Systems Thinking for Business Strategic Management: Innovation and Resilience

A special issue of Systems (ISSN 2079-8954). This special issue belongs to the section "Systems Practice in Social Science".

Deadline for manuscript submissions: 30 June 2026 | Viewed by 3182

Special Issue Editors


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Guest Editor
Faculty of Informatics, Juraj Dobrila University of Pula, Ulica Alda Negrija 6, 52100 Pula, Croatia
Interests: business process management; structural equation modelling

E-Mail Website
Guest Editor
Faculty of informatics, Juraj Dobrila University of Pula, Pula, Croatia
Interests: systems thinking; strategic management
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Special Issue Information

Dear Colleagues,

This Special Issue welcomes research that applies systems thinking to strategic management to help organizations innovate and remain resilient amid uncertainty, turbulence, technological disruption, and sustainability pressures. We seek contributions that treat organizations as complex, adaptive socio-technical systems embedded in broader ecosystems (customers, suppliers, platforms, regulators, and communities), where feedback loops, delays, nonlinearity, and emergent behavior shape strategic outcomes.

We welcome theoretical, methodological, and empirical papers that integrate systems concepts with strategy topics such as dynamic capabilities, platform orchestration, open innovation, digital transformation, sustainability transitions, and risk governance. Contributions may leverage system dynamics and complex systems modeling, agent-based and network models, hybrid modeling (e.g., combining simulation with machine learning or digital twins), multi-criteria decision analysis, operations research, scenario planning, simulation optimization, data-driven analytics, and participatory or design-science approaches that reveal structure–behavior links and translate systemic insights into action.

We particularly encourage work that bridges systems theory with contemporary strategic challenges such as digital transformation, AI-driven decision-making, sustainability transitions, and resilience under uncertainty. Of special interest are studies that explore how systems perspectives can illuminate the next generation of strategy and management challenges, particularly through data-rich systems strategy (e.g., integrating big data, machine learning, and causal inference with system dynamics and network models to uncover hidden structures and predict system evolution), AI-driven strategic management (e.g., examining how generative AI, digital twins, and autonomous decision systems reshape strategic learning, foresight, and organizational adaptation), and Human–AI teaming and decision augmentation (investigating how hybrid human–AI systems enhance or disrupt decision quality, resilience, and performance in complex adaptive organizations).

We especially welcome cross-sector and cross-level work (e.g., supply-chain resilience, innovation ecosystems, public–private collaborations), research in emerging markets, and design-oriented studies that produce actionable interventions (policies, decision-support tools, dashboards). Submissions should clarify mechanisms (feedbacks, trade-offs, tipping points) and demonstrate measurable impact on innovation, sustainability, or organizational resilience.

Dr. Darko Etinger
Dr. Katarina Kostelić
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Systems is an international peer-reviewed open access monthly journal published by MDPI.

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Keywords

  • systems thinking
  • strategic management
  • innovation ecosystems
  • organizational resilience
  • digital transformation
  • dynamic capabilities
  • scenario planning and risk governance
  • AI-driven strategic management
  • data-rich systems strategy
  • human-AI teaming

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Published Papers (4 papers)

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Research

21 pages, 359 KB  
Article
The Impact of Market Integration Construction on the Innovation of Key Core Technologies of Enterprises: From the Perspective of Complex Adaptive System Theory
by Jingzhao Zhu, Sheng Mai and Xiong Zheng
Systems 2026, 14(3), 280; https://doi.org/10.3390/systems14030280 - 5 Mar 2026
Viewed by 372
Abstract
Achieving breakthroughs in key core technologies is an inherent requirement for attaining a high level of scientific and technological self-reliance. The construction of a unified market (market integration construction) reshapes the rules of the innovation system and drives enterprises to tackle key core [...] Read more.
Achieving breakthroughs in key core technologies is an inherent requirement for attaining a high level of scientific and technological self-reliance. The construction of a unified market (market integration construction) reshapes the rules of the innovation system and drives enterprises to tackle key core technologies. Based on the theory of complex adaptive systems, this paper uses the data of China’s A-share listed companies from 2008 to 2023 and the statistical yearbook to study the impact of market integration construction on the key core technological innovation of enterprises and its mechanism. The empirical research results show that: (1) Market integration construction reconstructs the rules governing resource flow, competitive incentives, and collaborative networks, guiding enterprises to achieve the emergence of key core technologies through nonlinear interactions. (2) Market integration construction exerts distinct effects on key core technological innovation by enhancing industrial investment and financial investment. (3) Agile responsiveness positively moderates the relationship between market integration construction and key core technological innovation. (4) The positive impact of market integration construction on key core technological innovation is more pronounced in non-state-owned, follower, and large enterprises. This study provides a theoretical basis and practical insights for advancing market integration construction and tackling key core technologies. Full article
19 pages, 1244 KB  
Article
Anomaly Detection as a Key Driver of Digital Forensic Resilience: Empirical Evidence from Critical Infrastructure Experts
by Marija Gombar, Darko Možnik and Mirjana Pejić Bach
Systems 2026, 14(2), 213; https://doi.org/10.3390/systems14020213 - 17 Feb 2026
Viewed by 692
Abstract
Ensuring strategic resilience in critical infrastructures supported with a machine learning approach requires moving beyond compliance checklists and post-incident analysis toward proactive, intelligence-based approaches. This study introduces the Forensic Resilience Operational Model (FROM), a systems thinking framework designed to embed forensic intelligence into [...] Read more.
Ensuring strategic resilience in critical infrastructures supported with a machine learning approach requires moving beyond compliance checklists and post-incident analysis toward proactive, intelligence-based approaches. This study introduces the Forensic Resilience Operational Model (FROM), a systems thinking framework designed to embed forensic intelligence into the resilience cycle of complex socio-technical systems. To quantify this integration, the study investigates the determinants of the extent to which four operational pillars (forensic readiness, anomaly detection, governance and privacy safeguards, and structured intelligence integration) affect forensic resilience, using empirical survey data from 212 cybersecurity professionals across critical infrastructure sectors. We deploy Partial Least Squares Structural Equation Modelling (PLS-SEM) to investigate these relationships, and the results confirm that anomaly detection is the strongest contributor to forensic resilience, followed by structured intelligence integration and forensic readiness. Governance safeguards, while comparatively weaker, provide the necessary legitimacy and assurance of compliance. Supported with sector-specific case studies in the maritime, financial, and CERT domains, the findings highlight both the adaptability of the proposed FROM and the operational constraints encountered in real-world contexts. The study contributes to the field of systems-oriented strategic management by demonstrating that, when systematically embedded, forensic intelligence enhances adaptive capacity, supports predictive decision-making, and strengthens resilience in environments characterized by uncertainty and high complexity. Full article
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22 pages, 411 KB  
Article
Patient Capital and Supply Chain Resilience: A Dynamic Capabilities Perspective
by Ganli Liao, Yu Zhang, Suxiu Li and Yuanya Zhang
Systems 2026, 14(2), 195; https://doi.org/10.3390/systems14020195 - 11 Feb 2026
Viewed by 1004
Abstract
Against the backdrop of global value chain restructuring, geopolitical tensions, and recurrent external shocks, supply chain resilience has become a central concern for firms. While prior studies highlight technological, relational, and policy-related drivers of resilience, limited attention has been paid to the role [...] Read more.
Against the backdrop of global value chain restructuring, geopolitical tensions, and recurrent external shocks, supply chain resilience has become a central concern for firms. While prior studies highlight technological, relational, and policy-related drivers of resilience, limited attention has been paid to the role of capital characteristics, particularly patient capital. Based on dynamic capabilities theory, this study develops a “capital–capabilities–resilience” framework to examine how patient capital contributes to firms’ supply chain resilience. Using panel data of Chinese listed manufacturing firms from 2013 to 2024, this study employs multi-stage regression analyses and extensive robustness tests. The results show that patient capital significantly enhances supply chain resilience along both stability and efficiency dimensions, with innovation, absorptive, and integrative capability acting as key mediating mechanisms. Further heterogeneity analyses indicate that the positive association between patient capital and supply chain resilience is more pronounced among state-owned enterprises, larger firms, and firms with weaker financial performances. This study advances the literature by theorizing patient capital as a capability-enabling financial arrangement and by demonstrating how it contributes to supply chain resilience through dynamic capability development. The findings also offer policy implications for promoting long-term-oriented capital to enhance resilience in an uncertain global environment. Full article
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26 pages, 626 KB  
Article
Alumni Networks, Board Characteristics, and Artificial Intelligence Adoption: Evidence from Chinese Listed Companies
by Jiafeng Gu
Systems 2026, 14(2), 169; https://doi.org/10.3390/systems14020169 - 4 Feb 2026
Viewed by 482
Abstract
Alumni relationships are essential social capital that are significant in companies’ resource acquisition and information sharing. Using 2018 data from Chinese listed companies, this study examines the impact of the chairperson–alumni network on corporate artificial intelligence (AI) adoption. The results show that chairperson–alumni [...] Read more.
Alumni relationships are essential social capital that are significant in companies’ resource acquisition and information sharing. Using 2018 data from Chinese listed companies, this study examines the impact of the chairperson–alumni network on corporate artificial intelligence (AI) adoption. The results show that chairperson–alumni relations are positively associated with AI adoption. Moreover, the impact of chairperson–alumni networks on AI adoption may span industrial, administrative, and geographical boundaries. This study shows that chairperson–alumni networks can indirectly influence AI adoption by influencing board size. Finally, this study demonstrates the heterogeneity of the impact of the chairperson–alumni network on AI adoption. Full article
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