Web-Based Innovation Indicators – Which Firm Website Characteristics Relate to Firm-Level Innovation Activity?

42 Pages Posted: 24 Feb 2020 Last revised: 4 Dec 2020

See all articles by Janna Axenbeck

Janna Axenbeck

ZEW – Leibniz Centre for European Economic Research

Patrick Breithaupt

ZEW – Leibniz Centre for European Economic Research

Date Written: 2019

Abstract

Web-based innovation indicators may provide new insights into firm-level innovation activities. However, little is known yet about the accuracy and relevance of web-based information. In this study, we use 4,485 German firms from the Mannheim Innovation Panel (MIP) 2019 to analyze which website characteristics are related to innovation activities at the firm level. Website characteristics are measured by several text mining methods and are used as features in different Random Forest classification models that are compared against each other. Our results show that the most relevant website characteristics are the website’s language, the number of subpages, and the total text length. Moreover, our website characteristics show a better performance for the prediction of product innovations and innovation expenditures than for the prediction of process innovations.

Keywords: text as data, innovation indicators, machine learning

JEL Classification: C53, C81, C83, O30

Suggested Citation

Axenbeck, Janna and Breithaupt, Patrick, Web-Based Innovation Indicators – Which Firm Website Characteristics Relate to Firm-Level Innovation Activity? (2019). ZEW - Centre for European Economic Research Discussion Paper No. 19-063, Available at SSRN: https://ssrn.com/abstract=3542199 or http://dx.doi.org/10.2139/ssrn.3542199

Janna Axenbeck (Contact Author)

ZEW – Leibniz Centre for European Economic Research ( email )

P.O. Box 10 34 43
L 7,1
D-68034 Mannheim, 68034
Germany

Patrick Breithaupt

ZEW – Leibniz Centre for European Economic Research ( email )

P.O. Box 10 34 43
L 7,1
D-68034 Mannheim, 68034
Germany

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