Standard-Setting and Knowledge Dynamics in Innovation Clusters

Extensive research has been conducted on how firms and regions take advantage of spatially concentrated assets, and also why history matters to regional specialisation patterns. In brief, it seems that innovation clusters as a distinctive regional entity in international business and the geography of innovation are of increasing importance in STI policy, innovation systems and competitiveness studies. Recently, more and more research has contributed to an evolutionary perspective on collaboration in clusters. Nonetheless, the field of cluster or regional innovation systems remains a multidisciplinary field where the state of the art is determined by the individual perspective (key concepts could, for example, be industrial districts, innovative clusters with reference to OECD, regional knowledge production, milieus & sticky knowledge, regional lock-ins & path dependencies, learning regions or sectoral innovation systems). According to our analysis, the research gap lies in both quantitative, comparative surveys and in-depth concepts of knowledge dynamics and cluster evolution. Therefore this paper emphasises the unchallenged in-depth characteristics of knowledge utilisation within a cluster's collaborative innovation activities. More precisely, it deals with knowledge dynamics in terms of matching different agents´ knowledge stocks via knowledge flows, common technology specification (standard-setting), and knowledge spillovers. The means of open innovation and system boundaries for spatially concentrated agents in terms of knowledge opportunities and the capabilities of each agent await clarification. Therefore, our study conceptualises the interplay between firm- and cluster-level activities and externalities for knowledge accumulation but also for the specification of technology. It remains particularly unclear how, why and by whom knowledge is aligned and ascribed to a specific sectoral innovation system. Empirically, this study contributes with several descriptive calculations of indices, e.g. knowledge stocks, GINI coefficients, Herfindahl indices, and Revealed Patent Advantage (RPA), which clearly underline a high spatial concentration of both mechanical engineering and biotechnology within a European NUTS2 sample for the last two decades. Conceptually, our paper matches the geography of innovation literature, innovation system theory, and new ideas related to the economics of standards. Therefore, it sheds light on the interplay between knowledge flows and externalities of cluster-specific populations and the agents' use of such knowledge, which is concentrated in space. We find that knowledge creation and standard-setting are cross-fertilising each other: although the spatial concentration of assets and high-skilled labour provides new opportunities to the firm, each firm's knowledge stocks need to be contextualised. The context in terms of 'use case' and 'knowledge biography' makes technologies (as represented in knowledge stocks) available for collaboration, but also clarifies relevance and ownership, in particular intellectual property concerns. Owing to this approach we propose a conceptualisation which contains both areas with inter- and intra-cluster focus. This proposal additionally concludes that spatial and technological proximity benefits standard-setting in high-tech and low-tech industries in very different ways. More precisely, the versatile tension between knowledge stocks, their evolution, and technical specification & implementation requires the conceptualisation and analysis of a non-linear process of standard-setting. Particularly, the use case of technologies is essential. Related to this approach, clusters strongly support the establishment of technology use cases in embryonic high-tech industries. Low-tech industries in contrast rather depend on approved knowledge stocks, whose dynamics provide better and fast accessible knowledge inputs within low-tech clusters.innovation clusters, standard-setting, knowledge externalities and flows, knowledge alignment, mechanical engineering, biotechnology

The Industrial Application of Patent Analysis: An Empirical Study

This research investigates the value of patent analysis in an industrial context. An empirical approach is taken to test the benefits and limitations of a series of patent analysis techniques. The technology profiles of a group of competitor companies within the oil/petrochemicals area are mapped to evaluate the analysis techniques. Patent quantity analysis benefits from speed of execution but provides no indication of patent quality. The International Patent Classification (IPC) hierarchy can map a company’s technological diversity but the correlation of IPC categories with industry or product areas may present difficulties in a business-focused analysis. An experiment within the polymer chemistry area suggests there is a positive association between a patent’s citation counts and its commercial significance, as rated by expert grading. This supports the use of patent citation data to compare the quality of companies’ patent portfolios but the time lag to build citation counts may limit its usefulness in practice. Maps of inter-company patent references may indicate technological leadership but the value of other bibliographic-based techniques appears more marginal. A trend of inter-company differences in the volume of the ‘References Cited’ list is observed. If confirmed, this could impact the value of bibliographic-based patent analysis techniques. Patent analysis can assist in a merger evaluation, particularly at the due diligence phase, but it is often of secondary importance to financial and product market information. Several factors that may distort patent statistics are identified. These include inadequate company name consolidation, errors in patent classification and differences in national patent legislation. The study concludes that patent analysis has a valid place in the corporate environment, provided the output is interpreted judiciously

Text mining to gain technical intelligence for acquired target selection: A case study for China's computer numerical control machine tools industry

© 2016 Elsevier Inc. Technology strategy plays an increasingly important role in today's Mergers and Acquisitions (M&A) activities. Informing that strategy with empirical intelligence offers great potential value to R&D managers and technology policy makers. This paper proposes a methodology, based on patent analysis, to extract technical intelligence to identify M&A target technologies and evaluate relevant target companies to facilitate M&A target selection. We apply the term clumping process and a trend analysis together with policy and market information to profile present R&D status and capture future development signals and trends in order to grasp a range of significant domain-based technologies. Furthermore, a comparison between a selected acquirer and leading players is used to identify significant technologies and sub-technologies for specific strategy-oriented technology M&A activities. Finally, aiming to recommend appropriate M&A target companies, we set up an index-based system to evaluate the acquired target candidates from both firms-side perspective and target firm-side perspective and differentially weigh for specific M&A situations. We provide an empirical study in the field of computer numerical control machine tools (CNCMT) in China to identify technology M&A targets for an emerging Chinese CNCMT company — Estun Automation under different M&A strategies

Nanotechnology as general purpose technology

Scientific literature postulates that nanotechnology is to be considered as general purpose technology (GPT), characterized by pervasiveness, high technological dynamism and the inducement of innovations within a variety of applications. We set out to not only further systematize existing approaches investigating nanotechnology\u27s GPT traits based on patent applications, but to extend the analysis to academic publication data, in order to cover both knowledge creation and application development. By utilizing well established and consolidated indicators of GPT features, such as generality, diffusion, and forward citation rates, as well as contextualized technological coherence as a new weighted generality measure, we compare nanotechnology\u27s research output to the ones of ICT as accepted GPT and of the combustion engine as a non- GPT, representing an upper and lower benchmark, respectively. Moreover, we add the EU27 as new institutional setting. Our results indicate that while nanotechnology is not as clearly perceptible a GPT as ICT is, the potential to develop as such and hence to become an \u27engine of growth\u27 is clearly given

Mergers, acquisitions and technological regimes: the European experience over the period 2002-2005

Comparisons by countries and by sectors of mergers and acquisitions have usually been performed in separate fields of research. A first group of studies, focusing on international comparisons, has explored the role of corporate governance systems, investor protection laws and other countries’ regulatory institutions as the main determinants of takeovers around the world. A second group of contributions has attributed a central role to variations in industry composition, documenting that, in each country, mergers occur in waves and within each wave clustering by industry is observed. This paper aims to integrate both perspectives and to make comparisons by countries and by sectors, thus exploring the role of various driving forces on takeover activities. It also intends to consider the specific influence that technological regimes and their innovation patterns may exert in reallocating assets and moving capital among sectors. This will be done by examining the European experience of the last few years (2002-2005). We found that even in countries where transfer of control is a frequent phenomenon, mergers are less frequent in those sectors where innovation is a cumulative process and where takeovers may be a threat to the continuity of accumulation of innovative capabilities.Mergers and Acquisitions, Corporate Governance, Technological Regimes