor in the company and in one realistic method the % OEE has increase to 62.59%. Finally, an explanation on how to implement the Just in Time production in Viljavuuspalvelu Oy has been studied.

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Business intelligence (BI) is an information process that includes the activities and applications used to transform business data into valuable business information. Today’s enterprises are collecting detailed data which has increased the available business data drastically. In order to meet changing customer needs and gain competitive advantage businesses try to leverage this information. However, IT departments are struggling to meet the increased amount of reporting needs. Therefore, recent shift in the BI market has been towards empowering business users with self-service BI capabilities. The purpose of this study was to understand how self-service BI could help businesses to meet increased reporting demands. The research problem was approached with an empirical single case study. Qualitative data was gathered with a semi-structured, theme-based interview. The study found out that case company’s BI system was mostly used for group performance reporting. Ad-hoc and business user-driven information needs were mostly fulfilled with self-made tools and manual work. It was felt that necessary business information was not easily available. The concept of self-service BI was perceived to be helpful to meet such reporting needs. However, it was found out that the available data is often too complex for an average user to fully understand. The respondents felt that in order to self-service BI to work, the data has to be simplified and described in a way that it can be understood by the average business user. The results of the study suggest that BI programs struggle in meeting all the information needs of today’s businesses. The concept of self-service BI tries to resolve this problem by allowing users easy self-service access to necessary business information. However, business data is often complex and hard to understand. Self-serviced BI has to overcome this challenge before it can reach its potential benefits.

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The purpose of this thesis is to find out how outbound logistics process can be improved by reducing unnecessary waste in a globally dispersed make-to-order (MTO) supply chain. The research problem was addressed by a multinational corporation that aims to find a solution for reducing unnecessary waste in their outbound logistics process. The focus is on customized products that are delivered via sea transportation. Theoretical framework for improving outbound logistics processes in globally dispersed MTO supply chain was created based on business process management, Porter’s value chain theory, value stream mapping and current reality tree. The empirical research was conducted by using constructive approach due to its ability to research a practical problem and to improve the existing practices. The data was collected from ten semi-structured interviews and three non-participant observations. By analysing the data and applying the theoretical framework, five types of waste were detected in the process that were seen to derive from six root causes. Practical solution was constructed to reduce the waste in the process by combining the existing literature with the ideas raising from empirical data. The results of this thesis suggest that a MNC with a globally dispersed MTO supply chain can improve its outbound logistics process by applying activities that enhance internal and external integration, collaboration and coordination, and increase predictability of the process. This research has practical relevance both for the case company as well as for other MNCs with globally dispersed MTO supply chains that aim to improve their outbound logistics processes. This research contributes to the BPM and CRA research by providing an evidence for their applicability in the new context.

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The study approaches student travel from the perspective of postmodern consumption. The background is in the observation that the student travel market has a vast potential, but it is not necessarily capitalized upon to the extent it could. This might partly have to do with the peculiarities of postmodernity: consumption is characterized by unpredictability and abstract motives. The research questions are built around what constitutes student travel consumption and how can students be categorized according to motivation, behaviour and values. Also identity and expressiveness are present and it is evaluated, if travel services facilitate these background is the observation that the student travel market has a vast potential, but it is not necessarily capitalized upon to the extent it could be. This might partly have to do with the peculiarities of postmodernity: consumption is characterized by unpredictability and abstract motives. The research questions are built around what constitutes student travel consumption and how can students be categorized according to motivation, behaviour and values. Also identity and expressiveness are present and it is evaluated whether travel services facilitate these constructs. The topic is approached by discovering the key concepts such as self-identity. This was done in order to create survey questions that reflect the underlying theories. The survey was sent to chosen student groups of Turku School of Economics. The data was analyzed using statistical methods, mainly principal component analysis, in order to categorize students’ motives and behaviour into distinct profiles. The findings indicate that students have a high level of awareness in their travel consumption choices. Travel services seem to facilitate identity and lifestyle expressiveness, one central dimension of postmodernity. Psychographics such as motivation seem to work well as a segmentation criteria when it comes to the student traveler market. Travel offers students an opportunity for relaxation, escape, enjoyment and gaining new experiences and social contacts. Furthermore, the enjoyment of the travel experience extends to the pre- and post-trip time.

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The literature on agency suggests different implications for the use of export intermediaries. However, only few studies provide a view on import intermediaries. This thesis tries for its part to fill this research gap by studying the import intermediaries in the EU–Russia trade from a Russian industrial company’s point of view. The aim is to describe import intermediation and explain the need for import intermediary companies in the EU–Russia trade. The theoretical framework of this thesis originates from an article by Peng and York (2001), in which they study the performance of export intermediaries. This thesis applies resource-based theory, transaction cost theory and agency cost theory, following the idea of Peng and York. The resource-based theory approach is utilised for describing an ideal import intermediary company, and transaction cost theory provides a basis for understanding the benefits of using the services of import intermediary companies, while agency cost theory is applied in order to understand the risks the Russian industrial company faces when it decides to use the services of import intermediaries. The study is performed in the form of a case interview with a representative of a major Russian metallurgy company. The results of the study suggest that an ideal intermediary has the skills required specifically for the imports process, in order to save time and money of the principal company. The intermediary company helps reducing the amount of time the managers and the staff of the principal company use to make imports possible, thus reducing the salary costs and providing the possibility to concentrate on the company’s core competencies. The benefits of using the services of import intermediary companies are the reduced transaction costs, especially salary costs that are minimised because of the effectiveness and specialisation of import intermediaries. Intermediaries are specialised in the imports process and thus need less time and resources to organise the imports. They also help to reduce the fixed salary costs, because their services can be used only when needed. The risks of being misled by intermediaries are minimised by the competition on the import intermediary market. In case an intermediary attempts fraud, it gets replaced by its rival.

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The research topic of the work is: “Factors of innovation creation within functionally heterogeneous project teams”. The research question is “What are the factors of innovation creation within functionally heterogeneous project teams?” The subject of this research is to explore the teams of projects, aimed at creating innovations, and understand how innovation is generated through project team work within them in term of factors. In line with the purposes of this study, firstly, it was analyzed what factors of such teams’ work are affecting creating innovation positively and negatively on the base of chosen literature and a preliminary conceptional framework was formulated, and secondly, the research of the work of project teams in one of the divisions of ABB company has been done and other factors and interdependencies between them have been added to the conceptional framework. This final conceptional framework constitutes the essense of the work findings and can be used as a tool to analyze the innovation creation process in functionally heterogeneous project teams