Indicators on firm level innovation activities from web scraped data

Sajad Ashouri; Arho Suominen; Arash Hajikhani; Lukas Pukelis; Torben Schubert; Serdar Türkeli; Cees Van Beers; Scott Cunningham

doi:10.1016/j.dib.2022.108246

Indicators on firm level innovation activities from web scraped data

Data Brief. 2022 May 6:42:108246. doi: 10.1016/j.dib.2022.108246. eCollection 2022 Jun.

Authors

Sajad Ashouri^{1

2}, Arho Suominen^{1

2}, Arash Hajikhani^{1

3}, Lukas Pukelis⁴, Torben Schubert^{5

6}, Serdar Türkeli⁷, Cees Van Beers⁸, Scott Cunningham⁹

Affiliations

¹ Quantitative Science and Technology Studies, VTT Technical Research Centre of Finland, Tekniikantie 21, 02044 Espoo, Finland.
² Industrial Engineering and Management, Tampere University, Korkeakoulunkatu 8. PL 541, 33014 Tampereen Yliopisto, Finland.
³ LUT University, School of Business and Management (LBM), Yliopistonkatu 34, 53850 Lappeenranta, Finland.
⁴ Public Policy and Management Institute, Gedimino pr. 50 LT-01110 Vilnius, Lithuania.
⁵ Fraunhofer Institute for Systems and Innovation Research ISI, Breslauer Str. 48, 76135 Karlsruhe, Germany.
⁶ CIRCLE - Centre for Innovation Research, Sölvegatan 16, 22100 Lund, Sweden.
⁷ UNU-MERIT UM - United Nations University Maastricht Economic and Social Research Insitute on Innovation and Technology, Maastricht University, Boschstraat 24, 6211 Maastricht, the Netherlands.
⁸ Section Economics of Technology and Innovation, Department of Technology, Policy and Management, Delft University of Technology, Jaffalaan 5, the Netherlands.
⁹ School of Government and Public Policy, University of Strathclyde, Glasgow G1 1XQ, United Kingdom.

Abstract

This article presents data on companies' innovative behavior measured at the firm-level based on web scraped firm-level data derived from medium-high and high-technology companies in the European Union and the United Kingdom. The data are retrieved from individual company websites and contains in total data on 96,921 companies. The data provide information on various aspects of innovation, most significantly the research and development orientation of the company at the company and product level, the company's collaborative activities, company's products, and use of standards. In addition to the web scraped data, the dataset aggregates a variety firm-level indicators including patenting activities. In total, the dataset includes 21 variables with unique identifiers which enables connecting to other databases such as financial data.

Keywords: Big data; Firm-level data; Innovation; Text data; Web scraped data.