Algorithmic Governance Strategies: Shaping Workers, Firms, and Ecosystems in the Digital Economy

This project, titled Algorithmic Governance Strategies: Shaping Workers, Firms, and Ecosystems in the Digital Economy (ALGOS), investigates how digital platforms design and adapt their algorithms amid competing pressures from regulators, workers, and market forces. The proposal fits a Type B research framework, leveraging the PIs proven research leadership to pursue scientific insights with high academic and societal impact.

The study is built around four complementary research lines. The first explores how shared ownership (including institutional common ownership) and property rights constraints influence firms approaches to algorithmic secrecy and transparency. The second examines regulatory demands, stakeholder activism, and creative compliance, revealing why some platforms make only superficial adjustments to their algorithms while others undertake deeper reforms in response to legal pressures.

In the third line, the project focuses on how varying degrees of algorithmic transparency affect worker well-being, productivity, and trust. It advances the concept of calibrated algorithmic transparency, proposing that moderate disclosure can boost motivation and job satisfaction while preventing cognitive overload and preserving the platforms competitive edge. The fourth line shifts to the ecosystem level, assessing how algorithmic governance decisions can reinforce market power, shape competitive dynamics, and influence value distribution.

Methodologically, the project employs a multi-method design. Quantitative analyses (using panel data and difference-in-differences), qualitative approaches (interviews and qualitative comparative analysis), field experiments with digital labor platforms, and agent-based simulation models will be integrated to provide a holistic view. The research progresses over 48 months, starting with large-scale data collection on firm ownership, transparency policies, and labor regulations, and culminating in field experiments and ecosystem-level simulations.

Findings are expected to offer both theoretical and practical contributions. First, they will clarify how property rights, institutional pressure, and strategic considerations intersect to shape firms algorithmic governance choices. Second, they will detail how calibrated transparency influences worker outcomes. Finally, the research will illuminate ecosystem-wide consequences of algorithmic design, from collusive risks to enhanced innovation. Hosted at ESADE Business School, the project will benefit from robust data infrastructure and an international collaboration network, positioning it to deliver insights for academia, industry, and policymakers. By fostering richer theoretical integration across strategic management, institutional theory, and the emerging domain of platform regulation, ALGOS aspires to guide the development of more responsible, equitable, and competitive digital platforms.