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Yesterday’s giants and invisible colleges of today. A study on the ‘knowledge transfer’ scientific domain

Abstract

Despite ‘knowledge transfer’ emerged as a separate field of study at least three decades ago, its academic literature remains rather fragmented. To reduce complexity, several journals’ special issues have attempted to frame up the literature both in a qualitative way and in a quantitative manner. Although these reviews help to bring some order to a flourishing literature, the theoretical background of knowledge transfer field of study still needs clarification. Who are their foremost scholars? How do they gather in visible or invisible colleges? How far the scientific communities of such domain have evolved over time? Has the knowledge transfer topic gained the status of an independent scientific domain? This article aims at shedding light on the knowledge transfer domain by mapping the invisible colleges on which the discipline is based. Drawing evidence from a network analysis of the backwards citations of the second generation of knowledge transfer studies, the authors point out that although the entire scientific domain has reached a strongly connected international dimension, it still manifests a persistent fragmentation. The paradoxical presence of a popular scientific domain without a proper independent theoretical body is consequently underlined.

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Notes

  1. 1.

    The emergence of a second-generation studies is highlighted by Gulbrandsen et al. (2011). In their words, first generation scholarly research had been “focused on mapping the interaction, the motives for interaction, and the channel of interaction” (p. 1), while the second generation combines the use of more sophisticated methodological analysis with a more specific approach to collaboration, which often looks at individual academics instead of generic university-industry linkages.

  2. 2.

    Alessia Zuccala overcomes the de Solla Price’s classic definition (1963) that distinguishes ‘invisible colleges’—where people have to know each other personally—from ‘subject specialty’—in which the share of information and the common sense of interpretation of a situation can exist without personal relations.

  3. 3.

    For a detailed review on earlier science mapping and its techniques see Small (1999). For a more recent review focused on visualisation techniques see Börner et al. (2003) and Chen (2006).

  4. 4.

    The degree of a node is defined as the number of its neighbours. When weighted, the degree of a node corresponds to the sum of the weights of all edges of a node. The average weighted degree is calculated as the ratio between the weighted average and the number of edges. In our case, the weight of an edge coincides with the number occurrences of a co-authorship in the citation set.

  5. 5.

    Partitions were created by modularity optimisation following the Louvain method (Blondel et al. 2008). Resolution of communities was set at 1.5.

  6. 6.

    The core group of scholars that took part in this study come from the Sant’Anna School of Advanced Studies in Pisa (Italy), the University of Sussex’s SPRU in Brighton (UK), the Ludwing-Maximiliansa Universitatet in Munich (Germany), the Eindhoven University of Technology (The Netherlands), the Universitat Pompea Fabra in Barcelona (Spain) and the Université Lyon2 in France.

  7. 7.

    Nonetheless, psychology’s leading position could either be seen as a key strength whether seen from the perspective of domain’s capacity to stand-alone, or conversely, threatening the domain’s capability of absorbing and popularising knowledge from different scientific sub-fields.

  8. 8.

    In particular, Siegel’s node takes on a bridging function in the network by connecting the British community, mainly dealing with management of venture creation, with the American one, instead focused on academic IP protection related topics, of which Mary and Jerry Thursby and Frank Rothaermel are some of the most eminent scholars. The social network analysis identifies boundary spanners as brokers or as inter-cohesive nodes. Both connect different networks components, but while the latter is embedded in the communities he connects, the former has not a multiple and simultaneous belonging (Stark and Vedres 2009).

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Correspondence to Alberto Gherardini.

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Gherardini, A., Nucciotti, A. Yesterday’s giants and invisible colleges of today. A study on the ‘knowledge transfer’ scientific domain. Scientometrics 112, 255–271 (2017). https://doi.org/10.1007/s11192-017-2394-y

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Keywords

  • Knowledge transfer
  • University-industry relations
  • Invisible colleges
  • Innovation studies
  • Network analysis