PLATFORM SIGNALING FOR GENERATING PLATFORM CONTENT

• 成果类型: Article
• 署名作者: Hukal, Philipp; Henfridsson, Ola; Shaikh, Maha; Parker, Geoffrey
• 署名单位: Copenhagen Business School; University of Miami; University of London; King's College London; Dartmouth College
• 刊物名称: MIS QUARTERLY
• ISSN/ISSBN: 0276-7783
• DOI: 10.25300/MISQ/2020/15190
• 发表日期: 2020
• 页码: 1177-1205
• 关键词: mixed-methods research; logistic-regression models; boundary resources; complementary markets; digital innovation; owner entry; software; crowd; developers; ecosystems

摘要

The generation of platform content is essential for platform growth and competition. However, the overwhelming number of platform complementors makes it impossible for platform operators to engage in extensive communication with each complementor about which content contributions are desired. Therefore, platform operators need to find a way to signal strategic interests to platform complementors. In this paper, we employ a mixed-methods design using data from the geodata platform OpenStreetMap to develop and test two distinct types of platform signals as a means of implementing a platform operator's strategy: (1) opportunity signals, which aim to stimulate activity in new areas of the platform, and (2) endorsement signals, which aim to increase activity in existing areas of the platform. In particular, we examine how platform signals influence the generation of platform content in terms of the volume and diversity of information on the platform. We contribute important insights to the platform governance literature by developing and empirically testing a signaling perspective on the generation of platform content and discussing its implications for guiding platform complementors in content creation.