A critical function of an organization is to foster the level of integration
(coordination and cooperation) necessary to achieve its objectives. The need to
coordinate and motivation to cooperate emerges from the myriad dependencies
between an organization’s members and their work. Therefore, to reason about
solutions to coordination and cooperation problems requires a robust
representation that includes the underlying dependencies. We find that such a
representation remains missing from formal organizational models, and we
leverage semantics to bridge this gap. Drawing on well-established
organizational research and our extensive fieldwork with one of North America’s
largest municipalities, (1) we introduce an ontology, formalized in first-order
logic, that operationalizes concepts like outcome, reward, and epistemic
dependence, and their links to potential integration risks; and (2) present
real-world applications of this ontology to analyze and support integration in
complex government infrastructure projects. Our ontology is implemented and
validated in both Z3 and OWL. Key features of our model include inferable
dependencies, explainable coordination and cooperation risks, and actionable
insights on how dependency structures within an organization can be altered to
mitigate the risks. Conceptualizing real-world challenges like incentive
misalignment, free-riding, and subgoal optimization in terms of dependency
structures, our semantics-based approach represents a novel method for
modelling and enhancing coordination and cooperation. Integrated within a
decision-support system, our model may serve as an impactful aid for
organizational design and effectiveness. More broadly, our approach underscores
the transformative potential of semantics in deriving tangible, real-world
value from existing organization theory.
In this article, the authors discuss the importance of coordination and cooperation within organizations and highlight the need for a robust representation that includes the underlying dependencies between members and their work. They argue that existing formal organizational models lack this representation and propose the use of semantics to bridge this gap.
The authors introduce an ontology, formalized in first-order logic, that operationalizes concepts such as outcome, reward, and epistemic dependence, and their links to potential integration risks. They present real-world applications of this ontology in analyzing and supporting integration in complex government infrastructure projects.
One key feature of their model is inferable dependencies, which allows for a deeper understanding of the relationships between different elements of the organization. This helps in identifying coordination and cooperation risks and provides actionable insights on how dependency structures can be altered to mitigate these risks.
The authors also highlight how their semantics-based approach can conceptualize real-world challenges such as incentive misalignment, free-riding, and subgoal optimization in terms of dependency structures. This provides a novel method for modeling and enhancing coordination and cooperation within organizations.
By integrating their ontology within a decision-support system, the authors believe that it can serve as a valuable tool for organizational design and effectiveness. It provides a tangible way to derive real-world value from existing organization theory.
This content highlights the multi-disciplinary nature of the concepts discussed. It draws on well-established organizational research and applies semantics to enhance coordination and cooperation. By combining elements of logic, ontology, and organizational theory, the authors provide a holistic approach to addressing these complex challenges.