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Using big data for generating firm-level innovation indicators: A literature review

Christian Rammer and Nordine Es-Sadki

No 22-007, ZEW Discussion Papers from ZEW - Leibniz Centre for European Economic Research

Abstract: Obtaining indicators on innovation activities of firms has been a challenge in economic research for a long time. The most frequently used indicators - R&D expenditure and patents - provide an incomplete picture as they represent inputs and throughputs in the innovation process. Output measurement of innovation has strongly been relying on survey data such as the Community Innovation Survey (CIS), but suffers from several short-comings typical to sample surveys, including incomplete coverage of the firm sector, low timeliness and limited comparability across industries and firms. The availability of big data sources has initiated new efforts to collect innovation data at the firm level. This paper discusses recent attempts of using digital big data sources on firms for generating firm-level innovation indicators, including Websites and social media. It summarises main challenges when using big data and proposes avenues for future research.

Keywords: Big data; innovation indicators; CIS; literature review (search for similar items in EconPapers)
JEL-codes: C81 O30 (search for similar items in EconPapers)
Date: 2022
New Economics Papers: this item is included in nep-ban, nep-big, nep-cse, nep-cwa, nep-ino, nep-sbm and nep-tid
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