Paper Type

Complete

Abstract

Organizations are shifting from traditional business models towards a collaborative, data-centric paradigm, giving rise to data ecosystems. However, while opportunities for leveraging data in these ecosystems are vast, such ecosystems' structure, governance, and operation remain nebulous. Thus, our research delves into the operational intricacies of data ecosystems. Drawing upon a cluster analysis of 142 data ecosystem initiatives and integrating theoretical perspectives on data ecosystems and digital platforms, we identify five distinct archetypes characterized by variations in organizational structure, technical openness, actor interdependence, and governance. Our findings illuminate the core elements of data ecosystems and provide pragmatic insights for their application, fostering an understanding critical for designing multi-sided data platforms and governance mechanisms in public data spaces. This research contributes a comprehensive tool for academia to understand data ecosystems and a guide for industry practitioners to manage organizations within these complex structures.

Paper Number

1560

Comments

DATAECO

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Aug 16th, 12:00 AM

The Anatomy of Data Ecosystems: Identifying and Analyzing Archetypes

Organizations are shifting from traditional business models towards a collaborative, data-centric paradigm, giving rise to data ecosystems. However, while opportunities for leveraging data in these ecosystems are vast, such ecosystems' structure, governance, and operation remain nebulous. Thus, our research delves into the operational intricacies of data ecosystems. Drawing upon a cluster analysis of 142 data ecosystem initiatives and integrating theoretical perspectives on data ecosystems and digital platforms, we identify five distinct archetypes characterized by variations in organizational structure, technical openness, actor interdependence, and governance. Our findings illuminate the core elements of data ecosystems and provide pragmatic insights for their application, fostering an understanding critical for designing multi-sided data platforms and governance mechanisms in public data spaces. This research contributes a comprehensive tool for academia to understand data ecosystems and a guide for industry practitioners to manage organizations within these complex structures.

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