Regulating algorithms in digital platforms: challenges and policy recommendations

Purpose This study aims to address the critical gaps in the algorithmic governance deployed by digital platforms. It proposes a multistakeholder corporate governance framework to mitigate algorithmic risks by systematically diagnosing deficiencies across legislative, regulatory, corporate, industry and public dimensions. Design/methodology/approach This research uses a mixed-methods approach combining literature review; three illustrative case studies from Chi na (social media algorithms, dynamic pricing in travel platforms and AI-based hiring systems); and comparative policy analysis of regulatory frameworks in the European Union, USA and China. Case selection followed theoretical sampling across high-impact domains, with data drawn from investigative reports, academic studies and regulatory documents analyzed through thematic content analysis. Findings This study reveals systemic weaknesses in algorithmic governance, including insufficient board-level oversight, misaligned executive incentives, inadequate internal controls, fragmented regulation and weak stakeholder participation. These deficiencies lead to algorithmic harms such as information divides, price discrimination and hiring biases. Research limitations/implications This study’s primary limitation is its focus on the Chinese context and reliance on secondary data, which may affect generalizability. Future research should expand cross-jurisdictional empirical comparisons and investigate board-level governance practices for algorithmic oversight. Practical implications The framework provides actionable guidance for platform boards to establish ethics committees and align compensation with trust metrics. Regulators can develop risk-based oversight, and industry associations can facilitate standard-setting. Originality/value This research advances corporate governance scholarship by integrating algorithmic risk oversight into established governance frameworks. It contributes a novel multistakeholder model that translates systemic deficiencies into specific board responsibilities, regulatory approaches and stakeholder engagement mechanisms.