FW-HTF-RM: Collaborative Research: Understanding the Algorithmic Workplace: A Multi-Method Study for Comprehensive Optimization of Platforms

FW-HTF-RM：协作研究：理解算法工作场所：平台综合优化的多方法研究

• 批准号: 1928453
• 负责人: Juliet Schor
• 金额: $ 30.47万
• 依托单位: Boston College
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1928453&HistoricalAwards=false
• 关键词: FW; HTF; RM; Collaborative; Research

The emergence of the digital platform economy in recent years is rapidly transforming some kinds of economic activity. This project will develop new evidence about the workers, business organizations, and government institutions that are involved in the "algorithmic workplace" or "gig economy". The research team includes experts in social science, public policy, and engineering. The team will conduct research to document the experiences, attitudes, and needs of platform workers. They will use these findings to build a mathematical model of worker behavior that will be combined with business data from an industrial partner. The result will be a model that can predict how changes in business operations will affect worker outcomes. The team will use field experiments to test the model predictions. The results of this project will be new knowledge for businesses that need to retain and motivate their workforce, new evidence for policymakers that seek to understand how neighborhoods and communities are affected by the growth of platform work, and new empirical evidence about the benefits and risks of platform work for the US workforce.The team will undertake an interdisciplinary program of research aimed at generating theoretical and practical knowledge of issues that result from the advent of the algorithmic workplace in the United States. The project begins by conducting research on the attitudinal and behavioral characteristics of platform workers. Interviews and surveys will shed light on the occupational trajectories, experiences of risk, and regulatory preferences found among workers on several types of labor platforms. The team will analyze the qualitative data to shed new light over ongoing debates about the nature of algorithmic control of workers, the labor market dynamics which the platform economy fosters, and the policy preferences of workers themselves. A mathematical framework of worker behavior will be designed to model the fusion of these coded qualitative data with internal data from Deliv, a digital platform for package delivery. This will lead to a novel contribution of this project: agent-based modeling that can simulate the action of platform workers as they respond to shifts in the design of the algorithms on which platforms rely. This second stage of the research will be used to provide a deeper and better informed understanding of the strategies which workers employ as they respond to the technological changes programmers introduce in their efforts to refine the algorithms governing transactions made possible by platforms.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

近年来，数字平台经济的出现正在迅速改变着某些经济活动。该项目将开发有关参与“算法工作场所”或“零工经济”的工人、商业组织和政府机构的新证据。研究团队包括社会科学、公共政策和工程学专家。该团队将进行研究，记录平台工作人员的经历、态度和需求。他们将利用这些发现建立一个工人行为的数学模型，该模型将与来自工业合作伙伴的商业数据相结合。其结果将是一个模型，可以预测业务运营的变化将如何影响员工的工作成果。研究小组将通过实地实验来验证模型的预测。该项目的成果将为需要留住和激励员工的企业提供新知识，为政策制定者提供新证据，帮助他们了解社区和社区如何受到平台工作增长的影响，以及关于平台工作对美国劳动力的好处和风险的新经验证据。该团队将承担一个跨学科的研究项目，旨在为美国算法工作场所的出现产生的问题提供理论和实践知识。该项目首先对平台工作人员的态度和行为特征进行研究。访谈和调查将揭示在几种类型的劳动力平台上发现的工人的职业轨迹、风险经历和监管偏好。该团队将分析定性数据，为正在进行的关于算法控制工人的性质、平台经济促进的劳动力市场动态以及工人本身的政策偏好的辩论提供新的视角。将设计一个工作人员行为的数学框架，对这些编码的定性数据与来自Deliv（一个包裹递送数字平台）的内部数据的融合进行建模。这将导致这个项目的一个新贡献：基于代理的建模，可以模拟平台工作人员的行为，因为他们对平台所依赖的算法设计的变化做出反应。研究的第二阶段将用于更深入、更明智地了解工人在应对程序员引入的技术变革时所采用的策略，这些技术变革是为了改进由平台实现的管理交易的算法。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。