Systems doi: 10.3390/systems14111450

Authors: Shuangjie Li Liang Hao Liwei Guo

Existing efficiency assessments differ in scope and do not consistently distinguish local from complete-chain performance. This review combines bibliometric mapping with conceptual and methodological synthesis to clarify chain-wide efficiency in industrial and supply chains. Database searching and screening yielded 621 publications from the Web of Science Core Collection and Scopus, with corpus construction documented using an adapted PRISMA 2020 flow diagram. Descriptive statistics and author-keyword co-occurrence analysis reveal publication growth and seven coexisting thematic clusters, with increasing attention to digitalization, resilience, and disruption. Chain-wide efficiency covers the complete process from initial production to final consumption, including all relevant nodes and effective linkages within an explicitly defined assessment boundary. Efficiency–resilience trade-offs or synergies depend on resource use, risk type, node position, network structure and input substitutability. The comparison of four DEA-based approaches—black-box DEA, network DEA, game-theoretic DEA, and CoDEA—shows that they emphasize overall inputs and outputs, interstage linkages, actor decisions, and virtual efficiency transmission, respectively. The representative baseline formulations of these four DEA-based approaches have yet to adequately accommodate interpretable node linkages, dynamic shocks, and interactions among multiple actors within a single framework. Future research should strengthen common-dataset benchmarking and integrate efficiency measurement with shock propagation, member coordination, and network reconfiguration.

Systems doi: 10.3390/systems14111451

Authors: Jakob Yau Wesley Doorsamy

Modern infrastructure must evolve from reactive, centralised models towards proactive, resilient, and human-centric systems aligned with Industry 5.0. Digital Twin (DT) technologies have emerged as a promising enabler of this transition, but their widespread adoption remains constrained by complexity and cost barriers. This research addresses these challenges through the development and experimental evaluation of a modular, edge-based Digital Twin architecture for water utility management. The contribution lies not in the individual forecasting, sensing, or control technologies, but in their integration into a resource-constrained, closed-loop node and in the empirical characterisation of its prototype computing-hardware cost, computational requirements, storage demand, and physical actuation capability. The approach is demonstrated through a proactive rainfall prediction and hydraulic decision-support system. To support rainfall-informed control, the forecasting models were developed and evaluated using ERA5 reanalysis data from 2000 to 2026 as a consistent reference. The enhanced connected configuration, which incorporated the externally supplied weather-category input, achieved R2=0.8096 and RMSE =0.1454. When this input was withheld to represent the proposed reduced-input fallback configuration, the standalone configuration retained R2=0.4038 and RMSE =0.2574. During a separate 24 h prospective deployment evaluation, forecasts were generated in advance and subsequently compared with the corresponding ERA5 reanalysis record. During this monitored period, the deployed model reproduced rainfall timing and aggregate volume more closely than the physics-based API forecast. The resulting framework supports rainfall-informed, node-level hydraulic decision-making and autonomous pump actuation while maintaining operator visibility through a local SCADA interface. By performing meteorological telemetry processing, rainfall inference, water-storage-state assessment, data logging, and physical control locally, the architecture reduces dependence on continuous cloud connectivity for these operational functions. The results establish the technical feasibility of implementing predictive water-management functions within a low-cost, resource-constrained Digital Twin node. The prototype provides an experimentally characterised foundation for subsequent evaluation in larger hydraulic systems and future distributed, multi-node water-management applications.

Systems doi: 10.3390/systems14111449

Authors: Shota Suzuki Takuo Suganuma

This study examines how large language model (LLM) assessments were used in an actual university internal audit. We analyzed system outputs, audit records, and accounts from two meetings with audit staff. A cloud implementation of a previously developed method processed 1,860,622 voucher line items covering 12 months. Candidate analysis covered eight organizational units. Across three monetary thresholds, 949 threshold-specific candidates were assigned to the three higher review-priority categories. After audit-specific filtering, auditors reviewed approximately 700 candidates, exported 36 for detailed examination, and selected four for departmental inquiry. They compared their own assessments with LLM-generated rationales and retained some uncertain candidates for further investigation. They also used priorities to decide how thoroughly to review candidates, depending on the volume in each department. Thus, LLM output informed both the interpretation of transactions and the allocation of review effort. These findings extend research on human oversight by showing how scrutiny of LLM rationales can coexist with reliance on priorities when allocating review effort. Independent evaluation of detection performance and time savings remains necessary.

Systems doi: 10.3390/systems14111448

Authors: Xusheng Yao Xinyan Wang Xin Zhang Yanze Liu Zuanxu Chen Bo Xu

Global supply chain disruptions have heightened interest in understanding how firms develop the capacity to withstand, respond to, and recover from external shocks. Drawing on the resource-based view and dynamic capabilities theory, this study examines the relationship between artificial intelligence (AI) application intensity and firm-level supply chain resilience using panel data from Chinese A-share listed firms over the period 2007–2024. Empirical results reveal a positive and statistically significant association between AI application intensity and supply chain resilience, which is further verified via multiple robustness checks, including propensity score matching and an instrumental variable approach. Further analyses examine R&D expenditure and corporate reputation as potential explanatory pathways and identify a negative moderating role of corporate transparency, consistent with an information-substitution explanation. Heterogeneity analyses indicate that the positive association is more pronounced among firms facing greater environmental uncertainty, operating in higher-trust business environments, and exhibiting stronger environmental, social, and governance (ESG) performance. These findings contribute to the understanding of AI-related organizational capabilities and supply chain resilience, highlighting the importance of integrating AI applications with complementary organizational resources and tailoring AI-related strategies to firms’ operating environments.

Systems doi: 10.3390/systems14111446

Authors: Byoungjin Kim Nahyang Byun Eunseok Lee

South Korea’s Smart Farm Innovation Valley program integrates infrastructure, technology demonstration, training, entrepreneurship, and public support across four regional sites. This study examines changes in documented policy attention to the program from 2019 to June 2026. We analyzed 15,455 news articles, blog posts, online community discussions, and web documents retrieved from Naver, Daum, and Google using TEXTOM. Across three national policy contexts, we examined normalized concept prevalence and cosine-weighted lexical co-mention networks, supplemented by frequency-adjusted association measures and a fixed-margin null model. Attention to construction and project delivery declined, while education, entrepreneurship, rental access, support, and operation became more prominent. Network comparisons revealed substantial continuity between adjacent contexts alongside cumulative relational reweighting over the study period. Node connectivity largely tracked concept prevalence, but selected lexical co-mention pairs involving operation, demonstration, and data changed beyond fixed-margin expectations. Manual semantic validation was heterogeneous: adjudicated temporal point estimates opposed the full-corpus lexical directions for four focal concepts, and the highlighted lexical co-mention links were not independently corroborated as semantic associations. The findings provide a systems-oriented account of how policy-related issues are jointly represented in public discourse; however, they do not establish changes in institutional coordination, operational capacity, or program effectiveness.

Systems doi: 10.3390/systems14111447

Authors: Jaein Kim Kuk-Kyoung Moon

Understanding the social antecedents of eco-friendly vehicle purchase intentions is essential for advancing the transition toward sustainable urban mobility. From a socio-technical systems perspective, vehicle adoption depends not only on technologies and infrastructure but also on the social contexts in which users make decisions. Drawing on behavioral spillover theory and the theory of normative social behavior (TNSB), this study examines whether philanthropic engagement, namely charitable donation and volunteering, is associated with eco-friendly vehicle purchase intentions, and whether descriptive social norms (measured as perceived compliance with everyday civic rules) moderate these associations. Using weighted binary logistic regression with design-based standard errors and data from the 2024 Seoul Survey (n = 36,280), we found that charitable donation was positively related to purchase intention, whereas volunteering showed no significant overall association in the main-effects model. Descriptive norms moderated both associations: the association of donation was positive and significant at moderate-to-high norm levels, whereas the association of volunteering changed from negative at low norm levels to positive at high norm levels. The findings were robust to alternative specifications, although the norm-conditioned association of donation was concentrated in hybrid vehicle intention. These cross-sectional associations are consistent with cross-domain behavioral spillover and suggest that descriptive norms may constitute an important boundary condition. For urban mobility systems, the results suggest hypotheses, to be tested experimentally and longitudinally, that adoption-oriented policies may benefit from coordination with civic engagement initiatives and from attention to the normative context of everyday social life.

Systems doi: 10.3390/systems14111444

Authors: Jieun Lee Yuha Moon Jonghyuk Park Young Soo Park

Industry 4.0 increasingly requires intelligent safety monitoring systems capable of continuously recognizing and assessing workers’ safety status in complex industrial environments. In settings where multiple types of personal protective equipment (PPE) must be worn simultaneously, object detection alone is insufficient to determine whether individual workers are actually wearing the required PPE and how their wearing status changes over time. This study proposes a worker-centered systems framework that extends object detection toward continuous PPE safety-state assessment. The proposed framework integrates worker tracking, pose-based region-of-interest (ROI) generation, worker–PPE matching, temporal correction using an Ensemble Kalman Filter, and final wearing-status determination. The proposed framework was evaluated using work videos containing transitions between wearing and non-wearing states and visual disturbances such as sparks, smoke, and partial occlusions. Experimental results showed overall wear and non-wear precision values of 0.992 and 0.991, respectively, while recall for the non-wearing state reached 0.937 under visually challenging conditions. The framework processed an average of 41.83 frames per second. These results show that integrating spatial worker–PPE relationships with temporal state information extends object-level PPE detection toward continuous worker-level safety-state assessment. The proposed framework provides an integrated systems approach to worker-centered PPE compliance monitoring in Industry 4.0 workplaces.

Systems doi: 10.3390/systems14111445

Authors: Yanzhe Zhang Tongtong Li Jian Zhang

In this study, we ask whether digital trade restrictions are associated with manufacturing participation through cross-border production network exposure and whether any association varies with structural position. We combine the OECD Digital Services Trade Restrictiveness Index with value-added participation data for 35 countries and 14 manufacturing sectors from 2014 to 2021. Because the DSTRI changes in only 47 of 245 possible annual country transitions and country-year fixed effects absorb national main effects, every estimate is interpreted as a conditional association rather than a causal policy effect. Average domestic and partner exposure estimates are imprecise. The exploratory top-position interaction is negative in 82 of 84 multiverse specifications, but only 14 confidence intervals exclude zero. A pooled equality test confirms period heterogeneity: the 2018–2021 minus 2014–2017 interaction difference is 0.2644 (95% CI [0.0215, 0.5073]; wild p = 0.036). The common lagged sample, including the required main effect for outcome-derived annual position, yields a null annual position interaction (−0.0027; 95% CI [−0.0405, 0.0351]); its formal difference from the static interaction is 0.0886 (95% CI [0.0365, 0.1406]). Partner concentration and broad digital intensity do not validate the proposed mechanism. Fixed links map regulatory exposure, but no cascade, supplier substitution, or adaptation is observed. Therefore, the evidence supports a bounded systems robustness assessment and diagnostic policy use, not a general, causal, or time-invariant restriction effect.

Systems doi: 10.3390/systems14111443

Authors: Xinning Song Yarong Liu Guanjie Cao Hyung Jong Na

In corporate green transformation, environmental, social, and governance (ESG) responsibilities in the upstream supply chain are critical components of corporate governance, and disclosure enables outsiders to observe corporate governance practices. This study examines the association between substantive supply chain ESG disclosure (SSD) and green management innovation (GMI), and whether this association varies with three executive characteristics: environmental background, CEO gender, and managerial overconfidence. Using text from the ESG reports of Chinese firms listed on the Shanghai and Shenzhen A-share markets from 2016 to 2024, we employed the large language model DeepSeek to perform sentence-level identification, distinguishing between substantive and rhetorical content in supply chain ESG statements, and aggregated the results to construct a substantive disclosure index. Results show that SSD is positively associated with GMI. This association is stronger in firms with more executives with an environmental background and those led by female CEOs, and weaker in firms with greater managerial overconfidence. This study expands the measurement tools used in disclosure research. The findings also suggest that firms should shift their disclosure focus toward verifiable commitments and provide a new perspective and basis for regulatory evaluation to move from “whether disclosure occurs” to “whether substantive disclosure occurs”.

Systems doi: 10.3390/systems14111442

Authors: Zhijie Huang Xiaobo Li Tao Wang Liang Bai

Maintaining end-to-end connectivity under disruption is a central problem in systems resilience. This study examines how limited protection resources can increase the minimum node-removal cost required to disconnect a specified service. Mission-Path Cut Fortification (MPCF) models a directed service as a functional graph and treats protection as a finite increase in node-removal cost. Node splitting yields a compact mixed-integer linear program, and an independent cut-generation formulation verifies its optimal value. On 45 synthetic graphs, mean minimum-cut values are 33.62 for MPCF-Exact and MPCF-CG, 32.30 for MPCF-Greedy, 30.41 for PathFrequency, and 27.38 without fortification. Graph-level analyses treat budgets as repeated measurements, and a 90-graph extension reproduces the paired effects for the nine designated methods. Further experiments assess heterogeneous fortification costs and effectiveness. Scaling to 1000 nodes identifies the computational limits of both exact formulations through stopping times and optimality bounds. Ten source–sink cases from public transport and telecommunications networks demonstrate applicability to empirical path topologies. Partial-capacity analysis shows that complete-disconnection and residual-capacity criteria can favor different fortification sets. The findings support joint node-set selection for resistance to complete disconnection and show that the service criterion should be specified before resources are allocated.

Systems doi: 10.3390/systems14111440

Authors: Jian Wang Wenhui Song Tingting Zhu Ting Wang

Supply chain disruptions make procurement lead time (PLT) uncertain, so a reorder point that meets a target customer service level must be set against several sources of risk at once, including disruption-induced abnormal replenishment lead times. This paper models the abnormal PLT as a stochastic amplification of the normal PLT, LTA=LTN×DP with DP>1 by construction and extends the Normal Approximation Method (NAM) and the Compound Normal Distribution Method (CNDM) to this dependence structure under a cycle service level (CSL) constraint. The extended NAM uses the complete two-component mixture variance, including the between-state term that the classical variance average omits. For the extended CNDM the stationary points of the reorder point with respect to normal PLT volatility solve H(R)=0 under the within-state normal approximation of the two lead-time demand distributions, which has one or three simple roots on the non-degenerate parameter region; the two mean-based levels are reference values rather than thresholds. The service level and the reorder point are therefore linked through several distinct thresholds at which the effect of volatility changes sign, and the sign alternates across adjacent thresholds, which accounts for the procurement lead time paradox: a reduction in volatility need not lower the required inventory and raises the reorder point in some service-level regions. Monte Carlo experiments over sixty non-degenerate scenarios support this reading, with the CNDM showing a lower average absolute error than the NAM at all five target service levels while the NAM is closer in some individual scenarios. Lead time improvement measures should therefore be evaluated jointly with the service-level target, and reorder points should not be treated as one-off calibrations of a stable environment, because they need review when the disruption probability changes.

Systems doi: 10.3390/systems14111441

Authors: Kiran Fahd Sitalakshmi Venkatraman Sazia Parvin

Selecting a data-management subsystem is a consequential decision in data-intensive applications, including AI pipelines that rely on low-latency storage. Such decisions are often informed by lightweight, application-specific benchmarks whose measurement validity is rarely examined. This paper presents a validity-aware benchmarking workflow for comparing NoSQL data stores under application-representative CRUD workloads. The workflow incorporates a final validation stage that checks whether measured operations exhibit the expected behaviour before performance comparisons are made. The approach is demonstrated using a key-value store (Aerospike) and a document store (MongoDB). The validity checks identified two operations that performed no actual database work. MongoDB’s idiomatic read operation returned a cursor that was never iterated, causing reads to appear approximately 130 times faster for single-record workloads and 1000 times faster for bulk workloads than equivalent Aerospike reads. In addition, a MongoDB bulk update matched no documents because update keys were constructed incorrectly. Further validity threats included a missing secondary index, unequal bulk workloads, and a first-run warmup effect. Consequently, the remaining write measurements are reported descriptively, together with confidence intervals and run-level results. The study does not establish which engine delivers superior performance. Instead, it demonstrates how seemingly reasonable application-specific benchmarks can generate misleading conclusions and argues for an explicit validity-assessment stage, supported by a threat model, before benchmark results are used to inform subsystem selection and architectural decision-making.

Systems doi: 10.3390/systems14111439

Authors: Jeonghyeon Kim Junwoo Kim

With advancements in smart factory and IoT technologies, Automated Guided Vehicle (AGV) and Autonomous Mobile Robot (AMR) fleets continue to grow, and discrete-event simulation (DES) has become a key tool for operational design. However, DES-based studies tend to focus on scheduling and dispatching, while the routing scheme by which a vehicle determines its path during travel is often overlooked or left at the default shortest-path setting, despite it directly shaping how congestion and blocking arise. To address this gap, this study treats the routing scheme itself as the object of analysis and—within a commercial DES under a common layout, fleet, and demand—implements and compares three schemes: a static scheme (SR) and two dynamic schemes that avoid occupied segments during travel. This includes Distributed Dynamic Routing (DDR), a greedy control-point scheme, and Centralized Dynamic Routing (CDR), a Min-Cost Flow scheme. Rather than proposing a new routing algorithm, the study contributes a controlled comparison that isolates the extent to which the routing scheme alone changes the performance reported by a commercial DES, together with a reproducible way of embedding mid-travel rerouting in such a tool. Experiments on a unidirectional-path AGV system in FlexSim, covering twelve combinations of fleet size and load/unload time with 1000 runs each, show that DDR and CDR reduce the blocked time of the static default by a median of 97.8% and 73.5%, respectively, while the median change in makespan remains below 2%; these reductions come at the cost of 7.2% and 37.2% longer travel distances, respectively, and the preferable dynamic scheme depends on the fleet size and the load/unload time. These results demonstrate that the routing scheme is a decisive lever for both DES model fidelity and the performance of the AGV systems they represent, and that it should be selected and reported explicitly rather than left at the default setting.

Systems doi: 10.3390/systems14111438

Authors: Chen Jiang Juhong Chen Hao Wang Chenyu Ouyang Wenjing Liao Di Wu

Existing studies on end-of-life EV battery collection mostly rely on engineering retirement thresholds, overlooking consumers’ subjective retirement behavior and potentially misestimating collection quantity and quality. We develop a dual Nash bargaining model for a closed-loop supply chain that accounts for consumers’ subjective retirement threshold, and analyze collection incentives, pricing, and echelon utilization decisions among a battery manufacturer, an EV manufacturer, and an echelon utilization product manufacturer under four organizational modes. The results show that a higher subjective retirement threshold increases the number of naturally retired batteries and the quality of collected batteries, while optimal collection incentives generally decline and eventually reach zero; bargaining power shapes operational decisions and firms’ cooperation choices by affecting echelon utilization returns, material recycling opportunity costs, and profit allocation within coalitions. The echelon coalition strengthens collection incentives and promotes echelon utilization, whereas the battery coalition must balance material recycling returns against the opportunity cost of echelon utilization; although the full supply chain coalition achieves the highest total supply chain profit, it does not necessarily maximize the EV manufacturer’s profit. These findings provide a basis for EV manufacturers to optimize collection incentives and select cooperation modes, helping promote coordinated development and resource circulation in closed-loop supply chains for end-of-life EV batteries.

Systems doi: 10.3390/systems14111437

Authors: Omar Alharasees Farzad Zolfaghari Haitham A. Al Hasanat Artūras Kilikevičius Utku Kale

Purpose: This exploratory study examined whether nonlinear, time-frequency, directional, change-point, and visibility graph measures characterize physiological reorganization during real-flight operational transitions and whether the observed patterns differ by flight experience. Methods: Heart rate variability (HRV), respiration, skin temperature, and movement were recorded from twelve male pilots, comprising six experienced and six non-experienced participants, during resting (REST), normal-flight (NOR), and emergency-failure (EF) conditions. Sample entropy (SampEn), approximate entropy (ApEn), detrended fluctuation analysis (DFA), recurrence quantification analysis (RQA), continuous wavelet transform (CWT), segment-level classification, Granger-predictive modelling, cumulative sum (CUSUM), Bayesian change-point detection, and natural visibility graph (NVG) and horizontal visibility graph (HVG) analyses were applied. Results: In the pooled series for each cohort and condition, SampEn increased from REST to EF from 0.8412 to 1.7918 in the experienced group and from 0.8294 to 1.4251 in the non-experienced group. DFA α1 increased from 0.5418 to 1.4872 in the experienced group and from 0.5102 to 1.0621 in the non-experienced group. Recurrence rate declined from 0.3223 to 0.2428 in the experienced group and from 0.3058 to 0.2344 in the non-experienced group. EF scalograms showed a broader, visually V-shaped energy envelope over scale. The classification analysis was treated as an exploratory assessment of discrimination among the 71 analyzed windows. In the cohort-level directional networks, respiratory-to-cardiac links remained visible across the experienced-group conditions, whereas fewer such links were present in the non-experienced EF network than in its REST network. Bayesian posterior peaks occurred near scenario transition indices 12 and 34. NVG density was lower in EF than in REST in the experienced group (0.3333 vs. 0.1283) and the non-experienced group (0.4091 vs. 0.1247). Conclusion: The coordinated analysis characterized condition-related physiological patterns across complementary system representations and described experience-related differences within the study cohort.

Systems doi: 10.3390/systems14111436

Authors: Yuna Wang Zhenpeng He Tao Yu Zhisheng Peng

Prefabricated buildings are assembled from components designed, manufactured, transported, installed, and operated by different participants. Digital technologies can give these distributed activities a shared description of component geometry, identity, status, and quality, but their value depends on information remaining usable at each handover. This study examines where digital inventive activity is located within that system and how its technical concerns change over time. We classify 538 retained Chinese granted invention patents by functional subsystem and filing period and then compare subsystem counts, subsystem-specific latent Dirichlet allocation topics, and cross-period semantic associations. Standardized design, on-site assembly, and digital management account for 434 patents (80.67%), with off-site manufacturing, intelligent operation, and integrated delivery less represented. Later themes draw greater attention to component parameterization, quality and assembly control, and management integration. The findings map uneven inventive representation and proposed technical solutions that increasingly address interfaces; they do not show realized coordination, environmental improvement, or that low-patenting functions are bottlenecks. As a diagnostic input to systems engineering, the framework can indicate which functional handovers merit requirements, ownership, traceability, and performance investigation.

Systems doi: 10.3390/systems14111435

Authors: Xin Cui Guangzheng Sun Qingchun Meng

Major emergencies generate an acute demand for timely and reliable information while simultaneously amplifying the risk of misinformation diffusion on social media platforms. The regulator therefore needs not only to identify individual pieces of misinformation but also to infer a platform’s privately known misinformation-risk type. We develop a mechanism-design model in which verifiable collaborative disclosure and external monitoring jointly reduce unidentified misinformation and support platform risk screening. Three mechanisms are examined: screening based on disclosure–monitoring bundles, disclosure-only regulation, and ex-post auditing supported by credible penalties. Under the specified incentive and feasibility conditions, screening produces different equilibrium regimes as the platform’s commercial return from unidentified misinformation changes. A central result is counterintuitive: the high-risk platform may optimally face lower disclosure and monitoring requirements because this limits the information rent earned by the low-risk platform. We further show that differentiated and uniform disclosure-only arrangements yield the same optimal expected regulatory payoff, while screening can outperform disclosure-only regulation. When screening and ex-post auditing both satisfy their respective optimality and feasibility conditions, their relative performance depends on a critical auditing-cost threshold and distinct participation requirements. These findings provide insights into coordinating information acquisition and risk screening under asymmetric information.

Systems doi: 10.3390/systems14111433

Authors: Adel Benhamed Emna Bouzayani

This paper examines whether digitalization is associated with stronger links between green finance (GF), renewable-energy innovation (REI), and the green low-carbon energy transition across 19 G20 economies over 2000–2025. A data-consistency audit corrects the low-carbon electricity input. The benchmark Green Low-Carbon Energy Transition index (GLCET_B) is a transparent four-pillar composite covering renewable deployment, power-sector decarbonization, energy efficiency, and coal exit; PCA-based, equal-weight, and indicator-exclusion variants serve as measurement-sensitivity checks. The empirical sequence distinguishes confirmatory evidence from exploratory diagnostics. For the preferred benchmark, the LREI × DIG interaction is positive in TWFE-DK (0.0631, p < 0.001) and remains significant under 999-replication country-level wild-cluster inference (p = 0.011), pooled Common Correlated Effects (wild p = 0.009), cluster-aware DML (wild p = 0.001), first differences, complete-observation sensitivity, and all leave-one-country-out samples. Heterogeneous-slope CCE Mean Group estimates remain positive (0.044–0.074) but imprecise, indicating an average rather than uniform association. By contrast, GF × DIG is not robust under conservative small-cluster inference. The subgroup evidence suggests that the LREI–digitalization complementarity is concentrated in emerging/lower-digitalization G20 economies, but this result is interpreted cautiously because the subgroup cluster counts are small and digitalization groups coincide with emerging/advanced status. All findings are interpreted as conditional panel associations rather than causal or long-run effects.

Systems doi: 10.3390/systems14111434

Authors: Yang Wang Saihong Wang Zuoji Dong

Blocked bank withdrawals generate concentrated funding requests and online discussion, while discussion activity and funding resolution can follow different timelines. This study develops a four-party evolutionary game of regulators, financial institutions, information disseminators, and claimants. Original posts, publicly visible comments, and public resolution documents from the Henan village bank event provide the practical setting for examining strategic evolution under funding and information conditions. Regulatory credibility promotes orderly waiting when payment capacity, executable advance-payment arrangements, and reliable information provide support. When proactive action benefits all parties and unresolved demands dissipate faster than financial and information pressure accumulates, the system returns to coordinated governance after small perturbations. This study integrates funding arrangements, information governance, and multi-actor strategic interaction into a unified framework to examine payment-risk governance following blocked withdrawals.

Systems doi: 10.3390/systems14111432

Authors: Chao Cheng Jinlin Zhang

Artificial intelligence (AI) increasingly generates candidate hypotheses and designs, but candidates become usable knowledge only after specialists validate them. We study how this division of labor shapes the substitutability between AI and specialists in research as a whole. When generation and validation share a pool of specialists, the aggregate elasticity of substitution is a weighted average of the elasticities within generation and between the two tasks, with a weight equal to AI’s share in generation times the share of specialists in validation. Optimal staffing raises this weight as AI becomes abundant, so research is more complementary than its generation stage, and AI’s output elasticity in research rises only while the aggregate elasticity exceeds one. Gains confined to generation draw specialists into validation; sufficiently large gains in validation reverse the flow. In dynamic general equilibrium, the aggregate elasticity is a sufficient statistic for local aggregate dynamics, so these dynamics cannot reveal the task structure, but staffing data can. In an illustrative calibration to proxy evidence, the aggregate elasticity is 0.95 and ignoring validation overstates AI’s output elasticity by 25 percent. Whether that elasticity is already declining is not robust: the aggregate elasticity exceeds one in 22 percent of parameter draws.

Systems doi: 10.3390/systems14111431

Authors: Xiao Wang Jianjun Zhang

Improving the coupling coordination degree between new-type urbanization and rural revitalization does not necessarily narrow their relative development gap, complicating the selection of future development pathways. This study integrates forecasts of 43 indicators for 30 Chinese provinces based on 2014–2023 data, fixed-boundary TOPSIS recalculation, system dynamics, and NSGA-II multi-objective optimization to evaluate policy portfolios for 2024–2035. The optimization considers mean coupling coordination, mean absolute relative development gap, and standardized intervention intensity. Under business as usual (BAU), the coupling coordination degree rises from 0.6515 to 0.7396, while the relative gap widens from 0.0050 to 0.0707. Three independent optimization runs yield an approximate merged nondominated set of 411 portfolios. Compared with BAU, the comprehensive compromise portfolio increases mean coordination by 0.001853 (0.2627%) and reduces the mean gap by 0.001793 (4.0929%), with an intervention intensity of 0.2589. Compared with the balanced coordinated development scenario, it achieves nearly the same mean coordination with a 6.94% smaller mean gap and 53.57% lower intensity. Nevertheless, the gap continues to widen. Joint sensitivity tests show that coordination gains persist across the tested settings, whereas gap reductions depend on calibration. Rural broadband receives high allocations across tested policy menus, while grassroots management allocations vary more with menu and weighting assumptions. The findings demonstrate the value of jointly evaluating coordination, relative score balance, and adjustment requirements, with policy priorities conditional on the specified decision space.

Systems doi: 10.3390/systems14111430

Authors: Bogdan Andrei Dumitrescu Florin Andrei Adrian Enciu Cătălina Adriana Hândoreanu Ionel Leonida

This paper examines how real house prices and residential building permits change after tighter mortgage-borrowing rules in 26 European Union countries over 2010Q1–2024Q4. Credit, housing transactions and construction are treated as parts of a system with feedback and different adjustment delays. Local projections follow prices and permits for up to twelve quarters after changes in loan-to-value or debt-service-to-income limits. The full panel indicates a negative medium-term price pattern. This finding is supported by some data and inference checks but not consistently by weighting or alternative definitions of policy events. Building permits show reductions at some horizons, without a persistent response across specifications. Their uncertainty intervals remain too wide to exclude economically meaningful changes at most horizons. The evidence therefore provides partial support for price moderation and more limited support for a sustained reduction in authorised development. Examining both outcomes shows why the assessment of mortgage regulation should extend beyond prices to the progress of residential projects. The policy discussion draws on the literature to consider financial safeguards, targeted housing assistance and measures that expand supply.

Systems doi: 10.3390/systems14111429

Authors: Ying Li Youyi Wei Yantong Jin Gang Wu Chaozhe Jiang Fang Xu

This study examines supplier selection, alliance formation, benefit allocation, and risk sharing under a reverse vision-driven supply chain framework, using CRRC Tangshan’s lightweight rail vehicle project as the case setting. A bilateral innovation-investment model is developed to compare independent investment under non-alliance conditions with coordinated surplus-maximizing investment under an assumed binding joint R&D arrangement. Ridge regression is trained using 32 evaluation indicators from 87 historical suppliers to predict the innovation efficiency of 18 candidate suppliers, from which the 14 highest-ranked suppliers are selected for subsequent alliance analysis. Supplier-specific innovation-resource costs and coordination costs are incorporated into the bilateral model to determine critical synergy thresholds for alliance formation and feasible benefit-allocation intervals under individual rationality. For risk sharing, the Delphi method is used to determine indicator weights, fuzzy comprehensive evaluation assesses participants’ risk-bearing suitability, and an adjusted Shapley-value approach determines risk-sharing responsibilities based on marginal contributions to collective risk-bearing capability and individual suitability. The results show that critical synergy thresholds vary across the 14 manufacturer–supplier dyads, ranging from 0.004 to 0.032, reflecting heterogeneous innovation efficiency and cost conditions. Under the baseline scenario in which synergy is set at 1.5 times each critical threshold, feasible benefit-allocation intervals differ across suppliers, primarily reflecting their non-alliance payoffs. The risk-sharing results assign 64.718% of the alliance risk responsibility to the focal manufacturer and 35.282% to the 14 suppliers collectively, while benefit-allocation positions and risk-sharing responsibilities exhibit only partial correspondence. Sensitivity analysis indicates that higher fixed coordination costs may make alliance formation economically infeasible at the assumed synergy levels, whereas the relative ordering of supplier benefit requirements remains stable across the examined economically feasible scenarios. The study’s research contribution lies in linking reverse vision-driven supplier identification with the economic conditions for alliance formation and distinguishing benefit-allocation requirements from risk-sharing responsibilities. These findings provide a case-based reference for assessing alliance formation, benefit-allocation feasibility, and risk-sharing arrangements under heterogeneous participant conditions.

Systems doi: 10.3390/systems14111428

Authors: Rim Ben Salem

Organisations rely on warnings, notifications, microlearning, and simulated exercises to promote secure employee behaviour, yet repeated exposure can reduce responsiveness to a specific intervention, and sustained exposure across interventions can make further automated intervention undesirable. This paper proposes an exposure-aware self-adaptive architecture that separates three runtime decisions: whether an observed behavioural gap requires a response, whether accumulated cross-intervention burden still permits automation or calls for human review, and which eligible intervention is currently most suitable. Candidate selection combines intervention-specific responsiveness, which decreases with exposure and recovers over time, with employee-specific efficacy learned from observed outcomes, so that each decision is traceable to auditable runtime state. The architecture is evaluated through simulation; no organisational or employee data are used. A policy-independent synthetic generator (144 worlds, replicated on 144 independent worlds) compares it with nine baselines, including the Upper Confidence Bound (UCB) policy UCB1, Thompson sampling, discounted UCB, a Linear Upper Confidence Bound (LinUCB) contextual bandit, and round-robin rotation. Where repeated delivery attenuates the specific intervention, the architecture exceeds UCB1 by 0.049 and its own ablation by 0.073 on a synthetic outcome scale, but is level with LinUCB and at most marginally ahead of Thompson sampling (differences of at most 0.005) and slightly trails rotation; without exposure effects, exploitative selectors perform better. The contribution is therefore an auditable organisation of adaptation responsibilities, not a superior selection algorithm.

Systems doi: 10.3390/systems14111427

Authors: Diego R. Hijano Daniel A. Clark Heather Schoch

Health systems must improve frontline processes rapidly while maintaining strategic alignment, regulatory responsiveness, organizational learning, and sustained performance. This conceptual article examines how the revised July 2026 Baldrige Excellence Framework can serve as an integrating system for structured rapid improvement. A framework analysis mapped the six 2026 categories, three maturity pathways, embedded results items, and ADLI/LeTCI evaluation logic to common functions of time-bounded, team-based improvement. Structured rapid improvement is defined as a method-neutral construct that combines an explicit aim, analysis of current conditions, iterative testing guided by timely data, and deliberate planning for implementation, spread, and sustainment. Pediatric immunization is used as an illustrative socio-technical system because reliable delivery depends on interdependent clinical, informational, workforce, communication, supply, and governance processes. The maturity pathways distinguish operational awareness, process discipline, and systems integration, while embedded results require attention to levels, trends, comparisons, and integration rather than isolated post-intervention gains. Organizational Intelligence, agility and resilience, and the cross-cutting treatment of artificial intelligence extend the framework beyond local workflow redesign. A regulatory adaptation vignette illustrates how frontline learning and redesign must connect with leadership, strategy, organizational knowledge, workforce capability, and operational oversight. We propose that structured rapid improvement may become more durable, transferable, and aligned with organizational priorities when local redesign is connected to governance, organizational learning, workforce capability, performance feedback, and adaptation within an integrated organizational system. These relationships represent proposed systems mechanisms that require empirical evaluation.

Systems doi: 10.3390/systems14111426

Authors: L. Taylor Starr Daniel R. Herber

Lean Six Sigma (LSS) is document-centered in many organizations: project charters, control plans, measurements, analyses, approvals, and verification records are maintained as separate files whose consistency depends on manual reconciliation. This paper presents Model-Based Six Sigma (MBSS), a reusable Systems Modeling Language (SysML) Profile that represents DMAIC governance, evidence, measurement, analysis, improvement, and control concepts inside a Model-Based Systems Engineering (MBSE) environment. This paper focuses on the Profile’s architecture, methodology, design rationale, and formal and practitioner-based validation methodology of the Profile, with its application in a wing structure case study left for a follow-on paper. The completed Profile contains 50 stereotypes, 264 typed tagged properties, 32 executable validation rules, and nine modeling-responsibility families, which can be applied to consuming cases as an imported model. It uses concrete UML and SysML bases (including Actor, Activity, Requirement, Value Property, Constraint Block, TestCase, and State Machine), where those native constructs provide the required semantics. It also separates observed values, historical benchmarks, approved plans, configured calculations, executed results, acceptance decisions, and verification evidence. We further formalize the metamodel’s central single-source-of-truth design commitment as a structural design invariant, supported by stable element identity, provenance, version-controlled links, and tiered evidence records, that pursues the same anomaly-avoidance principle that underlies relational data normalization. None of the 32 rules checks for duplicate authoritative copies, so this commitment is not an automated check. All 32 validation rules execute against the completed Profile with zero violations on the accepted consumer baseline. Of these, two representative rules were additionally confirmed through an external neutral test harness to detect a controlled, single-element defect and to return to a zero-violation state after correction, and the other 30 have not yet been tested by defect injection. The completed metamodel was separately assessed for structural completeness by senior modeling practitioners. Empirical deployment, statistical validation, and a native Defects Per Million Opportunities and Sigma Level capability pathway are completed but left for follow-on papers.

Systems doi: 10.3390/systems14111425

Authors: Muhamed Begović Ahmad B. Hassanat Amel Kosovac Adnan Omerhodžić Teodora Kovačević

Reliable classification of the severity of traffic accidents requires appropriate treatment of class imbalance. This paper applies machine-learning methods to a verified and standardised database of police-recorded injury accidents from Sarajevo Canton, Bosnia and Herzegovina: 1517 accidents from August 2019 to December 2025, with 28 predictors. Severity was defined as a binary Killed or Seriously Injured (KSI) outcome: 410 Major (27.0%) and 1107 Minor (73.0%) accidents. Seventeen classifiers and a soft-voting ensemble were compared under 10 × 10 repeated stratified cross-validation, with Major-class recall as the primary measure. Precision, F1, balanced accuracy, the areas under the receiver operating characteristic and precision–recall curves (ROC-AUC, PR-AUC), and calibration were also reported. Classifiers were compared with the Nadeau–Bengio corrected resampled t-test. Random Data Partitioning with Voting Rule (RDPVR; recall 0.822 ± 0.056) and Balanced Random Forest (0.821 ± 0.063) recognised the most KSI accidents and did not differ significantly. The soft-voting ensemble and cost-weighted eXtreme Gradient Boosting (XGBoost) offered a better precision–recall balance (F1 0.749 and 0.733) and better-calibrated scores than these two ensembles. Leak-free threshold tuning moved the models along the precision–recall trade-off without materially changing F1. SHapley Additive exPlanations (SHAP) and permutation importance identified pedestrian involvement, location, accident year, primary-road category, and vertical geometry as the most important predictive features. Because police coordinates are approximate, a supportive analysis without them was also run: recall of the two leading ensembles fell only slightly, to 0.79–0.80. Performance was largely retained under spatial block validation. Forecasting from earlier years worked for 2022 (ROC-AUC 0.77–0.82) and moderately for 2023 (0.61–0.78), but collapsed for 2024–2025 (0.34–0.57). The models are post-crash severity classifiers, not prospective crash-location predictors, and must be revalidated before being applied to later years.

Systems doi: 10.3390/systems14111424

Authors: Jhon M. Lopez-Rodriguez Luis J. Mena Vanessa G. Félix Vicente García Homero Toral-Cruz Rodolfo Ostos Alberto Ochoa-Brust Djallel Eddine Boubiche Lyamine Guezouli Rafael Martínez-Peláez

Human behavior in cybersecurity results from the interplay among individual appraisals, organizational conditions, technological factors, and adversarial contexts. This structured literature review investigates the functions of behavioral theories, their extensions and integrations, and the explanatory roles attributed to seven sociotechnical dimensions. We conducted four topic queries in the Web of Science Core Collection in January 2026 and updated the screening in October 2026, targeting journal articles published between 2015 and 2025. After deduplication, 50 unique records remained from an initial 57. Title and abstract screening identified 28 relevant reports; three full texts were unavailable, leaving 25 studies meeting the final eligibility criteria. Protection Motivation Theory (PMT) was central to seven studies, explicit sociotechnical perspectives to four, and the Theory of Planned Behavior (TPB) to three. Cognitive mechanisms were empirically examined in 18 studies, while adversarial factors were contextualized in 21; this evidence reflects model roles rather than effect sizes. Theories combined appraisal and intention with social relationships, organizational factors, technology adoption, and computational modeling. The evidence base ranged from conceptual frameworks to simulated or observed behaviors, with clear distinctions between intentions, self-reported practices, and demonstrated security outcomes. This synthesis offers an evidence-based framework for selecting complementary explanations and guiding future empirical investigations of cybersecurity behavior.

Systems doi: 10.3390/systems14111422

Authors: Yuchen Cao Haifeng Gu

Existing research has largely examined digital transformation within individual organizations, paying limited attention to digital interdependence among actors within business ecosystems. Using panel data on Chinese A-share listed firms from 2013 to 2023, this study examines the relationship between bank–enterprise digital collaboration (BEDC) and corporate cross-regional investment. The results show that BEDC is positively associated with corporate cross-regional investment. Mechanism analyses provide suggestive evidence consistent with an improved information environment and greater access to bank credit as two potential channels. Further analyses show that this positive association is stronger among smaller firms and firms with lower geographic proximity to banking services, weaker lending relationships, lower industry entry barriers, and less developed local digital infrastructure. Economic consequence analyses further show that BEDC weakens the positive association between cross-regional investment and both investment inefficiency and overinvestment, with this moderating pattern becoming more pronounced as cross-regional investment increases. These findings suggest that cross-organizational digital collaboration may facilitate cross-regional resource flows and shape spatial resource allocation within business ecosystems.

Systems doi: 10.3390/systems14111423

Authors: Konstantinos I. Efthymiadis Athanasios P. Vavatsikos

Environmental, social and governance factors now shape corporate and investment decisions, driven by disclosure regulation and investor demand for comparable non-financial information. Evaluating such performance means combining conflicting, partly qualitative criteria on incommensurable scales, precisely the problem that multicriteria decision analysis was designed to solve. Existing reviews report which methods the field uses, not how these methods are combined, leaving the structural assumptions of the resulting frameworks unexamined. This review addresses that gap. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 statement, 105 peer-reviewed English-language publications from 2016 to 2026 were identified in Scopus (last searched on 30 June 2026). Each study is classified by the role these criteria play in it, and each framework as a three-stage decision system: weighting, standardization onto commensurable scales, and aggregation into a ranking. Design effort is uneven across the three stages: 48 distinct weighting procedures and 54 aggregation rules, against only 12 standardization procedures, two of which cover almost two thirds of the studies. Three quarters of frameworks let performance in one pillar offset performance in another, and almost none report how it would be recalibrated as conditions change. Both findings matter where such frameworks inform investment screening and supplier selection under continually changing disclosure rules. An eight-point research agenda follows.

Systems doi: 10.3390/systems14111421

Authors: Sijun He Wenlong Wang Ning Lu Tiecheng Ding Wenwen Chen

Passenger information systems help metro passengers access real-time operational information, yet the relationships between regional cultural design in these interfaces and passengers’ perceptions and usage intentions remain underexplored. This study extends the theory of planned behavior (TPB) by incorporating regional cultural presentation, perceived cultural identity, and trust to examine passengers’ intention to use regional culture-themed passenger interfaces (RCPIs). Survey data from 712 valid respondents, measured using 27 observed variables, were analyzed with partial least squares structural equation modeling. Attitude, subjective norm, perceived behavioral control, and trust directly predicted usage intention, with trust having the largest direct coefficient. Perceived cultural identity did not directly predict intention but acted indirectly through trust. Regional cultural presentation was positively associated with cultural identity and trust. These findings characterize associations among passengers’ evaluations of regional cultural presentation, perceived cultural identity, trust, and usage intention in metro passenger interfaces. The study provides context-specific evidence on passengers’ responses to regional culture-themed interfaces within an extended TPB framework and offers implications for interface design.

Systems doi: 10.3390/systems14111420

Authors: Shuang Yang Yanli Wang Qingnan Bu Liyun Han

Improving the quality of corporate environmental information disclosure (EID) can be framed as a multilevel principal–agent problem involving the central government, local governments, and firms. This study develops a central–local–firm evolutionary game model and exploits China’s Environmental Protection Admonishing Talk (EPAT) policy in a staggered difference-in-differences framework to examine how vertical accountability affects corporate EID quality. Using A-share listed firms from 2008 to 2020, we find that EPAT significantly improves EID quality, with the baseline estimate indicating an average increase of approximately 1.8 percentage points. The result remains positive across alternative staggered-DID estimators and a range of robustness checks. The enforcement-related results further show that EPAT is associated with higher local environmental protection expenditure and more environmental penalties, consistent with strengthened local environmental enforcement. The findings suggest that vertical accountability can improve EID quality and help mitigate principal–agent frictions in the EID process among the central government, local governments, and firms.

Systems doi: 10.3390/systems14111419

Authors: Ruiyang Sun Xiaofang Jin

Digitised community social-work services distribute access across digital, assisted, in-person, and outreach routes. This qualitative case study addresses a service-system problem: support can complete one task while the route to the next service stage and professional contact remains uncertain. Station A in Guangdong, China, was analysed through semi-structured interviews with 20 participants—eight older service users, six family members, three frontline social workers, one station manager, and two community volunteers—together with observation, service and activity records, platform materials, and policy documents. Eight focal service-user accounts formed the comparison. The analysis developed six case-derived access positions: independent digital access, assisted transition, visit-dependent contact, scheduled outreach, entry blockage, and informal fallback. Across these positions, service access depended on the fit among service stage, task requirements, scope of assistance, route convertibility, and professional-contact conditions. Registration assistance enabled entry in one episode, followed by an in-person route for the next service task. Offline routes produced contact conditions ranging from visit-dependent contact to scheduled outreach. The article develops stage–route–contact alignment to explain how support for one task and the route available for the next shape service continuity. The framework links these arrangements to the timing, directness, and continuity of professional contact.

Systems doi: 10.3390/systems14111417

Authors: Kyung-In Lim Seong-Ick Hong

Accelerating the circular economy transition requires policy arrangements that connect recurring resource-conversion activities, economic incentives, and credible verification across production systems. This study develops a systems policy framework for upcycling by linking consumption-tax incentives to verified circular material flows. Upcycling is conceptualized as a multi-actor material-conversion system integrating interdependent material, fiscal, and information-verification flows. The study combines qualitative comparative policy analysis and framework synthesis. Statutes, official policy documents, government guidance, and international-organization reports are analyzed by the policy functions they perform within the circular material-conversion system, including intervention stage, target activity, support basis, timing and refundability, and verification requirements. The analysis identifies a relative functional gap at the recurring acquisition-input-conversion stage: reviewed instruments commonly support specific products, transactions, capital investment, taxable income, or virgin-material disincentives, rather than verified and repeated resource conversion after commercialization. The proposed framework links incentives to verified acquisition, actual production input, and value-enhancing conversion. It establishes activity-based eligibility criteria and incorporates traceability requirements, safeguards against duplicate claims and excessive fiscal exposure, ex post verification, recapture, and periodic review. The resulting principles can be translated into VAT/GST-linked credits or refunds, separate business tax credits, environmental-tax mechanisms, and other fiscal architectures.

Systems doi: 10.3390/systems14111418

Authors: Lei Wang Rui Wang

Green development is confronted with the challenge of achieving a win–win outcome for both the economy and the environment. Digital and intelligent transformation offers a critical opportunity for the green development of enterprises. Drawing on panel data of Chinese A-share listed companies from 2015 to 2024, this study adopts a capability–resource synergy framework and employs empirical methods to investigate the complex mechanisms through which digital and intelligent transformation affects green technology innovation. The results indicate that digital and intelligent transformation significantly promotes green technology innovation among Chinese enterprises. Further analysis reveals that increasing government subsidies and enhancing absorptive capacity are two important mechanisms through which digital and intelligent transformation drives green technology innovation. Moreover, absorptive capacity also plays a threshold role. Heterogeneity analysis shows that the positive effect of digital and intelligent transformation on green technology innovation is more pronounced in state-owned enterprises, manufacturing firms, and heavily polluting enterprises. By adopting absorptive capacity as a theoretical lens, this study provides a knowledge-based explanation of how digital and intelligent transformation influences green technological innovation. Importantly, absorptive capacity serves a dual mediating and threshold function, which enhances the explanatory power and ensures a more comprehensive mechanistic analysis.

Systems doi: 10.3390/systems14111416

Authors: Leyla Gamidullaeva Sergey Vasin Natalia Roslyakova

Regional innovation policy requires well-founded choices of regions for comparative learning. This study examines whether similarity in economic structure helps identify persistent innovation benchmarks across 85 Russian territories in 2019–2021. Employment shares describe economic structure, while data envelopment analysis (DEA) relates innovation expenditure to innovative output in the following year. Structurally selected benchmarks are compared with alternative approaches, including random reference sets. We distinguish ratio retention (a sustained advantage in innovative output relative to expenditure) from projection participation (the possibility of contributing to the same recipient’s later optimal DEA projection). The latter criterion is exploratory. In the main specification, ratio retention occurs in 78.3% of initially selected peer–recipient pairs, while both conditions hold in 55.1% (joint retention). Structural selection shows no clear persistence advantage over random reference sets. Sustained relative performance therefore does not ensure continued DEA reference status. For regional authorities, the framework supports the periodic reassessment of comparison regions and the selection of cases for closer investigation of innovation performance. It does not establish the effects of policy transfer. Broad sector categories, nominal monetary indicators and a single subsequent evaluation window limit generalization.

Systems doi: 10.3390/systems14111415

Authors: Angelo Maurizio Galiano Giuseppe Dell’Erba Alberto Costantiello Cosimo Magazzino Angelo Leogrande

The Regional Innovation Scoreboard is the principal evidence base for European regional innovation policy. This paper asks what that source can identify, using the sales of new-to-market and new-to-firm innovations across 218 European regions over four Community Innovation Survey waves as a demonstration case. Three boundaries emerge. First, the annual file replicates biennial survey values, so the nominal eight-year panel holds four independent observations per region; ignoring this understates standard errors on registry indicators by up to 40 per cent and reverses one coefficient sign. Second, the leading regressor is negatively associated with innovative sales between regions and positively within them, and leave-one-country-out validation fails in levels but not on within-region deviations, locating much of the between variation in a national component, whether it reflects survey implementation or genuine national differences. Third, flexible learners outperform the linear specification only when validation folds share information within regions and country-waves, a result that rests on 218 regions and 21 countries, since the four survey waves alone could not rank the learners. Within these boundaries, only the SME product innovation incidence, partly linked to the outcome by definition, and trademark activity are associated with innovative revenue, and all estimates are correlational. A taxonomy built on the inputs alone is nearly orthogonal to the official classification. The Scoreboard supports longitudinal inference about a region’s own trajectory, not cross-sectional benchmarking.

Systems doi: 10.3390/systems14111414

Authors: Yi Li Lingqing Dong Zhixiang Yin Zhenbang Yue Li Li

Drawing on China’s Green Factory initiative and data from Chinese A-share listed manufacturing firms in the Shanghai and Shenzhen from 2012 to 2024, this study employs a staggered difference-in-differences model to examine the effect of green industrial policy on firms’ persistent green innovation. The results show that green industrial policy significantly promotes sustained green innovation. Mechanism analyses indicate that green industrial policy significantly promotes both knowledge recombination creation and knowledge recombination reuse, and both types of knowledge recombination are significantly positively associated with firms’ persistent green innovation. Heterogeneity analyses show that the effect is more pronounced in regions with stricter environmental regulation, firms with lower levels of green innovation bubbles, and firms with broader innovation boundaries, while it is weaker under less stringent regulation, more severe innovation bubbles, or narrower innovation boundaries. These findings provide empirical evidence and policy implications for jointly advancing economic development and environmental protection.

Systems doi: 10.3390/systems14111413

Authors: Kai Kang Yonghong Cheng

Artificial intelligence (AI) offers firms new ways to detect changes in their business environment. We examine how AI adoption relates to firm resilience, focusing on investment decisions and post-shock adjustment. Our sample comprises 44,855 firm-year observations of Chinese nonfinancial A-share listed firms, with resilience measured by annual changes in total factor productivity. We estimate models with firm and year fixed effects and conduct robustness checks using alternative measures and sample restrictions. We also estimate instrumental variable models using the interaction between a post-policy indicator and firms’ pre-policy AI adoption as the instrument. We find a positive and significant association between AI adoption and next-year firm resilience. The main robustness checks and instrumental variable estimates yield results in the same direction. To examine the investment allocation channel, we measure AI adoption, investment allocation, and resilience in successive years and use a firm-level bootstrap for inference. The results support a channel through reduced investment inefficiency. Evidence is significant for the overinvestment channel, but not for the underinvestment channel. Using the COVID-19 pandemic as a shock, we examine post-shock adjustment through cross-sectional regressions and dynamic panel analysis. Firms with higher pre-shock AI adoption experience larger subsequent rebounds and are more likely to return to their pre-shock level. The association with initial losses is not statistically significant. By distinguishing between types of investment deviation and examining post-shock recovery, this study provides evidence on how AI adoption relates to firms’ resource allocation and adaptation over time.

Systems doi: 10.3390/systems14111412

Authors: Angelo Maurizio Galiano Giuseppe Dell’Erba Cosimo Magazzino Alberto Costantiello Angelo Leogrande

The Regional Innovation Scoreboard ranks European regions by a composite index but reveals little about how innovation performance is composed, how persistent it is, and whether it translates into prosperity. Using data for 245 regions in 31 countries over 2016–2023, this study addresses three research questions with panel econometrics, cluster analysis, and machine learning. First, dynamic panel estimates that treat the indicators as endogenous indicate substantial persistence in performance and show that its most robust correlates are non-R&D investment and innovation and collaboration among small- and medium-sized enterprises. Second, clustering the components of the index, rather than the index itself, identifies ten innovation profiles that are weakly aligned with the official performance groups and correspond to distinct development models, from science-intensive metropolitan cores to fast-growing catching-up regions. Third, with GDP per capita as an external outcome and region-grouped validation, the indicators account for about two-thirds of cross-regional differences in prosperity, and their composition provides additional predictive information beyond the composite index, although they carry little information on short-run growth. Read together, the results show that stable rankings conceal changing configurations, that convergence has relied largely on factors other than innovation, and that policies should address region-specific bottlenecks.

Systems doi: 10.3390/systems14111411

Authors: Haibo Jia Jiaming Sun Can Liu Weifeng Huang Wanying Song

Using questionnaire data collected in 2019, this study examines how preparation conditions relate to perceived government financial reporting quality (GFRQ) in the first year of China’s new government accounting system. The multilevel socio-technical systems (MSTS) framework distinguishes departmental reporting as an operational layer and consolidated reporting as an integration layer. Separate respondent-level regressions use 5157 departmental and 672 consolidated questionnaires; they estimate associations within each report type, without testing interactions or information transmission between layers. Policy cognition and institutional support, and information systems and data integration are positively associated with GFRQ in both samples. Accounting foundation and accrual implementation are significant in the departmental sample. The prespecified coordination and supervision index is positive in both baseline models, although departmental inference is sensitive to scoring. These findings describe preparation conditions and quality evaluations in the 2019 survey. Comparisons across report types are descriptive; coefficient equality has not been formally tested. Cross-layer transmission and feedback remain theoretical propositions, while suggestions on responsibility tracing, reconciliation and error correction are directions for subsequent evaluation. The results are bounded by the survey’s institutional and technical context and do not establish later reform outcomes or current governance performance.

Systems doi: 10.3390/systems14111410

Authors: Jingzhao Zhu Sheng Mai Qian Chen Lingling Li

In the digital era, computing power deployment has emerged as a strategic resource for building enterprise innovation resilience; however, the mechanisms through which it exerts such effects remain unclear. Drawing on dynamic capability theory, this study examines how computing power deployment influences enterprise innovation resilience using a sample of Chinese A-share listed firms from 2012 to 2024. The results indicate that computing power deployment significantly enhances enterprise innovation resilience, and this finding holds after a series of robustness checks. Mechanism analysis shows that computing power deployment exerts its effects through two pathways: technology diversification, which strengthens knowledge recombination and trajectory switching capabilities, and organizational inertia, which ensures innovation process continuity and frees cognitive resources for higher-order reconfiguration. Heterogeneity analysis reveals that the effect is stronger among state-owned enterprises, large firms, firms in strategic emerging industries, and firms with high patient capital, reflecting four boundary conditions: resource foundation, organizational carrier, environmental fit, and temporal support. This study extends the antecedent research on innovation resilience by introducing the computing power perspective, reveals the transformation mechanisms and boundary conditions of computing power deployment, and provides implications for innovation resilience building and computing power resource allocation in the digital economy.

Systems doi: 10.3390/systems14111409

Authors: Kuan-Lung Daniel Chen Fatima Waseem Kristen Hayes Uriyoán Colón-Ramos

Background: Nutrition security is the ability to access, afford, prepare, and incorporate nutritious foods into daily life. Washington, DC’s Wards 7 and 8 have long experienced inequitable investment in food infrastructure, which is part of a complex place-based system, resulting in disparities in nutrition security and subsequent diet-related health outcomes. Methods: We worked with a Community Advisory Board composed of Wards 7 and 8 residents and practitioners across different sectors to map the complex system driving nutrition security in their community. Through a series of group model building activities, a causal loop diagram was synthesized by university researchers and presented back to the Community Advisory Board for feedback and edits. Results: The causal loop diagram (CLD) includes 26 variables and 11 highlighted feedback loops. The CLD spans individual healthy eating behavior, community norms, community ownership of food operations, and public policy. Discussion: The diagram provides a shared systems representation of the factors shaping nutrition security and identifies feedback structures and potential leverage points for collective action. We applied the social ecological model to analyze potential strategies for strengthening each level of feedback loops to promote healthy eating and achieve nutrition security.

Systems doi: 10.3390/systems14111408

Authors: Mehdi Safaei

Pharmaceutical supplier audits use different evidence related to service continuity, quality, traceability, and temperature control. This study uses seven operational indicators to examine whether three resilience-related profiles, assigned by an internal committee of five members, can be reproduced. It does not aim to predict independently observed disruption outcomes. The dataset covers 12 months of 2025 and contains 13,318 recorded evaluations of 441 anonymized suppliers from seven distribution hubs. In the ten-fold nested evaluation, suppliers were grouped and tree depth was selected within the inner folds. The decision tree obtained an accuracy of 0.9532, with a 95% t-based confidence interval of 0.9503–0.9562. Its macro-F1 was 0.9552 (0.9524–0.9579). For the October–December temporal test, suppliers had already appeared in the January–September training data. The accuracy was 0.9499. A further time-aware evaluation, with suppliers kept separate between training and testing, gave an accuracy of 0.9496 within the same pharmaceutical distribution network. This result does not represent external validation. In the test data permutation importance results, order fulfillment performance, the positively oriented Good Manufacturing Practice (GMP) alert score, and cold-chain logistics made the largest contributions. The committee classifications had limited agreement with clusters obtained using K-means, hierarchical clustering, and density-based clustering. The level of agreement also changed depending on the method selected. The trained decision tree has a depth of five, and its decision paths can be examined by human reviewers. These results show the agreement of the model with the committee’s recorded profiles. They do not show that actual shortages, disruptions, or recovery times can be independently predicted by the model.

Systems doi: 10.3390/systems14111407

Authors: Han Xiao Qi Tang

Renewable power fluctuations and uncertain ammonia synthesis performance complicate operational coordination in green hydrogen–ammonia systems. This study develops a closed-loop prediction–scheduling framework using dual Gaussian processes to characterize renewable power and process performance. Calibrated lower and upper bounds enter material and energy constraints, while multi-objective particle swarm optimization balances operating cost and schedule variation. A joint-risk index selects plan retention, local repair, or global re-optimization, combined with plan refresh and conditional Pareto reuse in rolling horizon scheduling. The framework is evaluated with 24 h aggregated simulations using public meteorological data and published experimental data. Paired comparisons across seven fixed scenarios show that event-triggered and periodic scheduling both completed all 20 runs per scenario while satisfying all hard constraints. Under the reported serial timing protocol, event triggering reduced total controller runtime by 15.30–34.73%. Of 234 supplementary stress-test requests, 177 completed the day, including 176 that satisfied all hard constraints and one with a terminal audit failure; 57 stopped during the search. These results show that the framework coordinates probabilistic prediction, physical constraints, and scheduling responses under the specified simulation conditions, providing a reproducible approach to operational optimization of green hydrogen–ammonia systems.

Systems doi: 10.3390/systems14111406

Authors: Yunfang Peng Chunfeng Wang Lijun Zhang Beixin Xia

To solve the Type-II two-sided assembly line balancing problem with alternative precedence relations, a mixed-integer programming (MIP) model and a constraint programming (CP) model are established, respectively, based on precedence graphs and if–then rules. Some small-sized instances are tested to verify that the CP model performs faster and better than the MIP model. For the large-sized problems, an adaptive iterative greedy (AIG) algorithm is proposed by improving the existing iterative greedy (IG) algorithm. In the initialization phase, the insert operation based on not violating the precedence relations is adopted. The adaptive neighborhood and operator selection mechanism are introduced in the local search phase. Comparing the results of the AIG algorithm with the MIP model and CP model, the proposed algorithm can effectively solve this problem. Computational results also reveal that the AIG algorithm performs better than the original algorithm in terms of solution quality and stability. Nevertheless, as a heuristic, the AIG algorithm cannot guarantee global optimality.

Systems doi: 10.3390/systems14111404

Authors: Marko Vulić Roberto Lujić Tomislav Šarić

Complex socio-technical decisions require explicit links between environmental analysis, strategic diagnosis and quantitative assessment. This study examines a sequential decision-support procedure using political, economic, social and technological (PEST) analysis, strengths, weaknesses, opportunities and threats (SWOT) analysis, the TOWS matrix and the Analytic Hierarchy Process (AHP). The approach is demonstrated by comparing five infantry fighting vehicles across five economic and operational criteria. PEST and SWOT inform the decision context and criteria but are not mathematically converted into AHP weights; the AHP pairwise comparisons were performed by the authors. Recalculation from the reported pairwise matrices yields a global priority of 0.318 for Bradley ODS. Controlled sensitivity analysis retains this alternative in first place in all 30 tested single-criterion perturbations, although some lower positions change. A supplementary Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) comparison likewise ranks Bradley ODS first but does not reproduce the entire AHP ordering. This study offers a reproducible case-based evaluation of an established combination of methods rather than a new decision algorithm; generalisation and independence of judgments remain limitations.

Systems doi: 10.3390/systems14111405

Authors: Arif Yildirim

Human–AI decision authority is analyzed in relation to changes in relative competence and decision risk, taking institutional oversight capacity into account. The proposed Co-Agency Equilibrium Theory (CAET) and Co-Agency Equilibrium Model (CAEM) offer a sociotechnical perspective on humans and AI working as co-agents with varying shares of decision authority. CAET is a normative design framework connecting relative competence, moral salience, irreversibility and independent oversight capacity with human authority and a normalized risk–oversight gap. CAEM combines a logistic policy surface, accountability gap feedback and a gradual adjustment of the human control level, with a switch to full human control if moral salience or irreversibility reaches or exceeds the corresponding threshold. The decision to switch is implemented in the following episode. The fixed point is also a unique point in cases of constant external inputs and convergence is achieved when the computed sufficient condition is satisfied. The authority boundary identifies whether the risk that is ceded to AI is within oversight capacity. Simulations use matched inputs for the feedback and no-feedback cases, covering coupled risks, changing capacity, noise and alternative risk functions. Even after the allocation has stabilized, a positive gap may remain due to a lack of sufficient capacity to oversee. In the example with time-varying capacity, feedback cut the cumulative positive gap by 6.4%; this was accompanied by more time with a positive gap and greater variation in authority. Delay in takeover means there is an extended period of exposure before people have effective control. These conclusions concern the model and its assumptions. The findings are not empirical validation, nor able to guarantee accountability or even safety.

Systems doi: 10.3390/systems14111403

Authors: Mengfan Sheng Zhiqiang Hou

Urban agglomerations are complex systems in which industrial, land, and economic subsystems coevolve. Using panel data from 48 cities in the Beijing–Tianjin–Hebei, Yangtze River Delta, and Pearl River Delta agglomerations from 2013 to 2023, this study examines how industrial structure optimisation (ISO) relates to urban economic resilience and how industrial land-use efficiency (ILUE) conditions this relationship. The coupling coordination degree (CCD) between ISO and ILUE is used to describe subsystem coordination states. The results show that ISO is positively associated with resilience in the full sample and in both Beijing–Tianjin–Hebei and the Yangtze River Delta, while the coefficient is positive but not significant in the Pearl River Delta. ILUE significantly strengthens the ISO–resilience relationship. CCD-based subgroup analysis further suggests a state-dependent pattern: in low-CCD systems, ISO and ILUE exhibit significant independent effects, whereas in high-CCD systems, these direct effects weaken and resilience gains are concentrated in their joint configuration. The moderating effect is significant across all three agglomerations and is particularly pronounced in the Pearl River Delta. These findings indicate that the resilience effects of industrial upgrading depend not only on land-use efficiency, but also on the coordination state of the industrial–land system.

Systems doi: 10.3390/systems14111402

Authors: Jie Chen Jiameng Yang Mengyuan Qiu Wenrui Zhang Suwan Li

Green travel is an effective approach to reducing carbon emissions from urban transport and promoting sustainable urban development. However, the factors influencing residents’ green travel behavior and the process through which travel intentions are translated into actual behavior remain insufficiently understood. This study aims to clarify how environmental conditions shape the relationship between green travel intention and behavior and to identify combinations of psychological and environmental factors associated with high levels of green travel behavior. To this end, it integrates the Theory of Planned Behavior (TPB) with Behavior Setting Theory (BST) to examine urban residents’ green travel behavior within a resident-level behavioral system. Environmental factors are classified into three dimensions to investigate how they moderate the relationship between green travel intention and behavior. Data from 707 valid questionnaires collected from residents in Nanjing, China, were analyzed using structural equation modeling (SEM). Fuzzy-set qualitative comparative analysis (fsQCA) was further employed to identify multiple configurations associated with high levels of green travel behavior. The results indicate that attitude, subjective norm, and perceived behavioral control positively influence green travel intention. Green travel intention, in turn, significantly promotes green travel behavior. Furthermore, the natural, built, and technological environments all strengthen the relationship between green travel intention and behavior. The fsQCA results identify six configurations grouped into three broader types, demonstrating that high green travel behavior can arise from multiple combinations of psychological readiness and environmental support. These findings clarify how individual decision processes and environmental conditions jointly shape behavioral outcomes. They also provide practical guidance for designing targeted policies to promote sustainable urban mobility.

Systems doi: 10.3390/systems14111401

Authors: Quhan Chen Li Zhu Haoyu Deng Huichao Wu

Resource-constrained cities often face aging infrastructure, fragmented governance, ecological risks, and limited public finance. These pressures are acute in historic districts, where heritage protection overlaps with residents’ everyday needs. This study examines a place-based micro-renewal project in Xiangtan, a resource-constrained legacy industrial city in central China, where urban renewal practices have received national-level recognition. It asks how micro-renewal can reconfigure blocked relations within a local urban system and whether these changes exhibit features associated with adaptive governance under fiscal and spatial constraints. The study combines the socio-ecological-technical systems (SETS) framework with Actor-Network Theory (ANT) and draws on institutional archives, semi-structured interviews, and participant observation. The findings identify three mechanisms: informal coordination, pragmatic recombination of institutional and technical resources, and cross-scale feedback between local implementation and higher-level review. These mechanisms helped reconnect fragmented actors and resources and enabled local adjustment during project implementation. The observed patterns of coordination, feedback, and adjustment are consistent with features of adaptive governance, while their contribution to durable adaptive capacity and longer-term urban resilience requires further longitudinal evidence. This study contributes to urban systems research by showing how place-based micro-renewal can reconfigure fragmented institutional, technical, and material relations during implementation in resource-constrained historic districts.

Systems doi: 10.3390/systems14111400

Authors: Sofiya Shevtsova Omar Ameir Šárka Vilamová Kamila Janovská Ondřej Grycz Lukáš Raszka

The transition toward a circular economy (CE) represents an urgent industrial imperative under the European Green Deal, requiring fundamental restructuring from linear throughput to closed-loop socio-technical systems. While small and medium-sized enterprises (SMEs) constitute over 99% of European businesses and generate two-thirds of private-sector employment, their circular adoption remains critically fragmented and restricted to incremental eco-efficiencies. Contemporary scholarship exhibits a profound theoretical divide: the firm-centric adoption literature frequently relies on an atomistic analytical perspective that presumes resource-poor enterprises can unilaterally resolve complex supply-chain interdependencies, while regional cluster economics maintains a passive agglomeration bias that neglects purposeful sustainability governance. Building on a theory-driven conceptual review of 65 scholarly works identified through structured database searches and citation chaining, this study proposes an integrative Macro–Meso–Micro framework explaining how innovation cluster governance may facilitate circular economy adoption among SMEs. The framework specifies four interrelated governance mechanisms: cross-boundary standards alignment, collective risk-sharing, collective learning, and intermediary orchestration. It further identifies boundary conditions—including anchor-firm capture, cognitive lock-in, and intermediary funding dependency—that may constrain the effectiveness of these mechanisms. Conceptually, the framework treats circularity among SMEs not solely as a firm-level attribute, but also as a potential emergent property of coordinated meso-level governance. Finally, we delineate an empirical agenda using Social Network Analysis, Structural Equation Modeling, and fuzzy-set Qualitative Comparative Analysis, and suggest considering complementary policy portfolios combining firm-level capability development with selective investment in shared coordination and testing infrastructures. The proposed relationships and their boundary conditions require further empirical validation across different industrial and institutional contexts.

Systems doi: 10.3390/systems14111399

Authors: Yuhao Zhang Svetoslav G. Georgiev Yang Cao

Demand forecasting and inventory management have evolved as parallel bodies of literature, despite their operational interdependence, and the resulting disconnect between prediction and decision has been diagnosed as a standing gap in operational research. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) protocol, this review systematically codes 46 studies published between 2010 and 2023 in journals listed by the Australian Business Deans Council, operationalizing an established prediction–inventory integration hierarchy to evaluate how modern artificial intelligence architectures couple prediction with decision-making. We find that predict-then-optimize (PtO) and end-to-end or joint learning (E2E) architectures co-evolve rather than succeed one another. Crucially, integration level is orthogonal to model class: seven of the seventeen E2E studies use no neural network, so decision-focused coupling does not inherently require the opacity of deep learning. Instead, architecture performance is highly contingent on a domain’s data regime and cost structure rather than algorithmic sophistication alone. We provide a contingency framework equipping academic researchers, analytics practitioners, and supply chain managers with actionable architecture-selection guidance, identifying hybrid PtO–E2E designs, which remain absent within this corpus, as the unresolved structural frontier of the predictive AI era.

Systems doi: 10.3390/systems14111398

Authors: Wontae Seo Wonil Hwang

Despite substantial investments in artificial intelligence (AI) training, logistics organizations often struggle to translate these investments into measurable improvements in employee performance. Drawing on the extended Technology Acceptance Model (TAM), Cognitive Load Theory, and Distributed Cognition Theory, this study examines how three AI-TPACK training dimensions—Strategic, Generative, and Optimization AI Training—are associated with employees’ innovative behavior through cognitive (Task–Technology Fit, AI Self-Efficacy) and affective (Perceived Technology Attractiveness, AI Usage Intention) mechanisms. Survey data from 245 logistics practitioners (cross-sectional, single-source) were analyzed using confirmatory factor analysis, competing structural models, and bootstrapped indirect effects in a final integrated model. The originally proposed dual-track structure was not supported; the data favored a cross-linked specification in which cognitive beliefs inform attitudes across tracks and attractiveness precedes usage intention. Strategic AI training was associated with innovative behavior indirectly, Generative AI training both directly and indirectly, and Optimization AI training showed no unique association once the other dimensions were controlled. Neither Training Environment Quality nor Supervisor Support Leadership moderated the hypothesized relationships in a robust way, although both showed direct associations with outcomes (Training Environment Quality with Task–Technology Fit, β = 0.288; Supervisor Support with innovative behavior, β = 0.141). These cross-sectional, single-source associations refine the technology acceptance literature for AI training and inform HRD strategies for digital transformation in logistics.

Systems doi: 10.3390/systems14111396

Authors: Deyu Wei Yongyu Wang

Data-factor allocation involves interrelated supply, circulation, and utilization functions, yet existing provincial assessments often emphasize aggregate development rather than internal system configuration. Using 18 indicators for 30 Chinese provinces from 2012 to 2023, this study develops a systems-oriented measurement framework that distinguishes overall attainment, subsystem balance, and relative bottlenecks. Entropy weighting and arithmetic–geometric aggregation are combined with regional inequality decomposition and distributional dynamics analysis. The results show that mean balance-adjusted capacity increased from 0.0449 in 2012 to 0.2125 in 2023, while subsystem balance evolved non-monotonically and showed no sustained improvement after 2018. Under the baseline measurement specification, the predominant relative bottleneck shifted from circulation in 2012 to utilization in 2023, with each identified as the weakest subsystem in 23 provinces. Net between-region differences accounted for an average of 69.34% of total inequality, while annual development-state transitions exhibited substantial persistence. These findings highlight the diagnostic value of examining internal functional configurations alongside aggregate capacity and provide a proxy-based framework for differentiated provincial assessment.

Systems doi: 10.3390/systems14111397

Authors: Matthew J. Lydon Ahmet Can Sabuncu Yunus Doğan Telliel Matthew Yun Noah Greskiewicz Ceren Yilmaz-Akayya Rand J. Spiro

Engineering troubleshooting involves making sense of trouble while working toward containment or resolution within the conditions of professional practice. As inquiry and action unfold, engineers’ understanding of the relevant problem may also change. This work analyzes semi-structured interviews with 21 engineers, each with more than ten years of industry experience, across 20 interviews and seven industry designations to examine how troubleshooting problems are formed and transformed in practice. The existing body of literature explains aspects of this work, including ill-structured problem solving, representational and experiential sensemaking, and the sociotechnical organization of engineering activity. We show that these dimensions operate jointly and recursively within professional engineering troubleshooting. Across the episodes, the operative problem changed as engineers revised what observations indicated, which system was under inquiry, what actions were available or warranted, how work had to be coordinated, and what could count as sufficient resolution within the relevant sociotechnical conditions. We argue that adequate descriptions of troubleshooting problem recognition, pursuit, and restructuring require attention to these relationships. For engineering education, the claim connects readiness for engineering troubleshooting in industry to a clear pedagogical goal: students need practice recognizing, framing, and revising their understanding of problems as evidence, representations, and constraints change.

Systems doi: 10.3390/systems14111395

Authors: Jacqueline Y. Sánchez-García Juan E. Núñez-Ríos Susana A. Ochoa-Torres Roberto Palacios Rodríguez

Static assessments of capabilities have shaped women’s leadership studies, which have limited our understanding of how these capabilities interact and evolve over time. From a dynamic perspective, this article examines whether the capabilities identified as priorities through expert judgment also function as leverage points within the leadership development system. We developed a System Dynamics model whose components were based on results previously obtained using the Analytic Hierarchy Process (AHP) based on the judgment of 20 executives. We evaluated the model through scenario simulations and global sensitivity analysis using Latin Hypercube Sampling (LHS) and Partial Rank Correlation Coefficient (PRCC). Leadership development appears to depend on interdependent capabilities, rather than on personal characteristics in isolation. Simulations of the proposed model suggest that static priority and dynamic leverage are not equivalent: the influence of a capability depends on its position in the feedback structure, its interactions with other capabilities, and the timing of intervention. This study helps explain how capabilities mutually reinforce, limit, and amplify one another over time, providing a systemic foundation for designing interventions to develop women’s leadership.

Systems doi: 10.3390/systems14111394

Authors: Babak Ziyae Khalid Al-Qatiti Adil Hassan Bakheet

This paper aims to develop a scenario-planning framework that integrates circular economy (CE) practices into humanitarian supply chains (HSCs) to enhance systemic resilience. Specifically, the research seeks to provide a strategic blueprint for humanitarian organizations to transition from traditional linear models to sustainable, resilient ecosystems that maintain high service levels amid extreme uncertainty. The study employs a mixed-methods design to develop and validate a framework for circular, resilient HSCs. The qualitative phase involves semi-structured interviews with experts to identify and contextualize key constructs related to CE and resilience in HSCs. In the second phase, Fuzzy Cognitive Mapping (FCM) models the causal relationships among the identified constructs, capturing the complexity and feedback dynamics inherent in HSCs. Finally, the study conducts a scenario analysis to assess the impact of alternative strategic configurations on overall system performance. The findings demonstrate that CE in resilient HSCs emerges from dynamic interactions among CE practices, adaptive capabilities, and collaborative system structures. Scenario planning further reveals that integrated strategies combining agility, local resource utilization, innovation, and policy support yield the highest levels of system adaptability and sustainability. This study contributes to the HSC resilience literature by integrating CE with scenario planning theory into a unified analytical framework. In practice, the study provides actionable insights for humanitarian organizations and practitioners by identifying key leverage points and strategic pathways for designing adaptive, regenerative, and sustainable humanitarian relief systems.

Systems doi: 10.3390/systems14111393

Authors: Feisal Hadi Masmali Tahir Hakim

Supply chain information systems increasingly need to support decisions, yet Internet of Things (IoT) and blockchain approaches remain largely data-centric. We propose a decision-centric system in which IoT data acquisition, an artificial intelligence decision engine and a blockchain layer form one closed loop: each daily routing plan is optimized jointly for cost, lateness and delivered demand, validated against shared partner constraints and recorded before execution. We evaluated it by simulation on the supply chain logistics problem dataset (41 real customers) over 30 paired seeds. A learned deep Q-network engine with decision-time rollout reduced cost per 1000 units delivered by 24.3% relative to a demand-aware heuristic and 28.0% relative to OR-Tools, deciding in 43 ms; seeding adaptive large neighborhood search (ALNS) with its plan gave the lowest cost, 28.0% below the heuristic and below ALNS alone in 29 of 30 seeds. Joint routing–demand optimization lowered cost per unit by 33–45% relative to a cost-only objective. Under hard time windows, a heterogeneous fleet and eleven other scenarios, rollout stayed 12–32% cheaper than the heuristic in all 130 paired runs, and seeded ALNS was cheapest in every setting. Evidence-based validation blocked every invalid plan with up to four of five validators faulty.

Systems doi: 10.3390/systems14111392

Authors: Li Yu Meiying Cai Hangbiao Shang Haiyan Li

Artificial intelligence (AI) is crucial for driving radical innovation, which is key for firms to gain and maintain long-term competitive advantage. However, relatively little is known about how radical innovation is shaped by strategic direction regarding AI, and the perspective from when this innovation takes place. Drawing on the knowledge-based view and the upper echelons theory, this study delves into how and when AI orientation impacts radical innovation. Based on data from 510 Chinese manufacturing listed firms over the period 2013–2023, our study demonstrates a significant positive effect of AI orientation on radical innovation, and provides evidence consistent with positive indirect associations through knowledge search and knowledge recombination creation. Our findings also provide evidence that CEO openness may strengthen the positive relationships of AI orientation with radical innovation and knowledge search. Further, our findings make contributions to strategic orientation and technological innovation literature, and offer implications for practice in AI-innovation research by stressing the influence of knowledge and CEO personality in radical innovation domains.

Systems doi: 10.3390/systems14111391

Authors: Yongwei Yu Yeheng Zhang Junhua Guo Junhui Qi

Digital and green transitions may help cities adjust to shocks, but existing studies have mainly examined digitalization, green innovation, or coordinated policies separately. Whether integration of digital and green technological knowledge is associated with urban economic resilience remains less clear. We examine this question using a panel of 264 Chinese cities from 2009–2023. Digital–green technology convergence (DGTC) is measured using patent IPC co-classification and cross-domain direct citations; resilience is measured as the deviation of actual economic performance from a city-specific trend fitted over 2008–2019. Two-way fixed-effects models use lagged DGTC, and shift-share instrumental-variable estimates and alternative measures provide additional checks. Both DGTC measures are positively associated with the resilience indicator. DGTC is also associated with stronger pure digital and green capability bases and more favorable intercity patent-transfer network conditions. These channel estimates are consistent with the proposed mechanisms but do not establish causal mediation. The association is more pronounced in cities with greater structural rigidity, shock exposure, transition pressure, or network embeddedness. By distinguishing technological recombination from parallel digital and green activity, the study connects the organization of urban knowledge with economic adaptation. The findings inform urban innovation governance while remaining conditional on the resilience measure and the instrumental-variable exclusion restriction.

Systems doi: 10.3390/systems14111390

Authors: Dongfeng Jia

Trade-in programs and consumer return policies are common in e-commerce. However, their interaction remains underexplored. We consider a durable-goods manufacturer that sells directly to consumers and resells returned products as open-box products. Within their common feasible regions, we compare four scenarios based on whether trade-in is offered and whether returns are allowed. Allowing returns can increase total new-product demand at high production costs, whereas offering trade-in always reduces it. Holding trade-in adoption fixed, allowing returns increases manufacturer profit, consumer surplus, and social welfare above a common production-cost threshold. Offering trade-in reduces consumer surplus and social welfare, although it can increase manufacturer profit. The two policies interact asymmetrically. Offering trade-in lowers the cost threshold above which allowing returns becomes profitable. By contrast, numerical results show that allowing returns can either raise or lower the corresponding threshold for trade-in. Each policy combination can be optimal, and offering both is optimal at sufficiently high production costs. Numerical extensions show that the two policies’ effects on manufacturer profit and consumer surplus largely persist when replacement consumers are less likely to be dissatisfied. They also persist when traded-in products have low recovery values.

Systems doi: 10.3390/systems14111389

Authors: De Zhao Shengpeng You Runze Mou

At urban intersections, trajectory prediction supports downstream planning, particularly for right-turning vehicles interacting with vulnerable road users (VRUs). Conventional proximity-based interaction modeling may fail to distinguish interactions relevant to future vehicle motion from weakly related neighbors. To address this issue, this study proposes a lightweight Risk Interaction Spatio-Temporal Graph Convolutional Neural Network (RI-STGCNN), which extends Social-STGCNN through risk-informed selective information propagation. An Interaction Risk Index (IRI) integrating relative distance, relative velocity, Time to Closest Approach (TCA), and participant type is used to characterize interaction relevance, while risk-aware filtering and feature fusion selectively propagate interaction information. The model generates a single deterministic 12-step trajectory from eight historical frames. Experiments on the SinD dataset show that RI-STGCNN achieves an ADE of 0.68 m and an FDE of 1.31 m, reducing the errors of Social-STGCNN by 16.0% and 13.8%, respectively. In right-turn–VRU conflict scenarios, the reductions reach 27.9% and 24.1%. Additional comparisons show lower errors than Multiclass-SGCN, whereas HiVT-64 achieves lower errors with a substantially larger parameter count. An exploratory analysis of 720 training-set interactions finds an association between IRI and future vehicle–VRU separation (Spearman’s ρ = −0.401), without establishing calibrated collision risk. With 19.6 k parameters and a single-sample inference time of 1.75 ms on a GTX 1650, the proposed model provides a compact approach to single-trajectory vehicle prediction.

Systems doi: 10.3390/systems14111388

Authors: Yibei Zhang Hanlong Liu Chenhao Zhang Maocan Song Lin Cheng

Park-and-ride (P&R) facility location optimization involves coupled facility-opening decisions and probabilistic traveler allocation. This study develops a Branch-and-Benders-Cut Decomposition (B&CBD) framework for exact optimization under a specified multinomial logit (MNL) discrete choice model. Following the reformulation of the nonlinear model as a mixed-integer linear programming (MILP) model, the framework exploits origin–destination (OD) separability by retaining facility-location decisions in the master problem and solving traveler-allocation decisions through independent subproblems. Benders decomposition is integrated with a branch-and-cut algorithm, embedding cut generation within a single search tree and avoiding repeated master-problem optimization in the conventional Benders loop. An in–out strategy further guides cut generation using interpolated separation points. Computational experiments on synthetic instances compare the proposed framework with classical Benders decomposition, its in–out variant, and direct MILP solution. B&CBD outperforms the tested Benders variants, although a direct solution is generally faster for small instances. Across 12 Chicago network-based instances, B&CBD reaches the prescribed optimality tolerance in all cases, compared with 10 for the direct solution, and achieves shorter runtimes in all six instances with 20 candidate facilities.

Systems doi: 10.3390/systems14111387

Authors: Livia Filip Stelian Brad Florin Lungu Ionuț Adrian Chiș Daniel Filip

Doctoral research monitoring in technical universities can be conceptualized as a socio-technical system in which research trajectories, supervisory practices, institutional rules, digital infrastructures, and assessment norms interact within a broader socioeconomic environment. This article develops a conceptual framework and a provisional diagnostic model (PDM) for Engineering and Management through an integrative conceptual synthesis. The framework specifies system boundaries and hypothesized reinforcing, balancing, and metric-gaming feedback loops. The model separates institutional opportunity conditions from evidence of individual progress and engagement and reports effective weights and evidence coverage alongside its aggregate score. It distinguishes research novelty from applied relevance through profile-specific contribution rules and introduces a separate, non-compensatory gate for novelty, research integrity, and methodological rigor. Fully specified synthetic examples demonstrate calculation, missing-data treatment, and parameter sensitivity. The framework is neither an empirically validated instrument nor a calibrated system-dynamics simulation. It provides an explicit conceptual specification for future testing and formative doctoral monitoring without treating resource access or output counts as sufficient evidence of research quality.

Systems doi: 10.3390/systems14111386

Authors: Hung-En Kao Shih-Ming Pi

Security monitoring is commonly treated as a detection problem, yet in certified information security management systems it operates as a socio-technical control whose effectiveness depends on people who adjudicate the alerts it produces. This study asks where the information that adjudication depends on resides, and what contemporaneous adjudication records offer as evidence that the control operated. It analyses the complete adjudication record of a public-sector security function over seventeen months: 423 alerts, each closed by one administrator who recorded the basis of the determination, matched against an independently timestamped coordination channel. Half the alerts were closed on documented information the deployed monitoring did not ingest, chiefly maintenance announcements; for restart-related alerts, announcement coverage was 91.5 per cent. Nearly half required verification with a responsible party, drawing on identifier records and operational knowledge. An independent coder reproduced the coding with substantial agreement. We interpret the findings as an information–integration gap in the observed deployment rather than a limit of detection: the information on which these alerts were closed was not among the detector’s inputs. Coordination between system owners and the security function operates as a control whose coverage can be measured, and adjudication records make its operation traceable to assessors.

Systems doi: 10.3390/systems14111384

Authors: Rui Qin Siwei Wang Danhua Zhao

Digital business ecosystems connect products, services and artificial intelligence through interdependent organisations. Delivery can continue while a service ceases to provide the value promised to its user. This conceptual study examines that discrepancy through a synthesis of 119 sources. Dynamic value coherence is the capacity to sustain a recognisable relationship between the value users expect and the value they experience as products, services or providers change, within a stated commitment and legitimate conditions of use. The commitment provides the reference for evaluation. Anchoring makes it recognisable in meaning and action; extension carries and adapts service functions across encounters; governance specifies permissions and correction responsibilities. These proposed relationships connect users’ recognition and realisation of value to the design and governance arrangements that sustain it through change. Four configurations compare how services support the commitment and adapt to changing tasks. A short hypothetical example distinguishes a breached commitment, an unmet preference and legitimate adaptation under the same observed change in behaviour. The source-linked concepts and attributes are distinguished from the authors’ theoretical synthesis, which includes four propositions for empirical testing. The framework offers a way to examine how users continue to recognise and realise value across providers, and how design and governance can sustain or restore that continuity.

Systems doi: 10.3390/systems14111385

Authors: Hisaya Sakashita Yuta Nakajima Hidekazu Nishimura

Digital transformation has expanded the use of audit analytics to detect internal control violations. However, detection logic is often embedded in system-specific queries and data preparation procedures, limiting reuse across heterogeneous systems. As a result, repeated adaptation is required when the same analysis is applied to different business processes or systems. This study proposes an ontology-based modeling approach that separates reusable rule-based analytical logic from domain-specific Business Semantics, application conditions, and source-specific data reconstruction. The approach uses a three-layer model: L2 for generic Business Semantics and rule-based analytical logic, L1 for domain-specific Business Semantics and application conditions, and L0 for reconstructed business data. The model is implemented using the Resource–Event–Agent ontology, Gal’s internal control axioms, the Ontological Modeling Language, and openCAESAR. The approach is evaluated as a proof of concept using controlled synthetic order-to-cash and procure-to-pay scenarios for candidate segregation-of-duties violations. The results show that the same L2-layer detection rules and SPARQL violation extraction query were reused without modification, while L1 definitions and L0 data reconstruction remained scenario-specific. All predefined positive, negative, and multiple-candidate test cases produced the expected results. The findings are limited to the evaluated synthetic scenarios and do not establish broader generalizability or scalability.

Systems doi: 10.3390/systems14111383

Authors: Xiao Cui Jiafei Qin Fengwen He Hongjie Wang Pei Yue Jie Zhang Zhenyun Hu Hexuan Hu

In the digital economy, data have become a new factor of production, making a rigorous and feasible data asset valuation system a practical necessity. As the supply chain sector advances toward digitalization and intelligent transformation, data assets have become a key source of competitive advantage for supply chain companies. Based on the modified cost approach, this study develops a valuation system comprising three subsystems: cost reconstruction, return enhancement, and value adjustment. First, data asset input costs are aggregated and converted into replacement costs. The cost–expense profit ratio is then introduced to estimate a theoretical benchmark value incorporating operating returns. Four groups of influencing factors—data quality and scale, the data asset market, data asset application, and value realization risk—are incorporated. The analytic hierarchy process (AHP) and fuzzy comprehensive evaluation (FCE) are combined to derive a value adjustment coefficient. Finally, the coefficient is applied to the theoretical benchmark value to obtain the data asset value. The system is applied to Company G, a supply chain company in China, as a case study. The results show that the replacement cost is RMB 1,804,126, the value adjustment coefficient is 0.8371, and the final estimated value is RMB 1,529,111.80. Sensitivity analysis reveals that direct and indirect costs exhibit the highest sensitivity coefficients of 0.566 and 0.434, respectively, followed by data quality and scale and data asset application. This study contributes to the methodological development of differentiated data asset valuation from a value formation perspective and provides practical insights for identifying data asset management priorities in supply chain companies.

Systems doi: 10.3390/systems14111382

Authors: Jiayun Nie Xiaohong Ren Guowei Liu

Understanding how comprehensive transportation network resilience emerges from complex causal interactions is essential for developing adaptive and sustainable regional transportation systems. Addressing the inability of conventional regression approaches to capture configurational effects among multiple factors, this study applies fuzzy-set qualitative comparative analysis (fsQCA) to identify pathways leading to high transportation network resilience in the Chengdu–Chongqing region. Using 209 city-year observations from 19 cities during 2014–2024, this study considers resilience as the outcome condition and incorporates ten antecedent conditions into the configurational framework. After direct calibration, necessity analysis, sufficiency analysis, and robustness tests are conducted. The results show that: (1) no single condition is necessary for achieving high resilience, confirming its configurational nature; (2) three equivalent pathways are identified: an economic foundation and digital infrastructure-supported pathway, an industrial–fiscal–governance collaborative low-risk pathway, and a fiscal–digital governance compensatory pathway under economic constraints. These pathways achieve an overall solution consistency of 0.9543 and coverage of 0.4223; (3) spatial structures significantly shape resilience outcomes, with the absence of high network dominance and low dual-core dependence consistently emerging as key conditions; (4) robustness tests confirm the stability of the configurations; and (5) differentiated strategies should be developed according to cities’ resource endowments and spatial constraints. This study advances resilience research by revealing configurational mechanisms and provides policy implications for transportation resilience governance in the Chengdu–Chongqing region and beyond.

Systems doi: 10.3390/systems14111381

Authors: Tongyu Wu Junjie Wang Minjie Li

Batteries are the core component of new energy vehicles (NEVs), and their supply chain resilience matters for the sustainable development of the industry. Using 326 valid questionnaires completed by employees of NEV battery companies in Fujian, Guangdong and Jiangxi, structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) were applied to examine how digital transformation, the three dimensions of supply chain dynamic capabilities (learning and absorption, innovation, and collaboration), and environmental dynamics are associated with supply chain resilience. Digital transformation is significantly and positively associated with resilience, both directly and indirectly through supply chain dynamic capabilities, which account for 47.09% of the total effect; collaboration carries the largest share among the three dimensions (34.66%). Environmental dynamics positively moderates this association. Necessity analysis indicates that no single antecedent condition is necessary for high resilience, while four configurations sufficient for high resilience were identified and summarized as three patterns, with a solution consistency of 0.877 and a solution coverage of 0.682. The pattern combining all three capability dimensions accounts for the largest share of membership in high resilience. High resilience therefore appears reachable through several functionally equivalent configurations rather than a single optimal combination of capabilities.

Systems doi: 10.3390/systems14111380

Authors: Zhaolin Zhao Shifa Liu Linlin Huang Yalei Yang Xianyin Zhan

Artificial intelligence (AI) integration in computing education is often evaluated as tool adoption, although course performance emerges from interdependencies among students, instructors, tasks, platforms, assessment, governance, and environmental constraints. This study conceptualized AI-enabled computing courses as socio-technical instructional systems and examined associations within a theoretically proposed readiness–quality–engagement–satisfaction pathway. The primary dataset comprised 122 responses from courses such as Algorithms and Data Structures, and Principles and Applications of Databases at a Chinese science and engineering university; 108 responses remained for inferential analysis after a conservative joint quality screen. A separate 57-response survey database (GaussDB) provided implementation-layer evidence. Factorability diagnostics, formative and reflective measurement assessment, partial least squares structural equation modeling (PLS-SEM), 5000-resample bootstrap indirect-effect analysis, sensitivity analysis, and correlation-based item-level importance–performance analysis were applied. Course readiness was associated with instructional system quality, which was associated with engagement. Quality was directly associated with satisfaction and indirectly associated through engagement, explaining 55.2% of satisfaction variance. Assessment innovation, AI/digital-skill weighting, teaching experience, case and courseware integration, resource renewal, and personalization were priorities; the GaussDB evidence highlighted connectivity and diagnostic usability. The results support a six-stage redesign loop centered on high-quality learning rather than maximum AI use and provide a reproducible baseline for longitudinal, multi-institutional evaluation.

Systems doi: 10.3390/systems14111379

Authors: Chien-Chih Wang Chun-Hua Chien Chi-Hsun Hung

Predictive performance in operational AI depends on deployment conditions, whereas model explanations alone do not determine feasible actions. This study developed and evaluated a scope-aware and explainable AI decision-support system for municipal waste collection dispatch in Yonghe District, Taiwan. A retrospective evaluation included 11,934 vehicle-day observations from 17 vehicles, and a six-month prospective deployment recorded 1989 vehicle-days. Ten classifiers were benchmarked using development-period data only. The selected XGBoost model achieved full-history weighted F1 values of 0.9261 in established-unit chronological evaluation and 0.913 under leave-one-vehicle-out (LOVO) validation; reduced-history values were 0.893 and 0.861, respectively. Class-specific diagnostics showed a red-state recall of 0.9358 chronologically and 0.9144 in pooled LOVO predictions. Under the same LOVO design, GBDT, LightGBM, and Random Forest achieved weighted F1 values of 0.901, 0.896, and 0.887, respectively. During prospective use, 143 of 209 evaluated red cases (68.4%) were scenario sensitive, and 94.6% of scenario evaluations were completed within the 30–60-min decision window. Because supervisors could act after viewing model outputs, prospective records were interpreted as workflow evidence rather than independent predictive validation. The performance envelope links each performance claim to the evaluated population, information availability, operational context, and validation boundary, while operational feasibility and human authorization govern how predictions inform dispatch decisions.

Systems doi: 10.3390/systems14111378

Authors: Qunxi Gong Ling Tang Yuanxiang Zhang Gengxuan Guo

The integration of the digital economy (DE) and green logistics (GL) is increasingly recognized as a critical pathway for modernizing logistics systems and achieving carbon neutrality. However, their spatiotemporal synergy remains underexplored. Utilizing panel data from 120 logistics hub cities (LHC) in China from 2013 to 2022, this study constructs a comprehensive framework to evaluate the coupling coordination degree (CCD) between DE and GL. We employ the Dagum Gini coefficient to dissect spatial disparities and integrate the CatBoost algorithm with SHapley Additive exPlanations (SHAP) to unravel the driving mechanisms of this coordination. The results reveal that: (1) The overall CCD in Chinese LHC exhibits a consistent upward trajectory, yet spatial development remains highly uneven, forming a distinct hierarchical spatial pattern. (2) Spatial disparities in the integration level have widened over time, with transvariation density constituting the primary source of overall inequality. (3) The CatBoost-SHAP analysis identifies urban economic density, urbanization level, advanced industrial structure, and human capital level as the paramount drivers. These findings enrich existing literature by providing nuanced, data-driven insights for policymakers to leverage digitalization, formulate spatially differentiated strategies, and foster sustainable logistics networks.

Systems doi: 10.3390/systems14111377

Authors: Jianxing Zhang Bin Ma Lei Ai Xinyi Song Jiayu Cheng Jianan Li Zhuting Yu

Financial decision-support systems must balance quality, cost, traceability, and controlled state reuse. Existing single-agent, retrieval-augmented, and always-on multi-agent pipelines leave the joint control of collaboration and shared-memory activation under-specified. The purpose of this study is to determine whether governed hierarchical memory with uncertainty-triggered routing can preserve financial sentiment quality while reducing coordination cost. We operationalize uncertainty with an input-derived ambiguity score: after a low-cost probe, below-threshold inputs short circuit, whereas flagged inputs escalate to governed collaboration. On the disjoint 2064-record remainder of Financial PhraseBank sentences_allagree, the proposed configuration achieves 0.9453 accuracy and 0.9364 macro-F1—within 0.0005 and 0.0006, respectively, of the direct baseline—while using 63.57% fewer tokens than always-on collaboration but 31.05% more than direct inference. Earlier 200-record development and agreement-shifted analyses are highly label-skewed and are treated as sensitivity evidence only. Ablations and trace audits identify routing as the measured source of efficiency; no isolated benchmark gain is attributable to the governance rule. Theoretically, the study separates computational activation from governed state reuse as control-plane mechanisms. Practically, managers can reserve collaboration for flagged inputs while retaining traceability, although the ambiguity proxy and governed-memory benefits require harder workflow validation.

Systems doi: 10.3390/systems14111376

Authors: Jiaji An Xinran Zhao He Di

The rapid expansion of technology finance poses complex challenges to systemic risk management, yet the existing literature lacks a game-theoretic framework to explain the dynamic risk transmission mechanisms involving investor sentiment and asset bubbles. This study examines the time-varying, nonlinear effects of technology finance on systemic risk through behavioral transmission channels by integrating a sequential game approach with a time-varying parameter stochastic volatility vector autoregression model. Using Chinese quarterly data from 2006Q1 to 2024Q4, this study captures endogenous market interactions and reveals a nonlinear, stage-dependent trajectory. Specifically, while technology finance amplifies systemic risk in the short term, it enhances system resilience over the long term. Furthermore, this paper identifies a cascading risk transmission mechanism: technology finance initially stimulates optimistic investor sentiment, driving short-term asset bubble formation and escalating systemic risk, whereas long-term patterns reflect market corrections driven by rational arbitrageurs and adaptive regulation. Exhibiting both stage and event dependence, these findings reconcile previously conflicting empirical evidence. Ultimately, this work develops a unified theoretical–empirical framework to elucidate how technology finance generates and transmits systemic risk, offering practical policy implications for fostering innovation while mitigating systemic risk.

Systems doi: 10.3390/systems14111375

Authors: Xingyi Yang Huini Zhou

The rapid growth of the new energy vehicle (NEV) market has heightened consumer attention to driving range, while information asymmetry concerning real-world driving performance complicates manufacturers’ information-disclosure decisions. This study examines how an NEV manufacturer selects an advertising structure and determines whether to disclose driving-range information within a two-echelon supply chain comprising a manufacturer and a dealer. We develop a game-theoretic model that incorporates manufacturer advertising, cooperative advertising, targeted-advertising efficiency, information-disclosure costs, and consumer trust in the absence of disclosure. We compare equilibrium outcomes across advertising structures to assess how advertising decisions interact with voluntary information disclosure and influence the performance of supply-chain members. The principal findings are as follows: (1) The manufacturer discloses the true driving range only when the realized range exceeds a critical threshold. Furthermore, neither advertising structure is universally optimal; the manufacturer’s preferred structure depends on advertising effectiveness and the channel’s demand-conversion capability. (2) Higher disclosure costs and greater consumer trust under non-disclosure raise the disclosure threshold, whereas greater advertising effectiveness can lower it. Nevertheless, advertising does not invariably strengthen disclosure incentives, as its effect depends on whether the advertising-related benefits of disclosure outweigh the associated costs. (3) The advertising and disclosure strategy that maximizes manufacturer profit does not necessarily benefit dealers and consumers simultaneously. Although cooperative advertising may increase manufacturer profitability, its effects on dealer outcomes and consumer welfare depend on advertising efficiency and demand-conversion effects.

Systems doi: 10.3390/systems14111374

Authors: Cun Li

Grandparents often take sustained responsibility for school escort, daily care, safety supervision, and emotional companionship, yet frequent contact does not necessarily produce reciprocal participation. This study treats interaction between grandparents and grandchildren as a socio-technical system and uses interviews and field observations for the systemic diagnosis, integrates the Framework Method, Soft Systems Methodology, Interpretive Structural Modelling and MICMAC analysis for design translation, and separately conducts a standardized-stimulus online concept appraisal. Fifteen factors formed a six-level hierarchy that converged on one proximal mechanism: the absence of reciprocal and complementary tasks. The diagnosis informed four concepts for domestic, mobility, public-space, and embodied-recreation settings. In the concept-stage public appraisal (N = 261), all four concepts received high ratings, but the composite evaluation indices did not detect robust differentiation after multiplicity correction. The only false-discovery-rate (FDR)-corrected item difference concerned whether grandparents’ knowledge, experience, or judgement had a clear role in the task; the mobility collaboration game scored highest. Exploratory indirect association findings were sensitive to model specification and sample definition. Among 203 codable open responses, anticipated implementation concerns differed between household and public-space concepts. The study proposes visible agency, a contribution that can shape a shared outcome, as a design proposition for reciprocal participation. Actual use remains to be tested.

Systems doi: 10.3390/systems14111373

Authors: Theresa Sobb Benjamin Turnbull Nour Moustafa

Modern systems-of-systems, such as national infrastructure networks, defence information environments, and financial platforms, must continue to operate even when components fail or are compromised by cyber-attacks. Traditional approaches to resilience focus on identifying and reinforcing critical nodes; however, these methods rely on complete network visibility, incur significant analytical overhead, and are vulnerable to structural changes. This paper introduces Stress-Induced Self-Organised Resilience (SISOR), a proactive approach to building resilience that leverages the natural adaptive behaviour of complex systems. SISOR works by intentionally applying minor, rolling disruptions across nodes in a system, prompting the formation of alternative pathways and service redundancies through self-organisation and feedback loops. Rather than preventing stress, SISOR utilises stress as a tool for resilience development. The approach is visibility-agnostic, computationally lightweight, and scales naturally with the system size. We formalise SISOR through a model that relates the optimal stress frequency to mission assurance priorities and the likelihood of a cyber-crisis. The result is a resilience strategy that strengthens systems before a disruption occurs, reducing the reliance on emergency adaptation during crises and improving survivability in high-consequence operational environments.

Systems doi: 10.3390/systems14111372

Authors: Hao Zhu Huiping Huang Junjian Gu

Employment adjustment under digital transformation is a multilevel outcome that depends not only on regional technical capability but also on the structural configuration and worker response conditions in which that capability is embedded. This study examines the relationship between provincial data-factor capability and individual employment in China by matching China Family Panel Studies data for 2012–2022 with a provincial DataIndex. Binary Logit models with province and year fixed effects reveal an age gradient: the employment association of DataIndex is positive for younger workers, weakens around midlife, and becomes negative at older ages. Province-year regressions further show that stronger data-factor capability is associated with industrial structure upgrading and greater regional innovation activity, while interaction tests indicate less favorable employment associations among agricultural-hukou and rural residents. These findings show that improvements in regional digital capability do not translate uniformly into employment gains. Instead, their labor-market consequences depend on worker adaptability and institutional and spatial conditions. The study therefore highlights the need to evaluate digital transformation not only through technological and structural progress, but also through the inclusiveness of its employment outcomes.

Systems doi: 10.3390/systems14111371

Authors: Amir Amrollahi Biuky Youness Javid

(1) Background: Startups operate in highly uncertain environments where ineffective risk management increases the likelihood of failure. While several risk management frameworks have been developed specifically for startups and SMEs, they typically lack systematic validation and quantitative decision support under uncertainty. General standards such as ISO 31000, COSO ERM, and PMBOK, in turn, are not designed specifically for the startup context. This study develops and structurally assesses an integrated, systems-oriented risk management framework that adapts established risk management processes to the specific characteristics of startups. (2) Methods: The framework was developed through a systematic literature review and examined using Axiomatic Design and Qualitative Research Synthesis. Structural consistency was assessed through the Independence Axiom, while agreement with the proposed classification was evaluated using expert judgments and inter-rater reliability measures (Cohen’s κ, ARI, and NMI). Real Options Analysis was incorporated into the quantitative risk analysis stage to evaluate alternative risk response strategies. (3) Results: The proposed framework comprises seven interconnected risk management processes. The Axiomatic Design matrix confirmed its structural consistency, and expert evaluation demonstrated substantial to almost perfect agreement (κ = 0.634–0.847, ARI = 0.609–0.846, NMI = 0.689–0.889). A single case study of a software startup provided initial evidence of the framework’s practical applicability and illustrated the identification of a preferred risk response strategy. (4) Conclusions: The proposed framework structurally assessed and conceptually examined a systematic approach to startup risk management by integrating structured risk management processes with quantitative decision support under uncertainty.

Systems doi: 10.3390/systems14111370

Authors: Huagang Tong

Universities increasingly seek to develop students’ innovation capability, but growth in student participation and project activity can outpace the mentoring, facilities, funding, and incubation capacity required to sustain it. This study examines the dynamic alignment between capability-related student conditions and institutional support capacity. A four-subsystem system dynamics model represents Student Motivation, Student Self-Efficacy, Innovation Skills, project flows, Campus Resources, Mentor Pool, Policy Support, and Innovation Output. The model is used to trace feedback, accumulation, capacity constraints, and implementation delays and to conduct counterfactual policy experiments over 240 months. Policy configurations are evaluated from the complete simulated trajectories by calculating the area under the curve (AUC) for Innovation Output, Student Motivation, and Campus Resources and applying Pareto dominance. The simulations show that strong incentives or rapid project expansion can generate short-term gains while increasing congestion, resource pressure, and burnout when institutional capacity adjusts too slowly. Eight configurations are non-dominated, indicating that no single policy simultaneously maximizes cumulative output, preserves motivation, and protects the resource base. The results are conditional on the stated model structure, parameterization, and single-institution calibration; they are intended to support policy deliberation rather than establish causal effects or make point predictions.

Systems doi: 10.3390/systems14111369

Authors: Tingli Liu Qingqing Tian Zihan Zhao Xinran Lu

This study examines the association between Open Government Data and manufacturing servitization from a value-chain perspective. Using panel data for A-share listed manufacturing firms registered in the Beijing–Tianjin–Hebei region during 2020–2024, we estimate fixed-effects models. The baseline estimates show a statistically significant positive association between Open Government Data and manufacturing servitization. Channel analyses provide indirect evidence consistent with resource allocation efficiency, smart manufacturing and transaction costs as potential pathways underlying this relationship. Supplementary instrumental-variable estimates also yield a positive coefficient, subject to the instrument’s identifying assumptions. Heterogeneity analyses reveal a stronger positive association among firms with more advanced digital transformation, consistent with complementarity between public data and internal digital capabilities. Stronger associations also appear among firms with lower innovation or adaptive capacity, suggesting a possible compensatory role for external information. Group-based coefficient tests support these contrasts, while continuous-interaction results are weaker. Further analysis identifies a positive association between data openness quality and manufacturing servitization. These findings inform discussions of public data reuse and manufacturing servitization by highlighting data quality and differences in firms’ capabilities.

Systems doi: 10.3390/systems14111368

Authors: Montserrat Rodriguez-Cotilla Diana Barrón Villaverde Ana Blanco-Ariza

This article analyzes the evolution of multistakeholder alliances in the context of social value creation. It mainly explores their next stage of evolution and understands their key characteristics. A qualitative approach was adopted, employing focus groups with leaders from four multistakeholder networks actively implementing programs in Latin America. Data analysis was conducted using the Atlas Ti software and NVivo software. The discussions were transcribed, and responses were systematically coded to extract insights into the main concepts related to value creation, mission, and impact. The results underscore the critical role of training for members in multistakeholder alliances, emphasizing collaboration among companies, governments, and the social sector to drive change through a unified agenda. The discussion stresses the importance of knowledge-sharing to ensure continuous positive transformation within the network. Accordingly, the article contributes valuable insights into the ongoing development of multistakeholder alliances and elucidates their mission and impact in the Latin American context.

Systems doi: 10.3390/systems14111367

Authors: Ruguo Fan Ziqiang Lu Xiaoyu Wang Rongkai Chen Zhixiang Yin

Public technology service platforms (PTSPs) increasingly rely on coalition structures to deliver complex services, yet achieving equitable benefit allocation remains a critical challenge for sustained collaboration. To address the allocation challenges across different evolutionary phases of PTSP coalitions, this study develops a stage-contingent governance framework that maps allocation mechanisms onto the platform lifecycle: transitioning from classical Shapley values during initial coalition formation, to Owen values under sub-coalition emergence, and ultimately to a Shapley-adjusted Q-Learning (SHAQ) framework during dynamic scaling. SHAQ integrates cooperative behavioral Q-learning with coalition-based allocation rules, enabling members to dynamically align incentives, reward high contributors, and discourage disengagement. MATLAB2023a simulations demonstrate that SHAQ consistently outperforms static allocation methods in terms of distributional fairness, core stability, and economic efficiency. By offering a robust and adaptive allocation mechanism, this study presents a practical pathway to strengthen trust and sustainability in PTSP coalitions.

Systems doi: 10.3390/systems14111366

Authors: Ashraf Zaghwan Indra Gunawan Yousef Amer

Australia’s transition toward net-zero emissions (NZE) requires the integration of renewable energy (RE) sources with substantially different capacity requirements and operational characteristics. However, existing transition assessments provide limited quantitative evaluation of how “Proposed”, “Anticipated”, and “Committed” renewable capacity additions may influence the required capacity pathway. This study develops a Multi-Mode Gradient Descent (MMGD) framework combining Standard Gradient Descent with an adopted Pseudo-Gradient approach to assess annual capacity additions for five energy sources: solar, wind, hydro, biomass, and battery storage. Australian Energy Market Operator (AEMO) capacity data are used as the reference, with “Proposed”, “Anticipated”, and “Committed” additions assessed under “Low”-, “Medium”-, and “High”-influence conditions, respectively. The MMGD results show substantial variation across these conditions. Relative to the AEMO reference (1.0 = 100%), the Low-influence results range from 0.22 to 1.43, Medium-influence from 1.10 to 7.16, and High-influence from 2.19 to 14.33 across the five energy sources. The MMGD results are benchmarked against the corresponding AEMO reference capacities to evaluate the sensitivity of the required renewable direction and magnitude of capacity adjustment under different influence conditions. The study contributes a gradient-based decision-support framework for quantitatively assessing renewable energy capacity pathways toward Australia’s 2050 NZE target.

Systems doi: 10.3390/systems14111365

Authors: Kunfeng Chen Zaisheng Zhang Meng Liu Xiangchun Li

In the context of increasing economic policy uncertainty and rapidly evolving digital technology, how do corporate innovation systems respond? Using data on China’s A-share listed firms from 2010 to 2024, we examine the relationship between firm-perceived economic policy uncertainty (FEPU) and collaborative open innovation. We find that FEPU is significantly and positively associated with collaborative open innovation, with this positive association primarily observed among larger firms and, for invention patents, stronger among state-owned firms. Moreover, we also find that artificial intelligence (AI)-related asset intensity serves as a key mediating channel linking FEPU to collaborative open innovation. Corporate ESG performance, as a boundary condition, plays a positive moderating role in the relationship between FEPU and collaborative open innovation. Further, higher institutional ownership strengthens ESG’s moderating role. This paper elucidates the new logic through which firms navigate external policy turbulence via open innovation, technological resource investment, and relational governance.

Systems doi: 10.3390/systems14111364

Authors: Ece Ucar E. Ertugrul Karsak

The increasing emphasis placed by countries on sustainability-oriented policy frameworks has heightened the need for robust analytical instruments capable of evaluating circular economy performance at the national scale. In response, this study develops a novel performance evaluation framework grounded in a common-weight network Data Envelopment Analysis (DEA) approach to benchmark countries’ circular economy outcomes. The proposed methodology integrates undesirable output data within a two-stage network structure, enabling a comprehensive comparative assessment of European Union member states in which air pollution indicators are explicitly modeled as interval data. The proposed framework generates a complete ranking of countries regarding circular economy performance and delivers a more realistic and policy-relevant assessment than conventional DEA-based approaches with an improved dispersion of input, intermediate measure and output weights.

Systems doi: 10.3390/systems14111363

Authors: Shaheen A. Abdulkareem

Evacuation models usually assume occupants receive accurate information, yet false messages and others’ reactions shape early decisions in building emergencies. This study links survey data, interpretable machine learning and agent-based modelling within Protection Motivation Theory and the Risk Information Seeking and Processing model. Two surveys of university populations (n = 176 and n = 203) were analysed with non-parametric and multivariate statistics, classifiers with SHAP attribution and K-Means clustering, yielding four behavioural archetypes. The archetypes parameterised a NetLogo model in which two false messages, that the alarm is a drill and that an exit is blocked, spread between agents. Coping appraisal, but not threat appraisal, was associated with expected reactions to an alarm. Concern about misinformation was not positively associated with sharing unverified information, whereas reliance on others’ reactions was associated with two of three sharing measures. In simulation, the false messages added 3–8 s to mean evacuation time, while high official trust combined with a fire alarm shortened it by 15 s at equal exposure, with less persistence of false information. Occupants with low coping appraisal were delayed most. These directions held across 200 parameter sets, identifying pre-crisis trust and information resilience as priorities for empirical testing.

Systems doi: 10.3390/systems14111362

Authors: Zehui Bu Zhongyuan Geng Jicai Liu

User-pay public–private partnership (PPP) infrastructure projects operate as socio-technical systems in which institutional conditions, project viability, contractual governance, and stakeholder behaviour jointly determine whether service value can be converted into sustainable operating revenue. However, existing research often treats these elements as isolated success factors rather than as an interdependent value creation system. This study develops a systemic framework for explaining value creation in user-pay PPP projects by integrating grounded theory, fuzzy Decision-Making Trial and Evaluation Laboratory (Fuzzy-DEMATEL), and Interpretive Structural Modelling–Cross-Impact Matrix Multiplication Applied to Classification (ISM-MICMAC). Grounded theory identifies 23 categories and integrates them into collaborative foundation, collaborative process, and value realization. The subsequent Fuzzy-DEMATEL and ISM-MICMAC analyses focus on 18 factors within the first two dimensions to examine their influence relationships, relative importance, and hierarchical structure. The results show a six-layer mechanism in which socioeconomic and legal environments form foundational drivers, project viability factors occupy intermediate layers, and concession governance and stakeholder collaboration transmit upstream conditions toward value realization. User willingness to pay exhibits the highest centrality, while stakeholder value co-creation willingness constitutes the most proximate behavioural condition. The findings recast user-pay PPP value creation as a layered socio-technical system and identify where interventions should target institutional enabling, project viability, governance design, and collaborative behaviour.

Systems doi: 10.3390/systems14111361

Authors: Hee-Ok Lee Dongseop Chung

Background: Whether corporate social responsibility (CSR) helps firms withstand external disruption, and how any advantage evolves as a shock unfolds, remains unresolved. Drawing on stakeholder theory, conservation of resources theory, and a systems-resilience perspective, we set out two competing predictions for the acute phase of COVID-19: an insurance-based loss-mitigation view and a resource-premium view. Methods: We use a balanced panel of 100 KOSPI-listed non-financial firms observed annually from 2016 to 2024 (900 firm-year observations) and estimate two-way fixed-effects difference-in-differences and event-study models, classifying firms by pre-crisis (2016–2019) CSR and clustering standard errors by firm. Results: Firms with higher pre-crisis CSR show a positive return-on-assets differential that appears in 2020, is statistically clear from 2021, and persists through 2024 without attenuating, although the recovery-phase differential is not statistically larger than the acute-phase differential. Each ESG sub-dimension is associated with the post-COVID-19 differential when examined separately, but only governance remains so when all three are included jointly. Conclusions: The estimates describe differential performance trajectories associated with pre-crisis CSR status rather than causal effects, and the design cannot identify the mechanism. The persistence pattern is somewhat more consistent with a resource-premium than a loss-mitigation view.

Systems doi: 10.3390/systems14111360

Authors: Yingnan Zhao Bo Yu Nannan Yu

As innovation activities become increasingly specialized across cities, intercity technology linkages have become increasingly important for integrating innovation and industrial chains. This study examines whether city-level conditions associated with chain integration help predict subsequent intercity technology linkages. Using 2010–2023 data for 41 cities in the Yangtze River Delta, we construct a potential intercity network using the Process-Based Integration Index (PII), a proxy for selected integration-related conditions, together with relative economic size and geographic distance, and then validate it against subsequent transfers of invention patent rights from research institutions to firms. The network was more connected on average in 2018–2023, while direct-linkage capacity and structural brokerage emerged as distinct structural roles. In fixed-holdout validation, incorporating the training-fitted PII raised the annual mean AUC from 0.8048 to 0.8334 and annual mean AP from 0.6216 to 0.6742. In rolling-origin validation, the pooled AUC rose from 0.7998 to 0.8312, the AP increased from 0.6164 to 0.6749, and the Brier score fell from 0.1938 to 0.1602. In a separate fitted-logit comparison, the composite PII specification maintained strong dyadic ranking performance with fewer modeled terms, while the unrestricted component-wise model achieved a lower Brier score. This cross-level framework supports regional network analysis, the prioritization of cross-city technology search, and the monitoring of intercity technology linkages.

Systems doi: 10.3390/systems14111359

Authors: Wei Wu Jingjing Jiang

We study how assumed pressure responses shape work hours, macroeconomic outcomes and welfare in a China-calibrated agent-based stock-flow-consistent model that combines a 2017 social accounting matrix with a 2016 CFPS schedule anchor. Household income-gap and employer-pressure loadings are scenario inputs rather than estimates; 1320 supplementary runs vary their signs and test the model’s mechanisms. Negative employer loadings reverse the hours response, and macroeconomic outcomes are not monotone in hours: under market-share competition, income-gap pressure alone raises output and lowers unemployment, whereas adding employer pressure lengthens hours, lowers output and raises unemployment. At the central loadings, pressure raises mean hours under competition by 13.75 h, or by 6.13 h with an upper-tail hours cost; remaining saturation at the hours bound limits quantitative interpretation. The competition-associated output loss survives removing the above-anchor labour increment or the markup-pressure term, and the pressure-induced output reversal survives unifying consumption propensities or removing the direct wage squeeze; its wage–income counterpart reflects mainly employment losses. At the reference unemployment penalty, valuing non-market time does not amplify the competition welfare loss in any of 80 sampled designs; only higher, exploratory unemployment weights do. The model supports conditional scenario analysis, not causal or policy-effect estimates for China.

Systems doi: 10.3390/systems14111358

Authors: Maurice Yolles

In 2022, a metacybernetic account argued that viruses are alive by moving the criterion for life from metabolism to organisation, treating the genome–capsid couple as autopoietic. This study reframes that conclusion with two constructs of Fisher-Generative Informational Realism (FGIR). The first distinguishes the boundary between a Complex Adaptive System (CAS) and a self-sustaining Complex Adaptive Autopoietic System (CAAS). The second embraces the coercivity law, which requires a system’s protoenergy, the informational effort needed to maintain a configuration, to exceed a threshold. Living systems can be argued to satisfy two conditions: a topological condition concerning the closure of their self-producing organisation and a resourcing condition concerning their capacity to supply the protoenergy needed to sustain that organisation. The idea that viruses are not autopoietic conflates these two conditions, since viruses satisfy the topological condition but fail the resourcing condition. The host, rather than the virus, holds the capacity to maintain the viral self-producing network, a condition termed borrowed closure. Identifying the viral protoenergy with the draw on the host, and letting self-supply return only when the lineage’s translation machinery is complete, yields a host-budget equation with a saddle-node bifurcation at a critical completion fraction. Given a near-all-or-nothing return, the barrier is structural rather than statistical, surviving stochastic and epidemiological reformulations and persisting under delay as an oscillatory failure. Its value, however, is schematic, lying between about 0.06 and 0.6 under the two regeneration forms. The account is falsifiable and taxonomically agnostic, as Carsonella ruddii shows, and the boundary is crossed only downward.

Systems doi: 10.3390/systems14111357

Authors: Dingyao Yu Huali Cai Hongtao Li Chunlei Shi Chunjia Han Zhen Tu Chenxi Zheng Yingcheng Xu Cui Tian

Green flight service uses incentive mechanisms to encourage passengers to participate in low-carbon value co-creation. However, willingness to make green choices does not necessarily translate into smooth participation, as service failures during implementation may create barriers to passenger participation. Drawing on Service System Theory, this study conceptualizes green flight as a service system involving passengers, airlines, service rules, and incentive mechanisms. Using 1161 passenger complaints collected from the Service Quality Supervision Platform of the Civil Aviation Administration of China between January 2021 and June 2025, Word2Vec-based semantic expansion and the Structural Topic Model (STM) were applied to identify service failures and corresponding recovery demands. The results show that major participation barriers include restricted service choice, inadequate information disclosure, imbalances between service rules and passenger rights and interests, service execution flaws, and failures in reward fulfillment and service response. Rigid rules restricting passengers’ ability to modify green flight options under irregular flight conditions represent the most prominent issue. These problems also show dynamic changes over time. Correspondingly, passengers’ recovery demands range from immediate remedies to systematic optimization, including responsibility-taking and rule improvement, compensation, explanations and notification, timely processing, reward fulfillment, service attitude improvement, and stronger internal governance. The findings indicate that sustainable service adoption depends not only on environmental willingness but also on whether the service system reduces participation costs and uncertainty. This study develops a “service failure–passenger demand–service recovery” framework for passenger-participatory sustainable services.

Systems doi: 10.3390/systems14111356

Authors: Bowen Shan Wenqian Jia Xiu Jin

As artificial intelligence (AI) increasingly reshapes how organizations operate, innovate, and compete, employees face increasing pressure to adapt to rapidly evolving digital work environments. However, whether employees translate AI-related awareness into innovative outcomes may depend not only on their proactive adaptation behaviors but also on contextual and individual conditions. Drawing on the job demand-resource theory and social cognitive theory, this study develops and tests a moderated mediation model in which AI crafting mediates the relationship between AI awareness and digital innovativeness, whereas perceived digital leadership and AI self-efficacy serve as contextual and individual boundary conditions, respectively. Using single-wave, single-source data collected from 606 employees in China’s IT and manufacturing industries, the results indicate that AI awareness is positively associated with digital innovativeness through AI crafting. Moreover, perceived digital leadership and AI self-efficacy strengthen the positive associations between AI awareness and AI crafting and between AI awareness and digital innovativeness. These findings extend research on AI awareness by examining how employees’ awareness of AI-related changes is associated with digital innovativeness through proactive work adjustment and by highlighting the complementary roles of perceived contextual support and individual capability beliefs.

Systems doi: 10.3390/systems14111355

Authors: Nina Carolin von Grumbkow Amelie Sprenger Cornelia Gräsel Kathrin Fussangel

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Systems doi: 10.3390/systems14111354

Authors: Ján Dvorský Iveta Chmielová Dalajková Judit Olah

The aim of this scientific article is to identify the key aspects of the concept of corporate social responsibility (CSR) based on managers’ psychological perceptions and to quantify their relationship with employee stability (ES). The subject of the research was selected aspects of CSR (strategic CSR management; effective implementation & communication; financial commitment; internal use & employee satisfaction; internal dissemination) and ES (organizational image; ethical corporate culture; safety and health protection; rewards, KPI and loyalty; growth through training). The quantitative research was carried out using a uniquely created questionnaire. The research sample contained 442 key managers from the business environment of the Czech Republic. The statistical hypotheses were evaluated using the structural equation modeling (SEM) method. The quantitative research revealed interesting findings. There are direct positive associations between the use of the aspects of the CSR concept and employee stability. Effective implementation & communication, together with financial commitment, are the aspects most strongly associated with employee stability. A surprising finding is that growth through training has no links to employee stability. On the contrary, organizational image, together with rewards and loyalty, are the key aspects with links to employee stability. The findings bring new impulses for owners and top managers, who are the key persons responsible for the management and sustainable growth of the enterprise and its activities.

Systems doi: 10.3390/systems14111353

Authors: Jack Homer

Simplified versions of three larger, previously published system dynamics policy simulation models were built and tested. The three models address (a) evolving use of a new medical technology; (b) the U.S. opioid epidemic; and (c) local healthcare system performance and financing. The smaller models produce key outputs and policy results that resemble those of the original larger models, although, of course, in a less thorough and detailed way. The purpose of this exercise was to determine whether simplification might be a broadly applicable strategy for modelers seeking to make their large policy models more transparent. If model simplification can lead to the same central policy findings as a larger version does, then it may serve as an additional tool for learning beyond descriptive documentation, experiential “flight simulators”, and loop dominance analysis of the large model.

Systems doi: 10.3390/systems14111352

Authors: Jingyi Zhuang Ziqi Zhao Mingliang Chen

Digital transformation has become a central strategic priority for firms, with its value creation increasingly extending beyond organizational boundaries through shared information systems, data exchange, and coordinated supply chain processes. This growing interdependence creates a strategic coordination problem because suppliers and customers may differ both in the emphasis they place on digital transformation and in the strategic objectives they pursue. Existing research provides limited understanding of how alignment in these two attributes is associated with supplier performance. We therefore distinguish digital orientation intensity fit from digital orientation strategic intent fit and examine their associations with supplier performance and the moderating role of supplier degree centrality. Using matched supplier–customer data for Chinese listed firms from 2001 to 2023, we find that digital orientation intensity fit is negatively associated with supplier performance, whereas digital orientation strategic intent fit exhibits an inverted U-shaped relationship with supplier performance. Supplier degree centrality weakens the negative relationship between intensity fit and supplier performance and steepens the inverted U-shaped relationship between strategic intent fit and supplier performance. This study contributes to the literature on digital orientation and strategic fit by adopting a supplier–customer dyadic perspective, distinguishing the performance implications of two forms of digital orientation fit, and identifying supplier network position as an important boundary condition. The findings also provide practical guidance for suppliers in managing digital collaboration with customers according to the form of alignment and their network position.