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Conventional and experimental indicators of knowledge flows


Arundel, A and Constantelou, A, Conventional and experimental indicators of knowledge flows, Knowledge Flows in European Industry, Routledge, Caloghirou Y, Constantelou A, and Vonortas N (ed), Oxon, pp. 45 - 66. ISBN 0415327075 (2006) [Research Book Chapter]

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Copyright Anthony Arundel and Anastasia Constantelou 2006.

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The last decade has seen an enormous increase in both policy and academic interest in the flows of knowledge between individuals, firms and institutions such as universities and government research labs and the role of such knowledge flows in innovation. The third edition of the Oslo Manual, for example, includes a separate chapter on the role of 'linkages' in innovation and how to measure linkages in innovation surveys. European policy at both the supra-national and national levels includes a diverse range of programmes to encourage knowledge flows, particularly between firms and the publicly-funded research infrastructure. This is based on a long-standing belief in a systematic failure of European firms to commercialize discoveries made by public universities and research institutes (European Commission [EC] 2001), although the causes of such a failure is the subject of a lively debate (Dosi et al. 2005).

The policy interest in innovation-related knowledge flows requires indicators of both the production of knowledge and also the extent and magnitude of knowledge-based transactions. The indicators used in the innovation economics literature fall into three categories: input or resource indicators, including R&D expenditures; output indicators; and progress indicators (Grupp 1998). The input indicators account for every type of resource involved in the innovation process including financial, technological and human resources. Output indicators refer to all of the results (both tangible and intangible) from investment in innovation, and progress indicators refer to the economic effects of innovation at the micro- and macro-level (Grupp 1998: 142). Many of the widely-available input and output indicators are proxy measures of knowledge flows because they give evidence of communications among individuals, firms and institutions during the innovation process (Leydersdorff and Scharnhorst 2003), but only a few indicators directly count or measure knowledge flows.

Item Details

Item Type:Research Book Chapter
Research Division:Commerce, Management, Tourism and Services
Research Group:Strategy, management and organisational behaviour
Research Field:Innovation management
Objective Division:Economic Framework
Objective Group:Management and productivity
Objective Field:Technological and organisational innovation
UTAS Author:Arundel, A (Professor Anthony Arundel)
ID Code:75683
Year Published:2006
Deposited By:Australian Innovation Research Centre
Deposited On:2012-02-09
Last Modified:2013-03-15

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