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Supply chain resilience development in the defence industry: an AI-assisted content analysis of annual reports
Linköping University, Department of Management and Engineering, Industrial Economics. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Management and Engineering, Industrial Economics. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-8147-4288
Linköping University, Department of Management and Engineering, Industrial Economics. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Management and Engineering, Industrial Economics. Linköping University, Faculty of Science & Engineering.
2026 (English)In: Supply chain management, ISSN 1359-8546, E-ISSN 1758-6852, Vol. 31, no 7, p. 38-52Article in journal (Refereed) Published
Abstract [en]

PurposeThis study aims to examine supply chain resilience (SCR) in the defence industry by mapping supply-side, demand-side and internal risk dimensions and corresponding mitigation strategies disclosed by seven publicly listed defence firms over 2014-2024. Drawing on Resource Dependence Theory (RDT), the study introduces the Strategic Risk and Resilience Roadmap (S3R) to explain how firms use bridging and buffering to manage evolving resource dependencies.Design/methodology/approachThe study uses a longitudinal qualitative content analysis of annual reports. It combines artificial intelligence (AI)-assisted extraction using large language models (LLMs), iterative prompt engineering and manual cross-validation against source reports to categorise risks, trace mitigation strategies and track shifts in disclosed mitigation postures across three disruption eras: Baseline (2014-2019), Pandemic (2020-2021) and Emerging Risk (2022-2024).FindingsFirms adapt SCR by rebalancing bridging and buffering as resource dependencies change across disruption eras. In the Baseline era, firms rely mainly on bridging to stabilise external dependencies; during the Pandemic, they scale buffering to protect continuity under acute shocks; from 2022, they combine to adopt a hybrid posture as constraints persist and multiply. Supplier capacity and availability dominate post-2022 and customer-side risk reorients from funding uncertainty to delivery-performance exposure during ramp-ups. S3R traces a path-dependent process in which shifts in resource dependence drive risk reassessment, posture recalibration and learning that strengthens SCR over time.Research limitations/implicationsWhile based on publicly available reports and AI-extracted content, the analysis may omit informal or undisclosed practices. Future research should triangulate findings with interviews and firm-level performance metrics to deepen the insights.Originality/valueThis paper applies a longitudinal, AI-assisted qualitative content analysis of annual reports across supply-side, demand-side and internal risk dimensions, and it extends RDT into SCR by revealing dynamic bridging and buffering cycles across three disruption eras. It offers theoretical insight into the temporal evolution of defence SCR and a practical, multi-dimensional diagnostic framework.

Place, publisher, year, edition, pages
EMERALD GROUP PUBLISHING LTD , 2026. Vol. 31, no 7, p. 38-52
Keywords [en]
Risk; Defence industry; Supply chain resilience; Mitigation strategies; Large language model; AI method
National Category
Business Administration
Identifiers
URN: urn:nbn:se:liu:diva-222760DOI: 10.1108/SCM-10-2025-1017ISI: 001733004900001Scopus ID: 2-s2.0-105037585707OAI: oai:DiVA.org:liu-222760DiVA, id: diva2:2052523
Available from: 2026-04-13 Created: 2026-04-13 Last updated: 2026-09-18
In thesis
1. Managing Supply Chain Complexity: A Study of Systems Integrators
Open this publication in new window or tab >>Managing Supply Chain Complexity: A Study of Systems Integrators
2026 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Over recent decades, developments such as outsourcing, globalisation, product variety, and customisation have increased the number, variety, and interdependence of elements in supply chains, often across more geographically dispersed settings, while recent disruptions have exposed how uncertainty and change make their behaviour less predictable. Supply chain complexity (SCC) is defined here as the condition arising from the interaction of structural and dynamic complexity across the supply, internal, and customer dimensions of a bounded supply chain. Structural complexity concerns the number, variety, and interdependence of elements, whereas dynamic complexity concerns uncertainty and change over time.

SCC is a defining condition for systems integrators, actors that coordinate supplier-side inputs, internal activities, and customer-side requirements into a functioning delivery arrangement. Research on SCC describes these structural and dynamic properties, but says less about translating description into judgement, that is, which forms of complexity support action, which constrain it, and how this should be reassessed as conditions change. The purpose of this thesis is to explore how supply chain complexity can be understood and managed by systems integrators across different operational conditions.

The thesis draws on four studies of renewable energy intermediaries, solar PV adoption, engineer-to-order defence procurement, and defence firm resilience. It develops the Complexity Value Compass (CVC), which connects profiling structural and dynamic complexity, placing the profile in a Cynefin-informed decision domain, and judging whether complexity should be absorbed, maintained, or reduced. Its central claim is that complexity is judged not by how much is present, but by whether it provides the capacity the prevailing response logic requires.

The thesis shows that complexity profiles do more than describe structural and dynamic complexity; they help assess what kind of decision context the profile creates. Structure matters because it shapes whether dynamic complexity remains contained within a dimension or spreads across the supply chain. By translating Cynefin into a supply-chain-specific interpretation logic, the thesis shows how such profiles can inform judgements about whether complexity should be absorbed, maintained, or reduced. The CVC therefore works as a compass for orientation rather than as a route plan prescribing a fixed path of action.

Abstract [sv]

Under de senaste decennierna har outsourcing, globalisering, produktvariation och kundanpassning gjort försörjningskedjor mer komplexa genom att öka antalet element, variationen mellan dem och deras inbördes beroenden, ofta över större geografiska avstånd. Samtidigt har senare tids störningar blottlagt hur osäkerhet och förändring gör försörjningskedjors beteende mindre förutsägbart. Försörjningskedjekomplexitet (SCC) definieras här som det tillstånd som uppstår ur samspelet mellan strukturell och dynamisk komplexitet över leverantörs-, intern- och kunddimensionerna i en avgränsad försörjningskedja. Strukturell komplexitet rör antalet element, deras variation och inbördes beroenden, medan dynamisk komplexitet rör osäkerhet och förändring över tid.

SCC är ett definierande villkor för systemintegratörer, aktörer som samordnar leverantörssidans insatser, interna aktiviteter och kundsidans krav till ett fungerande leveransupplägg. Forskningen om SCC beskriver dessa strukturella och dynamiska egenskaper, men säger mindre om hur beskrivning omsätts i bedömning, det vill säga vilka former av komplexitet som stödjer handling, vilka som begränsar den, och hur detta bör omprövas när förhållandena förändras. Avhandlingens syfte är att utforska hur försörjningskedjekomplexitet kan förstås och hanteras av systemintegratörer under olika operativa förhållanden.

Avhandlingen bygger på fyra studier om mellanhänder inom förnybar energi, adoption av solceller, inköp i engineer-to-order-projekt inom försvarsindustrin och resiliens i försvarsföretag. Den utvecklar Komplexitetsvärdekompassen (CVC), som knyter samman profilering av strukturell och dynamisk komplexitet, placering av profilen i en Cynefin-informerad beslutsdomän och bedömning av om komplexiteten bör absorberas, bibehållas eller reduceras. Dess centrala tes är att komplexitet inte bedöms utifrån hur mycket som vi finns, utan utifrån om den ger den kapacitet som den rådande responslogiken kräver.

Avhandlingen visar att komplexitetsprofiler inte bara beskriver hur strukturell och dynamisk komplexitet är fördelad, utan också hjälper till att bedöma vilken typ av beslutssituation profilen skapar. Strukturen påverkar om dynamisk komplexitet förblir avgränsad inom en dimension eller sprider sig mellan leverantörs-, intern- och kunddimensionerna. Genom att översätta Cynefin till en försörjningskedjespecifik tolkningslogik visar avhandlingen hur sådana profiler kan ligga till grund för bedömningen av om komplexitet bör absorberas, bibehållas eller reduceras. CVC fungerar därför som en kompass för situationsbedömning snarare än som en ruttplan som föreskriver en bestämd väg genom komplexiteten.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2026. p. 110
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 2545
Keywords
Supply chain complexity, Systems integration, Complexity management, Cynefin framework, Complexity Value Compass
National Category
Business Administration
Identifiers
urn:nbn:se:liu:diva-227720 (URN)10.3384/9789181186949 (DOI)9789181186932 (ISBN)9789181186949 (ISBN)
Public defence
2026-10-23, ACAS, A Building, Campus Valla, Linköping, 10:15 (English)
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Supervisors
Available from: 2026-09-18 Created: 2026-09-18 Last updated: 2026-09-18Bibliographically approved

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Aspeteg, JoakimHoltström, JohanRehme, JakobHavemo, Emelie

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