Bridging Systems Theory and Information Systems: A Framework for Designing Complex Information Systems

Ulvi Ibrahimli et al.

Journal of the Association for Information Systems2026article
AJG 4*ABDC A*
Weight
0.50

Abstract

Information Systems (IS) is rooted in systems theory, which offers powerful concepts to address challenges of growing system complexity and non-systemic design approaches in information systems. Despite its systemic origins, systems theory remains a peripheral topic in IS. The study addresses this gap by introducing a comprehensive framework of 52 systems-theoretical concepts to guide the design of complex IS artifacts. We synthesize scattered systems knowledge from diverse disciplines to provide a unified level of abstraction for complex information system design. We apply the framework to a use case of business reputation systems to show how the systems lens informs the design of a novel, complex information system. We make three key contributions to the literature. First, the framework provides a common ground for interdisciplinary research in information system design. Second, it offers a unified level of abstraction grounded in systems theory that serves as a coherent basis for artifact design. Third, it demonstrates the potential of systems theory as a foundational justificatory knowledge base. Furthermore, we provide guidance on applying the framework across multiple modes of reasoning, alongside further application guidelines. The study thus serves as a bridge between the body of systems knowledge and contextual design in IS.

Cite this paper

@article{ulvi2026,
  title        = {{Bridging Systems Theory and Information Systems: A Framework for Designing Complex Information Systems}},
  author       = {Ulvi Ibrahimli et al.},
  journal      = {Journal of the Association for Information Systems},
  year         = {2026},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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