Knowledge boundaries in enterprise software platform development: Antecedents and consequences for platform governance. (29th January 2018)

• Record Type: Journal Article
• Authors: Foerderer, Jens; Kude, Thomas; Schuetz, Sebastian Walter; Heinzl, Armin
• Is Part Of: Information systems journal. Volume 29:Number 1(2019)
• Page Start: 119
• Page End: 144
• Publication Date: 2018-01-29
• Subjects: case study -- enterprise software -- knowledge boundaries -- knowledge boundary resources -- platform ecosystems -- platform governance; Information technology -- Periodicals; Management information systems -- Periodicals; 303.4833
• DOI: 10.1111/isj.12186
• Languages: English
• ISSNs: 1350-1917

Abstract

Abstract: The widespread uptake of platform strategies turns many vendors of enterprise software into curators of an ecosystem of firms that collaboratively develop and commercialize a shared technology. As a platform owner's effectiveness in integrating knowledge across ecosystem participants will distinguish it from its competitors, we investigate the management of development‐related knowledge across firm boundaries. Our exploratory, multiple‐case study of 4 platforms illustrates how "knowledge boundaries" emerge between platform owners and complementors. We observe that knowledge boundaries are influenced by a platform's functional extent, interface design, and evolutionary dynamics, which create differences, dependencies, and novelty of development knowledge, resulting in qualitatively distinct types of knowledge boundaries. To overcome knowledge boundaries, platform owners provide various resources at the boundary, including information portals, documentation, helpdesks, and alignment workshops. We observe that in shaping these resources, platform owners face a trade‐off between providing knowledge at the right scope, while allowing for the scalability of knowledge resources for the entire ecosystem. Depending on their scope and scale, we classify knowledge boundary resources as broadcasting, brokering, and bridging, each representing qualitatively distinct patterns in managing knowledge in platform ecosystems. We conclude with implications for researchers and managers.