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Volume 13
Issue 4
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Systems, Volume 13, Issue 4 (April 2025) – 91 articles

Cover Story (view full-size image): Present-day systems are increasingly complex due to numerous subsystem interactions, such as those in electromechanical drivetrains and cooling systems. MBSE introduces system models to virtually represent architecture and behavior. These models rely on reusable system elements, improving development efficiency. However, standardized libraries for heat-exchanging systems are lacking. In the following paper, we present a method to identify reusable “solution elements” in thermal systems, focusing on functional and heat-transfer processes at the contact level. A case study focusing on an electric truck’s thermal management system demonstrates that 14 recurring elements can represent more than 300,000 thermal interactions, enabling efficient MBSE modelling. View this paper
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18 pages, 1541 KiB  
Article
The Development of a Methodology for Assessing Data Value Through the Identification of Key Determinants
by Daye Lee and Byungun Yoon
Systems 2025, 13(4), 305; https://doi.org/10.3390/systems13040305 - 21 Apr 2025
Viewed by 150
Abstract
This study introduces a methodology for assessing data value by identifying the key determinants that influence it. As data represents critical assets in modern business, companies must evaluate and use them strategically to maintain competitiveness. However, the intangible and complex nature of data [...] Read more.
This study introduces a methodology for assessing data value by identifying the key determinants that influence it. As data represents critical assets in modern business, companies must evaluate and use them strategically to maintain competitiveness. However, the intangible and complex nature of data makes objective valuation difficult. The proposed methodology categorizes data value determinants into two groups: essential value factors (completeness, accuracy, uniqueness, and consistency) and value-of-use factors (risk, timeliness, restrictive use, accessibility, and utility). This study analyzes the impact of each factor on the data value using quantitative methods. A regression analysis reveals the influence, interactions, and relative importance of these determinants. A real-world case study on the “Papers with Code” platform—widely used in machine learning research—demonstrates the methodology in practice. The results indicate that essential value factors, such as Percentage Correct and Task, have the strongest positive effect on data value, which underscores the importance of accuracy and relevance to specific applications. In contrast, factors such as Similar Datasets and Benchmarks reduce the data value, which highlights the need for uniqueness and differentiation in determining the value of a company’s data assets. This study provides practical guidelines for companies on the key factors to focus on when evaluating and managing data value. This study offers practical guidance on prioritizing value-related factors and enables more effective investment and utilization strategies. By addressing current limitations in data valuation and presenting a new approach, this study enhances data-driven decision-making and strengthens its associated competitive advantage. Full article
(This article belongs to the Special Issue Data-Driven Methods in Business Process Management)
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30 pages, 2851 KiB  
Article
Modernizing Small and Medium-Sized Enterprises: A Lean Audit Model for Digital Integration
by María Jesús Ávila-Gutiérrez, Antonio Córdoba-Roldán, Pablo Morato-Huerta and Juan Ramón Lama-Ruiz
Systems 2025, 13(4), 304; https://doi.org/10.3390/systems13040304 - 21 Apr 2025
Viewed by 238
Abstract
This study proposes an audit model to modernize artisanal manufacturing companies and facilitate their transition to Industry 4.0. Based on Lean Manufacturing, Lean Thinking, and Lean Management principles, the model enhances operational efficiency and competitiveness while considering the resource constraints of Small and [...] Read more.
This study proposes an audit model to modernize artisanal manufacturing companies and facilitate their transition to Industry 4.0. Based on Lean Manufacturing, Lean Thinking, and Lean Management principles, the model enhances operational efficiency and competitiveness while considering the resource constraints of Small and Medium-Sized Enterprises (SMEs). It provides a structured approach to identifying key improvement areas and guiding digital transformation. The research follows a four-phase methodology: (1) a company assessment questionnaire to diagnose the current state, (2) a method matrix to analyze improvement strategies, (3) a dimension map to structure key transformation areas, and (4) prioritization of improvement dimensions to define a tailored action plan. A case study in an SME validated its applicability. Findings show that the model helps identify critical improvement factors and implement targeted Lean interventions, enhancing Industry 4.0 readiness. It enables a progressive adoption of digital enablers while optimizing traditional manufacturing processes. The originality of this study lies in its integrated auditing framework, structured around four dimensions and twelve key factors. It introduces a 48-question assessment tool, methods matrices, and prioritization mechanisms. Additionally, it defines four strategic development stages—Readiness, Start-up, In-transition, and Advanced—providing a roadmap for continuous improvement in SMEs. Full article
(This article belongs to the Special Issue Digital Innovation and Business Model Transformation in Small- and Medium-Sized Enterprises)
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30 pages, 7693 KiB  
Article
Analyzing New Operation Strategy of Demand-Responsive Transports Using Discrete-Event Simulation Framework
by Seung-Wan Cho, Yeong-Hyun Lim, Seong-Hyeon Ju and Kyung-Min Seo
Systems 2025, 13(4), 303; https://doi.org/10.3390/systems13040303 - 21 Apr 2025
Viewed by 135
Abstract
Demand-responsive transport (DRT) provides flexible ride-sharing by dynamically adjusting routes based on real-time user demand, making it suitable for complex urban mobility needs. This study proposes a modular simulation framework based on the DEVS (Discrete Event System Specification) formalism and introduces an “express [...] Read more.
Demand-responsive transport (DRT) provides flexible ride-sharing by dynamically adjusting routes based on real-time user demand, making it suitable for complex urban mobility needs. This study proposes a modular simulation framework based on the DEVS (Discrete Event System Specification) formalism and introduces an “express service” strategy that enables direct trips without intermediate stops. The framework supports scenario-based analysis using key performance indicators (KPIs) and allows for flexible testing of operational strategies. Two experiments were conducted: the first validated the simulation model under varying demand and fleet conditions; and the second assessed the impact of the express service. Results showed that express passengers experienced significantly shorter waiting and riding times, while standard passenger service remained stable. The strategy also improved operational efficiency under constrained resources. This study contributes to a configurable simulation platform for evaluating differentiated DRT services and provides practical insights for adaptive service planning, especially in urban settings where tiered mobility solutions are increasingly needed. Full article
(This article belongs to the Special Issue Modelling and Simulation of Transportation Systems)
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19 pages, 601 KiB  
Article
Understanding Teachers’ Adoption of AI Technologies: An Empirical Study from Chinese Middle Schools
by Jin Zhao, Siyi Li and Jianjun Zhang
Systems 2025, 13(4), 302; https://doi.org/10.3390/systems13040302 - 21 Apr 2025
Viewed by 340
Abstract
The advancements in artificial intelligence (AI) technologies and the implementation of government policies are accelerating educational reform in China. In this context, understanding the critical factors influencing middle school teachers’ adoption of AI technologies for classroom instruction is essential for fostering the deep [...] Read more.
The advancements in artificial intelligence (AI) technologies and the implementation of government policies are accelerating educational reform in China. In this context, understanding the critical factors influencing middle school teachers’ adoption of AI technologies for classroom instruction is essential for fostering the deep integration of these technologies into teaching and improving teaching efficiency in middle schools. Grounded in the structural equation model (SEM) approach, this research integrates the Innovation Diffusion Theory, the Technology Acceptance Model (TAM), and the Unified Theory of Acceptance and Use of Technology (UTAUT), and proposes a structural model comprising 10 latent variables. A measurement model is then developed for each latent variable, forming the basis of a survey questionnaire. Through empirical research using the questionnaires of 202 middle school teachers, a validated structural equation model with strong model fitting is established. The findings indicate that the most influential factors positively affecting teachers’ willingness to use AI technologies, in descending order, are Interpersonal Relationships, Innovativeness, Mass Media, Compatibility, Perceived Usefulness, and Perceived Ease of Use. Similarly, factors positively influencing teachers’ actual usage behavior, ranked by impact, include teachers’ willingness, Facilitating Conditions, Career Aspiration, and Perceived Usefulness. Results involving the impact of teachers’ Interpersonal Relationships can update the theoretical understanding of the factors driving the integration of AI into teaching, and be used to put forward specific directions such as social network embedding for actionable practice recommendations. Full article
(This article belongs to the Section Systems Practice in Social Science)
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42 pages, 4070 KiB  
Article
The Coordinated Relationship Between the Tourism Economy System and the Tourism Governance System: Empirical Evidence from China
by Ning Wang and Gangmin Weng
Systems 2025, 13(4), 301; https://doi.org/10.3390/systems13040301 - 19 Apr 2025
Viewed by 172
Abstract
The development of tourism governance (TG) is influenced by the tourism economy (TE), and the development of TE is guaranteed by tourism governance. This study investigates the development levels of the tourism economy and tourism governance, as well as their interactive coordination in [...] Read more.
The development of tourism governance (TG) is influenced by the tourism economy (TE), and the development of TE is guaranteed by tourism governance. This study investigates the development levels of the tourism economy and tourism governance, as well as their interactive coordination in 31 Chinese provinces (including municipalities and autonomous regions) from 2012 to 2021. First, the vertical and horizontal differentiation method was employed to measure tourism economy and tourism governance development levels. Second, the Panel Vector Autoregression (PVAR) model was adopted to examine the Granger causality and the interactive effects between the tourism economy and tourism governance. Third, the coupled coordination model, kernel density estimation, and Markov chain model were combined to explore the degree of coordinated development and the spatio-temporal evolutionary trend of TE-TG. The findings reveal the following: (1) The development level of the tourism economy exhibits a fluctuating upward trend, with its spatial distribution pattern demonstrating a distinct coastal-to-inland decreasing gradient. Meanwhile, tourism governance shows a steady improvement trajectory marked by significant regional disparities. (2) A long-term equilibrium relationship has been established between the tourism economy and tourism governance, with bidirectional Granger causality observed between the two systems. (3) The coupled coordination between the tourism economy and tourism governance has progressively increased. However, the development level of tourism governance still lags behind that of the tourism economy. The eastern and central regions demonstrate significantly higher TE-TG coordination levels compared to the western and northeastern regions. Full article
(This article belongs to the Section Systems Practice in Social Science)
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20 pages, 661 KiB  
Article
Digital Entrepreneurial Orientation, Technology Absorptive Capacity, and Digital Innovation on Business Performance
by Sung Hee Jang and Chang Won Lee
Systems 2025, 13(4), 300; https://doi.org/10.3390/systems13040300 - 19 Apr 2025
Viewed by 224
Abstract
The purpose of this study was to investigate the factors affecting digital entrepreneurial orientation, technology absorptive capacity, and digital innovation in business performance. To achieve the purpose of research, digital entrepreneurial orientation, technology absorptive capacity, digital innovation, and business performance (financial and technological [...] Read more.
The purpose of this study was to investigate the factors affecting digital entrepreneurial orientation, technology absorptive capacity, and digital innovation in business performance. To achieve the purpose of research, digital entrepreneurial orientation, technology absorptive capacity, digital innovation, and business performance (financial and technological performance) were chosen as research variables to explore the relationship effects and medicating effects. Industry type variable was selected to examine moderating effect. Industry type, employees’ numbers, and sales volumes were used as control variables to identify compounding effects of variables. A survey questionnaire was developed, and the proposed model was analyzed to target 122 small and medium venture enterprises (SMEs) in Republic of Korea. Smart PLS 4.0 and SPSS 27.0 were utilized to derive the study results as follows. First, digital entrepreneurial orientation and technology absorptive capacity have a positive influence on digital innovation. Second, digital entrepreneurial orientation has a positive impact on technology absorptive capacity. Finally, digital innovation has a positive effect on financial and technological business performance. The results of this study provide strategic implications for digital innovation and business performance for firms pursuing digital transformation. Therefore, firm managers should prioritize digital entrepreneurial orientation and technology absorptive capacity to improve business performance. Full article
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27 pages, 6390 KiB  
Article
Resilience Analysis of Seaport–Dry-Port Network in Container Transport: Multi-Stage Load Redistribution Dynamics Following Cascade Failure
by Zhigang Lu and Wenhao Qiu
Systems 2025, 13(4), 299; https://doi.org/10.3390/systems13040299 - 19 Apr 2025
Viewed by 152
Abstract
Container shipping networks are vulnerable to cascading failures due to seaport disruptions, underscoring the need for resilient multimodal transport systems. This study proposes a cascading failure model for the seaport–dry-port network in container transport, incorporating a multi-stage load redistribution strategy (CM-SDNCT-MLRS) to enhance [...] Read more.
Container shipping networks are vulnerable to cascading failures due to seaport disruptions, underscoring the need for resilient multimodal transport systems. This study proposes a cascading failure model for the seaport–dry-port network in container transport, incorporating a multi-stage load redistribution strategy (CM-SDNCT-MLRS) to enhance network resilience. Extending the Motter–Lai framework, the model introduces multiple port state transitions and accounts for uncertainties in load redistribution, tailoring it to the cascading failure dynamics of SDNCT. Using empirical data from China’s coastal port system, the proposed MLRS dynamically reallocates loads through dry-port buffering, neighboring seaport sharing, and port skipping. This strategy effectively contains cascading failures, mitigates network efficiency losses, and protects major seaports while reducing mutual disruptions. Resilience analysis demonstrates that the network exhibits scale-free properties, with its resilience being highly sensitive to random port failures and critical port vulnerabilities. The experimental results highlight the pivotal role of dry ports, where operational numbers influence resilience more significantly than capacity. In addition, the study identifies the optimal port-skipping probability that mitigates cascading disruptions. These findings provide valuable insights for port management and logistics planning, contributing to the development of more resilient container transport networks. Full article
(This article belongs to the Topic Digital Technologies in Supply Chain Risk Management)
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27 pages, 1300 KiB  
Article
Organizational Work System as the Predictor of Creative Performance: A New Approach to the Learning Method System of Comprehensive Systems and Expansion of Research Field
by Zhiliang Lyu, Chengao Zhang and Xiu Jin
Systems 2025, 13(4), 298; https://doi.org/10.3390/systems13040298 - 18 Apr 2025
Viewed by 120
Abstract
Previous researchers have questioned and attempted to verify whether the association between organizational work system and individual and organizational performance indicates causality. A work system is a comprehensive concept; it may be of various types, and gaps exist between the type of organizational [...] Read more.
Previous researchers have questioned and attempted to verify whether the association between organizational work system and individual and organizational performance indicates causality. A work system is a comprehensive concept; it may be of various types, and gaps exist between the type of organizational work system and performance. To fill these gaps, we investigated the causal relationship between how a high-performance work system improves creative performance via work involvement through social exchange theory, expectancy theory, and the ability–motivation and opportunity framework. Therefore, we established an amalgamated research framework that uses the moderated mediation model of learning method system of comprehensive systems to facilitate creative performance. To verify the above, this study conducted an empirical study targeting 315 organizational members working in Chinese small and medium-sized enterprises (SMEs). For empirical analysis, we utilized SPSS Macro Process, AMOS, and SmartPLS 4 Program. We found that high-performance work systems significantly improve work involvement and creative performance. Additionally, work involvement acts as a mediator between high-performance work systems and creative performance. However, the moderating effect of the learning method system of comprehensive systems was not significant. Overall, this research was conducted in consideration of the fact that there is a considerable lack of empirical research verifying the relationship between high-performance work systems and creative performance that promotes survival and competitiveness for SMEs. In addition, the learning method system of comprehensive system has not been studied actively and it was utilized with the expectation that it would be a variable that would receive new attention through this study. Finally, this research is expected to contribute to the research fields of SMEs and organizational work systems. Full article
(This article belongs to the Special Issue Systems Analysis of Enterprise Sustainability)
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36 pages, 1370 KiB  
Article
Local Digital Economic Growth, Enterprise Digital Transformation, and Digital Dividends: Evidence from China
by Yunqi Yang and Grace T. R. Lin
Systems 2025, 13(4), 297; https://doi.org/10.3390/systems13040297 - 18 Apr 2025
Viewed by 146
Abstract
Achieving digital transformation in enterprises is vital for advancing the digital economy. Using the World Bank’s China Enterprise Survey data, this study investigates how local digital economic growth impacts enterprise transformation. Findings suggest that higher local digital growth significantly boosts enterprise transformation, thereby [...] Read more.
Achieving digital transformation in enterprises is vital for advancing the digital economy. Using the World Bank’s China Enterprise Survey data, this study investigates how local digital economic growth impacts enterprise transformation. Findings suggest that higher local digital growth significantly boosts enterprise transformation, thereby improving short-term operations and long-term innovation. Remarkably, threshold regression reveals a stronger impact on larger enterprises and those with higher human capital. Additional analyses demonstrate that effective access to digital dividends enhances enterprises’ production, R&D, and management. These results offer guidance for local governments, supporting digital shifts and helping enterprises tailor transformation strategies. Full article
(This article belongs to the Section Systems Practice in Social Science)
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37 pages, 18181 KiB  
Article
Smart Cities in the Global Context: Geographical Analyses of Regional Differentiations
by Kabeer Saleh Tijjani, Yasemin Sarıkaya Levent and Tolga Levent
Systems 2025, 13(4), 296; https://doi.org/10.3390/systems13040296 - 17 Apr 2025
Viewed by 304
Abstract
The increasing urbanisation and technological advancements have driven the global adoption of smart city initiatives, yet regional differences persist due to economic, social, and technological disparities. Despite the numerous studies on smart cities, there remains a research gap in comprehensive global analyses exploring [...] Read more.
The increasing urbanisation and technological advancements have driven the global adoption of smart city initiatives, yet regional differences persist due to economic, social, and technological disparities. Despite the numerous studies on smart cities, there remains a research gap in comprehensive global analyses exploring regional differentiations in smart city development. This study aims to examine how smart cities differentiate, especially through associations between regions and smart city dimensions. This study utilises data from the IMD Smart City Index 2023 and applies a multi-step methodology based on the United Nations’ geographic regions, employing geographical and statistical analyses. The findings reveal distinct regional differentiations, highlighting a clear Global North–South divide and notable subregional differentiations, including the North–South divide in the Americas and the East–West divide in Asia. The correlation analysis demonstrates significant relationships between smart city dimensions, with smart mobility and smart living exhibiting the highest association. The correspondence analysis further identifies four major regional concentration groups, notably the Global North, with equi-distant associations with all dimensions, and Asia, which is closely linked to smart governance. The findings confirm that smart city development is not uniform and is shaped by regional socio-economic and technological conditions and emphasises the need for context-dependent regional policies. Full article
(This article belongs to the Special Issue Smart Urban Planning and Governance: Rethinking Cities to Tackle Natural and Climate Risks)
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22 pages, 879 KiB  
Article
Breaking Down the Barriers to Innovation Quality: The Impact of Digital Transformation
by Mengmeng Meng, Siyao Fan, Jiasu Lei and Yinbo Feng
Systems 2025, 13(4), 295; https://doi.org/10.3390/systems13040295 - 17 Apr 2025
Viewed by 299
Abstract
While the influence of digital technologies on firms’ innovation performance has been examined in the digital transformation literature, the mechanism by which digital transformation affects innovation quality has remained largely unexplored. By analyzing a longitudinal sample of 17,216 China’s A-share listed companies from [...] Read more.
While the influence of digital technologies on firms’ innovation performance has been examined in the digital transformation literature, the mechanism by which digital transformation affects innovation quality has remained largely unexplored. By analyzing a longitudinal sample of 17,216 China’s A-share listed companies from 2009 to 2021 (excluding real estate and financial firms), we employed a fixed-effects regression model to investigate the impact of digital transformation on strategic risk-taking behavior. The findings indicate that digital transformation significantly enhances innovation quality. Market competition enhances the positive effect of digital transformation on innovation quality. Further analysis reveals that digital transformation has a positive impact on dynamic capability, which in turn mediates the relationship between digital transformation and innovation quality. Furthermore, digital transformation breaks down the barriers to innovation quality by reducing financing costs and financing constraints. These findings have implications for firms’ digital strategy in emerging economies. Full article
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42 pages, 2328 KiB  
Article
A Blockchain-Driven Cyber-Systemic Approach to Hybrid Reality
by Massimiliano Pirani, Alessandro Cucchiarelli, Tariq Naeem and Luca Spalazzi
Systems 2025, 13(4), 294; https://doi.org/10.3390/systems13040294 - 17 Apr 2025
Viewed by 316
Abstract
Hybrid Reality (HyR) is the place where human beings and artificial entities interact. HyR modelling relies simultaneously on the cognitive power of humans and artificial entities. In addition, HyR is an evolving paradigm where natural and artificial intelligence can intervene in processes that [...] Read more.
Hybrid Reality (HyR) is the place where human beings and artificial entities interact. HyR modelling relies simultaneously on the cognitive power of humans and artificial entities. In addition, HyR is an evolving paradigm where natural and artificial intelligence can intervene in processes that demand proper control. This work aims to lay the foundation for a systematic approach to understanding and modeling present and future human–machine symbiosis under a systems engineering perspective. It introduces a novel cyber-systemic methodology for managing the engineering of purposeful regulation for HyR phenomena by integrating the Blockchain technology framework and principled methods of cybernetics. This formalized interdisciplinary methodology integrates system dynamics, agent-based computation, artificial intelligence, and Blockchain-powered security and safety layers. The Blockchain framework, seen under a new cyber-systemic perspective, provides new opportunities and tools for the organization and control of HyR. A Cybersystemic Security Kit is here defined as a major component of the methodology, representing a candidate to offer viable breakthroughs in the field with respect to the best practices of Industry 5.0 when a systemically augmented perspective is adopted. Ongoing research and experimentation in the real field of sustainable supply chains is used as a motivating use case to support the proposed position. The industrial target is the primary one in its multi-dimensional and multi-faceted sustainability impacts, but this study will also reveal other potential societal areas of intervention. Full article
(This article belongs to the Special Issue CyberSystemic Transformations for Social Good)
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27 pages, 3166 KiB  
Article
Can Government Incentive and Penalty Mechanisms Effectively Mitigate Tacit Collusion in Platform Algorithmic Operations?
by Yanan Wang and Yaodong Zhou
Systems 2025, 13(4), 293; https://doi.org/10.3390/systems13040293 - 16 Apr 2025
Viewed by 163
Abstract
Algorithmic collusion essentially constitutes a form of monopolistic agreement that utilizes algorithms as tools for signaling collusion, making it particularly challenging for both consumers and antitrust enforcement agencies to detect. Algorithmic collusion can be primarily categorized into two distinct types: explicit collusion and [...] Read more.
Algorithmic collusion essentially constitutes a form of monopolistic agreement that utilizes algorithms as tools for signaling collusion, making it particularly challenging for both consumers and antitrust enforcement agencies to detect. Algorithmic collusion can be primarily categorized into two distinct types: explicit collusion and tacit collusion. This paper specifically investigates the phenomenon of platform-driven tacit algorithmic collusion within the platform economy. Employing an evolutionary game theory approach, we conduct a comprehensive simulation analysis of the economic system involving four key stakeholders: government regulators, platform operators, in-platform merchants, and consumers. This paper primarily investigates the conditions that may reduce the likelihood of platforms engaging in algorithmic tacit collusion, examines how government incentive–penalty mechanisms influence such collusive behaviors, and provides an in-depth analysis of the critical roles played by both in-platform merchants and consumers in detecting and exposing these practices. Full article
(This article belongs to the Section Systems Practice in Social Science)
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28 pages, 3658 KiB  
Article
Extended Application of Double Machine Learning in Corporate Financial Resilience Research: Based on Data Factor Marketization
by Fangzhou Song, Yang Huang and Chengkun Liu
Systems 2025, 13(4), 292; https://doi.org/10.3390/systems13040292 - 16 Apr 2025
Viewed by 316
Abstract
Corporate financial resilience and its integration with institutional reforms play a crucial role in promoting organizational sustainability in the digital economy. Previous research has predominantly focused on internal determinants of corporate financial resilience. However, it has paid limited attention to the role of [...] Read more.
Corporate financial resilience and its integration with institutional reforms play a crucial role in promoting organizational sustainability in the digital economy. Previous research has predominantly focused on internal determinants of corporate financial resilience. However, it has paid limited attention to the role of external institutional factors. This gap is particularly evident in the context of data factor marketization (DFM). We addressed this gap by investigating the impact of DFM on corporate financial resilience, drawing on resource dependence theory (RDT) to highlight the importance of the external policy environment and inter-organizational resource exchange. We employed a double machine learning (DML) framework to assess corporate financial resilience using comprehensive panel data from Chinese listed firms. This approach overcomes the limitations of traditional econometric methods by allowing nonlinear interactions and high-dimensional controls. The results show that DFM significantly enhances corporate financial resilience, with its impact varying across different institutional contexts. Additionally, firm characteristics moderate this relationship. Specifically, ownership structure strengthens or weakens the positive effect of DFM, while industry competition and geographical location have varying effects on resilience outcomes. We offered novel theoretical insights and practical guidance for policymakers seeking to leverage institutional reforms to enhance financial resilience within an increasingly volatile and uncertain business landscape. Full article
(This article belongs to the Special Issue Sustainable Business Models and Digital Transformation)
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28 pages, 584 KiB  
Article
Pathway to Smart Aviation: Identifying and Prioritizing Key Factors for Smart Aviation Development Using the Fuzzy Best–Worst Method
by Fei Gao and Weikai He
Systems 2025, 13(4), 291; https://doi.org/10.3390/systems13040291 - 15 Apr 2025
Viewed by 172
Abstract
Smart aviation has received significant attention from various stakeholders in China as its advancement holds crucial implications for the aviation industry, and there is a growing need for aviation authorities to assess the extent of its development. The evaluation of smart aviation development [...] Read more.
Smart aviation has received significant attention from various stakeholders in China as its advancement holds crucial implications for the aviation industry, and there is a growing need for aviation authorities to assess the extent of its development. The evaluation of smart aviation development processes rely on various factors that reflect the smart aviation development level, and these factors could help pave the way for the successful development of smart aviation. However, few studies have focused on the identification and prioritization of the key factors for smart aviation development, especially considering the uncertain nature of the problem. To this end, this study employs the grounded theory and the fuzzy best–worst method (BWM) to identify and prioritize the factors for smart aviation development. Through the utilization of grounded theory, 37 factors are determined to be critical for smart aviation development. Then, the fuzzy BWM is employed to evaluate and prioritize the identified factors considering their importance. The findings of this study reveal that the 4D track development level, proportion of R&D investment, and data resources sharing degree are the most influential factors for smart aviation development. By integrating grounded theory, fuzzy sets, and BWM, this study identifies and prioritizes the significant factors for smart aviation for the first time. In general, the outcomes of this study hold the potential to guide practitioners in focusing on the pivotal factors that contribute to smart aviation development. Full article
(This article belongs to the Section Systems Practice in Social Science)
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22 pages, 4223 KiB  
Article
Algorithmic Identification of Conflicting Traffic Lights: A Large-Scale Approach with a Network Conflict Matrix
by Sergio Rojas-Blanco, Alberto Cerezo-Narváez, Sol Sáez-Martínez and Manuel Otero-Mateo
Systems 2025, 13(4), 290; https://doi.org/10.3390/systems13040290 - 15 Apr 2025
Viewed by 191
Abstract
Efficient urban traffic management is crucial for mitigating congestion and enhancing road safety. This study introduces a novel algorithm, with code provided, to generate a traffic light conflict matrix, identifying potential signal conflicts solely based on road network topology. Unlike existing graphical approaches [...] Read more.
Efficient urban traffic management is crucial for mitigating congestion and enhancing road safety. This study introduces a novel algorithm, with code provided, to generate a traffic light conflict matrix, identifying potential signal conflicts solely based on road network topology. Unlike existing graphical approaches that are difficult to execute automatically, our method leverages readily available topological data and adjacency matrices, ensuring broad applicability and automation. While our approach deliberately focuses on topology as a stable foundation, it is designed to complement rather than replace dynamic traffic analysis, serving as an essential preprocessing layer for subsequent temporal optimization. Implemented in MATLAB, with specific functionality for Vissim users, the algorithm has been tested on various networks with up to 547 traffic lights, demonstrating high efficiency, even in complex scenarios. This tool enables focused allocation of computational resources for traffic light optimization and is particularly valuable for prioritizing emergency vehicles. Our findings make a significant contribution to traffic management strategies by offering a scalable and efficient tool that bridges critical gaps in current research. As urban areas continue to grow, this algorithm represents a step forward in developing sustainable solutions for modern transportation challenges. Full article
(This article belongs to the Special Issue Modelling and Simulation of Transportation Systems)
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29 pages, 3357 KiB  
Article
A Project-Based Organizational Maturity Assessment Framework for Efficient Environmental Quality Management
by Rashid Al-Marri, Galal Abdalla and Elsadig Mahdi
Systems 2025, 13(4), 289; https://doi.org/10.3390/systems13040289 - 15 Apr 2025
Viewed by 242
Abstract
This research aims to develop and validate an organizational maturity framework (OM framework) to assess an organization’s maturity and improve the operational performance of the EQM. The study adopts a multi-methods approach. Qualitative data are sourced from 18 respondents and analyzed through thematic [...] Read more.
This research aims to develop and validate an organizational maturity framework (OM framework) to assess an organization’s maturity and improve the operational performance of the EQM. The study adopts a multi-methods approach. Qualitative data are sourced from 18 respondents and analyzed through thematic analysis. The analysis reveals that pollution control and energy efficiency are the primary EQM concerns. The maturity assessment occurs through data from one or multiple sources, with the most preferred models being the five-phase models. Finally, maturation has diverse effects on EQM, which mirrors continuous improvement expectations. The quantitative study involved 212 respondents drawn from PBOs across the country. The data were analyzed through SEM, culminating in hypothesis testing. Three of the eight hypotheses were supported, including H4: Legal requirements have a statistically significant impact on PBO maturity (β = −0.150, p = 0.015); H5: Sustainability has a positive statistically significant impact on PBO maturity (β = 0.169, p = 0.045); and H1: the level of maturity determines efficiency in EQM (β = 0.066, p = 0.050). The rest of the variables have an inverse relationship or effects that are not statistically significant. The assessment of weightings for the determinants of PBO maturity culminates in the realization that the variables whose hypothesized relationships were confirmed received moderate priority. These findings explain why the determinants of PBO maturity only explain 8.8% of the variance in maturity, while the entire model explains only 3% of the EQM efficiency. The findings culminate in the validity of the operational instructions for improvement in the task specificity of PBO maturity for EQM performance and an improvement in the conceptualization of EQM efficiency among the PBOs. Full article
(This article belongs to the Special Issue Sustainable Project Management in Business)
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21 pages, 4883 KiB  
Article
The Influence of Conformity and Global Learning on Social Systems of Cooperation: Agent-Based Models of the Spatial Prisoner’s Dilemma Game
by Yunhwan Kim
Systems 2025, 13(4), 288; https://doi.org/10.3390/systems13040288 - 15 Apr 2025
Viewed by 177
Abstract
Individuals can learn about others from sources far from them, and conformity can operate not only on a local scale but also on a global scale. This study aimed to investigate the influence of conformity and global learning on social systems of cooperation [...] Read more.
Individuals can learn about others from sources far from them, and conformity can operate not only on a local scale but also on a global scale. This study aimed to investigate the influence of conformity and global learning on social systems of cooperation using agent-based models of the spatial prisoner’s dilemma game. Three agent-based models incorporating differing types of global conformity were built and analyzed. The results suggested that global learning was generally unfavorable for cooperation. However, in some cases, it enabled resistance to the dominance of defection. Moreover, referring to more diverse sources was less harmful to cooperation than referring to a larger number of similar sources. Evolutionary dynamics were generated according to how competing forces of cooperative and defective agents were balanced. Random drifts toward either the cooperation- or defection-dominant state occurred under some parameter conditions. Whether the drifts were equally or unequally probable toward either state differed according to the parameter conditions. This study highlights the importance of individuals’ psychological biases in the evolution of cooperation. It also shows that differing practices of those biases can generate different dynamics, resulting in the system having different states. Full article
(This article belongs to the Section Systems Practice in Social Science)
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39 pages, 3542 KiB  
Article
Mechanisms to Overcome the Homogenization of Rural Tourism Products and Improve the Competitiveness of Rural Tourist Destinations: A Case Study from China
by Yiqing Su, Youyan Wang and Rui Li
Systems 2025, 13(4), 287; https://doi.org/10.3390/systems13040287 - 15 Apr 2025
Viewed by 287
Abstract
The competitiveness of rural tourism destinations holds significant implications not only for local livelihood sustainability and regional development but also for the preservation and continuity of human civilization. However, developing countries face a critical challenge where rural tourism destination competitiveness is being progressively [...] Read more.
The competitiveness of rural tourism destinations holds significant implications not only for local livelihood sustainability and regional development but also for the preservation and continuity of human civilization. However, developing countries face a critical challenge where rural tourism destination competitiveness is being progressively undermined by the pervasive homogenization of tourism products. The existing literature demonstrates limited engagement with mitigation strategies for tourism product homogenization in examinations of rural destination competitiveness. This study conceptualizes tourism product homogenization as a manifestation of the tragedy of tourism commons, proposing that self-governance can foster rural tourism destination competitive advantages through resolving such collective action dilemmas. Employing a combined IAD-SES framework, the investigation analyzes interview data from Yuanjia Village in Shaanxi Province, China. The analysis delineates how self-governance dynamically enhances and sustains rural tourism destination competitiveness through four institutional mechanisms: provision rules, appropriation rules, monitoring protocols, and sanctioning systems. Furthermore, the findings reveal that the competitiveness driven by self-governance demonstrates the capacity to align individual interests with collective societal benefits. This research contributes to tourism scholarship by identifying novel institutional determinants of tourism destination competitiveness and proposing a policy framework for addressing product homogenization challenges throughout the rural tourism area life cycle. Full article
(This article belongs to the Special Issue Systems Thinking: Insights and Solutions to Complex Societal Challenges)
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26 pages, 2001 KiB  
Article
Dynamic Risk Transmission in the Chinese Hospitality Industry: A Time-Varying Analysis
by Ke Peng, Muhammad Munir, Jifan Ren, Yanzhe Feng and Shoaib Nisar
Systems 2025, 13(4), 286; https://doi.org/10.3390/systems13040286 - 13 Apr 2025
Viewed by 317
Abstract
Comprehending the dynamics of risk spillover across the value chain is indispensable for effective risk management, especially amid increasing economic and geopolitical uncertainty. This study investigates the mechanics of risk transmission within the value chain of the Chinese hospitality industry by employing a [...] Read more.
Comprehending the dynamics of risk spillover across the value chain is indispensable for effective risk management, especially amid increasing economic and geopolitical uncertainty. This study investigates the mechanics of risk transmission within the value chain of the Chinese hospitality industry by employing a Time-Varying Parameter Vector Autoregression (TVP-VAR) model using daily data from January 2015 to December 2023. Our research identifies key sub-sectors, such as hotel resort and luxury cruises, film and entertainment, malls and supermarkets, environmental and facilities services, air freight and logistics, and road transportation, as significant risk transmitters that affect the overall stability of the industry. Conversely, sectors such as restaurants, liquor and wine services, leisure services, and railway transport are designated as risk receivers. These results offer critical insights for stakeholders, emphasizing the necessity of comprehensive risk management strategies to reduce negative spillover effects, particularly in the context of economic shocks like the COVID-19 pandemic and geopolitical events like the Russia–Ukraine conflict. Full article
(This article belongs to the Section Systems Practice in Social Science)
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26 pages, 2119 KiB  
Article
Actor Network Model of the Construction Mechanism of a Technology Standardization Innovation Ecosystem—Haier Case Study
by Yu Yuan and Dengyun Ma
Systems 2025, 13(4), 285; https://doi.org/10.3390/systems13040285 - 12 Apr 2025
Viewed by 314
Abstract
As the competition of standards among enterprises turns to the competition among innovation ecosystems, how to construct the technology standardization innovation ecosystem (TSIE) is of great significance to enhance the competitiveness of enterprises and even industries. Based on the perspective of actor network [...] Read more.
As the competition of standards among enterprises turns to the competition among innovation ecosystems, how to construct the technology standardization innovation ecosystem (TSIE) is of great significance to enhance the competitiveness of enterprises and even industries. Based on the perspective of actor network theory (ANT) through the case study of Haier, this paper constructs an ANT model for the formation of a TSIE and tries to answer the following questions: how is the TSIE formed? how do the actors gather and what roles do they play in the formation process? and what role do technology standards play in the formation process? This research finds that the formation of the TSIE results from interactions among the actors of ANT over different periods. The focal actors play a crucial role; their roles change from the construction of their own actor network to the empowerment of the sub-actor network construction. Other actors evolve from being defined to defining roles themselves. Standards are also crucial throughout this process: initially, they recruit and coordinate the primary actors to form close relationships, and later they facilitate bidirectional regulation, enable standardization, and coordinate the formation and development of sub-ecosystems. This paper explores the evolution of TSIE through the lens of ANT, advancing its application within this context. It enriches the theoretical research on this subject and offers a theoretical foundation for large enterprise platforms to facilitate the transformation of TSIE. Full article
(This article belongs to the Special Issue Systems Approaches in Knowledge Management and Organizational Innovation)
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32 pages, 16909 KiB  
Article
Causation Analysis of Marine Traffic Accidents Using Deep Learning Approaches: A Case Study from China’s Coasts
by Zelin Zhao, Xingyu Liu, Lin Feng, Manel Grifoll and Hongxiang Feng
Systems 2025, 13(4), 284; https://doi.org/10.3390/systems13040284 - 12 Apr 2025
Viewed by 367
Abstract
In response to the increasing frequency of maritime traffic accidents along China’s coast, this study develops an accident-cause analysis framework that integrates an optimized Bidirectional Encoder Representations from Transformers (BERT) with a Bidirectional Long Short-Term Memory network (BiLSTM), combined with the Apriori association [...] Read more.
In response to the increasing frequency of maritime traffic accidents along China’s coast, this study develops an accident-cause analysis framework that integrates an optimized Bidirectional Encoder Representations from Transformers (BERT) with a Bidirectional Long Short-Term Memory network (BiLSTM), combined with the Apriori association rule algorithm. Systematic performance comparisons demonstrate that the BERT + BiLSTM architecture achieves superior unstructured-text-processing capability, attaining 89.8% accuracy in accident-cause classification. The hybrid framework enables comprehensive investigation of complex interactions among human factors, vessel characteristics, environmental conditions, and management practices through multidimensional analysis of accident reports. Our findings identify improper operations, fatigue-related issues, illegal modifications, and inadequate management practices as primary high-risk factors while revealing that multi-factor interaction patterns significantly influence accident severity. Compared with traditional single-factor analysis methods, the proposed framework shows marked improvements in Natural Language Processing (NLP) efficiency, classification precision, and systematic interpretation of cross-factor correlations. This integrated approach provides maritime authorities with scientific evidence to develop targeted accident prevention strategies and optimize safety management systems, thereby enhancing maritime safety governance along China’s coastline. Full article
(This article belongs to the Section Systems Theory and Methodology)
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53 pages, 1060 KiB  
Article
Research on the Impact of the Development of China’s Digital Trade on the International Competitiveness of the Manufacturing Industry
by Huilian Ma and Chengwen Kang
Systems 2025, 13(4), 283; https://doi.org/10.3390/systems13040283 - 11 Apr 2025
Viewed by 504
Abstract
The world is currently experiencing an unprecedented period of disruption. Traditional theories of comparative advantage can no longer serve as the sole drivers for enhancing the international competitiveness of China’s manufacturing industry. In this new era, the future development of China’s manufacturing industry [...] Read more.
The world is currently experiencing an unprecedented period of disruption. Traditional theories of comparative advantage can no longer serve as the sole drivers for enhancing the international competitiveness of China’s manufacturing industry. In this new era, the future development of China’s manufacturing industry has become a pressing issue that demands immediate attention. With the rapid advancement of next-generation digital technologies and information and communication technologies, global digital trade has surged, emerging as a key engine of economic growth for countries worldwide. This trend undoubtedly presents new opportunities and platforms for strengthening the international competitiveness of China’s manufacturing industry. How China’s manufacturing industry can effectively leverage digital trade to secure a competitive advantage amid intensifying global competition has become a critical and urgent area of research. Using panel data from 31 provinces, autonomous regions, and municipalities in China spanning from 2012 to 2022, this study develops a comprehensive evaluation framework for digital trade and manufacturing competitiveness. It empirically investigates the impact and mechanisms through benchmark regression models, mediation effect models, and spatial econometric models. The findings reveal that digital trade has a significant positive impact on the international competitiveness of China’s manufacturing industry. The effect of digital trade on competitiveness is most pronounced in the eastern region and least evident in the western region. Additionally, foreign direct investment and technological research and development capabilities are found to indirectly enhance the international competitiveness of the manufacturing industry. Furthermore, digital trade exhibits spatial spillover effects, wherein improvements in manufacturing competitiveness within one province positively influence neighboring provinces. This study offers valuable theoretical and policy implications for evaluating the impact of digital trade on the international competitiveness of manufacturing and strategies for enhancing it. Full article
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24 pages, 703 KiB  
Article
R&D Subsidies and Radical Innovation: Innovative Mindset and Competition Matter
by Xiaotong Huo, Shuyang Wang, Bowen Zheng and Xiaoyu Wu
Systems 2025, 13(4), 282; https://doi.org/10.3390/systems13040282 - 11 Apr 2025
Viewed by 365
Abstract
With the increasing focus on R&D (research and development) subsidies of various researchers, there is growing interest in how these subsidies affect radical innovation. Based on the limited attention paid to this area in the existing literature, this paper investigates the impact of [...] Read more.
With the increasing focus on R&D (research and development) subsidies of various researchers, there is growing interest in how these subsidies affect radical innovation. Based on the limited attention paid to this area in the existing literature, this paper investigates the impact of R&D subsidies on radical innovation. Using a sample of Chinese listed firms, we investigate how innovation orientation and competitive intensity moderate this relationship. By incorporating concepts from Path Dependence Theory, we propose that R&D subsidies alter firms’ assessment of the value and risk associated with investments in radical innovation, influencing their innovation strategies. Subsidies may increase the attractiveness of incremental innovations, which have lower volatility and faster returns, compared to radical innovations, which inherently involve higher risk and uncertainty. Based on the results of our analysis, we find that R&D subsidies negatively affect radical innovation, but firms with a stronger innovation orientation (which reflects their greater tolerance for risk) are less negatively affected. Conversely, an increase in the intensity of competition exacerbates the negative impact of subsidies because it induces firms to make safer incremental investments. The robustness analysis confirms that the main effects remain significant even when using alternative proxies for innovation. Our study sheds light on the mechanisms affecting the effectiveness of subsidies from the perspective of finance theory and highlights the conditions under which subsidies may unintentionally discourage radical innovation. Full article
(This article belongs to the Special Issue Systems Approaches in Knowledge Management and Organizational Innovation)
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21 pages, 986 KiB  
Review
Integrating Large Language Models into Medication Management in Remote Healthcare: Current Applications, Challenges, and Future Prospects
by Ho Yan Kwan, Jethro Shell, Conor Fahy, Shengxiang Yang and Yongkang Xing
Systems 2025, 13(4), 281; https://doi.org/10.3390/systems13040281 - 10 Apr 2025
Viewed by 433
Abstract
The integration of large language models (LLMs) into remote healthcare has the potential to revolutionize medication management by enhancing communication, improving medication adherence, and supporting clinical decision-making. This study aims to explore the role of LLMs in remote medication management, focusing on their [...] Read more.
The integration of large language models (LLMs) into remote healthcare has the potential to revolutionize medication management by enhancing communication, improving medication adherence, and supporting clinical decision-making. This study aims to explore the role of LLMs in remote medication management, focusing on their impact. This paper comprehensively reviews the existing literature, medical LLM cases, and the commercial applications of LLMs in remote healthcare. It also addresses technical, ethical, and regulatory challenges related to the use of artificial intelligence (AI) in this context. The review methodology includes analyzing studies on LLM applications, comparing their impact, and identifying gaps for future research and development. The review reveals that LLMs have shown significant potential in remote medication management by improving communication between patients and providers, enhancing medication adherence monitoring, and supporting clinical decision-making in medication management. Compared to traditional reminder systems, AI reminder systems have a 14% higher rate in improving adherence rates in pilot studies. However, there are notable challenges, including data privacy concerns, system integration issues, and the ethical dilemmas of AI-driven decisions such as bias and transparency. Overall, this review offers a comprehensive analysis of LLMs in remote medication management, identifying both their transformative potential and the key challenges to be addressed. It provides insights for healthcare providers, policymakers, and researchers on optimizing the use of AI in medication management. Full article
(This article belongs to the Special Issue Advances in the Modeling and Analytics of Health and Healthcare Systems)
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34 pages, 2037 KiB  
Article
Exploring Heuristics and Biases in Cybersecurity: A Factor Analysis of Social Engineering Vulnerabilities
by Valerică Greavu-Şerban, Floredana Constantin and Sabina-Cristiana Necula
Systems 2025, 13(4), 280; https://doi.org/10.3390/systems13040280 - 10 Apr 2025
Viewed by 648
Abstract
Cybersecurity threats increasingly exploit cognitive heuristics, yet their structured role in security decision-making remains underexplored. This study examines how heuristic-driven behaviors influence vulnerability to cyberattacks, particularly in social engineering contexts. Using Exploratory Factor Analysis (EFA), followed by Confirmatory Factor Analysis (CFA), we identified [...] Read more.
Cybersecurity threats increasingly exploit cognitive heuristics, yet their structured role in security decision-making remains underexplored. This study examines how heuristic-driven behaviors influence vulnerability to cyberattacks, particularly in social engineering contexts. Using Exploratory Factor Analysis (EFA), followed by Confirmatory Factor Analysis (CFA), we identified two key cognitive dimensions: risk perception and compliance and security, shaping security decisions. Regression and mediation analyses revealed that risk awareness influences protective behaviors, but a security paradox persists—many users recognize risks yet fail to act accordingly. Clustering techniques further classified individuals into distinct cybersecurity profiles, highlighting variations in susceptibility. This research bridges cognitive psychology and cybersecurity, offering insights for designing more effective awareness programs and interventions. Understanding these cognitive vulnerabilities is essential for improving cybersecurity resilience and risk mitigation strategies. Full article
(This article belongs to the Section Systems Practice in Social Science)
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29 pages, 7161 KiB  
Article
The Dynamic Evolution of Agricultural Trade Network Structures and Its Influencing Factors: Evidence from Global Soybean Trade
by Yue Liu, Lichang Zhang, Pierre Failler and Zirui Wang
Systems 2025, 13(4), 279; https://doi.org/10.3390/systems13040279 - 10 Apr 2025
Viewed by 275
Abstract
Under the rapid advancements in information technology, the complex network characteristics of agricultural product trade relationships among global economies have exhibited increasing prominence. This study takes the soybean trade market as an empirical case, employing a combination of social network analysis to investigate [...] Read more.
Under the rapid advancements in information technology, the complex network characteristics of agricultural product trade relationships among global economies have exhibited increasing prominence. This study takes the soybean trade market as an empirical case, employing a combination of social network analysis to investigate the dynamic evolution of agricultural trade network structures; then, the Temporal Exponential Random Graph Model (TERGM) is adopted to analyse the factors influencing the soybean trade network. Based on comprehensive empirical data encompassing soybean trade data among 126 economies from 2000 to 2022, this research demonstrates several key findings: Firstly, the soybean trade network is characterised by pronounced trade agglomeration effects and “small-world” properties, accompanied by heightened trade substitutability. Secondly, the network’s structural configuration has undergone a distinct transformation, shifting from a traditional single-core–periphery structure to a more complex multi-core–periphery architecture. Thirdly, in response to external shocks impacting network topology, the core structure exhibits greater resilience and stability, whereas the periphery displays heterogeneous responses. Finally, the evolution of soybean trade relations is governed by a dual mechanism involving both endogenous dynamics and exogenous influences. Full article
(This article belongs to the Section Systems Practice in Social Science)
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27 pages, 1843 KiB  
Article
Coupling Coordination Evaluation and Optimization of Water–Energy–Food System in the Yellow River Basin for Sustainable Development
by Pengcheng Zhang, Yaoyao Fu, Boliang Lu, Hongbo Li, Yijie Qu, Haslindar Ibrahim, Jiaxuan Wang, Hao Ding and Shenglin Ma
Systems 2025, 13(4), 278; https://doi.org/10.3390/systems13040278 - 10 Apr 2025
Viewed by 277
Abstract
Understanding the coupling mechanisms and coordinated development dynamics of the water–energy–food (WEF) system is crucial for sustainable river basin development. This study focuses on the Yellow River Basin, conducting a comprehensive analysis of the system’s coupling mechanisms and influencing factors. A structured evaluation [...] Read more.
Understanding the coupling mechanisms and coordinated development dynamics of the water–energy–food (WEF) system is crucial for sustainable river basin development. This study focuses on the Yellow River Basin, conducting a comprehensive analysis of the system’s coupling mechanisms and influencing factors. A structured evaluation framework is established, integrating the entropy weight–TOPSIS method, the coupling coordination degree model, and spatial correlation analysis. Empirical analysis is conducted using data from nine provinces (regions) along the Yellow River from 2003 to 2022 to assess the spatiotemporal evolution of the coupling coordination level. The Tobit regression model is employed to quantify the impact of various factors on the system’s coupling coordination degree. Results indicate that the comprehensive evaluation index of the WEF system in the Yellow River Basin exhibits an overall upward trend, with the system coupling degree remaining at a high level for an extended period, up from 0.231 to 0.375. The interdependence among the three major systems is strong (0.881–0.939), and while the coupling coordination degree has increased over time despite fluctuations, a qualitative leap has not yet been achieved. The evaluation index follows a spatial distribution pattern of midstream > downstream > upstream, characterized by a predominantly high coupling degree. However, the coordination degree frequently remains at a forced coordination level or below, with a general trend of midstream > downstream > upstream. From 2003 to 2008, a positive spatial autocorrelation was observed in the coupling and coordinated development of the WEF system across provinces, indicating a strong spatial agglomeration effect. By 2022, most provinces were clustered in “high-high” and “low-low” areas, reflecting a positive spatial correlation with minimal regional differences. Key factors positively influencing coordination include economic development levels, industrial structure upgrading, urbanization, and transportation networks, while technological innovation negatively affects the system’s coordination. Based on these findings, it is recommended to strengthen balanced economic development, optimize the layout of industrial structures, improve the inter-regional resource circulation mechanism, and promote the deep integration of technological innovation and production practices to address the bottlenecks hindering the coordinated development of the water–energy–food system. Policy recommendations are proposed to provide strategic references for the sustainable socioeconomic development of the Yellow River Basin, thereby achieving the high-quality coordinated growth of the water–energy–food system in the region. Full article
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19 pages, 1296 KiB  
Article
The Governance of PPP Project Resilience: A Hybrid DMATEL-ISM Approach
by Zhankun Liu, Nannan Wang and Qiushi Du
Systems 2025, 13(4), 277; https://doi.org/10.3390/systems13040277 - 9 Apr 2025
Viewed by 325
Abstract
Considering the inherent characteristics of long-term agreements, public–private partnership (PPP) projects are confronted with diverse uncertainties and external challenges. However, existing research has devoted limited attention to the resilience of PPP projects. This study seeks to identify governance factors influencing PPP project resilience [...] Read more.
Considering the inherent characteristics of long-term agreements, public–private partnership (PPP) projects are confronted with diverse uncertainties and external challenges. However, existing research has devoted limited attention to the resilience of PPP projects. This study seeks to identify governance factors influencing PPP project resilience and analyze the interconnections among these factors in fostering such resilience. A governance framework for PPP project resilience is proposed, comprising thirteen governance factors across four dimensions: institutional, organizational, contractual, and managerial factors. The interpretive structural modeling (ISM) and decision-making trial and evaluation laboratory (DEMATEL) techniques are adopted to explore the hierarchical relationships and interactive mechanisms among these governance factors in a systematic view. The findings reveal that strategic alliances, risk allocation and transfer, flexible contracting, and long-term relationship management represent core governance factors critical to enhancing project resilience. Institutional factors are identified as the most foundational determinants within the governance system, while contractual and managerial factors act as mediating elements facilitating the translation of institutional foundations into operational resilience. This study deepened the understanding of the practitioners with regard to the key governance factors and their inter-relationships, which can help systematically enhance the resilience of PPP projects. Full article
(This article belongs to the Section Systems Practice in Social Science)
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30 pages, 341 KiB  
Article
Global Power Dynamics in the Contemporary Space System
by Francisco Del Canto Viterale
Systems 2025, 13(4), 276; https://doi.org/10.3390/systems13040276 - 9 Apr 2025
Viewed by 513
Abstract
In the 21st century, the space system has experienced a substantial shift from a simple unipolar to a new and more complex structure. This transition is the result of the emergence of new space powers and global power dynamics. The central hypothesis of [...] Read more.
In the 21st century, the space system has experienced a substantial shift from a simple unipolar to a new and more complex structure. This transition is the result of the emergence of new space powers and global power dynamics. The central hypothesis of this research work is that the space system is undergoing an intersystem transition from a unipolar, U.S.-dominant, post-Cold War space system to a new and more complex structure that includes new space powers and a redistribution and rebalancing of power dynamics. The unipolar structure that prevailed in the post-Cold War era has been replaced by a new space system, in which emerging space powers exhibit global ambitions and a willingness to compete with and challenge the United States’ dominance. These shifts in the number of space actors, power dynamics, and the structure of the space system necessitate novel scientific approaches. This research postulates the utilization of systems science as a means to enhance our comprehension of the intersystem transition and the rebalancing of power in the space system in recent decades. The result of this study is a comprehensive analysis of the major space actors in the 21st-century space system, the analysis of the redistribution of power among them, and the new power structure that has emerged. Full article
(This article belongs to the Section Complex Systems and Cybernetics)
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