The different roles of algorithms in research on governmental decision-making for citizen services

Purpose The aim of this paper is to explore the role of algorithms in research focusing on automated decision-making of citizen services. Design/methodology/approach A scoping review of literature published between 2016 and 2025 was conducted. Studies were analyzed to identify how automated decision-making is conceptualized, the terminology used, the roles algorithms are assigned and the contexts in which they operate. Findings The review reveals significant conceptual ambiguity in research on automated decision-making. Furthermore, automated decision-making systems are shown to operate within broader socio-technical networks encompassing people, organizational structures, technologies and formal rules. Current research offers fragmented understandings of automated decision-making, focusing largely on administrative efficiency rather than citizen experiences. Practical implications The findings point to an urgent need for policy frameworks, standardized guidelines and training that embed public values such as fairness, transparency and accountability. Policies should promote digital literacy and citizen empowerment to ensure engagement with automated decision-making and algorithmic systems in citizen services and public sector governance. Originality/value This study contributes to a nuanced understanding of the complexity of automated decision-making, highlighting the context and institutional logic. Algorithms were found to play seven different roles supporting humans in automated decision-making processes. This, together with different degrees of automation in the decision-making process, challenges a more dualistic view of automated decision-making.