The PYRAMID Framework: A Hierarchical Systems Architecture for Multidisciplinary Knowledge Synthesis

ABSTRACT The growing volume and diversity of research across disciplines have intensified challenges in how empirical evidence is synthesized, interpreted and communicated. Although established synthesis and reporting frameworks have improved transparency, they typically conceptualize synthesis as a linear workflow and provide limited guidance on how evidence integration functions as a complex system. From a systems research perspective, knowledge synthesis can instead be understood as an adaptive process shaped by hierarchy, interaction, feedback and learning. This article introduces the PYRAMID framework, a domain‐agnostic, hierarchical systems architecture for knowledge synthesis. The framework conceptualizes synthesis as a system of interacting with empirical and analytical subsystems operating across successive levels of abstraction. Lower levels emphasize inclusive evidence acquisition and appraisal, intermediate levels support synthesis and pattern formation, and upper levels integrate analytical and modelling activities. Feedback and iteration are treated as structural system properties that enable adaptive refinement and epistemic robustness. The PYRAMID framework is intended as a methodological and communicative aid rather than a prescriptive procedure. It supports methodological pluralism, enhances traceability from evidence to conclusions and improves transparency and reflexivity in multidisciplinary research contexts. By reframing evidence synthesis as a system of inquiry, the framework contributes to systems research and behavioural science by offering authors a coherent way to design, reflect on and communicate complex synthesis processes across domains.

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Publication Details

Journal
Systems Research and Behavioral Science
Published
2026-08-20
DOI
https://doi.org/10.1002/sres.70143
Primary Topic
Complex Systems and Decision Making
Type
article
Field-Weighted Citation Impact
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article

The PYRAMID Framework: A Hierarchical Systems Architecture for Multidisciplinary Knowledge Synthesis

D. Abiya Chelliah, P. Jeya Sheela
Systems Research and Behavioral Science
Complex Systems and Decision Making
article

The PYRAMID Framework: A Hierarchical Systems Architecture for Multidisciplinary Knowledge Synthesis

D. Abiya Chelliah, P. Jeya Sheela
article en

Abstract

ABSTRACT The growing volume and diversity of research across disciplines have intensified challenges in how empirical evidence is synthesized, interpreted and communicated. Although established synthesis and reporting frameworks have improved transparency, they typically conceptualize synthesis as a linear workflow and provide limited guidance on how evidence integration functions as a complex system. From a systems research perspective, knowledge synthesis can instead be understood as an adaptive process shaped by hierarchy, interaction, feedback and learning. This article introduces the PYRAMID framework, a domain‐agnostic, hierarchical systems architecture for knowledge synthesis. The framework conceptualizes synthesis as a system of interacting with empirical and analytical subsystems operating across successive levels of abstraction. Lower levels emphasize inclusive evidence acquisition and appraisal, intermediate levels support synthesis and pattern formation, and upper levels integrate analytical and modelling activities. Feedback and iteration are treated as structural system properties that enable adaptive refinement and epistemic robustness. The PYRAMID framework is intended as a methodological and communicative aid rather than a prescriptive procedure. It supports methodological pluralism, enhances traceability from evidence to conclusions and improves transparency and reflexivity in multidisciplinary research contexts. By reframing evidence synthesis as a system of inquiry, the framework contributes to systems research and behavioural science by offering authors a coherent way to design, reflect on and communicate complex synthesis processes across domains.

Systems Research and Behavioral Science
St. John's College of Nursing (US), Manonmaniam Sundaranar University (IN), Krishi Vigyan Kendra, Ghatkhed Amravati (IN), Liverpool John Moores University (GB)
Quality Education
Openalex Percentile: Top 6%
Complex Systems and Decision Making
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