Systems

38 pages, 10356 KB

Open AccessArticle

When Do Competing New Energy Vehicle Manufacturers Cooperate Under Supply Disruption Risk? Emergency Procurement, Conversion Costs, and Market Outcomes

by Beile Feng, Wentao Zhan, Chencan Lin, Peilun Sun, Yitong Zhao and Minghui Jiang

Systems 2026, 14(8), 1034; https://doi.org/10.3390/systems14081034 - 21 Aug 2026

Viewed by 226

Abstract

Amid increasing upstream raw-material disruptions and battery supply uncertainty, NEV manufacturers may obtain emergency supply from vertically integrated competitors after a disruption, but must incur technology conversion costs. We develop a differentiated Cournot duopoly model with an outsourcing manufacturer and an integrated manufacturer [...] Read more.

Amid increasing upstream raw-material disruptions and battery supply uncertainty, NEV manufacturers may obtain emergency supply from vertically integrated competitors after a disruption, but must incur technology conversion costs. We develop a differentiated Cournot duopoly model with an outsourcing manufacturer and an integrated manufacturer to compare equilibrium, profit, and welfare outcomes with and without emergency procurement cooperation. The results show that cooperation has a clear feasibility boundary jointly determined by market potential, relative costs, and conversion costs, giving rise to competition-only, cooperation-only, and coopetition regimes. The cooperation option reshapes pre-disruption quantity decisions: the outsourcing manufacturer increases regular procurement, while the integrated manufacturer reduces its own-brand output by a larger amount. Within the cooperation region, higher conversion costs continuously reduce the outsourcing manufacturer’s profit, whereas the integrated manufacturer’s profit can be U-shaped. Greater product substitutability makes cooperation more fragile and widens the divergence between private profit incentives and supply-chain resilience. Consumer surplus and social welfare may also move in different directions, depending on the outsourcing manufacturer’s benchmark market share and conversion cost. A Nash-bargaining extension confirms the robustness of the activation condition and pre-disruption quantity-adjustment mechanism, while reducing emergency markups and improving consumer surplus. Full article

(This article belongs to the Section Supply Chain Management)

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26 pages, 6091 KB

Open AccessArticle

Evaluation of Green Strategies for Inland Vessels and Government Subsidy Policies by Evolutionary Game Model

by Yong-Bo Ji, De-Chang Li, Wei Song, Yi Luo, Li-Peng Wang, Da-Zhuang Liu, Kun Li, Fang-Fang Jiao and Hua-Long Yang

Systems 2026, 14(8), 1033; https://doi.org/10.3390/systems14081033 - 21 Aug 2026

Viewed by 185

Abstract

Environmental sustainability has become an increasingly critical issue in the inland shipping sector. The adoption of green-fuelled vessels, data-driven speed optimization enabled by digital and intelligent technologies, and the use of shore power during berthing can substantially reduce harmful emissions from shipping activities [...] Read more.

Environmental sustainability has become an increasingly critical issue in the inland shipping sector. The adoption of green-fuelled vessels, data-driven speed optimization enabled by digital and intelligent technologies, and the use of shore power during berthing can substantially reduce harmful emissions from shipping activities and enhance environmental performance. This study investigates the evolutionary stable strategy (ESS) of inland shipowners’ green initiatives under government subsidy schemes. Firstly, a decision-making framework is developed by incorporating price elasticity, market competition, green investment, and subsidy intensity, through which pricing, subsidies, demand, and profit decisions are jointly modeled. Secondly, a game-theoretic model involving two market participants under three alternative strategies is constructed, together with an effective solution approach. Thirdly, based on evolutionary game theory, the equilibrium strategies ultimately adopted by the majority of inland shipowners are derived, and sensitivity analyses of key parameters are conducted. The results indicate that: (1) shipowners implementing green strategies can achieve higher economic returns, and green strategies are expected to be adopted by approximately 71.55% of inland shipowners in the long-term; (2) governments should increase subsidy intensity in the early stage of green strategy development, while gradually reducing subsidies once the market reaches a stable equilibrium. The findings provide theoretical insights for inland shipowners’ strategic decisions in environmentally conscious markets and offer policy implications for governments seeking to design stable and effective subsidy mechanisms to promote the green transition of inland shipping services. Full article

(This article belongs to the Section Supply Chain Management)

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21 pages, 444 KB

Open AccessArticle

How Digital Orientation Promotes Technology Standard Innovation: The Serial Mediating Role of Organizational Unlearning and Knowledge Re-Orchestration

by Hong Jiang, Chen Chen and Ye Yuan

Systems 2026, 14(8), 1032; https://doi.org/10.3390/systems14081032 - 21 Aug 2026

Viewed by 299

Abstract

Against the backdrop of digital transformation, enterprises take digital orientation as a strategic foundation and compete for standard-setting authority to gain core competitive advantages. Although prior research indicates that digital orientation positively influences innovation, research on how digital orientation affects technology standard innovation [...] Read more.

Against the backdrop of digital transformation, enterprises take digital orientation as a strategic foundation and compete for standard-setting authority to gain core competitive advantages. Although prior research indicates that digital orientation positively influences innovation, research on how digital orientation affects technology standard innovation remains limited. Technology standard innovation under digital practices is more complex and knowledge-intensive than that in the traditional industrial era. The mechanism by which digital orientation drives technology standard innovation requires more attention. Drawing upon strategic management theory and resource orchestration theory, this study proposes a serial mediation model to reveal how digital orientation influences technology standard innovation. We collected survey data from 480 Chinese enterprises via questionnaires and tested the model using partial least squares structural equation modeling. The results indicated that digital orientation has a significant positive impact on technology standard innovation; organizational unlearning and knowledge re-orchestration play a serial mediating role in this relationship; and knowledge inertia negatively moderates the relationship between organizational unlearning and knowledge re-orchestration. This study offers insights for traditional enterprises establishing efficient organizational change and knowledge management mechanisms to gain standard influence and innovation benefits. Full article

(This article belongs to the Section Complex Systems and Cybernetics)

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19 pages, 849 KB

Open AccessArticle

Invisible Paradigms: A Critical Realist Analysis of Ontological, Epistemological, and Axiological Positioning in Three Engineering Education Research Journals

by Margaret A. L. Blackie and Jennifer M. Case

Systems 2026, 14(8), 1031; https://doi.org/10.3390/systems14081031 - 21 Aug 2026

Viewed by 278

Abstract

Engineering education research (EER) draws on a wide range of philosophical traditions, yet the ontological, epistemological, and axiological (OEA) commitments that shape how knowledge is produced are rarely made explicit in published work. This study investigated the prevalence and nature of OEA positioning [...] Read more.

Engineering education research (EER) draws on a wide range of philosophical traditions, yet the ontological, epistemological, and axiological (OEA) commitments that shape how knowledge is produced are rarely made explicit in published work. This study investigated the prevalence and nature of OEA positioning across a purposive sample of 54 papers published in 2024 in three Q1 engineering education journals: the Journal of Engineering Education, the European Journal of Engineering Education, and the Australasian Journal of Engineering Education. Using critical realism as a metatheoretical framework, we developed an OEA coding instrument and applied it through an AI-assisted abductive coding process, assigning ontological, epistemological, and two-level axiological codes to each paper and assessing their internal coherence. The overwhelming majority of papers carry implicit rather than declared OEA commitments, a pattern consistent across journals and methodologies. The field is genuinely philosophically plural, with ontological positions ranging from naïve realism to social constructionism and critical realism, but the lack of clarity in this space potentially has consequences for knowledge transfer to practice, cumulative knowledge-building, and the coherence of individual studies. Full article

(This article belongs to the Special Issue Sociotechnical Systems in Engineering Education)

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21 pages, 2701 KB

Open AccessArticle

How Travel-Scenario Factors Shape the Substitution of Ride-Hailing Services by “Metro+” MaaS Intermodal Trips: Evidence from Beijing MaaS

by Yan Xu, Chen Gao, Xiang-Long Liu, Xiang-Jing Li and Chang Wang

Systems 2026, 14(8), 1030; https://doi.org/10.3390/systems14081030 - 21 Aug 2026

Viewed by 297

Abstract

Mobility as a service (MaaS) has emerged as a means to promote multimodal public transport and shared mobility trips, with the “Metro+” integrated mobility approach being its primary form. However, it has recently witnessed major global providers’ bankruptcies. Therefore, this study aims to [...] Read more.

Mobility as a service (MaaS) has emerged as a means to promote multimodal public transport and shared mobility trips, with the “Metro+” integrated mobility approach being its primary form. However, it has recently witnessed major global providers’ bankruptcies. Therefore, this study aims to identify factors driving users’ substitution of ride-hailing by “Metro+” MaaS intermodal trips. Specifically, we took ride-hailing trips as the baseline and constructed a multinomial logit (MNL) model incorporating travel-scenario factors, including trip purpose, weather, and urgency. The results show that travel-scenario factors significantly affected “Metro+” MaaS intermodal trip adoption for urban medium–long-distance trips. Users preferred MaaS intermodal trips for long-distance trips amid clear weather and no time pressure, and they favored ride-hailing in extreme weather conditions or for time-sensitive trips. Therefore, MaaS providers should emphasize travel scenarios in their marketing messaging. Finally, marginal rate of substitution (MRS) and elasticity analyses were conducted, and several strategies were proposed: (1) increasing ride-hailing availability; (2) improving transfer facilities and conditions; and (3) implementing dynamic demand matching. The study facilitates the identification of market opportunities for MaaS instead of car usage, contributes to MaaS marketing and service strategy optimization, and promotes sustainable urban transportation system development. Full article

(This article belongs to the Special Issue Sustainable Urban Transport Systems)

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26 pages, 3940 KB

Open AccessArticle

An Event-Driven and Feasibility-Audited Decision-Support Framework for Dynamic Rescheduling of Inland Container Depot Truck Operations

by Shucheng Fan and Shaochuan Fu

Systems 2026, 14(8), 1029; https://doi.org/10.3390/systems14081029 - 20 Aug 2026

Viewed by 331

Abstract

Inland container depot (ICD) truck schedules must absorb new orders, service delays, appointment changes, congestion, and port cut-offs without destabilizing an already executed plan. This study asks whether event-triggered local repair can be separated into an explicit business-rule audit and a learned ranking [...] Read more.

Inland container depot (ICD) truck schedules must absorb new orders, service delays, appointment changes, congestion, and port cut-offs without destabilizing an already executed plan. This study asks whether event-triggered local repair can be separated into an explicit business-rule audit and a learned ranking of feasible task–vehicle actions. The proposed decision-support framework connects a static baseline, candidate task chains, six modeled hard-feasibility predicates, a Transformer encoder trained with proximal policy optimization (Transformer-PPO), and discrete-event execution logs. A five-seed, 120-episode confirmation gave Transformer-PPO a held-out online completion proxy (α_online) of 0.3226 and reward of 110.58, compared with 0.2581 and 61.87 for the matched multilayer perceptron (MLP); deterministic rules and search remained competitive. An independent audit of 4,968,000 action cells across 552 decision states found no disagreement with an independently coded oracle for the implemented hard predicates, while a reward-weight screen exposed the expected efficiency-stability trade-off. Together with a rolling-horizon comparator and a three-scale by three-disturbance stress test, the evidence supports an auditable system-integration contribution, not a new generic reinforcement learning (RL) algorithm or universal performance superiority. Claims are limited to synthetic simulation-based decision support. Full article

(This article belongs to the Section Systems Engineering)

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29 pages, 392 KB

Open AccessArticle

Consumers as the Demand-Side Buffer of Sustainable Supply Chains: The Formation and Boundary Conditions of Resilient Consumption Through Perceived ESG Legitimacy

by Sunghee Lee and Jinsoo Park

Systems 2026, 14(8), 1028; https://doi.org/10.3390/systems14081028 - 20 Aug 2026

Viewed by 283

Abstract

Sustainable supply chains carry a cost premium that can make their demand base fragile when economic shocks tighten household budgets, because the more expensive environmental, social, and governance (ESG)-aligned product is often among the first that consumers forgo. We propose extending resilience thinking [...] Read more.

Sustainable supply chains carry a cost premium that can make their demand base fragile when economic shocks tighten household budgets, because the more expensive environmental, social, and governance (ESG)-aligned product is often among the first that consumers forgo. We propose extending resilience thinking to the downstream, demand-side node of the supply chain: we frame premium-tolerant ESG consumption as a conceptual indicator of demand-side resilience—an absorptive buffer that may help keep sustainable supply chains viable through disturbance—and draw on signaling theory to model how it is formed. Using a nationally structured, quota-controlled survey of 3000 Korean consumers collected by the Korea Consumer Agency, we estimate a moderated-mediation structural equation model in which ESG signal trust is associated with resilient sustainable consumption through perceived ESG legitimacy, conditioned by income and perceived greenwashing. Because the data are cross-sectional, we report associations rather than causal effects. Trust was positively associated with perceived legitimacy, which in turn was associated with resilient sustainable consumption, so that legitimacy is the proximal correlate linking trust to resilience. Income moderated this conversion only modestly—the sustainability–resilience trade-off is statistically present but small in magnitude—while perceived greenwashing did not attenuate it, and its unexpected positive coefficient proved unstable across specifications and is not interpreted. A multi-group comparison indicated that the pattern of associations differs with the perceived credibility of the ESG signal environment: when third-party signals were perceived as credible, the trust–legitimacy–consumption route was more pronounced, whereas when they were not, trust was associated with consumption more directly. Consumers also expected ESG far more of large firms than of micro-enterprises. No supply-chain-level outcome was measured; the cross-level link is advanced as a proposition for future work. The study reframes supply chain resilience as partly demand-side, potentially sustained by credible, independently verified ESG signals rather than by firms’ own disclosure. Full article

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

24 pages, 528 KB

Open AccessArticle

Digital Transformation, Organizational Learning, and Supply Chain Resilience: An fsQCA Analysis

by Chen Yang, Qian Yang and Yi Lu

Systems 2026, 14(8), 1027; https://doi.org/10.3390/systems14081027 - 20 Aug 2026

Viewed by 369

Abstract

Global supply chains face increasingly frequent disruptions, which require organizations to strengthen supply chain resilience (SCR). Drawing on Organizational Information Processing Theory (OIPT), this study examines how digital transformation and organizational learning combine to enhance SCR. Using data from 61 Chinese high-technology firms, [...] Read more.

Global supply chains face increasingly frequent disruptions, which require organizations to strengthen supply chain resilience (SCR). Drawing on Organizational Information Processing Theory (OIPT), this study examines how digital transformation and organizational learning combine to enhance SCR. Using data from 61 Chinese high-technology firms, fuzzy-set qualitative comparative analysis (fsQCA) identifies two pathways to high SCR. The first is an ambidextrous learning-driven pathway. Exploitative and exploratory learning jointly help firms refine existing routines and develop adaptive responses to disruption-induced uncertainty. The second is a digitally driven pathway. Digital strategic planning and digital ecosystem coordination help firms structure disruption-related information and coordinate responses across supply chain partners. The configurations for non-high SCR further show that exploratory learning is important for interpreting unfamiliar signals and generating adaptive responses. These findings extend OIPT by showing that SCR emerges from distinct forms of fit between information processing requirements and organizational capabilities. They therefore provide a configurational explanation of resilience formation under uncertainty. Full article

(This article belongs to the Special Issue Supply Chain and Business Model Innovation in the Digital Era)

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25 pages, 849 KB

Open AccessArticle

When Does Sustainability Translate into Supply Chain Logistics Performance? The Moderating Role of National Digital-Technological Readiness

by Jeong Hyun Park, Sang Won Yoon and Seung Jun Lee

Systems 2026, 14(8), 1026; https://doi.org/10.3390/systems14081026 - 20 Aug 2026

Viewed by 278

Abstract

This study examines whether national digital technological readiness moderates the relationship between national sustainability performance and supply chain logistics performance. Using a panel of 157 countries across six biennial waves from 2010 to 2023 (N = 850), with every predictor measured two years [...] Read more.

This study examines whether national digital technological readiness moderates the relationship between national sustainability performance and supply chain logistics performance. Using a panel of 157 countries across six biennial waves from 2010 to 2023 (N = 850), with every predictor measured two years before the wave it explains, drawn from the World Bank Logistics Performance Index (LPI), the World Bank Sovereign ESG indicators, and the UNCTAD Frontier Technology Readiness Index (FTRI), we estimate a hybrid within-between panel model that separates durable cross-country differences from within-country change, with sustainability performance measured through three separately constructed environmental, social, and governance dimensions. Sustainability performance relates positively to logistics performance between countries, and the association strengthens with readiness. The association becomes statistically significant only above a readiness threshold on the FTRI scale, below which every low-income country in the sample falls. The moderating effect is driven by the social and governance dimensions rather than the environmental dimension. It operates on the sub-dimensions that domestic institutions govern, most notably customs and infrastructure, while disappearing for international shipping. The between-country interaction remains stable across alternative moderator definitions, alternative measure constructions, an expanded control set, and a permutation placebo test. This moderation follows the continuous level of readiness rather than income group boundaries. Grounded in Dynamic Capabilities Theory, the findings suggest that digital readiness functions as the capability through which sustainability investments translate into realized logistics performance, and they locate a readiness threshold with direct implications for the sequencing of development policy. Full article

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

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19 pages, 1298 KB

Open AccessArticle

Information Sharing and Green Innovation in a Low-Carbon Platform Supply Chain Under Cap-and-Trade

by Guojun Ji and Jie Qin

Systems 2026, 14(8), 1025; https://doi.org/10.3390/systems14081025 - 19 Aug 2026

Viewed by 264

Abstract

This study develops a game-theoretic model of a platform-led supply chain in which a manufacturer invests in green innovation under a cap-and-trade regulation. We examine how three information-sharing strategies—no sharing (NI), free sharing (FI), and paid sharing (TI)—affect the manufacturer’s green innovation level, [...] Read more.

This study develops a game-theoretic model of a platform-led supply chain in which a manufacturer invests in green innovation under a cap-and-trade regulation. We examine how three information-sharing strategies—no sharing (NI), free sharing (FI), and paid sharing (TI)—affect the manufacturer’s green innovation level, both firms’ profits, and total supply chain carbon emissions. Our analysis reveals that the effect of information sharing is state-dependent: when the realized market potential exceeds its prior expectation, sharing stimulates green innovation, raises platform profit, and reduces emissions; when demand falls below expectations, the opposite holds. For the platform, paid sharing delivers the highest expected profit by extracting the full value of demand information. Furthermore, the emission-reducing effect of information sharing outweighs the demand expansion effect under favorable demand conditions, leading to a net decrease in total carbon emissions. These results underscore the governance role of demand information in aligning economic and environmental goals in platform supply chains, and they offer actionable guidance for managers and policymakers. Full article

(This article belongs to the Special Issue Supply Chain Management towards Circular Economy)

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24 pages, 601 KB

Open AccessArticle

The Constraints of Domain Familiarity: AI Stars, Knowledge Diversity, and Breakthrough Innovation

by Xiao Li, Sheng Lin, Xianglan Chi, Jinmeng Yu and Jinlan Liu

Systems 2026, 14(8), 1024; https://doi.org/10.3390/systems14081024 - 19 Aug 2026

Viewed by 444

Abstract

While artificial intelligence (AI) is expected to drive paradigm-shifting transformations, many initiatives result in merely incremental optimization. Anchored in strategic human capital theory, this study shifts the analytical focus from the scale of elite technical talent, conceptualized as AI stars, to the configuration [...] Read more.

While artificial intelligence (AI) is expected to drive paradigm-shifting transformations, many initiatives result in merely incremental optimization. Anchored in strategic human capital theory, this study shifts the analytical focus from the scale of elite technical talent, conceptualized as AI stars, to the configuration of their knowledge structures to unpack this paradox. Using a dataset of 1270 medical AI patents from corporate R&D teams, we employed high-dimensional fixed-effects models to examine these dynamics. The results reveal that while the knowledge diversity of AI stars acts as a potent engine for breakthrough innovation, this generative capacity is attenuated by excessive domain familiarity. Specifically, direct domain familiarity (derived from internal experience) and indirect domain familiarity (absorbed through external collaborative networks) negatively moderate this relationship, a dynamic theorized to operate through internal cognitive entrenchment and external relational conformity, respectively. Extending the efficiency-driven consensus regarding bilingual expertise, these findings demonstrate that excessive domain embeddedness transforms from an informational bridge into a restrictive constraint during paradigm-shifting innovations, particularly within highly institutionalized environments. Full article

(This article belongs to the Topic Recent Applications of Artificial Intelligence in Economy and Society)

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32 pages, 3986 KB

Open AccessArticle

Development of a Cash Flow Growth Pathway Model for Predicting Lifecycle Transitions in Software SMEs

by Seong-Jun Hwang, Jong-Yi Hong and Kyung-Bo Park

Systems 2026, 14(8), 1023; https://doi.org/10.3390/systems14081023 - 19 Aug 2026

Viewed by 270

Abstract

This study develops a cash flow growth pathway model to analyze and predict the dynamic and nonlinear lifecycle trajectories of software SMEs. Specifically, it identifies lifecycle stages using cash flow patterns, maps transition pathways empirically, and develops a forecasting framework to predict subsequent [...] Read more.

This study develops a cash flow growth pathway model to analyze and predict the dynamic and nonlinear lifecycle trajectories of software SMEs. Specifically, it identifies lifecycle stages using cash flow patterns, maps transition pathways empirically, and develops a forecasting framework to predict subsequent lifecycle states using prior-period financial information. By extending the conventional lifecycle framework, the model captures heterogeneity within transitional and contractionary phases, which are particularly relevant in the software industry. The results show that cash flow-based lifecycle scoring is economically meaningful and significantly distinguishes high- and low-growth firms. Moreover, the transition pathway analysis indicates that firm development is not strictly sequential. Firms exhibit downward transitions and meaningful recovery pathways, in addition to strong persistence in expansionary stages. In the forecasting analysis, predictive performance varies substantially across alternative models and class-imbalance treatments. Resampling-based models consistently outperform those estimated on the original dataset, indicating that class imbalance is a critical issue in lifecycle prediction. Among the alternative specifications, the best-performing model achieves strong predictive performance, suggesting that prior-period lifecycle states and financial characteristics contain meaningful forward-looking information. This study contributes to the literature by combining lifecycle theory, cash flow analysis, pathway modeling, and predictive analytics within a unified framework. It also offers practical implications for managers, investors, and policymakers by providing a preliminary basis for monitoring transition-related risks and identifying firms with recovery potential in the software sector. Full article

(This article belongs to the Special Issue Digital Innovation and Business Model Transformation in Small- and Medium-Sized Enterprises)

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40 pages, 3823 KB

Open AccessArticle

Systems Modeling and Numerical Simulation of Financial Reporting Oversight Mechanisms

by Dongjie Lin

Systems 2026, 14(8), 1022; https://doi.org/10.3390/systems14081022 - 19 Aug 2026

Viewed by 327

Abstract

Financial reporting oversight evolves through repeated feedback among managerial incentives, audit detection, board oversight, regulatory intervention, and market trust. I develop a transparent recursive simulation model to examine whether specified mechanism combinations can generate distinguishable governance trajectories within its rules. Monte Carlo simulations [...] Read more.

Financial reporting oversight evolves through repeated feedback among managerial incentives, audit detection, board oversight, regulatory intervention, and market trust. I develop a transparent recursive simulation model to examine whether specified mechanism combinations can generate distinguishable governance trajectories within its rules. Monte Carlo simulations compare institutional scenarios, supported by analyses of uncertainty, alternative model designs, heterogeneous conditions, and a learning-agent extension. Within the simulations, high-transparency coordination generally produces the strongest governance outcomes, whereas weak governance remains consistently least favorable across the uncertainty analyses. In the model, governance improvement depends on interactions among disclosure, audit, regulation, and market feedback. In the learning-agent extension, learned policies yield less favorable governance and reporting outcomes than the fixed-policy benchmark. Chinese A-share evidence is broadly consistent with the main simulated patterns in direction, risk location, and broad ordering. These findings provide mechanism-sufficiency evidence within the declared rule family and explain how oversight signals become institutional outcomes and subsequent feedback. Full article

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

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28 pages, 3594 KB

Open AccessArticle

Uncertainty-Aware Source Apportionment of Soil Heavy Metals in a Coal–Steel Industrial Zone Using Inter-Metal Graph-Informed Dirichlet Neural Posterior Estimation

by Ahmet Altın, Bekir Fatih Kahraman, Yasin Özkan, Aytaç Altan and Yusuf Bahri Özçelik

Systems 2026, 14(8), 1021; https://doi.org/10.3390/systems14081021 - 18 Aug 2026

Viewed by 477

Abstract

Industrialization and mining raise the heavy metal burden of soil ecosystems and create risks for both the environment and human health. Apportionment becomes difficult when neighboring facilities emit overlapping metal signatures, and conventional receptor models compound the difficulty by returning contribution shares without [...] Read more.

Industrialization and mining raise the heavy metal burden of soil ecosystems and create risks for both the environment and human health. Apportionment becomes difficult when neighboring facilities emit overlapping metal signatures, and conventional receptor models compound the difficulty by returning contribution shares without an attached uncertainty statement. This study develops a probabilistic apportionment framework for the coal–steel industrial zone of Zonguldak, Turkey, using 93 georeferenced topsoil stations and eight priority metals. Graphical Lasso estimates a sparse conditional dependency graph whose nodes are the measured metals; fixed propagation over that graph expands each observation into a 24-dimensional relational representation; and a Dirichlet neural posterior estimator maps the representation to source contribution distributions. The Dirichlet parameterization enforces non-negativity and unit sum by construction and delivers 95% credible intervals at every station; empirical coverage on held-out simulations was 0.957 against a nominal 0.95. Averaged across the province, posterior mean contributions were 0.25 for the iron-and-steel sector, 0.25 for thermal power generation, and 0.50 for a composite residual class that combines geogenic background with unmodelled anthropogenic inputs. The two industrial signals concentrate around Ereğli and Çatalağzı, while the residual class dominates elsewhere. The graph employed here encodes chemical relationships among metals and not geographical relationships among stations; maps of the posterior estimates are reported as post hoc visualizations. The framework is offered as an uncertainty-aware methodological contribution, and comparison against established receptor models remains to be carried out. Full article

(This article belongs to the Section Artificial Intelligence and Digital Systems Engineering)

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21 pages, 6245 KB

Open AccessArticle

Enhancing Design Creativity Through Embodied Platforms: An Exploratory Study Comparing Desktop, Mixed Reality, and Virtual Reality in Design Education

by Wenjuan Wang, Zhaolin Lu, Siqi Yu, Haonan Yao, Fuqi Xie, Lingyun Yu and Yue Zhang

Systems 2026, 14(8), 1020; https://doi.org/10.3390/systems14081020 - 18 Aug 2026

Viewed by 231

Abstract

Design education places strong emphasis on fostering students’ creativity, and the rapid development of embodied immersive technologies presents new opportunities in this regard. This exploratory study recruits 34 university students with different levels of expertise (17 novices and 17 experienced learners). Each participant [...] Read more.

Design education places strong emphasis on fostering students’ creativity, and the rapid development of embodied immersive technologies presents new opportunities in this regard. This exploratory study recruits 34 university students with different levels of expertise (17 novices and 17 experienced learners). Each participant completes a 3D conceptual design task using three design platforms with varying levels of embodiment: desktop, Mixed Reality (MR), and Virtual Reality (VR). Data on self-reported sense of embodiment, design creativity, and behavioral patterns are collected and analyzed. The results suggest that the VR platform, which provides the highest level of embodiment, is associated with significantly higher overall creativity as well as six creativity dimensions: fluency, flexibility, elaboration, originality, aesthetics, and requirement fulfillment. In addition, students using the VR platform exhibit more frequent and interconnected transitions between design behaviors, suggesting more exploratory and flexible design processes. No significant interaction is observed between design platform and expertise level in the present sample, suggesting that the effects of platform embodiment are broadly similar for novice and experienced learners. Based on these findings, this study proposes action-based metaphor and contextual consistency as potential explanatory factors that may contribute to creativity enhancement in highly embodied design platforms. Practical implications are discussed from the perspectives of platform design, learner differences, and pedagogical strategies. Overall, this exploratory study provides preliminary empirical evidence for understanding how embodied design platforms may support creativity in immersive design education and offers a foundation for future research. Full article

(This article belongs to the Special Issue Emergent Interdisciplinary STEM Education Systems: XR and Applied AI Perspectives)

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21 pages, 2188 KB

Open AccessArticle

Automated License Plate Readers and Data Centers as Networked Mass Surveillance Infrastructure: The Systemic Erosion of Privacy and Free Expression

by Haris Alibašić

Systems 2026, 14(8), 1019; https://doi.org/10.3390/systems14081019 - 18 Aug 2026

Viewed by 903

Abstract

Automated license plate readers (ALPRs) are often evaluated as discrete police tools, although their public power arises from cross-vendor socio-technical infrastructure. This article examines roadside and mobile sensors, vehicle-attribute classification, cloud archives, commercial databases, real-time crime center integration, interagency access, automated alerts, and [...] Read more.

Automated license plate readers (ALPRs) are often evaluated as discrete police tools, although their public power arises from cross-vendor socio-technical infrastructure. This article examines roadside and mobile sensors, vehicle-attribute classification, cloud archives, commercial databases, real-time crime center integration, interagency access, automated alerts, and police action. Flock Safety supplies the principal documentary case because unusually extensive public records permit system-level tracing; Axon/Fusus, Motorola Vigilant/VehicleManager, and federal access to commercial ALPR data establish the wider vendor-independent boundary. A structured documentary analysis of 59 sources triangulates official records, peer-reviewed research, vendor materials used only for stated functions, and record-based investigations. It integrates boundary critique, control-structure mapping, feedback analysis, constitutional doctrine, a STRIDE-informed threat model, and empirical research on policing effectiveness and surveillance effects through 3 August 2026. The analysis identifies four conditional mechanisms: infrastructure aggregation, authority diffusion, asymmetric feedback, and rights invisibility. The article reformulates the Rights Control Deficit (RCD) as a non-arithmetic profile relation between operational demands and effective governance capacity and applies it to three documented configurations and a clearly labeled normative benchmark. Seven falsifiable propositions specify variables, indicators, suitable methods, and disconfirming conditions for later empirical study. A rights-preserving hybrid-intelligence architecture combines bounded automation with judicial authorization, short retention, sensitive-location protections, immutable audit, availability safeguards, independent review, contestability, sanctions, and credible termination authority. The evidence identifies capabilities, activated pathways, and conditional risks; it does not estimate population prevalence or a universal ALPR-specific causal effect. Meaningful human oversight is an institutional control property, not merely an officer’s presence at an interface. Full article

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26 pages, 937 KB

Open AccessArticle

Determinants of Machine Learning Project Success: A Structural Equation Modeling Study of the Machine Learning Canvas

by Martin Prause

Systems 2026, 14(8), 1018; https://doi.org/10.3390/systems14081018 - 18 Aug 2026

Viewed by 276

Abstract

Machine learning (ML) project outcomes emerge from the interplay of organizational and technical subsystems. A recent study of 65 experienced data scientists reported that more than 80% of AI projects failed, roughly twice the failure rate of traditional IT projects, even as AI [...] Read more.

Machine learning (ML) project outcomes emerge from the interplay of organizational and technical subsystems. A recent study of 65 experienced data scientists reported that more than 80% of AI projects failed, roughly twice the failure rate of traditional IT projects, even as AI coding assistants can accelerate implementation work. This study develops and empirically evaluates the Machine Learning Canvas (MLC), a project-level sociotechnical framework that integrates business strategy, software engineering, and data science in four interdependent dimensions: Strategy, Process, Ecosystem, and Support. Its novelty lies in connecting these organizational and technical dimensions in one measurement and structural model rather than treating business alignment, workflow, and infrastructure as separate concerns. Seven theory-derived hypotheses were tested with covariance-based structural equation modeling using survey data from 150 respondents who reported daily use of AI coding assistants. The results support a sequential association from Support through Strategy and Process to Ecosystem; Strategy and Ecosystem also show positive direct associations with perceived project success, whereas the Process–Success coefficient is negative after the other dimensions are controlled. The overall model fit is good. The findings position ML project success as a property of the sociotechnical system rather than coding productivity alone and present the MLC as a diagnostic and planning instrument. Because the outcome is perceived success and the sample is narrow, the findings do not establish causal effects or universal applicability. Full article

(This article belongs to the Section Artificial Intelligence and Digital Systems Engineering)

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21 pages, 1496 KB

Open AccessArticle

A Systems-Informed Assessment of Türkiye’s Digital, Human-Capability, and Innovation Enablers for Industry 5.0 Relative to the EU-27: An Integrated CRITIC–MARCOS and Entropy–TOPSIS Approach

by Alaeddin Koska

Systems 2026, 14(8), 1017; https://doi.org/10.3390/systems14081017 - 18 Aug 2026

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Abstract

Industry 5.0 reframes industrial transformation as a human-centric, sustainable and resilient socio-technical transition. Yet comparable country-level evidence on the capabilities that enable this transition remains limited, particularly for late-digitalizing economies. This study benchmarks Türkiye against the 27 European Union member states using a [...] Read more.

Industry 5.0 reframes industrial transformation as a human-centric, sustainable and resilient socio-technical transition. Yet comparable country-level evidence on the capabilities that enable this transition remains limited, particularly for late-digitalizing economies. This study benchmarks Türkiye against the 27 European Union member states using a systems-informed multi-criteria decision-making framework. Seven indicators represent three complementary capability domains: enterprise digitalization (artificial intelligence, cloud computing, data analytics and enterprise resource planning), human capability (basic or above-basic digital skills) and innovation capacity (R&D expenditure and high-technology exports). CRITIC–MARCOS is used as the primary model, while the full 2 × 2 combination of CRITIC and Entropy weighting with MARCOS and TOPSIS ranking, equal-domain weighting and indicator-exclusion tests assess sensitivity. Türkiye ranks 28th under CRITIC–MARCOS and remains between 26th and 28th across the principal specifications. Pairwise rank correlations range from 0.932 to 0.981, supporting the stability of Türkiye’s placement in the lower-readiness group despite variation in its exact rank across methods. Türkiye is below the unweighted EU-27 country mean for all indicators, with its largest relative shortfall in high-technology exports. The findings diagnose a structural gap in the digital, human-capability and innovation enablers of Industry 5.0; they do not measure the complete Industry 5.0 construct, particularly its direct human-centric, sustainability and resilience outcomes. Full article

(This article belongs to the Section Supply Chain Management)

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33 pages, 13386 KB

Open AccessArticle

Nonlinear Correlation Between Urban Common Prosperity and Healthy Development: A Multi-Source Big Data-Based System Analysis

by Yi Ge and Honggang Xue

Systems 2026, 14(8), 1016; https://doi.org/10.3390/systems14081016 - 18 Aug 2026

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Abstract

China pushes forward two key national strategies, namely common prosperity and Healthy China. Many papers have discussed how urban common prosperity and urban healthy development evolve across space, yet most of these works cannot match the practical needs of local high-quality urban construction [...] Read more.

China pushes forward two key national strategies, namely common prosperity and Healthy China. Many papers have discussed how urban common prosperity and urban healthy development evolve across space, yet most of these works cannot match the practical needs of local high-quality urban construction in Guangdong. This study takes various cities in Guangdong Province as the research area and utilizes multi-source big data from 2010 to 2025 so that it constructs a multidimensional evaluation system for the two major systems. Subsequently, this research employs methods including a deep weighted neural network to conduct empirical analysis. The results show that the urban common prosperity index in Guangdong Province exhibits an overall continuous upward trend. However, common prosperity gradually deviates from the development pattern that matches the economic driving forces. Meanwhile, the prominent advantages of urban healthy development gradually shift from eastern Guangdong to the core area of the Pearl River Delta, which establishes an overwhelming leading position for the Pearl River Delta. Furthermore, the regional development level plays a certain promoting role in healthy development. Spatially, common prosperity and urban healthy development exhibit phased non-linear characteristics, which encompass synchronous growth, growth rate divergence, and trend deviation. This study provides empirical evidence and practical support for Guangdong Province so that policymakers can comprehensively advance common prosperity and healthy city construction. Ultimately, these efforts optimize the regional development layout, which promotes high-quality and sustainable urban development. Full article

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

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23 pages, 402 KB

Open AccessArticle

Scientific Self-Management: A Critical Systems Response to Organisational Development Failure

by Petter Øgland and Gary Alan Evans

Systems 2026, 14(8), 1015; https://doi.org/10.3390/systems14081015 - 17 Aug 2026

Viewed by 438

Abstract

Approximately 70% of organisational development (OD) initiatives based on methodologies such as Total Quality Management (TQM), Business Process Reengineering (BPR), Lean, and Six Sigma are reported to fail. Critical Systems Thinking (CST) attributes many of these failures to poor implementation and inadequate attention [...] Read more.

Approximately 70% of organisational development (OD) initiatives based on methodologies such as Total Quality Management (TQM), Business Process Reengineering (BPR), Lean, and Six Sigma are reported to fail. Critical Systems Thinking (CST) attributes many of these failures to poor implementation and inadequate attention to organisational context, emphasising the need for critical awareness, political agency, and multimethodology. However, when OD work itself becomes a “bullshit job”, even CST’s principles may struggle to take hold. This paper develops Scientific Self-Management (SCSM), inspired by Community Operational Research (COR) and informed by Complex Adaptive Systems (CAS), as a bottom-up systems approach to such situations. A 42-month first-person action research study of a public-sector OD programme examines the practical feasibility of SCSM in a complex organisational setting. The study shows how bottom-up learning and self-directed engagement can restore meaning and generate local organisational improvements where conventional approaches struggle to gain traction, while also highlighting the political challenges of sustaining such initiatives over time. It contributes to the CST and COR literatures by extending systems practice to situations in which management is incompetent or hostile and organisational culture has become paralysed by pretence. The findings suggest that successful organisational development depends less on the choice of methodology than on creating organisational conditions that enable meaningful participation, learning, and continuous improvement. Full article

(This article belongs to the Special Issue Systems Thinking and Systems Practice)

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24 pages, 1065 KB

Open AccessArticle

Integrated Routing and Controlled-Segment Scheduling in Corridor-Based Drone Logistics Systems Under Minimum Headway Constraints

by Jien Liu and Senlai Zhu

Systems 2026, 14(8), 1014; https://doi.org/10.3390/systems14081014 - 17 Aug 2026

Viewed by 308

Abstract

Predefined low-altitude corridors create a coupled routing–scheduling problem when multiple drone routes enter the same controlled segment. This study separates an upstream control hub from its scarce directed hub–segment resource and develops an event-expanded continuous-time mixed-integer linear programming model with optional fleet activation, [...] Read more.

Predefined low-altitude corridors create a coupled routing–scheduling problem when multiple drone routes enter the same controlled segment. This study separates an upstream control hub from its scarce directed hub–segment resource and develops an event-expanded continuous-time mixed-integer linear programming model with optional fleet activation, complete-route energy and capacity checks, release precedence, minimum entry headway, holding, and downstream delay propagation. A headway-aware large neighborhood search (HA-LNS) combines route neighborhoods with a finite serial event decoder. Gurobi proves optimality on three small instances, and fixed-route timing MILPs exactly match the decoder, including for a repeated physical-hub visit. Across ten matched networks per scale, HA-LNS changes the mean objective relative to route-only LNS by 0.01%, 0.90%, and 2.33% at nominal scales 30, 50, and 100. Under high conflict-resource density, the reduction reaches 5.77%, while mean holding falls from 2.054 to 0.025 min. Simulated annealing is 1.04% better at scale 50 and statistically indistinguishable at scales 30 and 100, showing that the contribution is conflict-aware integration rather than universal heuristic dominance. The framework identifies directed-resource density as the main condition under which temporal coordination materially improves route decisions. Full article

(This article belongs to the Special Issue Advanced Transportation Systems and Logistics in Modern Cities)

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29 pages, 1800 KB

Open AccessArticle

A Convergent Perspective on Policy Communication on Social Media: A Mixed-Methods Approach Using Text Mining and Social Network Analysis

by Zenglei Yue and Guang Yu

Systems 2026, 14(8), 1013; https://doi.org/10.3390/systems14081013 - 17 Aug 2026

Viewed by 375

Abstract

Social media is a vital platform for policy communication, yet research rarely integrates content and structural features to evaluate communication effects multidimensionally. This study proposes a convergent framework combining text mining and social network analysis to assess policy communication effects and underlying mechanisms. [...] Read more.

Social media is a vital platform for policy communication, yet research rarely integrates content and structural features to evaluate communication effects multidimensionally. This study proposes a convergent framework combining text mining and social network analysis to assess policy communication effects and underlying mechanisms. Using China’s upgraded Mass Entrepreneurship and Innovation policy on Sina Weibo as a case, we analyze communication breadth, depth, audience sentiment, thematic focus, network topology, key nodes, and community characteristics. The results reveal that (1) communication breadth is dominated by official communicators, while audiences drive interactive depth, reflecting a “centralized broadcasting, decentralized engagement” model; (2) influential users express more positive attitudes than ordinary audiences; (3) discussions diversify from core innovation themes to micro-level concerns like regional development and talent policies; (4) the network shows loose global structure but strong local clustering, with bridging nodes posting less polarized, broader content. Theoretically, this study offers behavioral-level observations that align with key corollaries of the Spiral of Silence Theory—the tendency for individuals with deviating views to shift toward lower-visibility participation. These pattern-level findings offer a complementary empirical perspective on opinion expression in digital policy contexts. Practically, the findings offer preliminary insights that may inform adaptive, decentralized strategies for enhancing policy diffusion in similar social media contexts. Full article

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

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38 pages, 3263 KB

Open AccessArticle

One Plus One Is Greater than Two for Multiple Ridesharing Service Providers: A Theoretical Proof and an Algorithm for Sustainable Collaborative Ridesharing

by Fu-Shiung Hsieh

Systems 2026, 14(8), 1012; https://doi.org/10.3390/systems14081012 - 17 Aug 2026

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Abstract

Ridesharing is one type of sustainable transport mode that provides a promising approach to achieving the Sustainable Development Goals (SDGs). Although users can help mitigate CO₂ emissions and fuel consumption by using the services of a single ridesharing service provider, their requests [...] Read more.

Ridesharing is one type of sustainable transport mode that provides a promising approach to achieving the Sustainable Development Goals (SDGs). Although users can help mitigate CO₂ emissions and fuel consumption by using the services of a single ridesharing service provider, their requests may not be accepted because the service provider may not have a sufficient number of drivers to meet their requirements. The existence of multiple ridesharing service providers creates opportunities to satisfy more users’ requirements and enhance the sustainability of ridesharing services through collaboration. In one of our previous studies, we developed several metaheuristic algorithms to show the benefits of collaboration among multiple ridesharing service providers by comparing their performance with that of multiple ridesharing service providers operating independently without collaboration. However, the benefits of collaboration among multiple ridesharing service providers are demonstrated based on numerical results. There is currently no theoretical proof showing that collaboration among multiple ridesharing service providers always performs at least as well as independent operation. In addition, our previous study indicates that the development of a more effective algorithm is key to benefiting from collaboration among multiple ridesharing service providers. The goals of this study are twofold: (1) to develop a theory proving that the performance of multiple ridesharing service providers operating collaboratively is at least as high as that of multiple ridesharing service providers operating independently without collaboration and (2) to develop a more effective algorithm to further improve performance. The theory developed in this paper provides a formal proof of the benefits of collaboration among multiple ridesharing service providers for improving sustainability. The advanced algorithm proposed in this paper outperforms the 12 algorithms developed in our previous study. Full article

(This article belongs to the Special Issue Sustainable Strategies and Organizational Transitions for Green Economy)

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32 pages, 3223 KB

Open AccessArticle

Research on the Coupling Relationship Between Regional Green Transport Efficiency and High-Quality Economic Development

by Qing Du, Yangzhou Li, Yanfei Li, Cheng Li and Shiguo Deng

Systems 2026, 14(8), 1011; https://doi.org/10.3390/systems14081011 - 17 Aug 2026

Viewed by 188

Abstract

This study employs panel data from 11 provinces and municipalities along the Yangtze River Economic Belt spanning 2010–2021. It measures green transport efficiency (GTE) using principal component analysis (PCA) and the undesirable Super-SBM model while constructing an economic high-quality development index (HQEDI) through [...] Read more.

This study employs panel data from 11 provinces and municipalities along the Yangtze River Economic Belt spanning 2010–2021. It measures green transport efficiency (GTE) using principal component analysis (PCA) and the undesirable Super-SBM model while constructing an economic high-quality development index (HQEDI) through an entropy-weighted CRITIC approach. The study combines coupling coordination degree modeling with spatial autocorrelation analysis (Global Moran’s I, LISA, hotspot/coldspot detection) to empirically investigate their synergistic evolution mechanism. The findings indicate the following: (1) Multidimensional policy combinations exhibit a nonlinear threshold effect on enhancing green transport efficiency, with efficiency significantly rebounding post-2015 as low-carbon policies deepened. (2) High-quality economic development displays a dual-stage ‘convergence-divergence’ pattern, where downstream regions lead in HQEDI but mid- and upstream regions show faster growth in coordination and green dimensions. (3) The coupling coordination degree exhibits pronounced spatial spillover effects, with the global Moran’s I mean reaching 0.485. High-value clusters form in downstream regions, while upstream areas predominantly exhibit low-value clusters, revealing an ‘east-high, west-low’ regional differentiation pattern. (4) The gradient divergence mechanism stems from heterogeneity in infrastructure density, industrial structure, and policy responsiveness elasticity. Accordingly, it is recommended to establish a multi-level governance mechanism to dismantle administrative barriers and to construct a tripartite policy package integrating ‘digital transport, ecological compensation, and industrial radiation’ to advance coordinated basin development. Full article

(This article belongs to the Section Systems Engineering)

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22 pages, 956 KB

Open AccessArticle

Information-Flow Waste in Organizations: Conceptual Development and Empirical Validation of a Measurement Scale

by Runkai Tian, Taibo Chen, Fansen Kong, Siqi Zhang, Kaifang Ding and Ziyin Yu

Systems 2026, 14(8), 1010; https://doi.org/10.3390/systems14081010 - 17 Aug 2026

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Abstract

Information-flow waste refers to activities within organizational information flows that consume resources without creating value, yet standardized instruments for systematically measuring this construct remain lacking. This study aims to clarify the construct structure of information-flow waste and develop a corresponding scale. Candidate items [...] Read more.

Information-flow waste refers to activities within organizational information flows that consume resources without creating value, yet standardized instruments for systematically measuring this construct remain lacking. This study aims to clarify the construct structure of information-flow waste and develop a corresponding scale. Candidate items were generated through literature analysis, expert interviews, and cognitive interviews. The scale was then purified and validated using two independent manufacturing samples (n = 266 and n = 287) through exploratory factor analysis, confirmatory factor analysis, measurement invariance testing, and nomological validity testing. The results support a second-order structure comprising information acquisition, information transmission, information storage, and information processing, yielding a final 23-item Information-Flow Waste Scale. The scale demonstrates good reliability, convergent validity, and discriminant validity and achieves strict measurement invariance across production and operations, professional and technical, and supervisory and managerial job groups. Information-flow waste is significantly and positively associated with information overload, providing initial support for the scale’s nomological validity. This study provides a standardized measurement instrument for subsequent empirical research on information-flow waste and, in manufacturing contexts, a measurement basis for identifying manifestations of waste across stages of information flow and conducting subsequent problem analysis. Full article

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

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27 pages, 2972 KB

Open AccessArticle

An Open-Data-Driven Enhanced Bayesian Decision Network for System-Level UAV Accident-Severity Analysis and Response Simulation

by Ruimin Hao, Anning Ni, Jingbo Yin, Linjie Gao, Yutong Zhu, Xi Wang, Yizhou Wang and Xiaoning Zhang

Systems 2026, 14(8), 1009; https://doi.org/10.3390/systems14081009 - 17 Aug 2026

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Abstract

Unmanned aerial vehicle (UAV) accidents pose growing challenges to public safety and airspace management. This study develops an open-data-driven hierarchical Bayesian network (BN) with a Leaky Noisy-OR mechanism to analyse factors associated with consequence severity among recorded UAV accidents, and extends it to [...] Read more.

Unmanned aerial vehicle (UAV) accidents pose growing challenges to public safety and airspace management. This study develops an open-data-driven hierarchical Bayesian network (BN) with a Leaky Noisy-OR mechanism to analyse factors associated with consequence severity among recorded UAV accidents, and extends it to a Bayesian decision network for response simulation. Using 633 public accident records and matched meteorological data, 14 binary risk-factor nodes spanning human, machine, environmental, and management dimensions were constructed. Stratified five-fold cross-validation yielded a mean validation F1 score of 0.922 and an AUC of 0.784. Backward inference ranked airspace exposure, wind, and operation error highest under severe-consequence conditioning, whereas sensitivity analysis identified wind, bad weather history, and operation error as the most influential root-node parameters. Under the assumed directed acyclic graph (DAG), the bad weather history→weather→environment→risk state path had the highest average edge-influence score (0.853). Under the baseline safety-priority assumptions, the reroute strategy was preferred, yielding the highest expected utility (31.967) and reducing the model-estimated post-decision high-risk probability from 81% to 45%. Alternative preference settings ranked the adjust strategy first. The framework integrates open-data severity analysis with assumption-explicit response simulation. Full article

(This article belongs to the Topic Applications of Open Data in Different Disciplines)

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20 pages, 3072 KB

Open AccessArticle

Architecture-Driven Hardware-in-the-Loop Verification: A Bidirectional MBSE Framework Demonstrated on a Low-Cost UAV

by Md Robiul Islam, Aditya Akundi and Sergio A. Luna Fong

Systems 2026, 14(8), 1008; https://doi.org/10.3390/systems14081008 - 17 Aug 2026

Viewed by 357

Abstract

Integrating Model-Based Systems Engineering (MBSE) with Digital Twins (DTs) offers a promising way to transform static system models into dynamic, runtime-connected representations that enable execution, monitoring, and validation. Much current research in this area remains focused on descriptive modeling, simulation-based workflows, or unidirectional [...] Read more.

Integrating Model-Based Systems Engineering (MBSE) with Digital Twins (DTs) offers a promising way to transform static system models into dynamic, runtime-connected representations that enable execution, monitoring, and validation. Much current research in this area remains focused on descriptive modeling, simulation-based workflows, or unidirectional data flow, leaving a gap in methods that link architectural models directly to physical system behavior in a closed-loop system. This study fills that gap by proposing and demonstrating a four-layer framework that supports traceable, bidirectional interaction between a system’s architecture and its physical implementation. The framework consists of four interconnected layers: System Definition, Model Translation and Integration, Execution and Monitoring, and Feedback and Synchronization. The System Definition Layer captures mission goals, functional responsibilities, subsystem decomposition, and mission parameters in Capella using the Arcadia methodology. The Model Translation and Integration Layer translates these properties into executable commands via Python4Capella, converting architecture-level parameters into actionable instructions. The Execution and Monitoring Layer executes these commands in MATLAB, while the Feedback and Synchronization Layer returns runtime data to the model, supporting validation, model awareness, and refinement. A UAV case study is used to validate the framework: the UAV architecture is decomposed into key logical subsystems, and mission behaviors such as takeoff, movement, turning, and landing were modeled parametrically using the Property Values Management Tool (PVMT). These properties were translated into MATLAB commands, executed on a physical UAV, and evaluated based on telemetry-based mission distance accuracy. This work demonstrates that an MBSE model can serve not only as a design artifact but also as an authoritative, execution-connected component of a digital twin workflow. The framework contributes to MBSE-driven digital twin research by providing a structured process for integrating architecture, translation, execution, monitoring, and synchronization in a traceable manner. Overall, the study provides a scalable foundation for future developments in hardware-in-the-loop testing and digital twin applications for cyber–physical systems, and further empirical evaluation is needed to assess the framework’s transferability across domains. Full article

(This article belongs to the Special Issue Advancing Digital Engineering: Transforming Industries with Model-Based Systems Engineering and Digital Twin Technology)

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29 pages, 3639 KB

Open AccessArticle

From Responding to Co-Creating: Identifying Strategic CSR Processes Using Pre-Trained Language Models

by Xia Fan, Dongxia Cheng and Qianhua Lei

Systems 2026, 14(8), 1007; https://doi.org/10.3390/systems14081007 - 17 Aug 2026

Viewed by 282

Abstract

Corporate social responsibility (CSR) is shifting from compliance-driven to strategically embedded practice, yet large-scale identification of strategic CSR (SCSR) remains methodologically challenging due to reliance on surveys or ratings. This study proposes a hybrid identification framework combining pre-trained language models (PLMs) and Latent [...] Read more.

Corporate social responsibility (CSR) is shifting from compliance-driven to strategically embedded practice, yet large-scale identification of strategic CSR (SCSR) remains methodologically challenging due to reliance on surveys or ratings. This study proposes a hybrid identification framework combining pre-trained language models (PLMs) and Latent Dirichlet Allocation to conduct paragraph-level semantic analysis on 3022 CSR reports from Chinese manufacturing firms. The approach effectively identifies and extracts the topics of both strategic and non-strategic CSR. Findings show that only 25.6% of CSR behaviors simultaneously possess strategic intent, business synergy, resource investment, and value output. SCSR practices are highly concentrated on value chain optimization and R&D collaboration, with significant variations across ownership types and industry environments. This study contributes a novel PLM-based methodology for SCSR identification and offers empirical evidence and practical tools for CSR quality assessment, regulatory oversight, and strategic decision-making in manufacturing sectors. Full article

(This article belongs to the Section Artificial Intelligence and Digital Systems Engineering)

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30 pages, 2723 KB

Open AccessArticle

Adopting CER Technology and Coordination in Capital-Constrained Low-Carbon Supply Chains: A Fairness Concern Perspective

by Haiyang Cui, Yu-Wei Li, Gui-Hua Lin and Xide Zhu

Systems 2026, 14(8), 1006; https://doi.org/10.3390/systems14081006 - 17 Aug 2026

Viewed by 283

Abstract

Low-carbon transformation requires substantial investments, challenging capital-constrained manufacturers to adopt carbon emission reduction (CER) technologies. While external financing alleviates capital shortages, it cannot address potential profit imbalances that trigger fairness concerns. We investigate a low-carbon supply chain where a capital-constrained manufacturer adopts CER [...] Read more.

Low-carbon transformation requires substantial investments, challenging capital-constrained manufacturers to adopt carbon emission reduction (CER) technologies. While external financing alleviates capital shortages, it cannot address potential profit imbalances that trigger fairness concerns. We investigate a low-carbon supply chain where a capital-constrained manufacturer adopts CER technologies via a preferential bank loan and sells to a capital-abundant retailer. Unlike prior studies treating CER investments as one-time costs, we model CER technology as a quadratic per-unit royalty licensing fee. We find that, given consumers’ willingness to pay for low-carbon products, financing encourages CER upgrades but creates profit disparities unfavorable to the retailer. Incorporating the retailer’s fairness concerns, results show that compared to the non-fairness scenario, the manufacturer sets a lower wholesale price and cannot earn more. Conversely, the retailer strategically maintains or increases its order quantity, attaining higher profits. Furthermore, the optimal CER level remains invariant regardless of fairness preferences. Finally, supply chain coordination is achievable under specific conditions, yielding a win–win outcome where the manufacturer adopts CER technologies and the retailer’s fairness concerns are accommodated. The quadratic per-unit technology licensing fee we investigated maintains the manufacturer’s motivation and ensures the retailer’s fairness, contributing to the stable and sustainable evolution of low-carbon supply chains. Full article

(This article belongs to the Section Supply Chain Management)

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14 pages, 1221 KB

Open AccessArticle

Digital Health Literacy Profiles: A Cluster Analysis of Digital Health Application Users

by Nejc Bernik, Polona Šprajc, Miha Rupar and Eva Jereb

Systems 2026, 14(8), 1005; https://doi.org/10.3390/systems14081005 - 17 Aug 2026

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Abstract

The digital transformation of healthcare systems increasingly depends on the successful adoption and use of digital health technologies (DHTs) by healthcare users. In this context, digital health literacy (DHL) has emerged as a key factor influencing the effective use of digital health applications. [...] Read more.

The digital transformation of healthcare systems increasingly depends on the successful adoption and use of digital health technologies (DHTs) by healthcare users. In this context, digital health literacy (DHL) has emerged as a key factor influencing the effective use of digital health applications. Despite growing interest in DHL, limited research has focused on identifying distinct user profiles in the context of digital health applications. This study aims to identify DHL profiles among users of digital health applications in the Slovenian healthcare system. Data were collected from 247 respondents using the eHealth Literacy and Use Scale (eHLUS), which captures three dimensions: Autonomous Use and Technical Access, Digital Health Engagement, and DHL. Hierarchical cluster analysis (Ward’s method, Euclidean distance) was applied to identify user groups. The analysis revealed four distinct DHL profiles: Digitally Empowered Users, Digitally Vulnerable Users, Passive Digital Users, and Motivated Developing Users. The findings indicate substantial heterogeneity among users in their use of digital health applications across the dimensions of DHL. This study represents one of the first applications of the eHLUS instrument outside its original context and contributes to a better understanding of user diversity within digital healthcare systems. The findings offer a foundation for the development of targeted educational interventions, the reduction in digital inequalities, and the design of user-centered digital health applications that support the ongoing digital transformation of healthcare systems. Full article

(This article belongs to the Section Artificial Intelligence and Digital Systems Engineering)

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