Managing types of data products in information logistic networks

The rise of data products significantly impacts enterprise-wide data management. However, existing research predominantly emphasizes the data usage perspective, largely overlooking the provision perspective and the need for type-specific data product management. Drawing on information logistics as a conceptual foundation, this research integrates both data usage and provision perspectives. Through semi-structured interviews and an empirical assessment of 19 real-world data products from multiple organizations, we identify three distinct types: consolidating data products, centralized analytical data products, and decentralized analytical data products. The study also offers tailored, type-specific management approaches aligned with the unique provision and usage characteristics of each data product type. Advancing theoretical understanding by linking data provision and usage perspectives further emphasizes the importance of type-specific management approaches. Ultimately, the study provides actionable insights and a structured foundation for organizations to design and enhance their data product management strategies within the context of enterprise-wide data management.

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Publication Details

Journal
Journal of the Association for Information Systems
Published
2025-06-18
Primary Topic
Big Data and Business Intelligence
Type
article
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article

Managing types of data products in information logistic networks

Journal of the Association for Information Systems
Big Data and Business Intelligence
article

Managing types of data products in information logistic networks

article en

Abstract

The rise of data products significantly impacts enterprise-wide data management. However, existing research predominantly emphasizes the data usage perspective, largely overlooking the provision perspective and the need for type-specific data product management. Drawing on information logistics as a conceptual foundation, this research integrates both data usage and provision perspectives. Through semi-structured interviews and an empirical assessment of 19 real-world data products from multiple organizations, we identify three distinct types: consolidating data products, centralized analytical data products, and decentralized analytical data products. The study also offers tailored, type-specific management approaches aligned with the unique provision and usage characteristics of each data product type. Advancing theoretical understanding by linking data provision and usage perspectives further emphasizes the importance of type-specific management approaches. Ultimately, the study provides actionable insights and a structured foundation for organizations to design and enhance their data product management strategies within the context of enterprise-wide data management.

Journal of the Association for Information Systems
University of St.Gallen (CH), University of Applied Sciences St. Gallen (CH)
Industry, innovation and infrastructure
Openalex Percentile: Top 35%
Big Data and Business Intelligence
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