Towards dynamic decision-making in government as service organization: insights from systems thinking

Abstract

Purpose Service organizations operate in an increasingly complex and uncertain context that makes decision-making challenging. Despite well-recognized changes in the operational context of government as service organization, service literature has given surprisingly limited attention to what these changes imply for organizational decision-making. This study aims to face with the lack of fit of decision-making theorizing with the reality, within which most service practitioners operate, in order to foster the relevance of decision-making in service research and properly approach the false assumptions and misguided instructions for action. Design/methodology/approach To rectify the situation, the purpose of this paper is to advance a more holistic understanding of decision-making in government as service organization. The authors do so by reviewing the sparse, though insightful, prior literature on decision-making in service research and identifying four foundational assumptions of decision-making in the service context, that radically differ from the traditional assumptions of decision-making within the wider management literature. Findings The authors contribute to service research by further advancing the emerging dynamic understanding of decision-making by developing eight systems thinking-informed research propositions and a connected research agenda. In doing so, the paper offers the essential ground work that can revitalize the field of service management and equip it for facing the challenges that government as service organization is encountering in the 21st century. Originality/value The formulated eight research propositions demonstrate that decision-making in a government as service organization occurs within complex adaptive systems composed of multiple subsystems and is characterized by a high degree of unpredictability. It is a process influenced by multiple actors part of the system and subsystems, through multiple feedback loops, where the implications of prior decisions inform the future decisions.