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

近年来，数字平台经济的出现正在迅速改变着一些经济活动。这个项目将为参与“算法工作场所”或“零工经济”的工人、商业组织和政府机构提供新的证据。研究团队包括社会科学、公共政策和工程学方面的专家。该团队将进行研究，以记录平台工作人员的经验、态度和需求。他们将利用这些发现来建立工人行为的数学模型，并将其与来自工业合作伙伴的商业数据结合起来。其结果将是一个可以预测业务运营变化将如何影响员工结果的模型。该团队将使用现场实验来测试模型预测。该项目的结果将为需要留住和激励其员工的企业提供新的知识，为寻求了解平台工作的增长如何影响社区和社区的政策制定者提供新的证据，以及关于平台工作对美国劳动力的好处和风险的新的实证证据。该团队将开展一个跨学科的研究计划，旨在产生有关美国算法工作场所出现的问题的理论和实践知识。该项目首先对站台工人的态度和行为特征进行了研究。采访和调查将揭示在几种类型的劳动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，以揭示正在进行的关于工人算法控制的性质、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。将设计一个工人行为的数学框架，以模拟这些编码的定性数据与来自包裹递送数字平台Deliv的内部数据的融合。这将导致该项目的一个新贡献：基于代理的建模，它可以模拟平台工作人员在响应平台所依赖的算法设计变化时的行为。这项研究的第二阶段将被用来提供更深入和更知情的理解，以了解工人在应对程序员在努力完善由平台实现的交易管理算法时所采用的策略。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

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.