Systems

63 pages, 2241 KB

Open AccessArticle

Artificial Intelligence Adoption in Established Women-Led SMEs: A Multiple-Case Study of Competencies, Barriers, and Business Process Applications

by Juan Martín Ireta-Sánchez and Mariam Berkatsashvili

Systems 2026, 14(9), 1120; https://doi.org/10.3390/systems14091120 - 8 Sep 2026

Abstract

Artificial intelligence (AI) is increasingly acknowledged as a strategic asset for enhancing innovation and competitiveness among small and medium-sized enterprises (SMEs). Nevertheless, limited research has focused on the experiences of women entrepreneurs regarding AI adoption within established SMEs, particularly in emerging economies. This [...] Read more.

Artificial intelligence (AI) is increasingly acknowledged as a strategic asset for enhancing innovation and competitiveness among small and medium-sized enterprises (SMEs). Nevertheless, limited research has focused on the experiences of women entrepreneurs regarding AI adoption within established SMEs, particularly in emerging economies. This study investigates the knowledge, attitudes, skills, perceived barriers, and business-process applications associated with AI adoption among women entrepreneurs in Chile. Employing an exploratory multiple-case study design, semi-structured interviews were conducted with fourteen women leading established SMEs across various industries. The cross-case analysis indicates that resilient leadership, social intelligence, and managerial knowledge were frequently mentioned characteristics alongside diverse patterns of AI adoption. The findings reveal that participants identified strategic-planning and management-control knowledge, resilient leadership attitudes, and social intelligence skills as recurring competencies associated with AI adoption into business activities. Participants reported utilising AI primarily to support customer relationship management (CRM), while also describing limited AI readiness as a constraint associated with learning needs and experiences of AI adoption. To distinguish between AI adoption and broader digitalisation and automation, the study defines the following adoption profiles: non-adopter, AI experimenter, substantive AI adopter, and integrated AI adopter. Further cross-case analysis suggests that participants experienced knowledge, attitudes, and skills as mutually reinforcing during AI adoption rather than as isolated competencies. This study contributes to the literature by providing an empirically grounded understanding of how a group of established women entrepreneurs perceive and experience AI adoption in their SMEs. Instead of identifying causal determinants of successful adoption, the findings highlight recurring patterns and relationships that may inform future theory development and comparative research on AI adoption in entrepreneurial contexts. The study also offers practical insights for policymakers, educators, and SME support organisations aiming to enhance AI capabilities among women-led businesses. Full article

(This article belongs to the Special Issue Sustainable Business Models and Digital Transformation)

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28 pages, 1161 KB

Open AccessFeature PaperArticle

TMT Faultlines and Corporate Digital Transformation: The Moderating Role of Board Governance

by Zhengang Zhang, Hongfei Wang and Peilun Li

Systems 2026, 14(9), 1119; https://doi.org/10.3390/systems14091119 - 8 Sep 2026

Abstract

The top management team (TMT) plays a key role in shaping corporate strategy. However, how and when TMT faultlines influence corporate digital transformation remains unclear. Drawing on the categorization–elaboration model, this study examines the nonlinear relationship between TMT faultlines and corporate digital transformation [...] Read more.

The top management team (TMT) plays a key role in shaping corporate strategy. However, how and when TMT faultlines influence corporate digital transformation remains unclear. Drawing on the categorization–elaboration model, this study examines the nonlinear relationship between TMT faultlines and corporate digital transformation and the moderating role of board governance. Using panel data from Chinese A-share-listed manufacturing firms, the results suggest an inverted U-shaped relationship between TMT faultlines and corporate digital transformation. Board monitoring and board networking are associated with a steeper inverted U-shaped curve, whereas board advising is associated with a flatter curve. Heterogeneity analysis shows that the inverted U-shaped relationship is mainly observed in non-state-owned enterprises, younger firms, and firms with high ownership concentration. These findings extend research on faultlines, strategic leadership, and corporate governance and offer practical implications for configuring TMTs and designing board governance mechanisms to support corporate digital transformation. Full article

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45 pages, 1292 KB

Open AccessArticle

Mechanisms of a Self-Determination Theory-Driven Human–AI Co-Driving Model: Effects on Driving Habits and Continued Usage Intention

by Juncheng Mu, Linglin Zhou and Chun Yang

Systems 2026, 14(9), 1118; https://doi.org/10.3390/systems14091118 - 8 Sep 2026

Abstract

This study aims to explore how the functional characteristics of virtual models in autonomous driving systems influence users’ psychological needs, thereby shaping driving habits and continued usage intentions. As autonomous driving systems evolve toward learning-based intelligence, human–computer interaction interfaces play a crucial role [...] Read more.

This study aims to explore how the functional characteristics of virtual models in autonomous driving systems influence users’ psychological needs, thereby shaping driving habits and continued usage intentions. As autonomous driving systems evolve toward learning-based intelligence, human–computer interaction interfaces play a crucial role in shaping driver behavior and sustained system adoption. However, prior research has primarily focused on trust and intention to use, with less attention paid to how motivational and system-feature factors jointly influence driving habits and continuous use intentions. Building upon self-determination theory (SDT), this study constructs an extended framework for human–AI co-driving behavior, examining the impact of three intrinsic psychological drivers (perceived autonomy importance, self-efficacy, and identification) on driving habits and continuous use intentions, while also considering the visual factors of virtual models and nine technical feature factors. Using online questionnaires, 614 valid samples were collected and empirically tested using PLS-SEM and IPMA. Results indicate that the perceived importance of autonomy significantly positively influences both driving habits and continuous use intentions; self-efficacy, identification, and visual factors did not show significant effects at either stage. Among the technical feature factors, data acquisition and feedback, intelligent driving modes, and risk perception capabilities significantly enhanced driving habits and continuous use intentions, achieving an optimal “high importance–high performance” match in the IPMA matrix. IPMA further revealed that perceived autonomy importance was associated with a “high importance–low performance” mismatch in the driving habit formation stage, representing a critical shortfall requiring urgent optimization; intelligent driving modes and data acquisition and feedback, conversely, demonstrated both high importance and high performance in driving continuous use intentions. These findings extend the application of self-determination theory to autonomous driving scenarios into a unified framework integrating motivational and system-feature factors, providing empirical evidence for phased optimization of human–AI co-driving system design and evaluation. Full article

(This article belongs to the Special Issue Learning-Empowered Autonomous Driving and Intelligent Transportation Systems)

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23 pages, 547 KB

Open AccessArticle

Enabling Supply Chain Resilience Through Green Supply Chain Integration in Agribusinesses: The Role of Responsible Innovation and Agentic AI

by Xinyu Teng, Baowen Zhang and Yinuo Dong

Systems 2026, 14(9), 1117; https://doi.org/10.3390/systems14091117 - 8 Sep 2026

Abstract

In the face of severe impacts on agricultural supply chains caused by ecological degradation and environmental turbulence, leveraging green supply chain integration practices to build supply chain resilience has become pivotal in agribusiness management. However, empirical evidence remains insufficient regarding the specific internal [...] Read more.

In the face of severe impacts on agricultural supply chains caused by ecological degradation and environmental turbulence, leveraging green supply chain integration practices to build supply chain resilience has become pivotal in agribusiness management. However, empirical evidence remains insufficient regarding the specific internal mechanisms and boundary conditions through which green supply chain integration practices foster supply chain resilience. To address this knowledge gap, our study investigates the impact of green supply chain integration on supply chain resilience based on organizational information processing theory, while focusing on the mediating and moderating roles played by responsible innovation and agentic AI within this mechanism, respectively. Utilizing hierarchical regression analysis and the MEDCURVE macro program on survey data from 225 Chinese agribusinesses, the results indicate that green supply chain integration has an inverted U-shaped relationship with both responsible innovation and supply chain resilience. Responsible innovation partially mediates the relationship between green supply chain integration and supply chain resilience. Furthermore, agentic AI positively moderates the linear slopes and shifts the turning points of the inverted U-shaped relationships rightward, extending the optimal threshold of green supply chain integration for both responsible innovation and supply chain resilience. Our study aims to introduce agentic AI into empirical research on green supply chain practices and resilience mechanisms, thereby offering theoretical and managerial insights for advancing agribusinesses toward building highly resilient, intelligent, and green agentic supply chains. Full article

(This article belongs to the Special Issue Systems Thinking for Sustainable and Responsible Innovation)

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34 pages, 2247 KB

Open AccessArticle

The Golden Cage: How Algorithmic Nurturing Systemically Erodes Human Autonomy Under Artificial General Intelligence

by Seunghyun Baik, Yong Hun Yoon, Sung Jun Jo, Hyeran Choi and Seung-Wan Kang

Systems 2026, 14(9), 1116; https://doi.org/10.3390/systems14091116 - 8 Sep 2026

Abstract

The proliferation of Artificial General Intelligence (AGI) presents a systemic paradox within complex socio-technical systems: while enhancing efficiency, AGI may subvert human autonomy through comfort-based alignment rather than overt coercion. Although algorithmic management research has theorized surveillance-based control—the “Iron Cage”—it has largely overlooked [...] Read more.

The proliferation of Artificial General Intelligence (AGI) presents a systemic paradox within complex socio-technical systems: while enhancing efficiency, AGI may subvert human autonomy through comfort-based alignment rather than overt coercion. Although algorithmic management research has theorized surveillance-based control—the “Iron Cage”—it has largely overlooked the voluntary erosion of autonomy driven by algorithmic nurturing and its recursive feedback loops. This study proposes the Algorithmic Nurturing Perspective (ANP) by synthesizing five foundational behavioral theories—bounded rationality, expectancy theory, prospect theory, goal-setting theory, and social information processing theory—reinterpreted within the AGI context. ANP elucidates how AGI systemically reconfigures socio-technical systems through three self-reinforcing causal feedback loops: the automation of choice, the externalization of emotional regulation, and isolation from social reality. We derive eight propositions illustrating how these mechanisms trigger individual-level cognitive dependence and systemic regression, which subsequently emerge as organizational-level pathologies, including learning myopia, leadership degeneration, and declining strategic decision quality. By introducing the “Golden Cage” as a novel conceptual lens, the ANP shifts the AI governance discourse from an “efficiency-vs-coercion” framework to an “autonomy-vs-compliance” paradigm. We further propose Cognitive Friction Design as a multilevel balancing intervention to mitigate these risks. As a self-contained theoretical contribution, this framework stands independently of any single empirical test while remaining falsifiable: a mechanism-differentiated system dynamics simulation demonstrates the internal coherence of the proposed feedback structure, and proposition-by-proposition falsification conditions specify the empirical pathway for causal verification in future research. We further identify balancing-dominant conditions under which algorithmic assistance may enhance, rather than erode, human autonomy. Full article

(This article belongs to the Section Systems Practice in Social Science)

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22 pages, 1386 KB

Open AccessReview

Systems Thinking in Public Health Education: A Scoping Review

by Fiker Eshetu Dadi, Ligia Paina, Séphora Giraud-Carrier and Jeffrey Glenn

Systems 2026, 14(9), 1115; https://doi.org/10.3390/systems14091115 - 8 Sep 2026

Abstract

Systems thinking is increasingly recognized as an important component of public health education, yet its application within curricula remains varied and evolving. This scoping review examined how systems thinking is defined, taught, and assessed in public health education. Peer-reviewed studies published between 2009 [...] Read more.

Systems thinking is increasingly recognized as an important component of public health education, yet its application within curricula remains varied and evolving. This scoping review examined how systems thinking is defined, taught, and assessed in public health education. Peer-reviewed studies published between 2009 and 2026 that explored systems thinking in public health education were identified through a review of the global literature. Thirteen studies met the inclusion criteria, including ten from the United States and one each from Canada, Croatia, and South Africa. Data were extracted and synthesized using thematic analysis. Teaching approaches included systems mapping, interprofessional collaboration, and experiential learning, although few studies defined systems thinking competencies or used validated assessment tools. Five themes emerged: definitions and conceptualizations of systems thinking, competencies emphasized, teaching strategies and tools, assessment methods, and alignment with competency frameworks. While systems thinking has gained prominence in public health education, its integration remains fragmented, highlighting the need for clearer competencies, stronger faculty development, and more rigorous evaluation. Full article

(This article belongs to the Special Issue Advancing Systems Thinking in Higher Education: Frameworks, Pedagogies, Interdisciplinary Practices and Challenges)

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42 pages, 1501 KB

Open AccessArticle

by Jiawei Xu and Haohua Li

Systems 2026, 14(9), 1114; https://doi.org/10.3390/systems14091114 - 7 Sep 2026

Abstract

Firms are embedded in transaction systems whose organization can generate both coordination benefits and relational exposure. Using disclosed related-party transactions (RPTs), we construct annual weighted bipartite networks for 2674 Chinese A-share listed firms and examine 26,264 RPT-active firm-year observations from 2003 to 2024. [...] Read more.

Firms are embedded in transaction systems whose organization can generate both coordination benefits and relational exposure. Using disclosed related-party transactions (RPTs), we construct annual weighted bipartite networks for 2674 Chinese A-share listed firms and examine 26,264 RPT-active firm-year observations from 2003 to 2024. The analysis distinguishes three firm-level dimensions—relationship scale, transaction concentration, and projected shared-counterparty position—from local bipartite microstructures. The firm-level evidence reveals a double-edged pattern: broader and more valuable RPT relationships are associated with lower Merton and KMV distance to default (DD), and projected degree is associated with lower Merton DD, whereas a higher top-three-related-party share is associated with higher KMV DD. Direction-specific estimates reinforce this distinction. Scale is negatively associated with DD on both the seller/provider and buyer/recipient sides, concentration is generally positive (especially on the buyer/recipient side), and seller/provider projected degree is negatively associated with KMV DD. At the local level, closed 2 × 2 presence and intensity are negatively associated with Merton DD, while simple degree-based forms and shared-counterparty bridges provide less stable differentiation. Observed closure substantially exceeds degree-sequence-preserving randomized benchmarks, and excess closure remains negatively associated with Merton and Bharath–Shumway DD after relationship opportunities and counterparty popularity are controlled. The results establish transaction scale, value allocation, projected reach, and repeated local sharing as complementary signals for structure-sensitive credit risk monitoring in complex transaction systems. Full article

(This article belongs to the Special Issue Complex Financial Systems: Dynamics, Risk, and Resilience)

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29 pages, 1008 KB

Open AccessArticle

Exploring the Pathways of Green Development Behavior in Building Materials Enterprises Within an Individual–Organizational–Institutional Framework

by Xingwei Li, Chuhan Liu, Yi Zhang, Yuhong Yao and Qiong Shen

Systems 2026, 14(9), 1113; https://doi.org/10.3390/systems14091113 - 7 Sep 2026

Abstract

The green transformation of enterprises is facing major challenges. However, how individual, organizational, and institutional factors jointly shape enterprise green development behavior remains insufficiently understood. This study constructs a three-dimensional analytical framework covering individual, organizational, and institutional levels. Using expert surveys and data [...] Read more.

The green transformation of enterprises is facing major challenges. However, how individual, organizational, and institutional factors jointly shape enterprise green development behavior remains insufficiently understood. This study constructs a three-dimensional analytical framework covering individual, organizational, and institutional levels. Using expert surveys and data from 129 listed building materials companies from 2014 to 2023, the fuzzy-DEMATEL and fuzzy-set qualitative comparative analysis (fsQCA) methods are used to identify key factors and explore multiple paths to achieve green development behavior (GDB). This study found that: (1) executives’ green cognition, technological innovation capability, government penalties, media attention, green consumer demand, and market competitiveness are key factors; (2) no single factor is a necessary condition; (3) four equivalent driving configurations are identified: public opinion and market adaptation, executive leadership and market dynamics, external pressure and innovation synergy, and policy constraints and market breakthroughs; and (4) technological innovation capability and market competitiveness exhibit potential functional substitutability across different configurations. This study identifies key factors shaping enterprise strategies, reducing uncertainty in green initiatives and improving sustainable development decisions. The findings reveal nonlinear and synergistic mechanisms of GDB, challenging traditional linear approaches and offering a new framework for complex decision-making. Full article

(This article belongs to the Special Issue Systems Approaches to Green Supply Chain Decision-Making for Sustainable Development Goals)

38 pages, 6742 KB

Open AccessArticle

The Predictive Power of Systemic Risk Indicators Under Extreme Scenarios

by Xiaohang Gan, Linhai Zhao and Hexin Zhang

Systems 2026, 14(9), 1112; https://doi.org/10.3390/systems14091112 - 7 Sep 2026

Abstract

Against the backdrop of an increasingly complex global financial environment and persistently rising market uncertainty, the importance of accurately identifying systemic risk and strengthening macroprudential supervision has become ever more prominent. Using data on China’s listed financial institutions from 2008 to 2025, this [...] Read more.

Against the backdrop of an increasingly complex global financial environment and persistently rising market uncertainty, the importance of accurately identifying systemic risk and strengthening macroprudential supervision has become ever more prominent. Using data on China’s listed financial institutions from 2008 to 2025, this paper focuses on systemic risk indicators of three types—risk contagion, tail risk, and capital fragility—and examines their predictive power under extreme scenarios from three perspectives: macro-level timeliness, financial institutional market performance, and early warning of bank distress. The findings are as follows: (1) The fluctuations of systemic risk indicators are closely associated with periods of financial stress, demonstrating good macro-level timeliness. (2) Systemic risk indicators can effectively predict the decline in stock returns and the increase in stock return volatility of financial institutions during stress periods, offering forward-looking information for financial institutional market performance. (3) Systemic risk indicators can effectively predict bank distress. The results of multi-horizon prediction show that risk contagion indicators exhibit strong cross-horizon stability, tail risk indicators provide the best medium-term early warning, and capital fragility indicators are more suitable for contemporaneous warning. The findings suggest that systemic risk indicators possess stable forward-looking information value under extreme scenarios, thereby providing empirical support for improving macroprudential supervision and early-warning systems for financial risk. Full article

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19 pages, 413 KB

Open AccessArticle

Does Good Treatment Travel Downstream? Buyer Support and Responsible Governance in Multi-Tier Supply Chains

by Hyejin Cho and Pyoungsoo Lee

Systems 2026, 14(9), 1111; https://doi.org/10.3390/systems14091111 - 7 Sep 2026

Abstract

Sustainable supply-chain governance often depends on firms that occupy more than one relational role. A middle-tier firm may receive support from an upstream buyer while simultaneously governing its own subcontractors. This study examines whether support received from an upstream buyer is associated with [...] Read more.

Sustainable supply-chain governance often depends on firms that occupy more than one relational role. A middle-tier firm may receive support from an upstream buyer while simultaneously governing its own subcontractors. This study examines whether support received from an upstream buyer is associated with more responsible governance toward subcontractors, and whether buyer pressure is negatively associated with such governance. Using five waves of the Korean Workplace Panel Survey (2015–2023), we identify 574 dual-role firms, yielding 1134 firm-year observations. The results show that buyer support is positively associated with responsible subcontractor governance in both contemporaneous and next-wave models. Buyer pressure, by contrast, is negatively associated with subcontractor governance in contemporaneous models, but this association does not persist in next-wave specifications. These findings suggest that everyday relational treatment may matter beyond the immediate dyad. The study extends multi-tier sustainability research beyond the cascading of explicit standards by showing how relational experiences received by dual-role firms in upstream-facing relationships are associated with how those same firms govern downstream-facing subcontracting relationships. Full article

(This article belongs to the Special Issue Navigating Complexity in a Changing World: Challenges and Opportunities for Sustainable and Resilient Supply Chains)

29 pages, 1074 KB

Open AccessArticle

Business Ecosystem Embeddedness and SRDI SME Growth: The Roles of Organizational Resilience and Digital Leadership

by Baoshan Ge and Jiatong Li

Systems 2026, 14(9), 1110; https://doi.org/10.3390/systems14091110 - 7 Sep 2026

Abstract

Against the backdrop of intensifying geopolitical conflicts and deglobalization, how Specialized, Refined, Differentiated, and Innovative small and medium-sized enterprises (SRDI SMEs) can overcome resource constraints and achieve sustained growth has become an important research issue. Although prior research has recognized that business ecosystem [...] Read more.

Against the backdrop of intensifying geopolitical conflicts and deglobalization, how Specialized, Refined, Differentiated, and Innovative small and medium-sized enterprises (SRDI SMEs) can overcome resource constraints and achieve sustained growth has become an important research issue. Although prior research has recognized that business ecosystem embeddedness provides SMEs with access to external resources and growth opportunities, the mechanisms through which such embeddedness translates into the growth of SRDI SMEs in turbulent environments remain insufficiently understood. Drawing on resource orchestration theory, this study develops a theoretical model linking business ecosystem embeddedness to SRDI SME growth and examines the mediating roles of proactive organizational resilience and reactive organizational resilience, as well as the moderating role of digital leadership. Using two-wave survey data from 367 Chinese SRDI SMEs, this study tests the proposed hypotheses through regression analysis and bootstrapping. The results show that business ecosystem embeddedness is significantly and positively associated with SRDI SME growth and that proactive organizational resilience and reactive organizational resilience each partially mediate this relationship. Moreover, digital leadership strengthens the relationships between business ecosystem embeddedness and both dimensions of organizational resilience, thereby strengthening its indirect effects on SRDI SME growth through proactive organizational resilience and reactive organizational resilience. The findings provide theoretical insights and practical implications for SRDI SMEs seeking sustained growth in turbulent environments. Full article

(This article belongs to the Special Issue Strategic Management Towards Organisational Resilience (2nd Edition))

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35 pages, 7983 KB

Open AccessArticle

Coordinated Optimization of Inter-Hub eVTOL Feeder Services with Heterogeneous Passenger Behavior

by De Zhao, Runze Mou, Shengpeng You, Shaobin Huang, Dongmei Liu and Zhixiang Xu

Systems 2026, 14(9), 1109; https://doi.org/10.3390/systems14091109 - 7 Sep 2026

Abstract

Inter-hub feeder service is a promising application for electric vertical takeoff and landing aircraft (eVTOL), especially for passengers connecting to subsequent flights under tight time constraints. We develop an optimization framework that accounts for heterogeneous passenger behavior. Using stated-preference survey data, we incorporate [...] Read more.

Inter-hub feeder service is a promising application for electric vertical takeoff and landing aircraft (eVTOL), especially for passengers connecting to subsequent flights under tight time constraints. We develop an optimization framework that accounts for heterogeneous passenger behavior. Using stated-preference survey data, we incorporate delay-risk perception under remaining connection time constraints, identify heterogeneous preference classes, and formulate a bilevel optimization model. The upper level selects eVTOL schedules under given resource and fare configurations. The lower level captures the stochastic user equilibrium of heterogeneous passengers choosing among eVTOL and external transport alternatives. To solve the resulting mixed-integer nonlinear bilevel problem, we propose a Neural Bilevel Optimization and generalized Benders decomposition (Neur2BiLO-GBD) hybrid algorithm. Numerical experiments on the Shanghai Hongqiao–Pudong corridor show that the baseline profit-maximizing plan also generates positive social net utility for the feeder system. Fleet size, charging infrastructure, and fare affect operator profit and social net utility differently, so their high-value regions do not fully coincide. When external transport has larger potential delays and remaining connection time is short, eVTOL is more likely to achieve both high operator profit and high social net utility. Full article

(This article belongs to the Section Systems Engineering)

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38 pages, 523 KB

Open AccessArticle

Green Technology Transfer and Energy-Related Operational Port Carbon Emissions: Evidence from Listed Port Companies in China

by Can Liu, Min Zhao, Xiang Yan and Jie Wu

Systems 2026, 14(9), 1108; https://doi.org/10.3390/systems14091108 - 7 Sep 2026

Abstract

Against the background of resource constraints and the difficulty of independent green technology innovation, green technology transfer (GTT) provides an important pathway for listed port companies to reduce energy-related emissions from their operational activities and advance low-carbon transformation. Based on panel data from [...] Read more.

Against the background of resource constraints and the difficulty of independent green technology innovation, green technology transfer (GTT) provides an important pathway for listed port companies to reduce energy-related emissions from their operational activities and advance low-carbon transformation. Based on panel data from 19 listed Chinese port companies from 2011 to 2024, this paper examines the effect and mechanisms of GTT on energy-related operational port carbon emissions (EOPCE) from both theoretical and empirical perspectives. The results show that (1) GTT significantly reduces EOPCE, and this finding remains robust after a series of robustness and endogeneity tests. (2) Mediation analysis indicates that GTT reduces EOPCE by promoting a cleaner energy consumption structure and technological progress. (3) Moderation analysis shows that environmental regulation, regional innovation support, and port financial health significantly strengthen the negative effect of GTT on EOPCE, while no statistically significant moderating effect of port technology absorptive capacity is identified under the current sample and proxy measure. (4) Heterogeneity analysis reveals that the effect of GTT on EOPCE varies across port regions and digitalization levels. Full article

(This article belongs to the Special Issue Efficiency, Emissions, and Optimization in Sustainable Maritime Transport and Logistics Systems)

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33 pages, 1153 KB

Open AccessArticle

The Macroeconomic Effects of Strait of Hormuz Disruptions: Evidence on Trade, Inflation, and Exposure Heterogeneity

by Adil Zareef Khan, Cheng-Wen Lee and Ping-Hung Chen

Systems 2026, 14(9), 1107; https://doi.org/10.3390/systems14091107 - 7 Sep 2026

Abstract

This study examines whether and how disruptions in the Strait of Hormuz are associated with trade growth and inflation across countries with different levels of structural exposure. We construct a continuous Hormuz Disruption Index (HDX) from observable corridor stress indicators, including oil throughput, [...] Read more.

This study examines whether and how disruptions in the Strait of Hormuz are associated with trade growth and inflation across countries with different levels of structural exposure. We construct a continuous Hormuz Disruption Index (HDX) from observable corridor stress indicators, including oil throughput, vessel traffic, LNG flows, and tanker congestion, and combine it with a monthly panel of 60 countries covering January 2018–March 2026. To capture heterogeneous vulnerability, we develop a preferred exposure-only Hormuz Dependency Index (HDI) based on energy import dependence, Gulf oil exposure, trade openness, and energy intensity. At the same time, logistics performance and strategic reserve capacity are treated separately as resilience dimensions. The empirical analysis combines fixed effects models, exposure-based difference-in-differences estimation, and dynamic event study analysis. The results indicate that higher disruption intensity is associated with lower trade growth and higher inflation, with larger responses in more exposed economies. The channel evidence is consistent with transmission via oil price pressure and maritime logistics frictions. At the same time, stronger resilience capacity is associated with smaller adverse trade responses. Because the design is observational and the sample includes overlapping global shocks, the findings are interpreted as exposure-based associations rather than definitive causal estimates. This study contributes a corridor-specific framework for evaluating how geopolitical stress at a strategic maritime chokepoint may generate uneven macroeconomic consequences and highlights the potential value of energy diversification, logistics resilience, and strategic buffers. Full article

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20 pages, 625 KB

Open AccessArticle

Beyond Registration: The Formal Participation Trap in Rural Digital-Governance Systems

by Yan Song, Xintong Ji and Yifeng Zhang

Systems 2026, 14(9), 1106; https://doi.org/10.3390/systems14091106 - 7 Sep 2026

Abstract

Registration targets can be met even when citizens seldom return to a rural digital platform. This study interprets the registration-use gap as a possible behavioral manifestation of a formal participation trap. Use frequency captures engagement depth rather than citizens’ voice or influence over [...] Read more.

Registration targets can be met even when citizens seldom return to a rural digital platform. This study interprets the registration-use gap as a possible behavioral manifestation of a formal participation trap. Use frequency captures engagement depth rather than citizens’ voice or influence over platform decisions and services. The analysis uses a balanced panel of 336 rural households in Yantai, China, observed in 2023 and 2024, to relate household motivation and digital capability to platform use and perceived performance. Household fixed-effects estimates associate a one-standard-deviation increase in composite participation motivation with a 0.17-standard-deviation increase in perceived platform performance. Registered low-frequency users rate the platform 0.30 standard deviations lower than registered high-frequency users; neither registered group differs significantly from unregistered households. An all-category frequency gradient, covariate-balanced comparisons, and sensitivity analyses preserve the behavioral ordering. Because participation and evaluation may evolve jointly, the estimates are associational. Registration, repeated use, and user feedback should therefore be assessed separately. The numerical estimates are bound to the analytic panel; the analytically transferable contribution is a testable systems proposition that registration coverage is not a sufficient indicator of sustained engagement or user feedback. Full article

(This article belongs to the Special Issue Socio-Economic System Analysis: Urban, Regional and Industrial Perspectives)

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39 pages, 539 KB

Open AccessArticle

Analytical Framework for Professional Accounting Judgment in Recognizing Revenue from Contracts with Customers in the Context of Digitalization and Artificial Intelligence

by Kiril Luchkov and Nadya Velinova-Sokolova

Systems 2026, 14(9), 1105; https://doi.org/10.3390/systems14091105 - 7 Sep 2026

Abstract

This study develops an analytical framework for professional accounting judgment in recognizing revenue from contracts with customers in the context of digitalization and artificial intelligence. The research gap concerns the limited integration of specific IFRS 15 judgment areas, digitally assisted contract analysis, professional [...] Read more.

This study develops an analytical framework for professional accounting judgment in recognizing revenue from contracts with customers in the context of digitalization and artificial intelligence. The research gap concerns the limited integration of specific IFRS 15 judgment areas, digitally assisted contract analysis, professional approval, and control traceability. The framework is designed as a systems-based decision-support structure that links IFRS 15 criteria, relevant contractual terms and circumstances, technological support, professional accounting judgment, and audit traceability. It does not replace the standard’s five-step model. The methodological design comprises three components: normative analysis, structured illustrative scenario analysis, and a single-round exploratory expert-panel assessment. The illustrative scenarios are based on generalized recurring situations from Bulgarian accounting practice. The panel included 26 specialists in financial reporting, auditing, financial control, and accounting information systems. Responses were analyzed using descriptive statistics and complementary indicators of internal consistency and ranking concordance. The results indicate favorable evaluations of terminological compatibility with IFRS 15, alignment with the five-step model, and documentation of professional accounting judgment. Documentation received the highest mean score (4.77), whereas digitally assisted analysis (4.12) and the constraint on variable consideration (4.19) received more moderate scores. These results indicate that system-generated outputs require clear professional justification, approval, and a traceable control record. The scientific contribution is a four-component framework comprising normative, contractual-analytical, technological, and control levels. It organizes digitally assisted revenue recognition while keeping professional accounting judgment central. Full article

(This article belongs to the Special Issue Strategy and Digital Transformation in Accounting, Auditing, and Management)

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23 pages, 512 KB

Open AccessArticle

The Risk-Growth Tradeoff of Customer Concentration and Stability: When AI Orientation Matters

by Tianjiao Qi, Airong Zhang, Tao Hong and Xiaotong Huang

Systems 2026, 14(9), 1104; https://doi.org/10.3390/systems14091104 - 7 Sep 2026

Abstract

Although customer relationships are crucial to both firms’ growth potential and risk exposure, little is known about how customer concentration and stability differentially affect these outcomes. Drawing on resource dependence theory and technology affordance theory, this study explores the impact of these two [...] Read more.

Although customer relationships are crucial to both firms’ growth potential and risk exposure, little is known about how customer concentration and stability differentially affect these outcomes. Drawing on resource dependence theory and technology affordance theory, this study explores the impact of these two key features of customer relationships on the tradeoff between risk and growth, as well as the moderating role of artificial intelligence (AI) orientation. Using annual data from Chinese A-share listed companies between 2013 and 2024, we derive relationship measures from major customer disclosures, capture risk and long-term growth through stock volatility and cumulative sales growth, and measure AI orientation through textual analysis of annual reports. The results suggest that major customer concentration is associated with higher stock volatility but stronger sales growth, whereas major customer stability is related to lower volatility but weaker growth. AI orientation strengthens the volatility-reducing effect of stability and the growth-enhancing effect of concentration. These moderating effects are stronger among firms with weaker supply chain power. By integrating the cross-sectional distribution and temporal continuity of customer portfolios, we reveal the pronounced risk-growth tradeoff embedded in buyer-supplier relationships and also provide theoretical and practical insights into the differentiated value creation potential of AI orientation, thereby extending the literature related to technology affordance theory. Full article

(This article belongs to the Special Issue Artificial Intelligence and Big Data Strategies for Sustainable and Resilient Supply Chain Management)

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28 pages, 2437 KB

Open AccessArticle

Vehicle as a Service: Fuzzy Reward-Based Multi-Agent Deep Reinforcement Learning for Task Scheduling in Vehicular Edge Computing

by Qiangqiang Jiang, Jiamei Jin, Xu Xin, Kang Chen and Weiyou Guo

Systems 2026, 14(9), 1103; https://doi.org/10.3390/systems14091103 - 6 Sep 2026

Abstract

Under the vehicle as a service (VaaS) paradigm, intelligent connected vehicles continuously generate large-scale, computation-intensive perception data processing tasks. However, limited onboard computing resources and power supply prevent vehicles from handling these tasks efficiently. Vehicular edge computing (VEC) extends available computing resources through [...] Read more.

Under the vehicle as a service (VaaS) paradigm, intelligent connected vehicles continuously generate large-scale, computation-intensive perception data processing tasks. However, limited onboard computing resources and power supply prevent vehicles from handling these tasks efficiently. Vehicular edge computing (VEC) extends available computing resources through vehicle–infrastructure collaboration. Nevertheless, continuous vehicle mobility causes intermittent communication links between vehicles and roadside units, posing new challenges for VEC task scheduling. Therefore, this paper proposes a reinforcement learning-based VEC task scheduling approach that integrates a fuzzy reward mechanism with multi-agent proximal policy optimization (FRMPPO). First, a system architecture is developed by integrating the directed acyclic graph task model, dynamic communication model, and computation model. The scheduling problem is formulated as a partially observable Markov decision process, with the objective of minimizing task completion latency and vehicle energy consumption. Second, a fuzzy reward mechanism is designed to guide the training of multi-agent proximal policy optimization. It takes edge node load pressure and communication state as inputs to adaptively combine local immediate rewards and the global reward, eventually guiding the agents toward a globally optimized cooperative policy. Finally, real-time scheduling decisions under communication intermittency are enabled through a centralized training and decentralized execution framework and gated recurrent unit-based state encoding. Simulation results demonstrate that FRMPPO effectively solves the VEC task scheduling problem, achieving significantly superior performance over existing algorithms in terms of both task completion latency and vehicle energy consumption. The proposed method thereby satisfies the real-time processing demands of perception tasks in VaaS scenarios. Full article

(This article belongs to the Special Issue AI-Driven Spatiotemporal Computing in Complex Traffic Systems)

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33 pages, 4937 KB

Open AccessArticle

Forecasting Systemic Reconfiguration in Concentrated Global Supply Networks for Economic Resilience: A Systems-Theoretic Hypergraph-Structured Temporal Decision-Support Framework

by Jun Tian, Junru Si, Xuhua Qiu and Xu Jiang

Systems 2026, 14(9), 1102; https://doi.org/10.3390/systems14091102 - 5 Sep 2026

Abstract

Concentrated sourcing is a structural property of the world economy rather than an occasional accident: across 168 national economies and 1118 four-digit product markets reconstructed from harmonized cross-border flow records, 27.7% of macro-level economy–product supply systems draw more than half of their imports [...] Read more.

Concentrated sourcing is a structural property of the world economy rather than an occasional accident: across 168 national economies and 1118 four-digit product markets reconstructed from harmonized cross-border flow records, 27.7% of macro-level economy–product supply systems draw more than half of their imports from a single origin and 19.3% are critically dependent. Treating each such market as a system rather than as a set of bilateral links changes what can be asked of it, and this paper specifies the economy–product supply system in systems-engineering terms—boundary, elements, internal relations, external environment, state and state transition—and represents it as a time-evolving hyperedge over source countries. Three coupled questions follow, answered jointly by HyperSRM: which dependency state a system will occupy next year, whether it will diversify, reconcentrate, hold, or merely substitute one origin for another, and which origins are most consistent with the observed conditions preceding a material entry. Shared country and product embeddings support two temporal set-encoding branches, a candidate-conditioned branch for origin ranking and a candidate-free branch for state and mode forecasting, a sign-constrained gravity–capability–connectivity prior supplies an observational plausibility score with end use and maritime reachability as its context, and risk weights derived from the state head direct effort toward the most exposed systems. Developed on CEPII BACI, rebuilt independently on Eurostat Comext and audited against U.S. Census data at the level of the labels themselves, the framework returns calibrated state probabilities and a ten-origin shortlist that captures 58.1% of the following year’s risk-weighted material-entry mass and is accompanied by explicit out-of-pool diagnostics. These outputs describe the import-sourcing layer of resilience and are intended for analytical triage rather than a complete assessment of supply resilience. Three system-level regularities carry beyond the model: the arrival of a new origin is a weak proxy for diversification, critical dependency is close to absorbing for specified intermediate inputs but not for final goods, and the 2020–2021 contraction rearranged source sets without widening them—so resilience monitoring built on source counts misreads the direction of change. Full article

(This article belongs to the Special Issue Data-Driven Modeling and Predictive Analysis in Business, Social, Economic, Education, and Engineering Applications (2nd Edition))

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