40 resultados para aggregation of knowledge


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The importance of the regional level in research has risen in the last few decades and a vast literature in the fields of, for instance, evolutionary and institutional economics, network theories, innovations and learning systems, as well as sociology, has focused on regional level questions. Recently the policy makers and regional actors have also began to pay increasing attention to the knowledge economy and its needs, in general, and the connectivity and support structures of regional clusters in particular. Nowadays knowledge is generally considered as the most important source of competitive advantage, but even the most specialised forms of knowledge are becoming a short-lived resource for example due to the accelerating pace of technological change. This emphasizes the need of foresight activities in national, regional and organizational levels and the integration of foresight and innovation activities. In regional setting this development sets great challenges especially in those regions having no university and thus usually very limited resources for research activities. Also the research problem of this dissertation is related to the need to better incorporate the information produced by foresight process to facilitate and to be used in regional practice-based innovation processes. This dissertation is a constructive case study the case being Lahti region and a network facilitating innovation policy adopted in that region. Dissertation consists of a summary and five articles and during the research process a construct or a conceptual model for solving this real life problem has been developed. It is also being implemented as part of the network facilitating innovation policy in the Lahti region.

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Knowledge flow from the customers is an important resource for a company and therefore it should engage its customers in knowledge co-creation. Through providing a virtual customer environment (VCE) as knowledge creation and sharing platform a company can obtain this type of knowledge, which is important for strategic purposes. In the VCE the members of the virtual customer community (VCC) create and share knowledge individually and collectively in diverse roles, utilizing many interaction facilities. Creating a functional VCE is not either easy or quick task and a company needs to analyze various issues carefully. Providing such a VCE in which customers want to share their experiences and insights is however worth of considering, since it brings many benefits for the company. In this research the main benefit is stated as the supportative role of the VCE in the better management of the knowledge flow from the customers.

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Previous studies of the local involvement of multinational corporation (MNC) subsidiaries focus on host-country firms and local business partners such as suppliers and customers. The role of host-country universities in the same context of innovation networks is neglected. Furthermore, there are many organizational culture- and knowledge-related differences between universities and companies, and this is likely to pose additional challenges for successful collaboration. Early university-industry (U-I) studies have primarily been limited within a national boundary, being concerned with a single level of culture (i.e., at an organizational level) and one-way knowledge transfer from university to industry. Research on more dynamic knowledge interaction in multinational settings is lacking. This is particularly true in the business context of China. In today’s globalizing and rapidly changing organizations, addressing cultural differences and clashes is an everyday reality, and inter-cultural U-I collaboration is becoming a key asset for gaining global competitiveness. This study deals with Finnish MNC subsidiaries’ research collaboration with Chinese universities. It aims to explore the essence of such U-I collaboration and knowledge interaction, uncovering the deep functioning mechanisms of culture underlying effective collaborative knowledge creation and innovation. The study reviews critically different bodies of literature including knowledge management theories and studies, U-I collaboration and knowledge interaction, and cross-cultural research in terms of organizational knowledge generation and utilization. It adopts a case study strategy with qualitative research methods, and data is collected through in-depth interviews and participant observation. The study presents the following major findings: 1. In the light of a comprehensive analysis of U-I collaboration, an effective matching strategy is proposed, in the assumption that good alignment of knowledge interaction strategies and approaches with their corresponding knowledge type, capability development and research task may greatly enhance the effectiveness of cross-cultural U-I collaboration and knowledge interaction. 2. It is proposed that in the Chinese MNC context more dynamic types of knowledge interaction like knowledge co-creation should be of key concern particularly when dealing simultaneously with multi-disciplinary applied research of human factors and technologies. U-I knowledge interaction, otherwise, pays attention only to the study of one-way technology and knowledge transfer. 3. It is posited that the influence of culture on collaborative knowledge interaction can be studied in a valuable way when knowledge-related variables are simultaneously taken into account. A systematic analysis of the role of knowledge in cross-cultural knowledge interaction could best be approached from multi-aspects of knowledge including not only nature, characteristics and types of knowledge but also the process of knowledge (e.g., intensifications of knowledge interaction). 4. The study demonstrates the significant role of aspects of the host-country culture (e.g., Chinese guanxi) in U-I collaboration and knowledge interaction. This is evident, for instance, in issues related to interpersonal relationships and trust, true interest and the relatedness of the research, mutual commitment and learning, communication intensity and interaction, and awareness of cultural and knowledge-related differences between collaboration partners. Theoretical and practical implications of the findings are suggested and discussed.

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The study explores knowledge transfer between retiring employees and their successors in expert work. My aim is to ascertain whether there is knowledge development or building new knowledge related to this organisational knowledge transfer between generations; in other words, is the transfer of knowledge from experienced, retiring employees to their successors merely retention of the existing organisational knowledge by distributing it from one individual to another or does this transfer lead to building new and meaningful organisational knowledge. I call knowledge transfer between generations and the possibly related knowledge building in this study knowledge sharing between generations. The study examines the organisation and knowledge management from a knowledge-based and constructionist view. From this standpoint, I see knowledge transfer as an interactive process, and the exploration is based on how the people involved in this process understand and experience the phenomenon studied. The research method is organisational ethnography. I conducted the analysis of data using thematic analysis and the articulation method, which has not been used before in organisational knowledge studies. The primary empirical data consists of theme interviews with twelve employees involved in knowledge transfer in the organisation being studied and five follow-up theme interviews. Six of the interviewees are expert duty employees due to retire shortly, and six are their successors. All those participating in the follow-up interviews are successors of those soon to retire from their expert responsibilities. The organisation in the study is a medium-sized Finnish firm, which designs and manufactures electrical equipment and systems for the global market. The results of the study show that expert work-related knowledge transfer between generations can mean knowledge building which produces new, meaningful knowledge for the organisation. This knowledge is distributed in the organisation to all those that find it useful in increasing the efficiency and competitiveness of the whole organisation. The transfer and building of knowledge together create an act of knowledge sharing between generations where the building of knowledge presupposes transfer. Knowledge sharing proceeds between the expert and the novice through eight phases. During the phases of knowledge transfer the expert guides the novice to absorb the knowledge to be transferred. With the expert’s help the novice gradually comes to understand the knowledge and in the end he or she is capable of using it in his or her work. During the phases of knowledge building the expert helps the novice to further develop the knowledge being transferred so that it becomes new, useful knowledge for the organisation. After that the novice takes the built knowledge to use in his or her work. Based on the results of the study, knowledge sharing between generations takes place in interaction and ends when knowledge is taken to use. The results I obtained in the interviews by the articulation method show that knowledge sharing between generations is shaped by the novices’ conceptions of their own work goals, knowledge needs and duties. These are not only based on the official definition of the work, but also how the novices find their work or how they prioritise the given objectives and responsibilities. The study shows that the novices see their work primarily as maintenance or development. Those primarily involved in maintenance duties do not necessarily need knowledge defined as transferred between generations. Therefore, they do not necessarily transfer knowledge with their assigned experts, even though this can happen in favourable circumstances. They do not build knowledge because their view of their work goals and duties does not require the building of new knowledge. Those primarily involved in development duties, however, do need knowledge available from their assigned experts. Therefore, regardless of circumstances they transfer knowledge with their assigned experts and also build knowledge because their work goals and duties create a basis for building new knowledge. The literature on knowledge transfer between generations has focused on describing either the knowledge being transferred or the means by which it is transferred. Based on the results of this study, however, knowledge sharing between generations, that is, transfer and building is determined by how the novice considers his or her own knowledge needs and work practices. This is why studies on knowledge sharing between generations and its implementation should be based not only on the knowledge content and how it is shared, but also on the context of the work in which the novice interprets and shares knowledge. The existing literature has not considered the possibility that knowledge transfer between generations may mean building knowledge. The results of this study, however, show that this is possible. In knowledge building, the expert’s existing organisational knowledge is combined with the new knowledge that the novice brings to the organisation. In their interaction this combination of the expert’s “old” and the novice’s “new” knowledge becomes new, meaningful organisational knowledge. Previous studies show that knowledge development between the members of an organisation is the prerequisite for organisational renewal which in turn is essential for improved competitiveness. Against this background, knowledge building enables organisational renewal and thus enhances competitiveness. Hence, when knowledge transfer between generations is followed by knowledge building, the organisation kills two birds with one stone. In knowledge transfer the organisation retains the existing knowledge and thus maintains its competitiveness. In knowledge building the organisation developsnew knowledge and thus improves its competitiveness.

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The paper presents a study which is aimed at building a knowledge model for a case company – business incubator “Ingria” (St. Petersburg, Russia). The business incubator is one of its kind organization in St. Petersburg, and one of the few in Russia, providing services for innovative entrepreneurial companies at an international level. Business incubation impact is deeply researched from the point of view of knowledge engineering. The paper also provides a broad analysis of various knowledge engineering tools used for visualization of knowledge, as well as knowledge modeling techniques.

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The challenges of knowledge sharing after cross-border acquisitions are widely recognised. The study took a new view to the subject by applying a two-level framework provided by the knowledge governance approach. The purpose of the study was to investigate the effects of organizational mechanisms on the conditions of individuals for knowledge sharing in post-acquisition integration context. Qualitative research methods were used in this case study. Individual interviews were performed within an international firm after a recent cross-border acquisition. The results showed that integrators, the rotation of the personnel from the acquiring firm and visits and meetings enhance the conditions at the individual level for knowledge sharing after the acquisition. Respectively, strategic change, matrix structure and foreign HRM practices challenge the conditions at the individual level for knowledge sharing in the early post-acquisition integration phase. The findings are supported by the prior research on knowledge management in acquisitions. In particular, the study enlightens how organizational level actions influence the conditions of individuals for knowledge sharing. The study suggests that organizations should adjust organizational mechanisms to support the conditions of individuals, in order to promote knowledge sharing in the early phase of the integration.

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This study discusses the importance of diasporas’ knowledge with regard to the national competitive advantage of Finland. The purpose of this study is to suggest an interaction framework, which illustrates how diasporas can benefit the host country via intentional knowledge spillovers, with two sub-objectives: to seek which features are crucial for productive interaction between a host government and diasporas, and to scrutinize the modes of interaction currently effective in Finland. The theoretical background of the study consists of literature relating to the concepts of diaspora and knowledge. The empirical research conducted for this study is based on expert interviews. The interview data was collected between September and November 2013. Eight interviews were made; five with representatives of expert organizations, and three with immigrants. Thematic analysis was used to categorize and interpret the interview data. In addition, thematic networks were built to act as a basis of analysis. This study finds that knowledge, especially new combinations of knowledge, is a significant input in innovation. Innovation is found to be the basis of national competitive advantage. Thus the means through which knowledge is transferred are of key importance. Diasporas are found a good source of new knowledge, and thus may aid the innovative process. Host country stance and policy are found to have a major impact on the ability of the host country to benefit from diasporas’ knowledge. As a host country, this study finds Finland to have a very fragmented strategy field and a prejudiced attitude, which currently make it difficult to utilize the potential of diasporas. The interaction framework based on these findings suggests ways in which Finland can improve its national competitive advantage through acquiring the innovative potential of diasporas. Strategy revision and increased promotion are discussed as means towards improved interaction. In addition, the importance of learning is emphasized. The findings of this study enhance understanding of the relationship between the concepts of diaspora and knowledge. In addition, this study ties the relationship to economic benefit. Future research is, however, necessary in order to fully understand the meaning of the relationship, as well as to increase understanding of the generalizability of the interaction framework.

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A growing concern for organisations is how they should deal with increasing amounts of collected data. With fierce competition and smaller margins, organisations that are able to fully realize the potential in the data they collect can gain an advantage over the competitors. It is almost impossible to avoid imprecision when processing large amounts of data. Still, many of the available information systems are not capable of handling imprecise data, even though it can offer various advantages. Expert knowledge stored as linguistic expressions is a good example of imprecise but valuable data, i.e. data that is hard to exactly pinpoint to a definitive value. There is an obvious concern among organisations on how this problem should be handled; finding new methods for processing and storing imprecise data are therefore a key issue. Additionally, it is equally important to show that tacit knowledge and imprecise data can be used with success, which encourages organisations to analyse their imprecise data. The objective of the research conducted was therefore to explore how fuzzy ontologies could facilitate the exploitation and mobilisation of tacit knowledge and imprecise data in organisational and operational decision making processes. The thesis introduces both practical and theoretical advances on how fuzzy logic, ontologies (fuzzy ontologies) and OWA operators can be utilized for different decision making problems. It is demonstrated how a fuzzy ontology can model tacit knowledge which was collected from wine connoisseurs. The approach can be generalised and applied also to other practically important problems, such as intrusion detection. Additionally, a fuzzy ontology is applied in a novel consensus model for group decision making. By combining the fuzzy ontology with Semantic Web affiliated techniques novel applications have been designed. These applications show how the mobilisation of knowledge can successfully utilize also imprecise data. An important part of decision making processes is undeniably aggregation, which in combination with a fuzzy ontology provides a promising basis for demonstrating the benefits that one can retrieve from handling imprecise data. The new aggregation operators defined in the thesis often provide new possibilities to handle imprecision and expert opinions. This is demonstrated through both theoretical examples and practical implementations. This thesis shows the benefits of utilizing all the available data one possess, including imprecise data. By combining the concept of fuzzy ontology with the Semantic Web movement, it aspires to show the corporate world and industry the benefits of embracing fuzzy ontologies and imprecision.

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The objective of this thesis is to develop and generalize further the differential evolution based data classification method. For many years, evolutionary algorithms have been successfully applied to many classification tasks. Evolution algorithms are population based, stochastic search algorithms that mimic natural selection and genetics. Differential evolution is an evolutionary algorithm that has gained popularity because of its simplicity and good observed performance. In this thesis a differential evolution classifier with pool of distances is proposed, demonstrated and initially evaluated. The differential evolution classifier is a nearest prototype vector based classifier that applies a global optimization algorithm, differential evolution, to determine the optimal values for all free parameters of the classifier model during the training phase of the classifier. The differential evolution classifier applies the individually optimized distance measure for each new data set to be classified is generalized to cover a pool of distances. Instead of optimizing a single distance measure for the given data set, the selection of the optimal distance measure from a predefined pool of alternative measures is attempted systematically and automatically. Furthermore, instead of only selecting the optimal distance measure from a set of alternatives, an attempt is made to optimize the values of the possible control parameters related with the selected distance measure. Specifically, a pool of alternative distance measures is first created and then the differential evolution algorithm is applied to select the optimal distance measure that yields the highest classification accuracy with the current data. After determining the optimal distance measures for the given data set together with their optimal parameters, all determined distance measures are aggregated to form a single total distance measure. The total distance measure is applied to the final classification decisions. The actual classification process is still based on the nearest prototype vector principle; a sample belongs to the class represented by the nearest prototype vector when measured with the optimized total distance measure. During the training process the differential evolution algorithm determines the optimal class vectors, selects optimal distance metrics, and determines the optimal values for the free parameters of each selected distance measure. The results obtained with the above method confirm that the choice of distance measure is one of the most crucial factors for obtaining higher classification accuracy. The results also demonstrate that it is possible to build a classifier that is able to select the optimal distance measure for the given data set automatically and systematically. After finding optimal distance measures together with optimal parameters from the particular distance measure results are then aggregated to form a total distance, which will be used to form the deviation between the class vectors and samples and thus classify the samples. This thesis also discusses two types of aggregation operators, namely, ordered weighted averaging (OWA) based multi-distances and generalized ordered weighted averaging (GOWA). These aggregation operators were applied in this work to the aggregation of the normalized distance values. The results demonstrate that a proper combination of aggregation operator and weight generation scheme play an important role in obtaining good classification accuracy. The main outcomes of the work are the six new generalized versions of previous method called differential evolution classifier. All these DE classifier demonstrated good results in the classification tasks.

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This dissertation centres on the themes of knowledge creation, interdisciplinarity and knowledge work. My research approaches interdisciplinary knowledge creation (IKC) as practical situated activity. I argue that by approaching IKC from the practice-based perspective makes it possible to “deconstruct” how knowledge creation actually happens, and demystify its strong intellectual, mentalistic and expertise-based connotations. I have rendered the work of the observed knowledge workers into something ordinary, accessible and routinized. Consequently this has made it possible to grasp the pragmatic challenges as well the concrete drivers of such activity. Thus the effective way of organizing such activities becomes a question of organizing and leading effective everyday practices. To achieve that end, I have conducted ethnographic research of one explicitly interdisciplinary space within higher education, Aalto Design Factory in Helsinki, Finland, where I observed how students from different disciplines collaborated in new product development projects. I argue that IKC is a multi-dimensional construct that intertwines a particular way of doing; a way of experiencing; a way of embodied being; and a way of reflecting on the very doing itself. This places emphasis not only the practices themselves, but also on the way the individual experiences the practices, as this directly affects how the individual practices. My findings suggest that in order to effectively organize and execute knowledge creation activities organizations need to better accept and manage the emergent diversity and complexity inherent in such activities. In order to accomplish this, I highlight the importance of understanding and using a variety of (material) objects, the centrality of mundane everyday practices, the acceptance of contradictions and negotiations well as the role of management that is involved and engaged. To succeed in interdisciplinary knowledge creation is to lead not only by example, but also by being very much present in the very everyday practices that make it happen.