管理数字危机应对:平台标准和COVID-19接触者追踪的困境

Journal of business economics Pub Date : 2023-01-01 Epub Date: 2022-11-17 DOI:10.1007/s11573-022-01118-4
Felix B Buesching, Dennis M Steininger, Daniel J Veit
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引用次数: 2

摘要

为了应对新冠肺炎(COVID-19)大流行的影响,各种开发人员转向基于智能手机的接触者追踪,以应对手动追踪的挑战。由于网络效应的存在,即接触追踪应用程序的有效性随着用户数量的增加而增加,信息技术标准对技术的成功至关重要。欧洲的标准化工作导致在选择适当的技术架构方面作出各种权衡,因为一方面需要追踪接触者数据以遏制大流行病,另一方面又需要尽量减少数据以保护用户隐私,这两者之间存在矛盾的紧张关系。主要利用软件平台和标准文献,我们进行了一个解释性案例研究,以检查这种多层决策情况的出现和后果。我们的研究结果揭示了谷歌和苹果如何能够限制外部开发者的个人自由,从而有效地解决了欧洲标准之战。此外,我们确定并讨论了与接触者追踪应用标准化相关的各种短期和长期权衡,并将我们的研究结果转化为针对未来危机情况的政策制定者的建议。具体来说,我们提出了一个基于我们的数据的策略,使负责任的参与者能够在时间限制下做出以目标为导向的快速决策。
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Governing digital crisis responses: platform standards and the dilemma of COVID-19 contact tracing.

In response to the impact of the SARS-CoV-2 (COVID-19) pandemic, various developers turned to smartphone-based contact tracing to address the challenges of manual tracing. Due to the presence of network effects, i.e., the effectiveness of contact tracing applications increases with the number of users, information technology standards were critical to the technology's success. The standardization efforts in Europe led to a variety of trade-offs concerning the choice of an appropriate technological architecture due to the contradictory tensions resulting from the dualism between the need for contact tracing data to contain the pandemic and the need for data minimization to preserve user privacy. Drawing predominantly on the software platform and standards literature, we conduct an interpretive case study to examine the emergence and consequences of this multi-layered decision situation. Our findings reveal how Google and Apple were able to limit the individual leeway of external developers, thereby effectively resolving the European standards war. Furthermore, we identify and discuss the various short-term and long-term trade-offs associated with the standardization of contact tracing applications and translate our findings into recommendations for policy makers with respect to future crisis situations. Specifically, we propose a strategy grounded in our data that enables responsible actors to make goal-oriented and rapid decisions under time constraints.

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