Understanding transaction platform governance and conflicts: A configuration approach

Habib A. Islam, Matthew Farrell, Anil Nair and Jing Zhang

Technological Forecasting and Social Change, 2023, vol. 189, issue C

Abstract: Transaction platforms, such as Amazon and Uber, are emerging as central players in many segments of the global economy. Extant research has primarily focused on the impact of network effects on platform growth and rivalry, but not much is known about governance configurations in platforms and their impact on outcomes that are crucial to the long-term survival of the platform. In this study, using information asymmetry logic and the organizational governance literature derived from theories of the firm, we propose that the configurations of platform governance rules impact conflicts between platforms and sellers. Our empirical research context is the online auction and mail-order industry. Following an inductive approach, we first identify the sets of rules that platforms use in seller selection and engagement. Next, utilizing fsQCA analysis, we identify multiple configurations of governance rules that lead to different levels of platform-seller conflicts. We also find that effective configurations of governance rules are contingent upon platform strategies. Theoretical and empirical implications of the study on platform governance are discussed.

Keywords: Conflict; Information asymmetry framework, agency conflicts, governance theories, mixed method configuration approach; fsQCA; Transaction platforms; Platform governance (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:189:y:2023:i:c:s0040162523000677

DOI: 10.1016/j.techfore.2023.122382

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