China and Russia – two giants in the group of emerging markets – continue to attract wide attention as evolving science and technological superpowers. However, both countries demonstrate mixed success in innovation development and are struggling to overcome the legacies of the former state planning system and accelerate their transition to effective national innovation systems. This study employs a number of theoretical constructs and evidence sources to evaluate the existing path dependencies and compare the achievements of China and Russia in fostering development and effective systems of innovation and governance. A detailed analysis of the state planning legacies is provided together with a study of innovation system transformation and the role of public policy in (re)building national innovation capabilities in China and Russia. The system-evolutionary approach is applied to provide a detailed assessment of the strategic effort undertaken by the governments of both countries. Several government failures and path dependencies seem to prevent the nations from implementing a more effective reform. Yet, there are a number of complementarities and opportunities for mutual learning where both countries can benefit from closer collaboration. The challenges of turning universities into research institutions, increasing productivity of state-owned enterprises, constructing effective science parks, promoting indigenous innovation, ensuring more even distribution of innovation development across regions, turning ‘brain drain’ into ‘brain gain’, and improving intellectual property rights protection are common in Russia and China. As a lens through which to identify and assess innovation systems transformation, the thesis examines emerging nanotechnology development in China and Russia. Nanotechnology is a new science and technology area where policies seem to be independent of many system weaknesses and contribute to breaking existing development lock-ins due to its explorative nature and assumed transformative capacity. Yet, a number of path dependencies do exist in this area but seem to play a marginal role in its progression. An early assessment is provided of nanotechnology impacts on broader socioeconomic development of China and Russia in six key areas: institutional development, knowledge flows, and network efficiency; research and education capabilities; industrial and enterprise growth; cluster and network development; regional spread; and product innovation.The conclusion summarizes the main findings, revisits the major research questions, links the analysis to the conceptual framework, and offers a number of policy recommendations that seem relevant to both Russia and China with a need to increase the transparency of innovation policy, improve the regulation for innovation process, and promote growth of the private sector to ensure effective technology transfer.Results from this study have been reported in various forms in the author’s articles published in Research Policy, Science and Public Policy, Review of Policy Research, International Journal of Economics and Business Research, and European Journal of Development Research as well as presented at a number of international conferences (see Appendix).

Submitted by Juliana Tregnago (julianatregnago@gmail.com) on 2018-06-18T14:56:36Z No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Dissertação_ilmara_Versão Final 2018 - Final.pdf: 3009131 bytes, checksum: 754000508a433f0c384e6fdbc99f7888 (MD5) / Approved for entry into archive by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2018-06-19T13:28:31Z (GMT) No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Dissertação_ilmara_Versão Final 2018 - Final.pdf: 3009131 bytes, checksum: 754000508a433f0c384e6fdbc99f7888 (MD5) / Made available in DSpace on 2018-06-19T13:28:32Z (GMT). No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Dissertação_ilmara_Versão Final 2018 - Final.pdf: 3009131 bytes, checksum: 754000508a433f0c384e6fdbc99f7888 (MD5) Previous issue date: 2017-10-20 / FAPEAM - Fundação de Amparo à Pesquisa do Estado do Amazonas / Groups are a basic social structure, and as inside as outside of the academic world they form and change themselves in various ways for multiple purposes. While students form groups easily out of class, forming groups on a course can be an unnatural process. However, for collaborative learning to succeed, it is important to form groups that can be effective and efficient in accomplishing the objectives of the task. In this sense, it is sought to improve the interactions of students mainly in group activities. The group work is a resource widely used by the teacher, with the intention of encouraging students' interaction in collaborative activities. There is a lack of support for group creation in Virtual Learning Environments (VLEs). In this sense, Learning Path (LPs) can be resources to suggest groups of learners. The use of LPs is promising because it shows the paths taken by students in VLEs, which makes it possible to suggest groups based on these interactions, since to perform groups in the EAD modality is really a challenging task for the teacher. In general, in this modality, students only have 20% of face-to-face contact with each other and with the teacher, making it difficult to establish criteria for grouping. In this context, this research proposes a conceptual framework for the formation of groups in collaborative activities, through data extracted from the LPs graphs, to assist the teacher in the teaching-learning process. To verify the feasibility of the proposed conceptual framework, the M-CLUSTER tool was developed that analyzes the attributes described below and suggests the formation of groups. The mechanism emphasizes the formation of groups by applying the K-Means algorithm, which is used with three similarity metrics, which are the distances: Euclidean, Manhattan and Cosine, using attributes (vertex access, quantity, dispersion and variances of the standard edges, forward and return, and student id) obtained through the data extracted from the LPs. Meetings were held with the teachers (specialists) to validate the results. In the case study, M-CLUSTER used the attributes and classified them with K-Means, obtaining three clustering results, one for each metric. The teacher chooses among the suggestions generated and makes one available to the students so they can choose their partners within the cluster, thus forming the groups. These groups suggested by the tool were validated and visualized by the teacher, from two representations, one descriptive and one visual through bubble charts. To validate the suggested groups, two activities were carried out in the discipline, in the first activity, the students chose their group partners and in the second, the groups were formed according to the suggestions of the tool. According to the results obtained from the case study shows that the tool obtained satisfactory results where 75% of students matched or improved their individual scores in relation to those achieved in the first activity. / Grupos são estruturas sociais básicas, tanto dentro quanto fora do mundo acadêmico, eles se formam e se modificam em vários modos para múltiplos propósitos. Enquanto alunos, formar grupos fora de sala de aula aparenta ser mais fácil, por sua vez, em ambiente educativo formar grupos pode ser um processo complexo. Contudo, para que a aprendizagem colaborativa seja bem-sucedida, é importante formar grupos que possam ser efetivos e eficientes em realizar os objetivos da tarefa. Nesse sentido, busca-se melhorar as interações dos discentes principalmente em atividades em grupo. O trabalho em grupo é um recurso bastante usado pelo docente, com o intuito de incentivar a interação dos alunos nas atividades colaborativas. Há nos AVAs uma deficiência em dar suporte à criação de grupos. As Trilhas de Aprendizagem (TAs) podem ser recursos para sugerir grupos de aprendizes. O uso de TAs é promissora porque mostra os caminhos percorridos pelos alunos nos AVAs, o que possibilita sugerir grupos baseados nessas interações, pois realizar grupos na modalidade EAD é realmente uma tarefa desafiadora para o docente. No geral, nessa modalidade, os alunos só possuem 20% do contato presencial entre si e com o docente, dificultando estabelecer critérios para realizar os agrupamentos. Diante deste contexto, nesta pesquisa é proposta um framework conceitual para formação de grupos em atividades colaborativas, por meio dos dados extraídos dos grafos das TAs, para auxiliar o docente no processo de ensinoaprendizagem. Para verificar a exequibilidade do framework conceitual proposto foi desenvolvida a ferramenta M-CLUSTER que analisa os atributos descritos as seguir e sugere a formação de grupos. O mecanismo dá ênfase à formação dos grupos aplicando o algoritmo K-Means, que é utilizado com três métricas de similaridade, que são as distâncias: Euclidiana, Manhattan e Cosseno, usando os atributos (média de acesso de vértices, quantidade, dispersão e variâncias das arestas padrão, avanço e retorno e id do aluno) obtidos por meio dos dados extraídos das TAs. Foram realizadas reuniões com os docentes (especialistas) para validar os resultados. No estudo de caso, o M-CLUSTER usou os atributos e os classificou com o KMeans, obtendo três resultados de agrupamentos, um para cada métrica. O docente escolhe dentre as sugestões geradas e disponibiliza uma delas aos estudantes para eles escolherem seus parceiros dentro do cluster, assim formando os grupos. Esses grupos sugeridos pela ferramenta foram validados e visualizados pelo docente, a partir de duas representações, uma descritiva e outra visual por meio de gráficos de bolhas. Para validar os grupos sugeridos, foram realizadas duas atividades na disciplina, na primeira atividade, os estudantes escolheram seus parceiros de grupo e na segunda, os grupos foram formados de acordo com as sugestões da ferramenta. De acordo com os resultados obtidos do estudo de caso mostra que, a ferramenta obteve resultados satisfatórios onde 75% dos alunos igualaram ou melhoraram suas notas individuais em relação às alcançadas na primeira atividade.

Abstract The purpose of this thesis is to examine the role of learning and the constituents of learning in creating process innovations and realizing organizational change. Organizational learning was studied and the data was collected in process development projects, in which process simulations were used as a development method for process innovations and change. The empirical research was carried out mainly in 1988–2001. In this thesis, the results of those studies are reflected on, together with the recent literature related to organizational learning theories in the context of process innovations and management of change. Specifically, the concepts of learning enablers, learning outcomes (intangible/tangible), learning paths, and their relationships are studied. Qualitative longitudinal action research with case studies and abductive reasoning are used as the research methods throughout this thesis. The data consists of 34 cases and 99 process simulations in 12 different industries and varies from large core processes to support processes. The case organizations were mainly Finnish companies with Finns as the majority of participants. One case organization was from Switzerland, and in five cases, multicultural groups participated in the process simulations. In each project, process simulations were used at least once during a change project, in some cases even five to eight times. The data analysis proceeded in an abductive manner throughout the included five articles, and the findings are summarized based on the research questions. The theoretical contribution of this thesis is fourfold. The findings give new understanding 1) about learning enablers, their relationships to each other and influence on learning and process innovations, 2) about the role of intangible and tangible learning outcomes in individual and organizational learning processes and 3) about learning paths in process innovations and related change processes. The thesis also defines 4) a model for effective learning processes in change projects concerning process innovations. The contribution in the practical and managerial context should be applicable field of North and West European commercial organizations. This thesis highlights individual and organizational learning in the creation of process innovations, and it also defines the features of an effective development method for creating and implementing process innovations. / Tiivistelmä Tämän väitöskirjan tarkoituksena on tutkia organisaation oppimisen ja sen eri osatekijöiden roolia prosessi-innovaatioiden luomisessa ja muutoksen aikaansaamisessa organisaatiossa. Organisaation oppimista tutkittiin ja aineisto kerättiin prosessien kehittämisprojekteissa, joissa prosessisimulaatioita käytettiin prosessi-innovaatioiden menetelmänä. Tutkimuksen aineisto kerättiin pääsiassa vuosien 1988–2001 aikana. Tässä väitöskirjassa näitä tuloksia analysoidaan vallitsevien organisaatio-oppimisen teorioiden valossa prosessi-innovaatioiden ja muutoksen johtamisen asiayhteydessä. Erityisesti tutkitaan oppimisen mahdollistajia, oppimisen tuloksia (aineettomia/aineellisia), oppimisen polkuja ja kaikkien näiden keskinäisiä suhteita. Tutkimusmenetelmänä on käytetty laadullista pitkittäistä toimintatutkimusta tapaustutkimuksineen ja abduktiivisine päättelyineen. Aineisto koostuu 34 tapaustutkimuksesta ja 99 prosessisimulaatiosta, jotka toteutettiin 12 eri toimialalla, ja vaihtelevat ydinprosesseista tukiprosesseihin. Suurimmaksi osaksi tapausorganisaatiot olivat suomalaisia yrityksiä, ja yksi tapausorganisaatio oli sveitsiläinen. Projektiryhmät olivat pääasiassa suomalaisia, mutta monikulttuurinen ryhmä osallistui prosessisimulointiin viidessä tapaustutkimuksessa. Jokaisessa projektissa prosessisimulointia käytettiin ainakin kerran muutosprojektin aikana, joissakin tapauksissa jopa viidestä kahdeksaan kertaan. Väitöskirjan viiden artikkelin aineiston analysointi suoritettiin abduktiivisen päättelyn periaattein, ja tutkimuksen tulokset esitetään tutkimuskysymysten mukaisesti. Tutkimuksen teoreettinen tulos kohdistuu neljään osa-alueeseen. Tulokset lisäävät ymmärrystä 1) oppimisen mahdollistajista, niiden suhteesta toisiinsa ja vaikutuksesta oppimiseen ja prosessi-innovaatioihin, 2) aineettomien ja aineellisten oppimistulosten roolista yksilön ja organisaation oppimisprosesseissa, ja 3) prosessi-innovaatioiden ja niihin liittyvien muutosprosessien oppimisen poluista. Tutkimus myös määrittelee 4) prosessi-innovaatioita koskevien muutosprojektien oppimista korostavan mallin. Tutkimuksen tuloksia voitaneen soveltaa Pohjois- ja Länsi-Euroopan yritysmaailmassa. Tutkimus korostaa yksilön ja organisaation oppimisen merkitystä prosessi-innovaatioiden luomisessa ja lisäksi se määrittelee vaikuttavan prosessi-innovaatioiden kehittämisen ja käyttöönoton menetelmän piirteet.