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Purpose: This paper aims to investigate the antecedents of recombinant innovation from the perspective of ego–network dynamics, and further disentangle whether ego–network stability or ego–network expansion is more conducive to recombinant innovation under heterogeneous knowledge base. Design/methodology/approach: This paper uses 1,801 patent data in China's biotechnology field as a sample and adopts fixed effects regression model to examine the effects of ego–network dynamics on recombinant innovation and further uses the Wald tests to discern which ego–network dynamic is more conducive to recombinant innovation under heterogeneous knowledge base. Findings: The empirical results indicate that ego–network dynamics have a positive impact on recombinant innovation. Specifically, for firms with high knowledge breadth and high knowledge depth as well as high knowledge breadth and low knowledge depth, ego–network stability is more conducive to recombinant innovation. By contrast, for firms with low knowledge breadth and high knowledge depth, recombinant innovation benefits more from ego–network expansion. As for firms with low knowledge breadth and low knowledge depth, both ego–network stability and ego–network expansion can promote recombinant innovation, while the effects are not significant. Practical implications: This research may enlighten managers to choose suitable ego–network dynamics strategies for recombinant innovation based on their knowledge base. Originality/value: This research not only contributes to the literature on recombinant innovation by revealing the impact of different ego–network dynamics on recombinant innovation but also contributes to network dynamics theory by exploring whether ego–network stability or ego–network expansion is more conducive to recombinant innovation under a heterogeneous knowledge base. [ABSTRACT FROM AUTHOR]

Purpose: Prior literature has long argued that knowledge networks contain great opportunities for innovation, and researchers can identify these opportunities using the properties of knowledge networks (PKNs). However, previous studies have examined only the relationship between structural PKNs (s-PKNs) and innovation, ignoring the effect of qualitative PKNs (q-PKNs), which refer to the quality of the relationship between two elements. This study aims to further investigate the effects of q-PKNs on innovation. Design/methodology/approach: Using a panel data set of 2,255 patents from the Chinese wind energy industry, the authors construct knowledge networks to identify more PKNs and examine these hypotheses. Findings: The results show that q-PKNs significantly influence recombinant innovation (RI), reflecting the importance of q-PKNs analysed in this study. Moreover, the results suggest that the combinational potential of an element with others may be huge at different levels of q-PKNs. Originality/value: This study advances the understanding of PKNs and RI by exploring how q-PKNs impact RI. At different levels of PKNs, the potential of the elements to combine with others and form innovation are different. Researchers can more accurately identify the opportunities for RI using two kinds of PKNs. The findings also provide important implications on how government should provide support for R&D firms. [ABSTRACT FROM AUTHOR]

We leverage the knowledge network representation of the Medical Subject Heading (MeSH) ontology to infer conceptual distances between roughly 30,000 distinct MeSH keywords — each being prescribed to particular knowledge domains — in order to quantify the origins of cross-domain biomedical convergence. Analysis of MeSH co-occurrence networks based upon 21.6 million research articles indexed by PubMed identifies three robust knowledge clusters: micro-level biological entities and structures; meso-level representations of systems, and diseases and diagnostics; and emergent macro-level biological and social phenomena. Analysis of cross-cluster dynamics shows how these domains integrated from the 1990s onward via technological and informatic capabilities — captured by MeSH belonging to the "Technology, Industry, and Agriculture" (J) and "Information Science" (L) branches — representing highly controllable, scalable and permutable research processes and invaluable imaging techniques for illuminating fundamental yet transformative structure–function–behavior questions. Our results indicate that 8.2% of biomedical research from 2000 to 2018 include MeSH terms from both the J and L MeSH branches, representing a 291% increase from 1980s levels. Article-level MeSH analysis further identifies the increasing prominence of cross-domain integration, and confirms a positive relationship between team size and topical diversity. Journal-level analysis reveals variable trends in topical diversity, suggesting that demand and appreciation for convergence science vary by scholarly community. Altogether, we develop a knowledge network framework that identifies the critical role of techno-informatic inputs as convergence bridges — or catalyzers of integration across distinct knowledge domains — as highlighted by the 1990s genomics revolution, and onward in contemporary brain, behavior and health science initiatives. [ABSTRACT FROM AUTHOR]

To what degree has the vast space of higher-order knowledge combinations been explored and how has it evolved over time? To address these questions, we first develop a systematic approach to measuring combinatorial innovation in the biomedical sciences based upon the comprehensive ontology of Medical Subject Headings (MeSH) developed and maintained by the US National Library of Medicine. As such, this approach leverages an expert-defined knowledge ontology that features both breadth (27,875 MeSH analyzed across 25 million articles indexed by PubMed that were published from 1902 onwards) and depth (we differentiate between Major and Minor MeSH terms to identify differences in the knowledge network representation constructed from primary research topics only). With this level of uniform resolution, we differentiate between three different modes of innovation contributing to the combinatorial knowledge network: (i) conceptual innovation associated with the emergence of new concepts and entities (measured as the entry of new MeSH) and (ii) recombinant innovation, associated with the emergence of new combinations, which itself consists of two types: peripheral (i.e. combinations involving new knowledge) and core (combinations comprised of pre-existing knowledge only). Another relevant question we seek to address is whether examining triplet and quartet combinations, in addition to the more traditional dyadic or pairwise combinations, provides evidence of any new phenomena associated with higher-order combinations. Analysis of the size, growth, and coverage of combinatorial innovation yield results that are largely independent of the combination order, with some subtle caveats identified at higher order (i.e. beyond the common dyadic or pairwise representation of combinations). Our main results are two-fold: (a) despite the persistent addition of new MeSH terms, the network is densifying over time meaning that scholars are increasingly exploringand realizing the vast space of all knowledge combinations and (b) conceptual innovation is increasingly concentrated within single research articles, a harbinger of the recent paradigm shift towards convergence science. [ABSTRACT FROM AUTHOR]

Digitization is increasing the complexity and variety of educational services supplied and demanded. However, there is a lack of a systematic treatment of this phenomenon from the perspective of innovation and entrepreneurship. This paper employs the complex adaptive systems approach to explore how digitization changes the characteristics, generativity (combinatorial possibilities) and architecture of online educational services. Our main claims are that: (a) online courses (OCs) are modular complex hierarchical systems; (b) the development of new OCs is a significant type of innovation (not limited merely to technological change) brought about by entrepreneurial reconfiguration of modules that create new combinations in the design space of new educational services; (c) these new combinations generate new OC systems; and (d) OCs are embedded in broader institutional and social structures (e.g. universities) that co-evolve with technological change. By means of a formal combinatorial model, we examine the computational mechanism and the principles of connection-making that govern how new OCs are created and adapted. [ABSTRACT FROM AUTHOR]

Although many methods have been proposed for engineering service systems and customer solutions, most of these approaches give little consideration to recombinant service innovation. Recombinant innovation refers to reusing and integrating resources that were previously unconnected. In an age of networked products and data, we can expect that many service innovations will be based on adding, dissociating, and associating existing value propositions by accessing internal and external resources instead of designing them from scratch. The purpose of this paper is to identify if current service engineering approaches account for the mechanisms of recombinant innovation and to design a method for recombinant service systems engineering. In a conceptual analysis of 24 service engineering methods, the study identified that most methods (1) focus on designing value propositions instead of service systems, (2) view service independent of physical goods, (3) are either linear or iterative instead of agile, and (4) do not sufficiently address the mechanisms of recombinant innovation. The paper discusses how these deficiencies can be remedied and designs a revised service systems engineering approach that reorganizes service engineering processes according to four design principles. The method is demonstrated with the recombinant design of a service system for predictive maintenance of agricultural machines. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this paper is twofold. First, to understand recombinant innovation (RI) as a potentially significant part of an open innovation (OI) strategy and second, to suggest key routines which would underpin a capability for RI, locating these within the context of enhanced absorptive capacity (AC). Finally, the paper considers how such routines could be developed, drawing on some case examples.Design/methodology/approach The authors start with a literature review on OI and use the lens of AC to explore challenges in finding, assimilating and deploying external knowledge posed by the emerging knowledge-rich context of OI. The authors then explore one OI route – RI – and suggest a model framework for operationalizing it based on routines for search, acquisition, assimilation and deployment.Findings The authors suggest three sets of routines required for RI, around abstract-driven search (ADS), brokerage and cyclic adaptation. As with much of the now widely available toolkit for OI, the challenge is one of moving from potential to realized opportunity and this will require investments in learning and capability building.Originality/value The authors suggest that for organizations to enhance their AC around RI, three core routines are needed: ADS, brokerage and cyclic adaptation. [ABSTRACT FROM AUTHOR]

Today, the EU has changed its economic development support strategy for regions from a mainly procedural budgeting model to a more substantive one, especially regarding the priority to promote regional innovation. Thus, instead of a regional operational programme that emphasized budgetary controls, phasing and expenditure refinement, this was to be paralleled by a regional innovation strategy (RIS phase 3 or RIS3) to attract EU regional funding assistance. This was a radical departure from all hitherto prevailing ERDF/FEDER methodologies by which regions and their member states submitted such funding requests. This article explores this policy transition, its strengths and weaknesses. In particular, it presents empirically informed accounts of the ways in which RIS3 was received, comprehended and implemented in three regions of Portugal. In addition, it presents results of interviews also conducted with key central state actors in Lisbon. A major aim was to see how each policy level reacted to the way innovation was pre-defined in terms of regional ‘smart specialization' whereby regions dropped un-innovative activities and projected their best candidate specializations. Questioning of the validity of the notion in the innovation context occurs based on both primary and secondary research. A secondary aim was to investigate the methodologies, concepts and policy frameworks actually deployed in developing RIS3s in three Portuguese regions; Algarve, Centro and Norte. Third, another important aim in a follow-up section was to conduct anex postevaluation of the resulting approved implementation strategy. Discussion and conclusions are drawn in the final section. [ABSTRACT FROM AUTHOR]

Evolutionary economic geographers propose that regional diversification is a pathdependent process whereby industries grow out of pre-existing industrial structures through technologically related localised knowledge spillovers and learning. This article examines whether this also applies to emerging radical technologies that create the foundation for new industries. The article develops a new measure for technological relatedness between the knowledge base of a region and that of a radical technology based on patent classes. It demonstrates that emerging fuel cell technology develops where the regional knowledge base is technologically related to that of fuel cells and consequently confirms the evolutionary thesis. [ABSTRACT FROM AUTHOR]

Copyright of Regional Studies is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper investigates the antecedents of patent importance by looking at the prior knowledge set of academic inventors. Using independent methodologies, we distinguish between the scientific knowledge set and the technical knowledge set, and separate these from other kinds of prior expertise. We find that the patents of the inventors who have a prior scholarly knowledge of the topic are on average more important (more cited after 6 years). Conversely, we find an inverted U-shape relationship between prior technical relatedness and patent importance. These results are potentially useful to support the work of practitioners such as university technology managers, which often face difficulties in identifying the importance and perspective value of the disclosed inventions, amid high market and legal uncertainty and budget shortages. [ABSTRACT FROM AUTHOR]

Mashups enable end-users to "mix and match" data and services available on the web to create applications. Their creation is supported by a complex ecosystem of i) data providers who offer open APIs to users, ii) users who combine APIs into mashups, and iii) platforms, such as the ProgrammableWeb or Mashape, that facilitate the construction and publication of mashups. In this article, we argue that the evolution of the mashup ecosystem can be explained in terms of ecosystem niches anchored around hub or keystone APIs. The members of a niche are focused on an area of specialization (e.g., mapping applications) and contribute their knowledge to the value proposition of the ecosystem as a whole. To demonstrate the formation of niches in the mashup ecosystem, we model groups of related mashups as species, and we reconstruct the evolution of mashup species through phylogenetic analysis. [ABSTRACT FROM AUTHOR]