Martin Kauschinger, Maximilian Schreieck, Markus Böhm, and Helmut Krcmar (2021) – 16th International Conference on Wirtschaftsinformatik, Essen, Germany
Research on digital platform ecosystems is growing rapidly. While the relevance of third-party applications is commonly known, scholars have made only minor attempts to analyze knowledge sharing between platform owners and third-party developers. We find that third-party application development is a knowledge intensive task that requires knowledge to cross organizational boundaries. In this paper, we use computational analytic methods to analyze knowledge sharing in a digital platform ecosystem. We collected trace data about a third-party developer ecosystem with frequent knowledge exchange between the platform owner and third-party developers. We developed a web scraper and retrieved all 4866 pages of SAP’s developer community that were tagged ‘SAP Cloud Platform’. Next, we used text mining to render a topic model. Based on the latent dirichlet allocation algorithm, we extracted 25 topics that were frequently discussed in the community. We clustered the topics into the following six meta-topics: User Accounts and Authentication, Connectivity, Cloud Database, Specific Technologies, SAP Resources, and Installation. Platform owners can use our approach to (1) identify frequently discussed topics, (2) generate meta-knowledge in these topics and (3) use the meta-knowledge to improve their platform core and its boundary resources.
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