Hannes Toivanen

African regional innovation systems: bibliometric analysis of research collaboration patterns 2005---2009

Understanding the nature and dynamics of Africa’s collaborative research networks is critical for building and integrating the African innovation system. This paper investigates the collaborative structure of the African research systems, with focus on regions and integration. Drawing on a bibliometric analysis of co-authorship of African research publications in 2005–2009, we propose an empirically derived grouping of African research community into three distinct research regions: Southern–Eastern, Western, and Northern. The three regions are established and defined in terms of active co-authorship clusters within Africa, as well as through co-authorship links with non-African countries and regions. We examine co-authorship links both at the national and city levels in order to provide a robust and nuanced empirical basis for the three African research regions. The collaboration patterns uncovered cast light on the emerging innovation systems in Africa by pointing out the differing national, regional, and global roles of countries and cities within collaborative research networks. Lack of research capabilities is the primary factor arresting the development of African innovation systems, but our analysis also suggests that Africa’s internal research collaboration suffers from structural weaknesses and uneven integration. We also identify that South Africa, and some emerging new research hubs, hold critical networking function for linking African researchers.

Map of science with topic modeling: Comparison of unsupervised learning and human-assigned subject classification

The delineation of coordinates is fundamental for the cartography of science, and accurate and credible classification of scientific knowledge presents a persistent challenge in this regard. We present a map of Finnish science based on unsupervised‐learning classification, and discuss the advantages and disadvantages of this approach vis‐à‐vis those generated by human reasoning. We conclude that from theoretical and practical perspectives there exist several challenges for human reasoning‐based classification frameworks of scientific knowledge, as they typically try to fit new‐to‐the‐world knowledge into historical models of scientific knowledge, and cannot easily be deployed for new large‐scale data sets. Automated classification schemes, in contrast, generate classification models only from the available text corpus, thereby identifying credibly novel bodies of knowledge. They also lend themselves to versatile large‐scale data analysis, and enable a range of Big Data possibilities. However, we also argue that it is neither possible nor fruitful to declare one or another method a superior approach in terms of realism to classify scientific knowledge, and we believe that the merits of each approach are dependent on the practical objectives of analysis.

Waves of Technological Innovation: The Evolution of the US Pulp and Paper Industry, 1860–2000

Technological innovation, big and small, has played a critical role in the evolution of the modern United States pulp and paper industry since its origins in the early nineteenth century. New technological knowledge and its implementation, more than anything else, gave entrepreneurs, firms, industries, and whole regions, the ability to create or capture new markets, or erect new production hubs, and to forge ahead competitors.

The shift from theory to innovation: the evolution of Brazilian research frontiers 2005–2011

Proliferation of emerging economies as significant sources of competitive knowledge is a key feature of globalisation, often driven by government policies fostering domestic research-based innovation capabilities. To cast light on this common emerging economy effort to move from catch-up towards the global innovation frontier, we analyse the evolution of the focus of Brazilian research frontiers 2005–2011 with bibliometric methods. Our results demonstrate a gradual and moderate shift from theoretical scientific knowledge to more innovation-centred knowledge in the most influential Brazilian research, indicating the increased prominence and quality of innovation focused efforts in countrys knowledge system. Thus, the recent expansion of Brazils innovation system is accompanied by qualitative transformations of the research system, in part driven by nationally emerging research fields and technologies. Conceptually, we consider the overall importance of scientific research for developing and emerging economy innovation system build-up.

The global inventor gap: Distribution and equality of world-wide inventive effort, 1990-2010

Applying distance-to-frontier analysis, we have used 2.9 million patents and population data to assess whether the relative capacity of world countries and major regions to create new knowledge and technology has become globally more equal or less equal between 1990 and 2010. We show with the Gini coefficient that the global distribution of inventors has become more equal between major countries and regions. However, this trend has been largely due to the improved performance of only two major countries, China and India. The worst performing regions, totalling a population of almost 2 billion, are actually falling behind. Our results suggest that substantial parts of the global population have fallen further behind countries at the global frontier in their ability to create new knowledge and inventions, and that the catch-up among the least developed and middle-income countries is highly uneven, prompting questions about the nature and future of the global knowledge economy.

Innovation, the informal economy and development: The case of Zambia

National systems of innovation have been serving as the conceptual framework and vehicle to address poverty and national competitiveness in developing countries. Zambia has been building its NSI since 1964, but the existing system suffers from serious shortcomings related to an insufficient conceptually inclusive framework and the absence of direct and concrete pro-poor innovation policy instruments. The system lacks strong interactive dynamics and suffers from weak governance. Zambia has also followed an export-driven industrial economy, but the expected knowledge spill-over gains from large mining operations have not been realised. The paper examines national innovation strategies by emphasising the importance of the informal sector and the potential for innovation at grass-roots level. It examines the evolution of science and technology policies by highlighting how the excluded areas can be included. The absence of pro-poor innovation and lack of inclusive policies are highlighted as factors contributing to low productivity and socioeconomic imbalances.

Unsupervised learning based patent landscapes using full-text patent data

The complexity technologies require that companies have in-depth knowledge of the nature and effect of knowledge - its depth and breadth. Companies need to master expanding technological knowledge bases creating tensions for MOT. We examine how big data in patent landscaping creates insights into MOT. Using big data to manage Competitive Technical Intelligence, companies can foster new forms of adaptive learning processes in MOT. This however requires that managers augment human judgment with machine-learning tools, prompting challenges to management traditions. We demonstrate how unsupervised learning creates insight into MOT by identifying topical knowledge foci and showing the dynamics of knowledge domains among companies. Using unsupervised learning and network analysis; we show how a semantic analysis leads to the identification of opportunities in complex environments. We illustrate this using a case in globally operating telecommunication companies using a full-text copy of USPTO-database with approximately 6 million patents data. Our results show the landscape of the companies and the underlying knowledge embedded in the companies. We discuss how managers can evaluate their technological knowledge against competitors, balancing current needs with the adoption of new knowledge. We further discuss how a semantic analysis can lead to the discovery of latent patterns and identification of opportunities.

Research and development: Bibliometric analysis of knowledge flows of Brazilian research 2005–2009

By examining the knowledge in- and outflows in Brazilian research 2005–2009, we undertake comparative bibliometric analysis of the dynamics of knowledge creation in development context. Specifically, we analyse knowledge creation dynamics to find out how knowledge flows between developing countries and the “North” shape research and its exploitation.