Themes and methods in supply chain viability research

This paper presents a conceptual analysis of themes and methods in supply chain viability (SCV) research. We delineate SCV micro and macro perspectives, define viability capabilities, critically assess existing modelling approaches, and outline future research directions. Through analysis, SCV emerges as a concept for architecting and managing the supply chain based on proactive design of adaptability across multiple levels, including reconfigurable networks, processes, and products. We discuss synergies of SCV with resilience and show how viability extends the system boundary towards a new perspective of supply chain management, focusing on business continuity, survival, and purpose coherence. In viability research itself, we observe a transition from static optimisation to simulation-based stress testing, dynamic control, and digital twins and AI. We show that SCV research deals with complex systems characterised by non-monotonic processes, multiple operating modes, and structural dynamics, capable of coping with unknown future conditions and whose elements exhibit unpredictable, non-stationary, and non-linear behaviours. This complexity highlights the need for further research in SCV grounded in a combination of engineered variety with emergent adaptive behaviours. By consolidating a future research agenda, this paper offers a reference point for scholars and practitioners.

Authors

Institutions

Publication Details

Journal
International Journal of Production Research
Published
2026-08-27
DOI
https://doi.org/10.1080/00207543.2026.2707318
Primary Topic
Quality and Supply Management
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Themes and methods in supply chain viability research

Dmitry Ivanov
International Journal of Production Research
Quality and Supply Management
article

Themes and methods in supply chain viability research

Dmitry Ivanov
article en

Abstract

This paper presents a conceptual analysis of themes and methods in supply chain viability (SCV) research. We delineate SCV micro and macro perspectives, define viability capabilities, critically assess existing modelling approaches, and outline future research directions. Through analysis, SCV emerges as a concept for architecting and managing the supply chain based on proactive design of adaptability across multiple levels, including reconfigurable networks, processes, and products. We discuss synergies of SCV with resilience and show how viability extends the system boundary towards a new perspective of supply chain management, focusing on business continuity, survival, and purpose coherence. In viability research itself, we observe a transition from static optimisation to simulation-based stress testing, dynamic control, and digital twins and AI. We show that SCV research deals with complex systems characterised by non-monotonic processes, multiple operating modes, and structural dynamics, capable of coping with unknown future conditions and whose elements exhibit unpredictable, non-stationary, and non-linear behaviours. This complexity highlights the need for further research in SCV grounded in a combination of engineered variety with emergent adaptive behaviours. By consolidating a future research agenda, this paper offers a reference point for scholars and practitioners.

International Journal of Production Research
Berlin School of Economics and Law (DE)
Deutsche Forschungsgemeinschaft
Openalex Percentile: Top 6%
Quality and Supply Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.