Artificial Intelligence and Algorithmic Management in Food Delivery Platforms: Implications for Decent Work: A Systematic Literature Review and Research Agenda

This thesis examines how artificial intelligence (AI)–enabled algorithmic management(AM) reshapes labour conditions in platform-based food-delivery work, with aparticular focus on its implications for decent work. It aims to provide acomprehensive and integrated understanding of this phenomenon by synthesisingboth regulatory developments and academic research, while identifying keyconceptual, empirical, and policy gaps for future investigation.Design /methodology/approach – The study adopts a dual analytical approach that integratesregulatory and academic perspectives. First, it examines policy reports andinstitutional publications from major international and European bodies,including the European Commission, OECD, ILO, and EU agencies, to analyse theevolving regulatory landscape of algorithmic management. Second, it conducts asystematic literature review of peer-reviewed journal articles indexed in theWeb of Science database. Following the SPAR-4-SLR protocol, the study combinesbibliometric techniques with qualitative content analysis. This integratedapproach enables a comprehensive examination of both the governance frameworksand the intellectual structure of research on AM in platform-based work.Findings –The f indings show that AM operates as a socio-technical governance system thatreshapes work organisation, managerial control, and worker experience infood-delivery platforms. It exhibits a dual character: while enhancingcoordination and efficiency, it also intensifies surveillance, reducesautonomy, and creates risks for fairness, wellbeing, and decent work. Workerresponses are not passive but involve adaptation and resistance, highlightingthe dynamic nature of algorithmic control. From a regulatory perspective,existing frameworks provide important but fragmented protections and remainonly partially aligned with AI-enabled labour realities. From an academicperspective, the literature is rapidly expanding but conceptually uneven: whilethemes such as platform work, autonomy, and worker behaviour arewell-developed, governance-related dimensions, particularly transparency,fairness, and algorithmic accountability, remain underdeveloped. The evidencebase is also geographically concentrated and methodologically dominated byquantitative approaches.Originality/value – This thesi s contributes by bridging regulatory analysis and academicliterature to offer a holistic and integrated framework linking algorithmicmanagement to the concept of decent work. It advances existing knowledge byconnecting technological, organisational, and labour-oriented perspectives andby identifying key gaps in governance, fairness, and worker protection. Thestudy also develops a structured research agenda and provides policy-relevantinsights for designing more transparent, accountable, and human-centredalgorithmic management systems.