Knowledge and Management Models for Sustainable Growth

In the last years sustainability has become a topic of global concern and a key issue in the strategic agenda of both business organizations and public authorities and organisations. Significant changes in business landscape, the emergence of new technology, including social media, the pressure of new social concerns, have called into question established conceptualizations of competitiveness, wealth creation and growth. New and unaddressed set of issues regarding how private and public organisations manage and invest their resources to create sustainable value have brought to light. In particular the increasing focus on environmental and social themes has suggested new dimensions to be taken into account in the value creation dynamics, both at organisations and communities level. For companies the need of integrating corporate social and environmental responsibility issues into strategy and daily business operations, pose profound challenges, which, in turn, involve numerous processes and complex decisions influenced by many stakeholders. Facing these challenges calls for the creation, use and exploitation of new knowledge as well as the development of proper management models, approaches and tools aimed to contribute to the development and realization of environmentally and socially sustainable business strategies and practices

Igniting technological modernization through science towns and technology parks: the case of Russia

Since the turn of the 21st century, the Russian state has attempted to address the country’s excessive dependence on natural resources. It has implemented an ambitious programme of economic modernization, including giving innovation more policy prominence and boosting state funding for research and development (R&D) and innovation. The programme includes a plethora of new initiatives, including innovation strategy documents, R&D funding for institutions, and state support for innovation infrastructure (e.g. clusters, science towns, and science and technology parks). However, despite investing substantial resources in science and technology since 2000 in a variety of forms and with an impressive legacy of scientific R&D from the Soviet period, Russia is still faring comparatively poorly in innovation outcomes, such as the number of innovative enterprises and international patent registrations. This thesis attempts to understand why Russia is performing comparatively poorly in innovation outcomes. It takes a multidisciplinary approach to examine why Russia is not doing as well in economic catch up and innovation as, for example, China. Following Taylor’s (2016) emphasis on the political economy of science, technology, and innovation policies, it suggests that a country’s political economy model is an important driver of innovation performance. The thesis finds that Russia has implemented a wide range of approaches to accelerate growth based on innovation and knowledge and provides new empirical material on Russia’s science towns and technology parks. Yet for all the good intentions and effort, Russia’s larger political economy model, as analysed here, has substantially hindered its rate of innovation and diffusion into commercial enterprises. The challenge of technological modernization is a matter of public concern and a problem to be solved by a diverse range of institutions and societal actors. Accordingly, technological modernization is enlightened by several conceptual perspectives. The five most helpful perspectives used in this thesis are certain modernization theories; rent-seeking (who benefits from modernization processes); neo-Schumpeterian and co-evolutionary growth approaches; innovation systems and innovation policies; and finally, sistema (Ledeneva, 2013), a political economic approach that explains key aspects of Russia’s current authoritarian system

Going Global: The Challenges for Knowledge-based Economies

The present volume aims to provide a comprehensive and systemic overview of the challenges that going global poses to knowledge based economies. Its focus is four-fold. 1) Firstly, it investigates why companies, especially high-tech firms, go global, i.e. which are the drivers that push companies to locate – R&D facilities in particular – elsewhere than in the home country. The analysis of the competitive advantages that enterprises seek in the host countries also includes the new techno-economic geography that emerges. Attention is devoted to the time frame of these phenomena and to features such as the development stage of the home and host country, the characteristics of both firms and industries, and the Product Life Cycle of the latter. 2) Secondly, it analyses the impact that the various corporate relocation phenomena might have on intellectual capital, innovative output and the labour market, and growth and development. (Re)locating in fact impacts on knowledge creation, exploitation – including the use of IPRs – , absorption, circulation and spillovers. In turn, these play a fundamental role in shaping the productivity, competitiveness, and ultimately growth and development of both enterprises and countries. 3) Thirdly, it addresses the questions of if and to what extent the current and prospective global dynamics call for new types of governance. Such a need arises if different policy domains have to converge towards common strategic welfare enhancing objectives. Attention is also devoted to the various policies put in place by small open economies that ‘go global’, such as Finland. 4) Fourthly, it addresses the sustainability aspects of going global by investigating how to better share the social, economical and ecological benefits and responsibilities arising from globalisation, technological change, and innovation. It analyses the impact that globalisation and the knowledge-based paradigm might have on both developed and developing countries.R&D, innovation, outsourcing, offshoring, knowledge spillovers

Universities' academic research and knowledge-transfer activities in a catch-up country: the case of Korea

The main research topic of this study is universities’ academic research and knowledge-transfer activities in a catch-up country, particularly the relationship between the two activities, which has been rarely examined in previous research. In order to understand this issue against existing literature, a critical review of previous studies has been attempted, considering the idiosyncratic characteristics of the Korean national innovation system. As a result, at the three analysis levels (i.e. national, organisational and individual levels), we propose three conceptual elements respectively: a tentative historical path of universities in catch-up countries; critical factors influencing knowledge transfer activities of universities in catch-up countries; and academics operating in synergy mode. Thereafter, based on the methodology integrating not only the three analysis levels but also qualitative and quantitative approaches, we analyse the data collected from the interviews with Korean academics, survey responses from Korean academics and government White Papers on the activities of Korean universities. The results show a close and positive relationship between Korean universities’ academic research and knowledge-transfer activities across the three levels. Firstly, during the last several decades, the Korean government has strongly encouraged the development of teaching, academic research and knowledge-transfer activities of Korean universities in harmony with the different developmental stages of Korean industry. This has resulted in selective patterns of the universities’ three activities (e.g. concentration of scientific activities in certain fields). Secondly, organisational factors such as scientific capacity and industry funding are important for universities’ knowledge-transfer activities in a catch-up country, which corroborates the positive relationship between the two activities. Finally, in terms of the factors influencing the synergy mode (i.e. a positive relationship between academic research and knowledge-transfer activities), academics’ career stage and disciplines are important. This is related to the rapid expansion of the Korean academic system and the selectivity found in its activities. Based on these findings, it is tempting to conclude that universities in East Asian catch-up countries have developed their own academic system different from those in developed countries, which can be characterised as having strong government control and a high level of interaction with other actors in the national innovation system. Therefore, the application of the controversy over the direct economic contribution of universities in western countries to the context of catch-up countries is quite limited

The evolution of innovation networks : an automotive case study

Competitive pressure forces firms to continuously develop new ideas, invent new technologies and bring new products to the market in order to survive the destructive part of Schumpeterian innovation competition. This holds particularly for the automotive industry in Germany, challenged by firms from emerging markets which are able to offer their products for lower prices. In the competition for new technological solutions, competences and cutting-edge knowledge are success factors. New knowledge stimulates the emergence of new ideas that can be transformed into innovation. Such knowledge can partly be generated internally in the companies R&D laboratories. However, relying on internal knowledge generation is no longer sufficient. Participation in innovation networks which allow for access to external knowledge, and applying innovation cooperation as a strategic tool to acquire necessary knowledge which cannot be developed in-house opens up rich opportunities to complement and recombine the own knowledge-base. Thus, knowledge becomes the most important source of competitive advantage. In this dissertation, I analyze the drivers of innovation networks evolution among a sample of German automotive firms.Innovationsnetzwerke dienen im innovationsökonomischen Kontext dazu, komplexe Innovationsprozesse durchzuführen, besser mit technologischer Unsicherheit umzugehen und Gelegenheiten zu gegenseitigem Lernen und Austausch von Wissen zu schaffen (Pyka, 2002). Im Rahmen meines Dissertationsprojektes untersuche ich die zeitliche strukturelle Entwicklung eines Innovationsnetzwerks in der deutschen Automobilindustrie. Im Mittelpunkt stehen dabei die treibenden Faktoren der Netzwerkstrukturveränderung. Das untersuchte Netzwerk basiert auf der Teilnahme von Unternehmen an kollaborativen Forschungsprojekten (Verbundforschung), welche aus Bundesmitteln gefördert werden. Dabei untersuche ich die Relevanz der Akteurseigenschaften (auf individueller und dyadischer Ebene), wie auch eines endogenen Faktors als Determinanten für die Wahrscheinlichkeit eine Kooperation einzugehen. Die in diesem Zusammenhang aus theoretischen Überlegungen abgeleiteten Hypothesen werden mit Hilfe des sogenannten stochastic actor-based model for network dynamics (Snijders, 1996; Snijders, 2001) getestet. Die empirischen Ergebnisse deutschen darauf hin, dass wissensbezogene Faktoren (Absorptionsfähigkeit, technologische Distanz und Modularität der Wissensbasis) wichtige Determinanten der Netzwerkentwicklung sind. Darüber hinaus zeigt sich, dass Transitivität ein endogener hoch signifikanter Faktor ist. Zudem spielt die Kooperationserfahrung wie auch die geographische Distanz eine Rolle. Dagegen haben die Firmengröße wie auch die Industrieerfahrung keinen signifikanten Einfluss auf der Wahrscheinlichkeit einer Teilnahme an einem Verbundforschungsprojekt

Ettevõtete innovatsioonistrateegiate dünaamika ja seosed avaliku sektori toetustega

Innovatsiooni peetakse õigustatult majandusarengu võtmeks. Innovaatilisuse suurendamiseks toetatakse eraettevõtlust riikliku abiga, millest tulenevalt tekib küsimus – kas toetused tõepoolest muudavad ettevõtete käitumist? Doktoritöö keskendub ettevõtete innovatsioonistrateegiate dünaamikale ning seostele ettevõtlustoetustega. Viimased võivad olla näiteks investeeringute tegemiseks, teadus- ja arendustegevuseks, innovatsioonide turule toomiseks, turundusplaanideks, jne. Eesti näitel on hinnatud ettevõtete innovatsioonistrateegiaid, mis toetuvad ühistele sisenditele. Olgu selleks koostööpartnerite valik, valikud investeeringute tegemisel või teadmiste allikad. Selgub, et ettevõtted on võimelised oma innovatsioonistrateegiat muutma tihti, vajadusel mõne aasta jooksul. Siiski on tegemist astmelise arenguga, kõigepealt tulevad lihtsamad strateegiad ja alles seejärel keerulisemad. Seosed ettevõtlustoetustega ei ole ühtsed. Näiteks investeeringutoetustega ettevõtted võtavad suurema tõenäosusega kasutusele lihtsamad innovatsioonistrateegiad. Teadus- ja arendustegevusele suunatud toetustega ettevõtted aga juba keerulisemad strateegiad. Töötajate oskuste arendamisele suunatud toetustega ettevõtted püsivad kauem innovaatilised. Siiski on mitmed toetuste tüübid, kus pole selge, et nad üldse oleks seotud innovatsioonistrateegiatega. Doktoritööst ilmneb, et ettevõtlustoetused peaksid olema disainitud täpsemaid tegevuspõhiseid sihtgruppe silmas pidades. Innovatsioonistrateegiates ei tasu oodata suuri hüppeid vaid järkjärgulist arengut. Kuid oma sihtgrupis peaksid nad olema piisavalt väljakutsuvad, et toetada strateegiaid mis on kogu majandusele kasulikud – avatud, koostööaltid ja teadmuspõhised.Innovation has been on the forefront of public policy as a panacea for economic ills for a long time. Governments on various levels support the creation and diffusion of innovations in private firms with public money. It is justified to ask – does it change firm behaviour? The thesis analyses whether firms change their innovation strategies if they have received business support. The support can be in various forms, such as financial aid to investments, training and skill development, developing marketing plans and exporting plans, innovation and R&D assistance, and so forth. Based on the Estonian example, some commonalities can be established about innovation strategies. Firms adopt different styles of creating innovations relying on diverse inputs, such as their cooperation partners, investment choices or information sources. Firms change between different strategies often and with a short time-frame, in less than two years. Meaning that with proper incentives, it is possible to influence firm behaviour without long lags. However, shifts between strategies show incremental evolution. Firms without any innovation strategies develop simple strategies first, followed by more complex strategies later. The relationship with business support is not uniform. Support for physical capital investments is positively related with simple innovation strategies. Support for innovation and R&D activities is more related with complex innovation strategies, based on open innovation strategies and cooperation with universities. Firms with training and skill development instruments are less likely to stop being innovative at all. Business support should adapt to the proper target audience. Leap-frogging might have limits if firms are very inexperienced. In addition, policy instruments ought to be demanding for firms. Innovation policy instruments should be challenging enough to create strategies that we wish to promote — cooperative, open and R&D intensive.https://www.ester.ee/record=b530632