TY - JOUR
T1 - Algorithmic Decision Systems in Organizations: Reviewing Opportunities, Risks, and Governance Implications
AU - Elena Petrova
AU - Ivan Georgiev
AU - Nikolay Stoyanov
AU - Petar Kolev
JF - Journal of Digital Business and Management Studies
JO - J. Digit. Bus. Manag. Stud.
Y1 - 2024
VL - 4
IS - 2
SP - 43
N2 - Algorithmic decision systems (ADS) are rapidly transforming organizational decision-making by automating routine and complex processes across strategy, operations, human resources, and customer management. Drawing on peer-reviewed literature, this research agenda article examines the evolution of ADS from traditional human-centric models to hybrid human–algorithm configurations and increasingly autonomous systems. It highlights substantial opportunities, including enhanced efficiency, scalability, and data-driven precision, alongside critical risks such as algorithmic bias, opacity, reduced accountability, and erosion of human judgment. Governance challenges—encompassing fairness, transparency, explainability, and ethical oversight—remain unresolved and demand new theoretical and managerial frameworks. The paper first traces the historical and technological trajectory of algorithmic integration in organizations, then analyzes emerging dynamics, including bias amplification, tensions in human–AI interaction, and dependence risks. A conceptual roadmap visualizes these interrelationships and pathways for governance intervention. By synthesizing insights from leading journals in management, information systems, and strategy, the article identifies persistent theoretical gaps in organizational adaptation, legitimacy, and long-term societal impact. It concludes with a structured future research agenda comprising twelve targeted questions to guide scholars and practitioners toward responsible ADS deployment. This work contributes a comprehensive foundation for advancing theory and practice in digital business and management studies.
UR - https://imbaspub.com/c828493735
ER -