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Empirical Analysis of Hierarchical Pathfinding in Lifelong Multi-Agent Pathfinding with Turns
Evaluating the Benefits and Drawbacks of Visualizing Systems Modeling Language (SysML) Diagrams in the 3D Virtual Reality Environment
The Impact of System Models on Systems Thinking in the Context of Climate Change in Elementary School
Unravelling the Motivational Dynamics of Established Entrepreneurs: A Systems Perspective

Journal Description

Systems

Systems is an international, peer-reviewed, open access journal on systems theory in practice, including fields such as systems engineering management, systems based project planning in urban settings, health systems, environmental management and complex social systems, published monthly online by MDPI. The International Society for the Systems Sciences (ISSS) is affiliated with Systems and its members receive a discount on the article processing charges.

Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
High Visibility: indexed within Scopus, SSCI (Web of Science), Ei Compendex, dblp, and other databases.
Journal Rank: JCR - Q1 (Social Sciences, Interdisciplinary) / CiteScore - Q2 (Modeling and Simulation)
Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 18.8 days after submission; acceptance to publication is undertaken in 2.8 days (median values for papers published in this journal in the first half of 2025).
Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.

Impact Factor: 3.1 (2024); 5-Year Impact Factor: 3.1 (2024)

Imprint Information Journal Flyer Open Access ISSN: 2079-8954

Latest Articles

30 pages, 1020 KiB

Open AccessArticle

Beyond the Counter: A Systemic Mapping of Nanostore Identities in Traditional, Informal Retail Through Multi-Dimensional Archetypes

by David Ernesto Salinas-Navarro, Eliseo Vilalta-Perdomo and Christopher Mejía-Argueta

Systems 2025, 13(7), 546; https://doi.org/10.3390/systems13070546 (registering DOI) - 5 Jul 2025

This study examines the identity of nanostores—micro, independent grocery retailers—through a systemic, stakeholder-informed lens to promote their survivability and competitiveness. Moving beyond traditional operational descriptions, it introduces a multidimensional framework that examines what nanostores do (X), how they do it (Y), and why [...] Read more.

This study examines the identity of nanostores—micro, independent grocery retailers—through a systemic, stakeholder-informed lens to promote their survivability and competitiveness. Moving beyond traditional operational descriptions, it introduces a multidimensional framework that examines what nanostores do (X), how they do it (Y), and why they matter (Z), which is complemented by the use of the TASCOI tool to produce identity statements. Based on survey data collection and a thematic analysis of nanostore stakeholder responses in Mexico City, the research categorises identity statements into six 2 × 2 matrices across four dimensions: operational, functional, relational, and adaptive. This analysis yields twenty-four archetypes that capture the diversity, complexity, and adaptability of nanostores. The findings reveal that nanostores are not a homogeneous category. They simultaneously exhibit characteristics of multiple archetypes, blending retail function, social embeddedness, and entrepreneurial adaptation. This study contributes to the nanostore and micro-enterprise literature by operationalising identity description and offers practical insights for supporting diverse shop types through context-sensitive policy and business strategies. While this study ensures internal validity and reliability through systematic coding and stakeholder feedback, it acknowledges limitations in its generalisability. Future research may build on this work through comparative studies, longitudinal tracking, and direct engagement with nanostore owners and their communities to further understand the dynamics of their identity and their resilience in evolving retail landscapes. Full article

(This article belongs to the Special Issue Systems Thinking: Insights and Solutions to Complex Societal Challenges)

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29 pages, 2426 KiB

Open AccessArticle

Domain Knowledge-Enhanced Process Mining for Anomaly Detection in Commercial Bank Business Processes

by Yanying Li, Zaiwen Ni and Binqing Xiao

Systems 2025, 13(7), 545; https://doi.org/10.3390/systems13070545 (registering DOI) - 4 Jul 2025

Process anomaly detection in financial services systems is crucial for operational compliance and risk management. However, traditional process mining techniques frequently neglect the detection of significant low-frequency abnormalities due to their dependence on frequency and the inadequate incorporation of domain-specific knowledge. Therefore, we [...] Read more.

Process anomaly detection in financial services systems is crucial for operational compliance and risk management. However, traditional process mining techniques frequently neglect the detection of significant low-frequency abnormalities due to their dependence on frequency and the inadequate incorporation of domain-specific knowledge. Therefore, we develop an enhanced process mining algorithm by incorporating a domain-specific follow-relationship matrix derived from standard operating procedures (SOPs). We empirically evaluated the effectiveness of the proposed algorithm based on real-world event logs from a corporate account-opening process conducted from January to December 2022 in a Chinese commercial bank. Additionally, we employed large language models (LLMs) for root cause analysis and process optimization recommendations. The empirical results demonstrate that the E-Heuristic Miner significantly outperforms traditional machine learning methods and process mining algorithms in process anomaly detection. Furthermore, the integration of LLMs provides promising capabilities in semantic reasoning and offers explainable optimization suggestions, enhancing decision-making support in complex financial scenarios. Our study significantly improves the precision of process anomaly detection in financial contexts by incorporating banking-specific domain knowledge into process mining algorithms. Meanwhile, it extends theoretical boundaries and the practical applicability of process mining in intelligent, semantic-aware financial service management. Full article

(This article belongs to the Special Issue Business Process Management Based on Big Data Analytics)

14 pages, 681 KiB

Open AccessArticle

Using Systems Thinking to Manage Tourist-Based Nutrient Pollution in Belizean Cayes

by Daniel A. Delgado, Martha M. McAlister, W. Alex Webb, Christine Prouty, Sarina J. Ergas and Maya A. Trotz

Systems 2025, 13(7), 544; https://doi.org/10.3390/systems13070544 (registering DOI) - 4 Jul 2025

Tourism offers many economic benefits but can have long-lasting ecological effects when improperly managed. Tourism can cause overwhelming pressure on wastewater treatment systems, as in Belize, where some of the over 400 small islands (cayes) that were once temporary sites for fishermen have [...] Read more.

Tourism offers many economic benefits but can have long-lasting ecological effects when improperly managed. Tourism can cause overwhelming pressure on wastewater treatment systems, as in Belize, where some of the over 400 small islands (cayes) that were once temporary sites for fishermen have become popular tourist destinations. An overabundance of nitrogen, in part as a result of incomplete wastewater treatment, threatens human health and ecosystem services. The tourism industry is a complex and dynamic industry with many sectors and stakeholders with conflicting goals. In this study, a systems thinking approach was adopted to study the dynamic interactions between stakeholders and the environment at Laughing Bird Caye National Park in Belize. The project centered on nutrient discharges from the caye’s onsite wastewater treatment system. An archetype analysis approach was applied to frame potential solutions to nutrient pollution and understand potential behaviors over time. “Out of control” and “Underachievement” were identified as system archetypes; “Shifting the Burden” and ‘‘Limits to Success’’ were used to model specific cases. Based on these results, upgrading of the wastewater treatment system should be performed concurrently with investments in the user experience of the toilets, education on the vulnerability of the treatment system and ecosystem, and controls on the number of daily tourists. Full article

(This article belongs to the Special Issue Systems Thinking: Insights and Solutions to Complex Societal Challenges)

36 pages, 1590 KiB

Open AccessArticle

Concept of an Integrated Urban Public Transport System Linked to a Railway Network Based on the Principles of a Timed-Transfer Timetable in the City of Prievidza

by Zdenka Bulková, Eva Brumerčíková, Bibiána Buková and Tomáš Mihalik

Systems 2025, 13(7), 543; https://doi.org/10.3390/systems13070543 (registering DOI) - 4 Jul 2025

Urban public transport represents a fundamental pillar of a sustainable transport system and a key subsystem within the broader mobility framework in urban environments. This paper focuses on the analysis and optimization of the public transport system in the city of Prievidza and [...] Read more.

Urban public transport represents a fundamental pillar of a sustainable transport system and a key subsystem within the broader mobility framework in urban environments. This paper focuses on the analysis and optimization of the public transport system in the city of Prievidza and the nearby town of Bojnice in Slovakia, which currently face challenges such as low system attractiveness, operational inefficiency, and weak integration with regional railway transport. This study presents the results of a comprehensive analysis of existing public transport services in Prievidza and Bojnice, including an assessment of passenger flows, line network structure, transfer connections, and operational parameters. Based on the identified deficiencies, a new urban public transport network system is proposed, emphasizing direct links to the railway network. This methodology is developed in the context of an integrated timed-transfer timetable, with defined system time slots at the main transfer hub and a newly designed line network with standardized paths and regular intervals. The proposed system ensures significantly improved connectivity between urban transport and rail services, reduces deadhead kilometres, lowers the number of required vehicles, and leads to a reduction in operational costs by up to 20%. The resulting model serves as a transferable example of efficient service planning in medium-sized cities, with a focus on functional integration, operational efficiency, and sustainable urban development. Full article

(This article belongs to the Special Issue Optimization-Based Decision-Making Models in Rail Systems Engineering)

26 pages, 997 KiB

Open AccessArticle

The Effects of Land Use Mix on Urban Vitality: A Systemic Conceptualization and Mechanistic Exploration

by Yuefei Zhuo, Hangang Hu and Guan Li

Systems 2025, 13(7), 542; https://doi.org/10.3390/systems13070542 - 2 Jul 2025

Urban vitality, a critical emergent property of complex urban systems, is pivotal for sustainable, human-oriented urbanization. While land use mix (LUM) is recognized as a key strategy for shaping these systems, the systemic mechanisms through which its multifaceted dimensions influence urban vitality across [...] Read more.

Urban vitality, a critical emergent property of complex urban systems, is pivotal for sustainable, human-oriented urbanization. While land use mix (LUM) is recognized as a key strategy for shaping these systems, the systemic mechanisms through which its multifaceted dimensions influence urban vitality across spatio-temporal scales remain underexplored. This study examines the complex and spatially heterogeneous impacts of land use mix on 24 h urban vitality in Ningbo, China, conceptualizing the city as a dynamic socio-spatial system. By integrating multi-source data (Baidu Maps, POI, and OSM) and employing OLS and geographically weighted regression (GWR) models, we unravel these systemic relationships. Key findings include the following: (1) LUM significantly enhances urban vitality, acting as a crucial urban system configuration for both daytime and nighttime activity. (2) The efficacy of LUM stems more from systemic interconnections—convenient access to adjacent spaces (proximity) and functional coordination among diverse land uses—than mere compositional diversity, emphasizing the importance of interrelated elements within the urban fabric. (3) The system’s response to LUM exhibits significant spatial and temporal heterogeneity; proximity’s impact is most variable, while diversity and coordination effects are more stable, underscoring the dynamic and context-dependent nature of these interactions. (4) System-adaptive strategies are crucial: newly developed urban areas benefit from foundational infrastructure and land use diversity (system inputs), while revitalizing older towns requires optimizing spatial accessibility and functional coordination (enhancing existing system linkages). These findings advance the theoretical systems-based theoretical understanding of the LUM–vitality nexus while offering practical insights for urban planners and policymakers. Full article

(This article belongs to the Special Issue Complex Systems Theory in Regional and Urban Marketing: Strategies for Resilient, Sustainable, and Smart Cities)

21 pages, 4238 KiB

Open AccessArticle

Time-Varying Reliability Analysis of Integrated Power System Based on Dynamic Bayesian Network

by Jiacheng Wei, Tong Chen, Haolin Wen and Haobang Liu

Systems 2025, 13(7), 541; https://doi.org/10.3390/systems13070541 - 2 Jul 2025

In response to the limitations of traditional static reliability analysis methods in characterizing the reliability changes of the Integrated Power System, this paper proposes a time-varying reliability analysis framework based on a Dynamic Bayesian Network. By embedding a multi-physics coupled degradation model into [...] Read more.

In response to the limitations of traditional static reliability analysis methods in characterizing the reliability changes of the Integrated Power System, this paper proposes a time-varying reliability analysis framework based on a Dynamic Bayesian Network. By embedding a multi-physics coupled degradation model into the conditional probability nodes of the Dynamic Bayesian Network, a joint stochastic differential equation for the degradation process was constructed, and the dynamic correlation between continuous degradation and discrete fault events throughout the entire life cycle was achieved. A modified method for modeling continuous degradation systems was proposed, which effectively solves the numerical stability problem of modeling complex degradation systems. Finally, the applicability and correctness of the model were verified through numerical examples, and the results showed that the analysis framework can be effectively applied to time-varying reliability assessment and dynamic health management of complex equipment systems such as the Integrated Power System. Full article

(This article belongs to the Special Issue Advances in Reliability Engineering for Complex Systems)

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31 pages, 4591 KiB

Open AccessArticle

Modeling Affective Mechanisms in Relaxing Video Games: Sentiment and Topic Analysis of User Reviews

by Yuxin Xing, Wenbao Ma, Qiang You and Jiaxing Li

Systems 2025, 13(7), 540; https://doi.org/10.3390/systems13070540 - 1 Jul 2025

The accelerating pace of digital life has intensified psychological strain, increasing the demand for accessible and systematized emotional support tools. Relaxing video games—defined as low-pressure, non-competitive games designed to promote calm and emotional relief—offer immersive environments that facilitate affective engagement and sustained user [...] Read more.

The accelerating pace of digital life has intensified psychological strain, increasing the demand for accessible and systematized emotional support tools. Relaxing video games—defined as low-pressure, non-competitive games designed to promote calm and emotional relief—offer immersive environments that facilitate affective engagement and sustained user involvement. This study proposes a computational framework that integrates sentiment analysis and topic modeling to investigate the affective mechanisms and behavioral dynamics associated with relaxing gameplay. We analyzed nearly 60,000 user reviews from the Steam platform in both English and Chinese, employing a hybrid methodology that combines sentiment classification, dual-stage Latent Dirichlet Allocation (LDA), and multi-label mechanism tagging. Emotional relief emerged as the dominant sentiment (62.8%), whereas anxiety was less prevalent (10.4%). Topic modeling revealed key affective dimensions such as pastoral immersion and cozy routine. Regression analysis demonstrated that mechanisms like emotional relief (β = 0.0461, p = 0.001) and escapism (β = 0.1820, p < 0.001) were significant predictors of longer playtime, while Anxiety Expression lost statistical significance (p = 0.124) when contextual controls were added. The findings highlight the potential of relaxing video games as scalable emotional regulation tools and demonstrate how sentiment- and topic-driven modeling can support system-level understanding of affective user behavior. This research contributes to affective computing, digital mental health, and the design of emotionally aware interactive systems. Full article

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

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20 pages, 1067 KiB

Open AccessArticle

The Impact of Dual-Channel Investments and Contract Mechanisms on Telecommunications Supply Chains

by Yongjae Kim

Systems 2025, 13(7), 539; https://doi.org/10.3390/systems13070539 - 1 Jul 2025

This study examines how contract structures influence coordination and innovation incentives in dual-channel telecommunications supply chains. We consider a setting where a mobile network operator (MNO) supplies services both directly to consumers and indirectly through a mobile virtual network operator (MVNO), which competes [...] Read more.

This study examines how contract structures influence coordination and innovation incentives in dual-channel telecommunications supply chains. We consider a setting where a mobile network operator (MNO) supplies services both directly to consumers and indirectly through a mobile virtual network operator (MVNO), which competes in the retail market. Using a game-theoretic framework, we evaluate how different contracts—single wholesale pricing, revenue sharing, and quantity discounts—shape strategic decisions, particularly in the presence of investment spillovers between parties. A key coordination problem emerges from the externalized gains of innovation, where one party’s investment generates value for both participants. Our results show that single wholesale and revenue sharing contracts often lead to suboptimal investment and profit outcomes. In contrast, quantity discount contracts, especially when combined with appropriate transfer payments, improve coordination and enhance the total performance of the supply chain. We also find that innovation led by the MVNO, while generally less impactful, can still yield reciprocal benefits for the MNO, reinforcing the value of cooperative arrangements. These findings emphasize the importance of contract design in managing interdependence and improving efficiency in decentralized supply chains. This study offers theoretical and practical implications for telecommunications providers and policymakers aiming to promote innovation and mutually beneficial outcomes through well-aligned contractual mechanisms. Full article

(This article belongs to the Special Issue Systems Methodology in Sustainable Supply Chain Resilience)

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34 pages, 3561 KiB

Open AccessArticle

Research on Pricing and Effort Investment Decisions for Dual-Channel Fresh Product Supply Chain Under the Participation of Third-Party Logistics Provider

by Yunting Wu, Aimin Zhu, Lijuan Yu and Wenbo Wang

Systems 2025, 13(7), 538; https://doi.org/10.3390/systems13070538 - 1 Jul 2025

This study takes the dual-channel fresh product supply chain involving the participation of third-party logistics (3PL) as the background to explore how 3PL makes choices between homogeneous and differentiated logistics service strategies and how the supply chain formulates optimal decisions under different logistics [...] Read more.

This study takes the dual-channel fresh product supply chain involving the participation of third-party logistics (3PL) as the background to explore how 3PL makes choices between homogeneous and differentiated logistics service strategies and how the supply chain formulates optimal decisions under different logistics service strategies to achieve maximum benefits. This paper constructs a sequential game model of the three-tier supply chain composed of 3PL, a supplier, and a retailer; uses the consumer utility function to describe market demand; and considers different logistics service strategies adopted by 3PL. It compares and analyzes the equilibrium strategies under the traditional retail channel (O Model), the homogeneous cold-chain service dual-channel model (D1 Model), and the differentiated cold-chain service dual-channel model (D2 Model). The results show the following: (1) The D1 Model reduces the transportation cost of the supply chain through economies of scale. Under the D2 Model, the transportation and sales prices of the offline channels are higher than those of the online channels, while the online marketing effort is higher than that of the offline channels. (2) The profits generated by the dual-channel models (D1 Model and D2 Model) are both higher than those of O Model. In most cases, the D1 Model generates the highest system profit. However, in scenarios where consumers are highly sensitive to freshness and marketing efforts, the system profit of the D2 Model is higher than that of the D1 Model. (3) The supply chain has lower pricing and effort input when consumers are more sensitive to prices and higher pricing and effort input when consumers are more sensitive to freshness. These findings contribute valuable insights to the field of supply chain management, particularly in the context of fresh product supply chains involving 3PL. They underscore the importance of considering consumer behavior and logistics service strategies in optimizing supply chain performance and highlight the potential trade-offs between standardization and differentiation in logistics services. Full article

(This article belongs to the Section Supply Chain Management)

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27 pages, 898 KiB

Open AccessArticle

Information Systems Quality and Corporate Sustainability: Unpacking the Interplay of Financial Reporting, Artificial Intelligence, and Green Corporate Governance

by Nidal Neiroukh and Dilber Çağlar

Systems 2025, 13(7), 537; https://doi.org/10.3390/systems13070537 - 1 Jul 2025

This study explores how the quality of information systems quality in management accounting (ISQMA) is associated with corporate sustainability (CS), focusing on the role of financial reporting accuracy and contextual enablers such as artificial intelligence (AI) and green corporate governance (GCG). Drawing on [...] Read more.

This study explores how the quality of information systems quality in management accounting (ISQMA) is associated with corporate sustainability (CS), focusing on the role of financial reporting accuracy and contextual enablers such as artificial intelligence (AI) and green corporate governance (GCG). Drawing on the Resource-Based View and Contingency Theory, the study investigates whether accurate financial data reporting (AFDR) functions as a mechanism through which ISQMA contributes to sustainability outcomes, and whether the presence of AI and GCG strengthens these associations. Empirical data were collected from 257 accounting and finance professionals working in Jordanian commercial banks, providing a robust setting where digital infrastructure and sustainability imperatives converge. The results reveal that ISQMA is positively associated with both AFDR and CS, with AFDR partially mediating this relationship. Moreover, AI and GCG were found to strengthen the relationships between ISQMA and AFDR, and between ISQMA and CS, respectively. These findings underscore that accurate, reliable financial reporting, and strong governance practices enhance the value of digital information systems in achieving corporate sustainability objectives. By integrating information quality, technological capabilities, and governance mechanisms, this study offers a comprehensive understanding of how banks can align their digital infrastructure with sustainable performance goals. The insights contribute to the growing discourse on digitally enabled sustainability and offer actionable implications for both practitioners and policymakers in emerging markets. Full article

(This article belongs to the Special Issue Information Systems Driving Corporate Sustainability)

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26 pages, 1260 KiB

Open AccessArticle

Dual-Path Model of Team Communication and Shared Mental Models in Entrepreneurial Education: Enhancing Team Efficacy in Higher Education Using PLS-SEM

by Shuangshuang Fan, Shali Wang, William Mbanyele and Yongliang Zhang

Systems 2025, 13(7), 536; https://doi.org/10.3390/systems13070536 - 1 Jul 2025

This study explores the influence of team communication (TC) and shared mental models (SMMs) on entrepreneurial team efficacy (ETE) within the context of Chinese higher education, introducing a dual-path model to reconcile the discrepancy between policy expectations and practical outcomes in entrepreneurship education. [...] Read more.

This study explores the influence of team communication (TC) and shared mental models (SMMs) on entrepreneurial team efficacy (ETE) within the context of Chinese higher education, introducing a dual-path model to reconcile the discrepancy between policy expectations and practical outcomes in entrepreneurship education. Utilizing partial least squares structural equation modeling (PLS-SEM) on data from 475 university-based questionnaires from March to May in 2024 in China, the research reveals that structured internal communication significantly enhances the alignment of learning goals, teammate cognition, and activity synchronization, thereby fostering SMMs as a pivotal psychological infrastructure. The findings indicate that shared learning goals and cognitive convergence are primary drivers of task performance, whereas coordinated activity states are more influential in strengthening relational cohesion. The study challenges the conventional “communication frequency–efficacy paradox” by demonstrating distinct pathways through which internal and external communication mechanisms differentiated impact task and relational outcomes. Additionally, demographic analyses highlight that team maturity and age diversity positively correlate with task efficacy, while gender and disciplinary heterogeneity show no significant association. Theoretically, this research advances the understanding of team collaboration dynamics and contextualizes Western entrepreneurship theories within China’s collectivist framework. Practically, it provides robust, evidence-based strategies for refining communication protocols and enhancing both collaborative efficiency and innovation in entrepreneurial education settings. Full article

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20 pages, 617 KiB

Open AccessArticle

The Influence Mechanism of Government Venture Capital on the Innovation of Specialized and Special New “Little Giant” Enterprises

by Qilin Cao, Tianyun Wang, Shiyu Wen, Lingyue Zhou and Weili Zhen

Systems 2025, 13(7), 535; https://doi.org/10.3390/systems13070535 - 1 Jul 2025

Specialized and special new “little giant” enterprises are characterized by specialization, refinement, uniqueness, and innovation. They have relatively strong innovation capabilities and enterprise vitality. However, they also face problems such as high innovation costs, long investment recovery cycles, and high risks of investment [...] Read more.

Specialized and special new “little giant” enterprises are characterized by specialization, refinement, uniqueness, and innovation. They have relatively strong innovation capabilities and enterprise vitality. However, they also face problems such as high innovation costs, long investment recovery cycles, and high risks of investment returns, which lead to information asymmetry and financing difficulties. Government venture capital is a policy fund provided by the government and established with the participation of local governments, financial institutions, and private capital. They can utilize fiscal policies to attract market funds and support the development of key industries. Therefore, in this study, the first through sixth batches of specialized and special new “little giant” enterprises listed on the A-share and New Third Board from 2013 to 2023 were taken as samples, and their investment behavior and investment effects were empirically studied using the multiple linear regression method. The investment behavior of government venture capital tends to target strategic emerging industries. The intervention of government venture capital can enhance the innovation of “little giant” enterprises and has an impact through the intermediary mechanism of R&D investment. This paper draws conclusions and puts forward relevant policy suggestions for supporting the development of “little giant” enterprises. Full article

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

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27 pages, 9166 KiB

Open AccessArticle

Meta-Learning-Based LSTM-Autoencoder for Low-Data Anomaly Detection in Retrofitted CNC Machine Using Multi-Machine Datasets

by Ji-Min Woo, Seong-Hyeon Ju, Jin-Hyeon Sung and Kyung-Min Seo

Systems 2025, 13(7), 534; https://doi.org/10.3390/systems13070534 - 1 Jul 2025

In recent manufacturing environments, the use of digitally retrofitted equipment has grown substantially, yet this trend also amplifies the challenge of ensuring stable operation through effective anomaly detection. Retrofitted systems suffer from two critical obstacles: a severe scarcity of labeled data and substantial [...] Read more.

In recent manufacturing environments, the use of digitally retrofitted equipment has grown substantially, yet this trend also amplifies the challenge of ensuring stable operation through effective anomaly detection. Retrofitted systems suffer from two critical obstacles: a severe scarcity of labeled data and substantial variability in operational patterns across machines and products. To overcome these issues, this study introduces a novel anomaly detection framework that integrates Model-Agnostic Meta-Learning (MAML) with a Long Short-Term Memory Autoencoder (LSTM-Autoencoder) under a multi-machine-based task formulation. By constructing meta-tasks from time-series datasets collected on multiple five-axis computer numerical control (CNC) machines, our method enables rapid adaptation to unseen machines and production scenarios with only a few training examples. The experimental results demonstrate that, even under data-scarce conditions, the proposed model achieves an accuracy of 98.02% and an F1-score of 94.74%, representing improvements of 4.2 percentage points in accuracy and 16.9 percentage points in F1-score over conventional transfer learning approaches. Furthermore, in cross-validation on entirely new machine data, our framework outperforms existing models by 18.1% in accuracy, evidencing superior generalization capability. These findings suggest that the proposed multi-machine-based Model-Agnostic Meta-Learning Long Short-Term Memory Autoencoder (MAML LSTM-Autoencoder) can significantly enhance operational efficiency and reduce maintenance costs in retrofitted manufacturing equipment, thereby improving overall productivity and paving the way for real-time industrial deployment. Full article

(This article belongs to the Special Issue Data-Driven Analysis of Industrial Systems Using AI)

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22 pages, 1598 KiB

Open AccessArticle

Research on the Spatial Correlation Pattern of Sustainable Development of Cities in the Yangtze River Delta Region of China, Based on the Dynamic Coupling Perspective of “Ecology-Economy”

by Zhujie Chu, Qi Ge and Lufa Zhang

Systems 2025, 13(7), 533; https://doi.org/10.3390/systems13070533 - 1 Jul 2025

Focusing on the dynamic change process of urban ecology and economy, this paper explores the spatial correlation pattern of cities in the Yangtze River Delta (YRD) region for sustainable development from 2012 to 2023 based on the coupled coordination model, gravitational model, and [...] Read more.

Focusing on the dynamic change process of urban ecology and economy, this paper explores the spatial correlation pattern of cities in the Yangtze River Delta (YRD) region for sustainable development from 2012 to 2023 based on the coupled coordination model, gravitational model, and social network analysis (SNA). First, the sustainable development level of the city shows a certain upward trend in the time dimension. In the spatial dimension, there is significant regional differentiation, which roughly shows the development characteristics of gradual increase from the interior to the coast. Second, cities with lower-level sustainable development and higher-level sustainable development always maintain their own stability, but being adjacent to a city with lower-level sustainable development increases the probability of an improvement. Third, cities that play an important role in driving the level of spatial correlation for sustainable development are mainly concentrated in the central and eastern parts of the YRD, with Shanghai, Suzhou, Nanjing, and Hangzhou being the most important radiation centers in the pattern of spatial correlation. Fourth, the affiliation system of sustainable development gradually changes from the double core system of Shanghai–Suzhou to the triple core system of Shanghai–Suzhou–Hangzhou to drive and lead the development of the subordinate cities. Fifth, the spatial network can be categorized into four plates: benefit, overflow, bilateral spillover, and broker, with obvious linkage effects between plates. Full article

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

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20 pages, 2061 KiB

Open AccessArticle

Mathematical Modeling Approach to Assessing Math Education Levels in Secondary and High Schools: Pandemic Impact and Post-Pandemic Projections

by Sakar Ismael Gharib, Bilgen Kaymakamzade, Ahmet Karahan and Murat Tezer

Systems 2025, 13(7), 532; https://doi.org/10.3390/systems13070532 - 1 Jul 2025

This study compares the views of mathematics teachers in private and public schools on mathematics education during the COVID-19 pandemic from their perspectives after the pandemic, focusing on factors influencing secondary and high school mathematics education. In this study, the survey method was [...] Read more.

This study compares the views of mathematics teachers in private and public schools on mathematics education during the COVID-19 pandemic from their perspectives after the pandemic, focusing on factors influencing secondary and high school mathematics education. In this study, the survey method was used to collect data. The survey method was employed to obtain information for this investigation. During the 2023–2024 school year, 644 math teachers took part in the study. Of these, 260 were from private schools, and 384 were from public schools. There are 10,323 teachers in public schools and 694 in private schools, and this sample size is more than the 371 participants that are needed for statistical purposes (based on Cochran’s formula at a 95% confidence level and a 5% margin of error). A scale consisting of thirteen 5-point Likert-type questions was developed by researchers for data collection, and mathematical modeling techniques were employed. Factor analysis using SPSS 24.00 revealed four key factors influencing teachers’ responses: teachers’ professional development and support, job satisfaction, students’ engagement, and teaching experience. The results highlight significant disparities between public and private schools in mathematics education, attributed to various factors to be elucidated further in the subsequent discussion. Full article

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

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35 pages, 2423 KiB

Open AccessArticle

Inclusive Internal Financing, Selective Internal Financing, or Hybrid Financing? A Competitive Low-Carbon Supply Chain Operational and Financing Strategies

by Xiaoli Zhang, Lin Zhang and Caiquan Duan

Systems 2025, 13(7), 531; https://doi.org/10.3390/systems13070531 - 1 Jul 2025

Amidst escalating concerns about climate change, manufacturers are increasingly pressured to adopt a low-carbon supply chain (LCSC). Financial constraints deter numerous companies from embracing low-carbon initiatives in a competitive landscape. Inclusive internal financing (IIF) provides operational funds from capital-abundant members to capital-constrained members, [...] Read more.

Amidst escalating concerns about climate change, manufacturers are increasingly pressured to adopt a low-carbon supply chain (LCSC). Financial constraints deter numerous companies from embracing low-carbon initiatives in a competitive landscape. Inclusive internal financing (IIF) provides operational funds from capital-abundant members to capital-constrained members, resolving funding shortages internally within the system. However, when dominant members cannot support all such enterprises, selective internal financing (SIF) or hybrid financing (HF) becomes necessary. This paper studies the operation and financing strategies of a competitive LCSC. Within the framework of an LCSC where two capital-constrained retailers compete, using Stackelberg game theory and the backward induction method, three game-theoretical models are developed under IIF, SIF, and HF. The results indicate that increased competition intensity reduces product sales price, the manufacturer’s carbon emission reduction level, and profit. When competition intensity is high, SIF more effectively enhances carbon emission reduction level, product sales quantity, and profit acquisition. HF reduces profits for the allied retailer and diminishes its competitiveness, yet enhances the competitive strength of the rival retailer. Numerical analysis demonstrates that when equity financing in HF exceeds 0.546, the allied retailer becomes unprofitable and is driven out of the market. This study complements LCSC finance research and provides references for supply chain operations and financing strategy formulation. Full article

(This article belongs to the Section Supply Chain Management)

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21 pages, 538 KiB

Open AccessArticle

AI Awareness and Employee Innovation: A Dual-Pathway Moderated Mediation Model Within Organizational Systems

by Zhaoqi Li, Myeong-Cheol Choi and Hann-Earl Kim

Systems 2025, 13(7), 530; https://doi.org/10.3390/systems13070530 - 1 Jul 2025

Amid AI-driven organizational transformation, employees’ subjective evaluations of AI technologies—referred to as AI awareness—have become a critical psychological factor influencing innovation behavior. This study aims to uncover how AI awareness affects employee innovation performance through behavioral pathways and examines the moderating role of [...] Read more.

Amid AI-driven organizational transformation, employees’ subjective evaluations of AI technologies—referred to as AI awareness—have become a critical psychological factor influencing innovation behavior. This study aims to uncover how AI awareness affects employee innovation performance through behavioral pathways and examines the moderating role of individual achievement motivation in this process. Grounded in Cognitive Appraisal Theory and the Dual Pathway Model, we construct a dual-path mediation model, in which proactive and withdrawal behaviors act as mediators, and achievement motivation serves as a boundary condition. Based on a two-wave survey of 413 knowledge workers in China’s high-tech sector, the proposed model was empirically tested using moderated mediation analysis (PROCESS macro). The results reveal that AI awareness has a significant dual-path effect on innovation behavior: on the one hand, it promotes innovation by stimulating proactive behavior; on the other hand, it may suppress innovation by inducing withdrawal behavior. Moreover, achievement motivation plays a crucial moderating role in this mechanism by strengthening the positive mediating effect of proactive behavior and weakening the negative mediating effect of withdrawal behavior. This study conceptualizes AI awareness as a psychological input encompassing both perceived opportunity and perceived threat, clarifies the behavioral response mechanisms of employees facing AI, and highlights the boundary-regulating role of individual motivation in organizational adaptability. Practically, the study suggests designing differentiated HR interventions based on employees’ cognitive appraisals and motivational profiles to enhance human–AI collaboration, foster innovation resilience, and improve organizational adaptability amid digital transformation. Full article

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

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33 pages, 8044 KiB

Open AccessArticle

Building Ledger Dossier: Case Study of Seismic Damage Mitigation and Building Documentation Tracking Through a Digital Twin Approach

by Giovanni De Gasperis, Sante Dino Facchini and Asif Saeed

Systems 2025, 13(7), 529; https://doi.org/10.3390/systems13070529 - 1 Jul 2025

In recent years, numerous regions worldwide have experienced devastating natural disasters, leading to significant structural damage to buildings and loss of human lives. The reconstruction process highlights the need for a reliable method to document and track the maintenance history of buildings. This [...] Read more.

In recent years, numerous regions worldwide have experienced devastating natural disasters, leading to significant structural damage to buildings and loss of human lives. The reconstruction process highlights the need for a reliable method to document and track the maintenance history of buildings. This paper introduces a novel approach for managing and monitoring restoring interventions using a secure and transparent digital framework. We will also present an application aimed at improving building structures with respect to earthquake resistance. The proposed system, referred as the “Building Ledger Dossier”, leverages a Digital Twin approach applied to blockchain to establish an immutable record of all structural interventions. The framework models buildings using OpenSees, while all maintenance, repair activities, and documents are registered as Non-Fungible Tokens on a blockchain network, ensuring timestamping, transparency, and accountability. A Decentralized Autonomous Organization oversees identity management and work validation, enhancing security and efficiency in building restoration efforts. This approach provides a scalable and globally applicable solution for improving both ante-disaster monitoring and post-disaster reconstruction, ensuring a comprehensive, verifiable history of structural interventions and fostering trust among stakeholders. The proposed method is also applicable to other types of processes that require the aforementioned properties for document monitoring, such as the life-cycle management of tax credits and operations in the financial or banking sectors. Full article

(This article belongs to the Special Issue Advancements in Practical Applications of Agents, Multi-Agent Systems and Digital Twins)

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26 pages, 2120 KiB

Open AccessArticle

Strategic Interaction Between Brands and KOLs in Live-Streaming E-Commerce: An Evolutionary Game Analysis Using Prospect Theory

by Shizhe Shao, Yonggang Wang, Zheng Li, Luxin Li, Xiuping Shi, Hao Liu and Ziyu Gao

Systems 2025, 13(7), 528; https://doi.org/10.3390/systems13070528 - 1 Jul 2025

This study adopts an evolutionary game theory framework and focuses on the strategic interaction between brands and KOLs. It examines how the two parties interact under conditions of uncertainty and risk, especially when the KOLs’ contract fulfillment capability is low, and how they [...] Read more.

This study adopts an evolutionary game theory framework and focuses on the strategic interaction between brands and KOLs. It examines how the two parties interact under conditions of uncertainty and risk, especially when the KOLs’ contract fulfillment capability is low, and how they adjust strategies to achieve sustainable collaboration. Different from previous studies, this paper not only examines objective parameters such as commission rate, brand value, return cost, and reputation risk, but also introduces behavioral factors, including risk preference, loss aversion, and the psychological perception of gains and losses. By modeling the decision-making process of KOLs and brands under uncertainty and risk, the key factors affecting the evolution of cooperation strategies are identified. The simulation results show that although the cooperation strategy (such as information disclosure and truthful promotion) can achieve stability under certain conditions, the system is highly sensitive to external factors (such as environmental uncertainty) and internal psychological factors (such as risk preference and loss sensitivity). This study provides practical suggestions for brands and KOLs to promote long-term cooperation, emphasizing the importance of incentive coordination, reputation risk management, commission structure optimization, and psychological perception regulation. These findings provide practical guidance for enhancing the sustainability of brand–KOL collaborations. Full article

(This article belongs to the Section Supply Chain Management)

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27 pages, 1156 KiB

Open AccessArticle

Novel Conformable Fractional Order Unbiased Kernel Regularized Nonhomogeneous Grey Model and Its Applications in Energy Prediction

by Wenkang Gong and Qiguang An

Systems 2025, 13(7), 527; https://doi.org/10.3390/systems13070527 - 1 Jul 2025

Grey models have attracted considerable attention as a time series forecasting tool in recent years. Nevertheless, the linear characteristics of the differential equations on which traditional grey models rely frequently result in inadequate predictive accuracy and applicability when addressing intricate nonlinear systems. This [...] Read more.

Grey models have attracted considerable attention as a time series forecasting tool in recent years. Nevertheless, the linear characteristics of the differential equations on which traditional grey models rely frequently result in inadequate predictive accuracy and applicability when addressing intricate nonlinear systems. This study introduces a conformable fractional order unbiased kernel-regularized nonhomogeneous grey model (CFUKRNGM) based on statistical learning theory to address these limitations. The proposed model initially uses a conformable fractional-order accumulation operator to derive distribution information from historical data. A novel regularization problem is then formulated, thereby eliminating the bias term from the kernel-regularized nonhomogeneous grey model (KRNGM). The parameter estimation of the CFUKRNGM model requires solving a linear equation with a lower order than the KRNGM model, and is automatically calibrated through the Bayesian optimization algorithm. Experimental results show that the CFUKRNGM model achieves superior prediction accuracy and greater generalization performance compared to both the KRNGM and traditional grey models. Full article

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