An Optimisation Approach for Prioritising Actions to Mitigate Collaborative Knowledge Management Barriers
Year: 2026
Type: conference-paper
Abstract: Collaborative Knowledge Management (CKM) initiatives often struggle in practice because organisations face everyday managerial challenges such as limited coordination, misaligned objectives, uneven skills, and unclear documentation practices. Although many studies identify these barriers, managers still lack simple tools that help them decide which improvement actions should be implemented first when time, budget, and organisational capacity are limited. This paper proposes an optimisation-based approach designed to support these decisions. The model helps organisations select the combination of actions that is expected to reduce management-related knowledge barriers the most, while considering real-world constraints such as budget limitations, implementation capacity, feasibility conditions, and logical relationships between actions, including prerequisites and mutually incompatible initiatives. Besides suggesting which actions to implement, the approach also shows how much each barrier is likely to decrease, helping managers clearly understand the expected benefits and making the results easier to explain and discuss in decision-making processes. Finally, a real application illustrates how the proposed approach supports managerial decision-making by identifying practical actions, such as training initiatives, coordination mechanisms, and clear documentation practices, that can simultaneously reduce several management barriers and prepare the organisation for more advanced collaborative knowledge initiatives in later implementation phases. Future research may extend the proposed approach by incorporating uncertainty in the estimation of action effectiveness, multi-period planning considerations, and dynamic learning mechanisms that update decision recommendations as new implementation data becomes available.
Language: English
Subfield: Information Systems and Management
Field: Decision Sciences
Domain: Social Sciences
Open Access status: diamond
Award: G3847466715
OpenAlex ID: W7204240547