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

机译:共享经济平台的大数据治理与算法管理:新兴市场乘法的情况

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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 GoJek, 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.
机译:虽然分享经济平台的增长严重依赖于数据和算法的治理,但优化服务流程和运作,因此对深化对共享经济平台的数据治理的理解,对较少的关注。因此,我们在印度尼西亚的一个本地拥有的乘车共享平台上进行了深入的案例研究,探索了关于工作分配,性能和评级系统的大数据和分析算法的黑暗面,以及法律和道德问题。 19世纪半结构化访谈是用四个主要的Go-Jek利益相关者进行:(1)司机,(2)消费者,(3)数据科学家(4)监管机构。本研究有助于三种新兴市场环境中大数据治理和算法管理的实践。首先,本研究发现了算法管理在riveShing平台中的负面后果。其次,本研究将法律和道德问题呈现为新兴市场的主要监管挑战。最后,我们开辟了分享经济平台利益相关者的“黑匣子”的大数据治理。

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