Systematizing the lexicon of platforms in information systems: a data-driven study

Christian Bartelheimer (), Philipp Heiden, Hedda Lüttenberg and Daniel Beverungen
Additional contact information
Christian Bartelheimer: Department of Information Systems
Philipp Heiden: Department of Information Systems
Hedda Lüttenberg: Hamm-Lippstadt University of Applied Science, Production and Quality Management
Daniel Beverungen: Department of Information Systems

Electronic Markets, 2022, vol. 32, issue 1, No 21, 375-396

Abstract: Abstract While the Information Systems (IS) discipline has researched digital platforms extensively, the body of knowledge appertaining to platforms still appears fragmented and lacking conceptual consistency. Based on automated text mining and unsupervised machine learning, we collect, analyze, and interpret the IS discipline’s comprehensive research on platforms—comprising 11,049 papers spanning 44 years of research activity. From a cluster analysis concerning platform concepts’ semantically most similar words, we identify six research streams on platforms, each with their own platform terms. Based on interpreting the identified concepts vis-à-vis the extant research and considering a temporal perspective on the concepts’ application, we present a lexicon of platform concepts, to guide further research on platforms in the IS discipline. Researchers and managers can build on our results to position their work appropriately, applying a specific theoretical perspective on platforms in isolation or combining multiple perspectives to study platform phenomena at a more abstract level.

Keywords: Platform; Text mining; Machine learning; Data communications; Interpretive research; Systems design and implementation (search for similar items in EconPapers)
JEL-codes: L86 (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s12525-022-00530-6

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