Empirical Insights into Intangible Assets, Open Innovation and Firm Embeddedness in Regional Innovation Systems in Europe
257 Appendix Appendix A: Normalized Co-Occurrence Calculation Where: c12 = 0 when n12 = 0; i.e., k1 and k2 do not co-occur (terms are mutually exclusive). c12 > 0 when n12 > 0; i.e., k1 and k2 co-occur (terms are not mutually exclusive). c12 = 1 when n12 = n1 = n2; i.e., k1 and k2 co-occur whenever either terms occurs. Appendix B: KWIC-Analysis (Key-words in context) The term key-word-in-context (KWIC) was coined by an IBM engineer in the 1960s to refer to an analysis which is used to systematically analyze qualitative data by converting key words and statements (quotes) from the primary data into matrices in a coherent and organized manner (for more description see BERNARD and RYAN, 2010). The matrix of firm regional embeddedness (figure 19) was operationalized by using a scale ranging from one to four: “One” indicates a low level of embedded relationships and a pas- sive mode of knowledge sourcing (lowest degree of embeddedness; type: SOSD). “Two” indicates a low level of embedded relationships with an active mode of external knowledge sourcing (type: RTTS). “Three” indicates a high level of embedded relationships with a rather passive mode of external knowledge sourcing (type: RKM). Finally, “four” illustrates the high- est level of regional embeddedness (type: REIF). Each quote (Q1-Qn) in the 56 transcribed and coded interviews was converted into one of these categories. Additionally, for each quote, we indicated whether it referred to one of the following subsystems of a RIS, as de- fined by COOKE et al. (2004): (1) Knowledge Generation & Diffusion...
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