The Innovation Process – Aiming towards Innovativeness in a Construction Company

The bachelor’s thesis concentrates on the innovativeness in the construction industry. The purpose of the thesis is to define the innovation as a concept reflected on a context of the construction industry. The second objective is to examine how the construction companies could foster and increase the innovativeness. The third objective was to find out tools, methods and phases of the front-end of the innovation process. The construction industry is often considered as a traditional and an old-fashioned manufacturing industry. The innovation or the innovativeness rarely linked to the construction industry. Productivity is a common problem in the construction industry. The construction industry needs to increase the productivity to compete in a globalized world. The productivity can be increased by the innovation. The thesis based on a literature review. The findings from the literature include a description of the innovation as a concept, the innovative culture and the innovation process as a context of the construction industry. The phases of the front-end of the innovation process were explained. Customers centered approach was taken into account in the innovation process. The required tools and methods for managing the front-end of the innovation process were illustrated. The thesis ensures the importance of the innovation facing challenges of the construction industry. Managing the front-end of the innovation is the most important aspect to stand out from the less innovative companies. To take a full advantage of the innovation companies cannot fear of changes. The innovation process requires a full support of the top management of the company. Taking into consideration a theoretical aspect of the thesis a further research is required to respond practical needs of the company. Tools and methods should be considered according the company’s needs and activities. Company’s existing state and culture should be examined before implementing the front-end of the innovation process to ensure the functionality.

Modeling and developing a customer-oriented configuration process in a mass customization environment

In this thesis the main objective is to examine and model configuration system and related processes. When and where configuration information is created in product development process and how it is utilized in order-delivery process? These two processes are the essential part of the whole configuration system from the information point of view. Empirical part of the work was done as a constructive research inside a company that follows a mass customization approach. Data models and documentation are created for different development stages of the configuration system. A base data model already existed for new structures and relations between these structures. This model was used as the basis for the later data modeling work. Data models include different data structures, their key objects and attributes, and relations between. Representation of configuration rules for the to-be configuration system was defined as one of the key focus point. Further, it is examined how the customer needs and requirements information can be integrated into the product development process. Requirements hierarchy and classification system is presented. It is shown how individual requirement specifications can be connected for physical design structure via features by developing the existing base data model further.

"Fuzzy front end" ja sen menestyksekäs johtaminen teollisuusyrityksessä

Työssä käsitellään innovaatioprosessin ensimmäistä ”fuzzy front end” -vaihetta, jota työssä kutsutaan front end -vaiheeksi. Front end -vaihe on innovaatioprosessin alustava tutkimus ja suunnittelu vaihe ennen teknistä kehittämisvaihetta. Front end -vaihetta on tutkittu innovaatioprosessin osista vähiten, sekä se on useimmille yrityksillä sumea ja vaikeasti käsitettävä. Tutkimusten mukaan front end -vaiheen osaaminen on kuitenkin erittäin merkittävä tekijä yrityksen innovatiivisuudelle. Työssä avataan innovaatioprosessin sisältöä ja tavoitteita, sekä vertaillaan käytössä olevia malleja front end -vaiheen rakenteesta. Työssä selvitetään avaintekijöitä front end -vaiheen menestykseen ja tehokkuuteen. Lisäksi käsitellään johtamisen tekijöitä, jotka edesauttavat onnistumaan front end -vaiheessa.

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 ADAPTATION PROCESS AND CHALLENGES OF EDUCATION EXPORT

The purpose of this study is to investigate the challenges of the adaptation process of education export. The research is conducted as a single case study that concentrates on three education export projects. The case company in the research is Team Academy. The study goes through the different forms of education export, the adaptation of education export and the challenges of the education export –process by means of theory and empirical data. The research is carried out as a qualitative research and the method used is a qualitative content analysis. More specifically the research is an abductive content analysis. The research data is collected in four in-depth interviews from Team academy representatives who have been strongly involved in certain education export –project of Team Academy. The research confirms the theory in the challenge of hierarchy, funding and registration issues, and refutes it in the challenge of competition, legislation, different governmental attitudes and knowledge in productization. The main challenges of the adaptation process are related to funding, differences in values, sudden changes, the complex nature of the learning model, concept of time, teamwork as method and accreditation. It is highlighted that in the future operations, anticipating problems that arise from for example cultural differences and differences in values, communication, managing the money flows and the company form is recommended. Future research could continue with investigating the suitable company form for education exports of this kind, and how to stand out and communicate when operating under another institution. It is considered a potential risk that a brand encloses the brand that operates under it.