Data Governance Decisions for Platform Ecosystems

Abstract

Platform ecosystem has become an information system research subject after many years of industry success. The concept of platform ecosystem facilitates fast and self-growing of a platform by encouraging data contribution/consumption of multiple networks, and thus the importance and value of data in platforms is accentuated. It is essential to understand how data should be managed in platform ecosystems where there is complicated relationships between multiple participating groups. However, this topic has been rarely addressed in industry and academia. Industry governance frameworks focus on organizational data, and prior research on platform ecosystem is still in early-stage. To response to the limitation, we propose critical data governance decisions for platform ecosystems, and discuss how they have to be implemented in practice. This study supports right decision making about data, and facilitates a secure platform ecosystem. We perform a case study to illustrate the practical implications of this study.

Towards a Taxonomy of Ecosystem Data Governance

“…Polycentricity indicates balance and alignment of decision-rights relying on ecosystem participants for establishing decision-making consensus [17,30,66]. Monocentric approaches are centered on focal actors that are capable of cultivating the ecosystem and enforcing decisions [67,68].…”

Introduction to the Minitrack on Managing the Dynamics of Platforms and Ecosystems

“…With investigative lenses turned toward specific industries, papers explored the emergence of dynamic capabilities in the Internet of Things [22], the robotics sector [23], microservices [24], the fintech sector [25], and the automotive industry [26]. Management issues brought about by rapidly advancing technologies were addressed in papers on the alignment of information technologies with business strategies [27], shifting to the cloud [28], blockchain value creation [29], data governance decisions [30], and crowdworking [31]. The identification of success, failures, and unintended consequences prompted an expressed desire for deeper understanding of the management dynamics.…”

Mapping Platform Urbanism: Charting the Nuance of the Platform Pivot

“…This process is not meant to conduct deep, theoretical analysis of specific examples, but instead to establish the general trends and insights that can inform future practice. Three criteria were used to sample examples for the urban data market datasets: Lee et al (2018) Lemon, 2015. This model proposes five viewpoints in the management of distributed information systems: enterprise, information, computational, engineering, and technology.…”

“…dimensions. Given our interest in how data markets and platforms are configured, we also drew on recent interdisciplinary literature on platforms and data markets to analytically develop these categories (see Langley & Leyshon, 2017;Lee, Zhu, & Jeffery, 2018;Plantin et al, 2018;Schreieck, Wiesche, & Krcmar, 2016 ). Results were synthesised using a design thinking methodology, as part of broader project deliverables such as apps and reports that are outside the scope of this article.…”