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- Autorinnen/Autoren:
- Nielsen, Aisada; Walter, Achim; Sienknecht, Monika; Vehmeyer, Benjamin; Geierhos, Michaela
- Dokumenttyp:
- Konferenzbeitrag / Conference Paper
- Titel:
- Measuring the Multidimensionality of Absorptive Capacity through AI-enabled Website Analysis
- Titel Konferenzpublikation:
- 32nd Innovation and Product Development Management Conference 2025 Proceedings
- Veranstalter (Körperschaft):
- European Institute for Advanced Studies in Management (EIASM)
- Konferenztitel:
- IPDMC 2025 - 32nd Innovation and Product Development Management Conference
- Tagungsort:
- Porto, Portugal
- Jahr der Konferenz:
- 2025
- Datum Beginn der Konferenz:
- 11.06.2025
- Datum Ende der Konferenz:
- 13.06.2025
- Jahr:
- 2025
- Sprache:
- Englisch
- Abstract:
- This study presents a novel method for developing and validating a measure for absorptive capacity (AC) using AI-enabled text analysis of website text. While AC constitutes an important ability for firms with well-documented relevance in the management literature, its multifaceted nature poses challenges for measurement and methodological rigor. Given the complexity and ambiguity in mapping empirical measures to AC’s dimensions, it is often used as a general-purpose construct without sufficient distinction from its outcomes (e.g., R&D intensity). This study addresses these limitations by proposing a method to capture the AC dimensions based on longitudinal analysis of corporate website data with state-of-the-art large language models. We test the validity and reliability of the text-based indicator through comparisons with established survey items and inter-model reliability tests. The dataset consists over 1,500,000 filtered website snapshots from 157 German firms, from 2008-2024. The proposed method provides a comprehensive and dynamic tool for measuring absorptive capacity, facilitating methodological rigor in AC research.
- Fakultät:
- Fakultät für Informatik
- Institut:
- INF 7 - Institut für Datensicherheit
- Professorin/Professor:
- Geierhos, Michaela
- Forschungszentrum:
- CODE
- Open Access:
- Nein / No
- Sonstige Angaben:
- Voraufnahme
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