Measuring the digitalisation of firms: A novel text mining approach

Arbeitspapier

Due to the omnipresence of digital technologies in the economy, measuring firm digitalisation is of high importance. However, current indicators show several shortcomings, e.g., they lack timeliness and regional granularity. In this study, we show that advances in text mining and comprehensive firm website content can be leveraged to generate real-time and large-scale estimates of firm digitalisation. We use a transfer learning approach to capture the latent definition of digitalisation. For this purpose, we train a random forest regression model on labeled German newspaper articles and apply it on firm's website content. The predictions are used as a continuous indicator for firm digitalisation. Plausibility checks confirm the link to established digitalisation indicators at the firm and sectoral level as well as for firm size classes and regions. Lastly, we illustrate the indicator's potential for giving timely answers to pressing economic issues by analysing the link between digitalisation and firm resilience during the Covid-19 shock.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Series: ZEW Discussion Papers ; No. 22-065

Klassifikation und Themen

• Klassifikation: Wirtschaft ; Forecasting Models; Simulation Methods ; Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access ; Innovation; Research and Development; Technological Change; Intellectual Property Rights: General
• Thema: web-mining ; text as data ; machine learning ; digitalisation

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Axenbeck, Janna ; Breithaupt, Patrick
• Ereignis: Veröffentlichung
• (wer): ZEW - Leibniz-Zentrum für Europäische Wirtschaftsforschung
• (wo): Mannheim
• (wann): 2022

Weitere Informationen

• Handle: http://hdl.handle.net/10419/268244
• Letzte Aktualisierung: 10.03.2025, 11:44 MEZ