Modelling Knowledge Flows and Leakages: A Systemic Hydrological Approach to High‐Complexity Innovation Environments

ABSTRACT Prevailing Knowledge Management (KM) models offer limited support for detecting Critical Knowledge erosion before it compromises strategic resilience. This study proposes the Hydrological Model of Knowledge Dynamics for Science, Technology, and Innovation (ST&I) , a systemic artifact that represents knowledge flows, stocks, losses, and governance controls in ST&I environments. Based on literature review, bibliometric analysis, and field observation in the Brazilian Aerospace and Defense sector, the model formalizes a functional isomorphism between hydrological and Dynamic Knowledge Management (DKM) processes. The propositions, framed as hypotheses for future empirical validation, explain how organizational amnesia may emerge from attrition‐driven drainage, obsolescence‐related evaporation, crisis‐driven outflow, and monitoring failures. The article also distinguishes Essential Knowledge from Critical Knowledge as knowledge‐stock categories requiring different governance logics. Rather than claiming empirically validated effects, the study provides a structured conceptual lens for examining knowledge vulnerability and supporting diagnostic routines in volatile, high‐complexity sectors.

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Publication Details

Journal
Knowledge and Process Management
Published
2026-08-18
DOI
https://doi.org/10.1002/kpm.70151
Primary Topic
Supply Chain Resilience and Risk Management
Type
article
Field-Weighted Citation Impact
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article

Modelling Knowledge Flows and Leakages: A Systemic Hydrological Approach to High‐Complexity Innovation Environments

Antonio Ramalho de Souza Carvalho
Knowledge and Process Management
Supply Chain Resilience and Risk Management
article

Modelling Knowledge Flows and Leakages: A Systemic Hydrological Approach to High‐Complexity Innovation Environments

Antonio Ramalho de Souza Carvalho
article en

Abstract

ABSTRACT Prevailing Knowledge Management (KM) models offer limited support for detecting Critical Knowledge erosion before it compromises strategic resilience. This study proposes the Hydrological Model of Knowledge Dynamics for Science, Technology, and Innovation (ST&I) , a systemic artifact that represents knowledge flows, stocks, losses, and governance controls in ST&I environments. Based on literature review, bibliometric analysis, and field observation in the Brazilian Aerospace and Defense sector, the model formalizes a functional isomorphism between hydrological and Dynamic Knowledge Management (DKM) processes. The propositions, framed as hypotheses for future empirical validation, explain how organizational amnesia may emerge from attrition‐driven drainage, obsolescence‐related evaporation, crisis‐driven outflow, and monitoring failures. The article also distinguishes Essential Knowledge from Critical Knowledge as knowledge‐stock categories requiring different governance logics. Rather than claiming empirically validated effects, the study provides a structured conceptual lens for examining knowledge vulnerability and supporting diagnostic routines in volatile, high‐complexity sectors.

Knowledge and Process Management
Department of Aerospace Science and Technology (BR)
Industry, innovation and infrastructure
Openalex Percentile: Top 7%
Supply Chain Resilience and Risk Management
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Modelling Knowledge Flows and Leakages: A Systemic Hydrological Approach to High‐Complexity Innovation Environments — Antonio Ramalho de Souza Carvalho · Knowledge and Process Management (2026) | TGRS Research Map | TGRS