Big data governance and algorithmic management in sharing economy platforms: A case of ridesharing in emerging markets

Jessica Basukie, Yichuan Wang and Shuyang Li

Technological Forecasting and Social Change, 2020, vol. 161, issue C

Abstract: Although the growth of a sharing economy platform relies heavily on the governance of data and algorithms to optimise service process and operation, relatively little attention has been given to deepening the understanding of the data governance of sharing economy platforms. Accordingly, we performed an in-depth case study at Go-Jek, a locally-owned ride-sharing platform in Indonesia to explore the dark side of big data and analytical algorithms regarding work assignment, performance and rating system, and legal and ethical concerns. Nineteen semi-structured interviews were conducted with four primary Go-Jek stakeholders: (1) drivers, (2) consumers, (3) data scientists, (4) regulatory bodies. This study contributes to the practice of big data governance and algorithmic management in the emerging market context in three ways. First, this study finds the negative consequences of algorithmic management in the ridesharing platform. Second, this study presents the legal and ethical concerns as the main regulatory challenges in the emerging market. Finally, we open up the “black box” of big data governance for the stakeholders of the sharing economy platform.

Keywords: Sharing economy; Ridesharing; Big data management; Algorithmic management; Emerging markets (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:161:y:2020:i:c:s0040162520311367

DOI: 10.1016/j.techfore.2020.120310

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