Systems

50 pages, 1421 KB

Open AccessArticle

Strategy, Structure and Systems: Sun Tzu’s Thinking and the Holonic Network of the Toyota Dealer System (TDS)—A Romanian Case Study

by Aurel Burciu, Carla Alexandra Barbosa Pereira, Nicolae-Florin Prunău, Rozalia Kicsi, Denisa-Alexandra Chifan, Camelia Băeșu and Alexandra Maria Danileț

Systems 2025, 13(8), 723; https://doi.org/10.3390/systems13080723 - 21 Aug 2025

Viewed by 743

Abstract

Globally, 93 million cars are currently produced, with Toyota accounting for about 10% of the global market. However, its position is more modest in the Electric Vehicle (EV) industry. The automotive industry in Romania began at Dacia Pitesti in the 1970s, based on [...] Read more.

Globally, 93 million cars are currently produced, with Toyota accounting for about 10% of the global market. However, its position is more modest in the Electric Vehicle (EV) industry. The automotive industry in Romania began at Dacia Pitesti in the 1970s, based on a license obtained from Renault. This research explores how a profound strategic vision, inspired by Sun Tzu’s philosophy, can influence a company’s organizational structure over time. In Toyota’s case, this vision resulted in a dealer network that functions not only as a logistics system but also as a holonic system. The study is based on 194 questionnaires administered by the authors, along with 40 interviews with managers and specialists from Toyota Dealers Romania. Its novelty lies in analyzing the Toyota Dealer System (TDS) through the concept of holonic networks. The study concludes that the success of keiretsu groups is explained by combining Sun Tzu’s thinking with the principles of holonic networks. The findings are valuable both conceptually, for future research, and practically, as they offer clear directions for developing strategies and organizing a company’s market relationships. Full article

(This article belongs to the Section Supply Chain Management)

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32 pages, 2414 KB

Open AccessArticle

Can EU Countries Balance Digital Business Transformation with the Sustainable Development Goals? An Integrated Multivariate Assessment

by Emilia Herman and Maria-Ana Georgescu

Systems 2025, 13(8), 722; https://doi.org/10.3390/systems13080722 - 21 Aug 2025

Viewed by 588

Abstract

The aim of the study was to evaluate the digital business transformation across EU countries and its relationship with key Sustainable Development Goals (SDGs): SDG 8 (Decent Work and Economic Growth), SDG 9 (Industry, Innovation, and Infrastructure), and SDG 13 (Climate Action). The [...] Read more.

The aim of the study was to evaluate the digital business transformation across EU countries and its relationship with key Sustainable Development Goals (SDGs): SDG 8 (Decent Work and Economic Growth), SDG 9 (Industry, Innovation, and Infrastructure), and SDG 13 (Climate Action). The Digital Business Transformation Index, developed from eleven digital technology indicators related to e-business and e-commerce, is constructed using Principal Component Analysis to provide a comprehensive framework for assessing digitalization at the enterprise level. The results reveal substantial disparities among member states, with northern and western countries leading, while southern and eastern countries are lagging behind. Regression analyses show a strong positive relationship between digital business transformation and SDG 9 and a negative association with SDG 13. Cluster analysis identifies six groups of countries with varying levels of digital and sustainability performance and emphasizes the need for tailored policy responses. Evidence confirms a digital–green trade-off in many EU countries; however, strategic policy integration can mitigate this challenge. The findings underline the importance of targeted investments in R&D, digital infrastructure, and ICT training, particularly in underperforming regions. Tailored measures are essential to ensure that digital business transformation aligns with inclusive and sustainable development across the EU. Full article

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

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32 pages, 1886 KB

Open AccessArticle

A PDCA-Based Decision-Making Framework for Sustainable Marketing Communication Strategies: A Case Study of a Slovak Telecommunications Company

by Miroslava Řepová, Lucie Lendelová and Viliam Lendel

Systems 2025, 13(8), 721; https://doi.org/10.3390/systems13080721 - 21 Aug 2025

Viewed by 550

Abstract

With the rapid development of technology, an increasingly competitive environment, and evolving consumer behaviour, the use of modern marketing tools has become a key challenge for companies of various types (manufacturing, providing services, sports organizations, universities, etc.). Although sustainable digital communication methods are [...] Read more.

With the rapid development of technology, an increasingly competitive environment, and evolving consumer behaviour, the use of modern marketing tools has become a key challenge for companies of various types (manufacturing, providing services, sports organizations, universities, etc.). Although sustainable digital communication methods are gaining prominence, existing research often focuses merely on describing communication trends without providing decision-making frameworks for strategy optimisation. This paper addresses this gap by mapping the current state of marketing communication strategies among large telecommunication companies in Slovakia and assessing their impact on customer behaviour and market position. Data were analysed through a combination of qualitative and quantitative research methods, including document analysis, annual reports, surveys, and personal observations. One enterprise was selected for detailed data analysis. The results confirm a significant relationship between the use of communication channels and the company’s market position, brand popularity, and the strong influence of employee recommendations. Unlike previous studies, which predominantly describe marketing communication trends and tools, this research integrates the evaluation of communication strategy effectiveness with a systematic management decision-making model based on the PDCA (Plan-Do-Check-Act) continuous improvement cycle. This approach enables continuous optimisation of sustainable communication strategies and provides actionable managerial guidance for improving resource allocation, market position, and organisational adaptability in dynamic market environments. Full article

(This article belongs to the Special Issue Decision-Making in Sustainable Business Models: Prediction and Modeling)

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23 pages, 3243 KB

Open AccessArticle

Research on Dynamic Measurement and Early Warning of Systemic Financial Risk in China Based on TVP-FAVAR and Deep Learning Model

by Hufang Yang, Luyi Liu, Jieyang Cui, Wenbin Wu and Yuyang Gao

Systems 2025, 13(8), 720; https://doi.org/10.3390/systems13080720 - 21 Aug 2025

Viewed by 841

Abstract

With the accelerated development of economic globalization, it is of great significance to strengthen the ability to measure, evaluate, and warn of systemic financial risks for preventing and defusing financial risks. Thus, this research established the Time-Varying Parameter Factor-Augmented Vector Autoregression model (TVP-FAVAR), [...] Read more.

With the accelerated development of economic globalization, it is of great significance to strengthen the ability to measure, evaluate, and warn of systemic financial risks for preventing and defusing financial risks. Thus, this research established the Time-Varying Parameter Factor-Augmented Vector Autoregression model (TVP-FAVAR), combined with the Markov Regime Switching Autoregressive Model, to dynamically measure China’s systemic financial risk. The network public opinion index is constructed and introduced into the financial risk early warning system to capture the dynamic impact of market sentiment on financial risks. After testing the nonlinear causal relationship between financial indicators based on the transfer entropy method, the Transformer deep learning model is applied to build a financial risk early warning system, and the performance is compared to traditional methods. The experimental results showed that (1) the trend of the systemic financial risk index based on the dynamic measurement of the TVP-FAVAR model fitted the actual situation well and that (2) the Transformer model public opinion index could fully and effectively mine the nonlinear relationship between data. Compared to traditional machine learning methods, the Transformer model has significant advantages in stronger prediction accuracy and generalization ability. This study provided a new technical path for financial risk early warning and has important reference value for improving the financial regulatory system. Full article

(This article belongs to the Special Issue Ensemble Learning-Driven Models for Managerial System Modelling and Applications)

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17 pages, 1841 KB

Open AccessArticle

A System Dynamics Framework for Port Resilience Enhancement Along Maritime Silk Road: Insights from ESG Governance

by Xiaoming Zhu, Shenping Hu, Zhuang Li and Jianjun Wu

Systems 2025, 13(8), 719; https://doi.org/10.3390/systems13080719 - 20 Aug 2025

Viewed by 341

Abstract

Port resilience performance (PRP) is a critical factor in advancing the sustainable development of the 21st Century Maritime Silk Road (MSR). The Environmental, Social, and Governance (ESG) framework, widely recognized as a cornerstone of global sustainability efforts, offers a robust foundation for enhancing [...] Read more.

Port resilience performance (PRP) is a critical factor in advancing the sustainable development of the 21st Century Maritime Silk Road (MSR). The Environmental, Social, and Governance (ESG) framework, widely recognized as a cornerstone of global sustainability efforts, offers a robust foundation for enhancing PRP. This study employs a system dynamics (SD) approach to explore the impact of ESG on PRP along the MSR. By developing an ESG evaluation index system and a resilience assessment framework, the research examines the mechanisms and evolutionary patterns through which ESG influences port resilience. Simulations are conducted for four strategic ports: Chattogram Port, Singapore Port, Gwadar Port, and Djibouti Port. The findings reveal that ESG initiatives significantly enhance PRP, with Singapore Port exhibiting the most stable and rapid resilience improvement. In contrast, the other ports demonstrate varying levels of adaptation and enhancement. Among the intervention strategies, prioritizing social dimension (S) improvements proves most effective for achieving rapid short-term resilience gains. This study offers both theoretical insights and practical strategies for strengthening port resilience and fostering sustainable development along the MSR. Full article

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

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19 pages, 554 KB

Open AccessArticle

Leaders’ Calling and Employees’ Innovative Behavior: The Mediating Role of Work Meaning and the Moderating Effect of Supervisor’s Organizational Embodiment

by Yuyang Cao, Peng Wen and Liqiong Luo

Systems 2025, 13(8), 718; https://doi.org/10.3390/systems13080718 - 20 Aug 2025

Viewed by 423

Abstract

The objective of this research is to investigate whether and how leaders’ sense of calling influences employees’ innovative behavior, and to explore the conditions that may define the boundaries of this effect. Based on the theory of interpersonal sensemaking, this research conducted an [...] Read more.

The objective of this research is to investigate whether and how leaders’ sense of calling influences employees’ innovative behavior, and to explore the conditions that may define the boundaries of this effect. Based on the theory of interpersonal sensemaking, this research conducted an empirical analysis using data from 186 pairs of supervisor-subordinate matching questionnaires and developed a moderated mediation model. We hypothesized and found that: first, leaders’ calling directly enhanced employees’ innovative behavior; second, the relationship between the leaders’ calling and employees’ innovative behavior was mediated by the employee’s sense of work meaning; third, the supervisor’s organizational embodiment positively regulated the relationship between the leaders’ calling and the employee’s sense of work meaning. Specifically, when the degree of the supervisor’s organizational embodiment is higher, the relationship between the leaders’ calling and the employee’s work meaning will be stronger. At the same time, the supervisor’s organizational embodiment positively regulates the mediating effect. Specifically, when the degree of the supervisor’s organizational embodiment is higher, the mediating effect of the employee’s work meaning is stronger. Full article

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

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19 pages, 1221 KB

Open AccessArticle

Comparative Analysis of Standard Operating Procedures Across Safety-Critical Domains: Lessons for Human Performance and Safety Engineering

by Jomana A. Bashatah and Lance Sherry

Systems 2025, 13(8), 717; https://doi.org/10.3390/systems13080717 - 20 Aug 2025

Viewed by 480

Abstract

Standard Operating Procedures (SOPs) serve a critical role in complex systems operations, guiding operator response during normal and emergency scenarios. This study compares 29 SOPs (517 steps) across three domains with varying operator selection rigor: airline operations, Habitable Airlock (HAL) operations, and semi-autonomous [...] Read more.

Standard Operating Procedures (SOPs) serve a critical role in complex systems operations, guiding operator response during normal and emergency scenarios. This study compares 29 SOPs (517 steps) across three domains with varying operator selection rigor: airline operations, Habitable Airlock (HAL) operations, and semi-autonomous vehicles. Using the extended Procedure Representation Language (e-PRL) framework, each step was decomposed into perceptual, cognitive, and motor components, enabling quantitative analysis of step types, memory demands, and training requirements. Monte Carlo simulations compared Time on Procedure against the Allowable Operational Time Window to predict failure rates. The analysis revealed three universal vulnerabilities: verification steps missing following waiting requirements (70% in airline operations, 58% in HAL operations, and 25% in autonomous vehicle procedures), ambiguous perceptual cues (15–48% of steps), and excessive memory demands (highest in HAL procedures at 71% average recall score). Procedure failure probabilities varied significantly (5.72% to 63.47% across domains), with autonomous vehicle procedures showing the greatest variability despite minimal operator selection. Counterintuitively, Habitable Airlock procedures requiring the most selective operators had the highest memory demands, suggesting that rigorous operator selection may compensate for procedure design deficiencies. These findings establish that procedure design approaches vary by domain based on assumptions about operator capabilities rather than universal human factors principles. Full article

(This article belongs to the Section Systems Engineering)

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25 pages, 7822 KB

Open AccessArticle

An Emergency Scheduling Model for Oil Containment Boom in Dynamically Changing Marine Oil Spills: Integrating Economic and Ecological Considerations

by Yuanyuan Xu, Linlin Zhang, Pengjun Zheng, Guiyun Liu and Dan Zhao

Systems 2025, 13(8), 716; https://doi.org/10.3390/systems13080716 - 20 Aug 2025

Viewed by 475

Abstract

Marine oil spills pose substantial risks to human society and ecosystems, resulting in significant economic and ecological consequences. Timely containment of oil films is a complex and urgent task, in which the efficient scheduling of oil containment booms plays a crucial role in [...] Read more.

Marine oil spills pose substantial risks to human society and ecosystems, resulting in significant economic and ecological consequences. Timely containment of oil films is a complex and urgent task, in which the efficient scheduling of oil containment booms plays a crucial role in reducing economic and ecological losses caused by oil spills. However, due to dynamically changing marine oil spills, the length of boom required and the losses caused by oil spills are inherently uncertain. This study aims to optimize the containment of oil films, exploring the interrelationships among oil films, spill losses, and scheduling decisions for booms. By incorporating economic and ecological losses into decisions, this study proposes a scheduling model for oil containment booms to minimize spill-related losses while reducing scheduling time. Additionally, an improved Multi-Objective Grey Wolf Optimization algorithm is used to solve the problem. A hypothetical case study is then conducted in the Zhoushan sea area of the East China Sea. The proposed scheduling scheme achieves a containment time of 8.9781 h and reduces total spill losses to CNY 313.68 million. Compared with a scheme that does not consider spill losses, the proposed method achieves a nearly 24% reduction in losses while maintaining comparable efficiency. Full article

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25 pages, 1872 KB

Open AccessArticle

Food Safety Risk Prediction and Regulatory Policy Enlightenment Based on Machine Learning

by Daqing Wu, Hangqi Cai and Tianhao Li

Systems 2025, 13(8), 715; https://doi.org/10.3390/systems13080715 - 19 Aug 2025

Viewed by 528

Abstract

This paper focuses on the challenges in food safety governance in megacities, taking Shanghai as the research object. Aiming at the pain points in food sampling inspections, it proposes a risk prediction and regulatory optimization scheme combining text mining and machine learning. First, [...] Read more.

This paper focuses on the challenges in food safety governance in megacities, taking Shanghai as the research object. Aiming at the pain points in food sampling inspections, it proposes a risk prediction and regulatory optimization scheme combining text mining and machine learning. First, the paper uses the LDA method to conduct in-depth mining on over 78,000 pieces of food sampling data across 34 categories in Shanghai, so as to identify core risk themes. Second, it applies SMOTE oversampling to the sampling data with an extremely low unqualified rate (0.5%). Finally, a machine learning prediction model for food safety risks is constructed, and predictions are made based on this model. The research findings are as follows: ① Food risks in Shanghai show significant characteristics in terms of time, category, and pollution causes. ② Supply chain links, regulatory intensity, and consumption scenarios are among the core influencing factors. ③ The traditional “full coverage” model is inefficient, and resources need to be tilted toward high-risk categories. ④ Public attention (e.g., the “You Order, We Inspect” initiative) can drive regulatory responses to improve the qualified rate. Based on these findings, this paper suggests that relevant authorities should ① classify three levels of risks for categories, increase inspection frequency for high-risk products in summer, adjust sampling intensity for different business entities, and establish a dynamic hierarchical regulatory mechanism; ② tackle source governance, reduce environmental pollution, upgrade process supervision, and strengthen whole-chain risk prevention and control; and ③ promote public participation, strengthen the enterprise responsibility system, and deepen the social co-governance pattern. This study effectively addresses the risk early warning problems in food safety supervision of megacities, providing a scientific basis and practical path for optimizing the allocation of regulatory resources and improving governance efficiency. Full article

(This article belongs to the Topic Digital Technologies in Supply Chain Risk Management)

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19 pages, 2251 KB

Open AccessArticle

An Optimization Model of Coupled Medical Material Dispatching Inside and Outside Epidemic Areas Considering Comprehensive Satisfaction

by Jun Yang, Xiaofei Ye, Shuyi Pei, Xingchen Yan, Tao Wang, Jun Chen, Pengjun Zheng and Rongjun Cheng

Systems 2025, 13(8), 714; https://doi.org/10.3390/systems13080714 - 19 Aug 2025

Viewed by 407

Abstract

This study addresses the critical challenge of emergency material distribution during atypical public health crises, using the COVID-19 pandemic in Hubei Province as a representative case. An innovative internal–external coupled dispatching framework is proposed by integrating regional medical resource allocation with cross-regional supply [...] Read more.

This study addresses the critical challenge of emergency material distribution during atypical public health crises, using the COVID-19 pandemic in Hubei Province as a representative case. An innovative internal–external coupled dispatching framework is proposed by integrating regional medical resource allocation with cross-regional supply chain networks. Our methodology employs the SEIR epidemiological model to forecast infection rates and corresponding material demands, then incorporates bidirectional dispatching efficiency as a key determinant of demand urgency. Through systematic risk stratification of affected areas, we develop a dual-objective optimization model that simultaneously minimizes logistical time and cost, solved by the NSGA-II algorithm. The results demonstrate that the internal–external coupled emergency material dispatching approach significantly enhances demand satisfaction in affected regions and improves overall dispatching effectiveness. This study offers practical recommendations and valuable references for emergency material dispatching during public health crises. Full article

(This article belongs to the Special Issue Modeling and Simulation Innovations for Advanced Logistics Systems Management)

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22 pages, 1326 KB

Open AccessArticle

Exploring Influential Factors of Industry–University Collaboration Courses in Logistics Management: An Interval-Valued Pythagorean Fuzzy WASPAS Approach

by Shupeng Huang, Kun Li, Chuyi Teng, Manyi Tan and Hong Cheng

Systems 2025, 13(8), 713; https://doi.org/10.3390/systems13080713 - 19 Aug 2025

Viewed by 329

Abstract

The development of E-commerce and digitalization drives the rapid change in logistics management practices and poses challenges to traditional talent training modes in logistics field. Nowadays, companies expect university graduates equipped with more practical logistics skills to connect tighter with the industry. This [...] Read more.

The development of E-commerce and digitalization drives the rapid change in logistics management practices and poses challenges to traditional talent training modes in logistics field. Nowadays, companies expect university graduates equipped with more practical logistics skills to connect tighter with the industry. This motivates universities to establish more practically relevant curriculums to enhance students’ career competitiveness. Under such background, industry–university collaboration courses are increasingly adopted in higher education institutes in logistics discipline. Due to the difference between this type of course and the traditionally taught courses, the learning outcome of it can be difficult to guarantee. Therefore, it is necessary to identify the influential factors of the learning outcomes of industry–university collaboration courses and establish the actionable strategies to enhance course quality. However, the current literature in logistics management education has little focus on this topic, resulting in gaps on clarifying the influential factors of learning outcomes of industry–university collaboration courses in this discipline. Applying a mixed method, this study conducted a case study for an industry–university collaboration course of a logistics discipline in a Chinese university. The interval-valued Pythagorean fuzzy (IVPF) numbers and the Weighted Aggregated Sum Product Assessment (WASPAS) methods were used. The results showed that there are 15 factors which can influence the outcomes of industry–university collaboration courses in logistics discipline. Among them, the most important factor is the working environment, followed by the students’ own ability. Also, the results indicated that students’ optimistic attitudes towards the course, whether students take the course seriously, and course evaluations can be influential factors for good learning outcomes. The sensitivity analysis was then conducted, showing that the results were robust. This study can contribute to the existing literature by providing a theoretical framework to understand and assess the quality of industry–university collaboration courses in logistics and relevant subjects, as well as offering new analytical tools for management educational studies. Moreover, this study can provide practical implications for educators to develop and maintain good industry–university collaboration courses and trainings. Specifically, a practical life-cycle view was suggested to put pertinent efforts in all periods before/during/after the course to achieve high course outcomes. Full article

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

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26 pages, 1553 KB

Open AccessArticle

A Cooperative Game Theoretical Approach for Designing Integrated Photovoltaic and Energy Storage Systems Shared Among Localized Users

by Zhouxuan Chen, Tianyu Zhang and Weiwei Cui

Systems 2025, 13(8), 712; https://doi.org/10.3390/systems13080712 - 18 Aug 2025

Viewed by 543

Abstract

To address the increasing need for clean energy and efficient resource utilization, this paper aims to provide a cooperative framework and a fair profit allocation mechanism for integrated photovoltaic (PV) and energy storage systems that are shared among different types of users within [...] Read more.

To address the increasing need for clean energy and efficient resource utilization, this paper aims to provide a cooperative framework and a fair profit allocation mechanism for integrated photovoltaic (PV) and energy storage systems that are shared among different types of users within a regional alliance, including industrial, commercial, and residential users. A cooperative game model is proposed and formulated by a two-level optimization problem: the upper level determines the optimal PV and storage capacities to maximize the alliance’s net profit, while the lower level allocates profits using an improved Nash bargaining approach based on Shapley value. The model simultaneously incorporates different real-world factors such as time-of-use electricity pricing, system life cycle cost, and load diversity. The results demonstrate that coordination between energy storage systems and PV systems can avoid 18% of solar curtailment losses. Compared to independent deployment by individual users, the cooperative sharing model increases the net present value by 8.41%, highlighting improvements in cost-effectiveness, renewable resource utilization, and operational flexibility. Users with higher demand or better load–generation matching gain greater economic returns, which can provide decision-making guidance for the government in formulating differentiated subsidy policies. Full article

(This article belongs to the Section Systems Engineering)

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32 pages, 2039 KB

Open AccessArticle

A Systematic Study on Embodied Carbon Emissions in the Materialization Phase of Residential Buildings: Indicator Assessment Based on Life Cycle Analysis and STIRPAT Modeling

by Miaoyi Wang, Yuchen Lu, Chenlu Yang and Mingyu Yang

Systems 2025, 13(8), 711; https://doi.org/10.3390/systems13080711 - 18 Aug 2025

Viewed by 474

Abstract

Against the backdrop of intensifying global climate change and advancing the goal of the “dual-carbon” strategy, the built environment is being viewed as a complex socio-technical system in which technological, economic, demographic and institutional subsystems are coupled and evolving at different scales. As [...] Read more.

Against the backdrop of intensifying global climate change and advancing the goal of the “dual-carbon” strategy, the built environment is being viewed as a complex socio-technical system in which technological, economic, demographic and institutional subsystems are coupled and evolving at different scales. As a core node in this system, residential buildings not only carry infrastructural functions, but are also deeply embedded in energy flows, material cycles and behavioural structures, which have a significant impact on carbon emissions. Given the high volume of residential buildings in China and the significant differences between urban and rural construction, there is an urgent need to systematically identify and analyse the implicit carbon emissions during the materialisation phase. In this paper, from the perspective of systems engineering, we selected 30 urban and rural residential buildings in provinces and cities from 2005 to 2020 as the research objects, adopted the life cycle assessment (LCA) method to account for the implied carbon emissions in the materialisation stage, and systematically identified the driving factors of carbon emissions based on the Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) model. From this study, we made the following conclusions: (1) the total carbon emissions of residential buildings in urban and rural areas in China continue to rise during the materialisation stage, showing a spatial pattern of “high in the south-east and low in the north-west”, with a significant trend of structural transformation in urban and rural areas and with steel–concrete structures dominating in towns and cities, and bricks and steel being used in rural areas. (2) Resident population and disposable income are generally positive driving factors, while the influence of industrial structure and energy intensity is heterogeneous between urban and rural areas. For overall residential buildings, every 1% increase in resident population and income will lead to a 1.055% and 0.73% increase in carbon emissions, respectively. The study shows that life-cycle-oriented carbon accounting and the identification of multidimensional driving mechanisms are of great policy value in developing urban–rural differentiated emission reduction paths and enhancing the effectiveness of carbon management in the building sector. Full article

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

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27 pages, 7563 KB

Open AccessArticle

Evaluation of the Dynamic Behavior and Vibrations of the Operator-Vehicle Assembly in Electric Agricultural Tractor Operations: A Simulation Approach for Sustainable Transport Systems

by Teofil-Alin Oncescu, Ilona Madalina Costea, Ștefan Constantin Burciu and Cristian Alexandru Rentea

Systems 2025, 13(8), 710; https://doi.org/10.3390/systems13080710 - 18 Aug 2025

Viewed by 466

Abstract

This study presents an advanced simulation-based methodology for evaluating the dynamic vibrational behavior of the operator–vehicle assembly in autonomous electric agricultural tractors. Using the TE-0 electric tractor as the experimental platform, the research is structured into three integrated stages. In the first stage, [...] Read more.

This study presents an advanced simulation-based methodology for evaluating the dynamic vibrational behavior of the operator–vehicle assembly in autonomous electric agricultural tractors. Using the TE-0 electric tractor as the experimental platform, the research is structured into three integrated stages. In the first stage, a seated anthropometric virtual model of the human operator is developed based on experimental data and biomechanical validation. The second stage involves a detailed modal analysis of the TE-0 electric tractor using Altair Sim Solid, with the objective of determining the natural frequencies and vibration modes in the [0–80] Hz range, in compliance with ISO 2631-1. This analysis captures both the structural-induced frequencies—associated with the chassis, wheelbase, and metallic frame—and the operational-induced frequencies, influenced by the velocity and terrain profile. Subsequently, the modal analysis of the “Grammer Cabin Seat” is conducted to assess its dynamic response and identify critical vibration modes, highlighting how the seat behaves under vibrational stimuli from the tractor and terrain. The third stage extends the analysis to the virtual operator model seated on the tractor seat, investigating the biomechanical response of the human body and the operator–seat–vehicle interaction during simulated motion. Simulations were carried out using SolidWorks 2023 and Altair Sim Solid over a frequency range of [0–80] Hz, corresponding to operation on unprocessed soil covered with grass, at a constant forward speed of 7 km/h. The results reveal critical resonance modes and vibration transmission paths that may impact operator health, comfort, and system performance. The research contributes to the development of safer, more ergonomic, and sustainable autonomous agricultural transport systems. By simulating real-world operation scenarios and integrating a rigorously validated experimental protocol—including vibration data acquisition, biomechanical modeling, and multi-stage modal analysis—this study demonstrates the importance of advanced modeling in optimizing system-level performance, minimizing harmful vibrations, and supporting the transition toward resilient and eco-efficient electric tractor platforms in smart agricultural mobility. Full article

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

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35 pages, 1909 KB

Open AccessArticle

Forging Resilient Urban Ecosystems: The Role of Energy Structure Transformation Under China’s New Energy Demonstration City Pilot Policy

by Mo Li, Ming Yang, Nan Xia, Sixiang Cai, Yuan Tian and Chengming Li

Systems 2025, 13(8), 709; https://doi.org/10.3390/systems13080709 - 18 Aug 2025

Viewed by 377

Abstract

Against the background of global climate change and increasing ecological vulnerability, enhancing ecosystem resilience has become a core task for coping with environmental shocks and achieving sustainable development. The urban energy structure plays a critical role in influencing the green development of the [...] Read more.

Against the background of global climate change and increasing ecological vulnerability, enhancing ecosystem resilience has become a core task for coping with environmental shocks and achieving sustainable development. The urban energy structure plays a critical role in influencing the green development of the economy and the enhancement of environmental resilience. Existing studies have revealed the role of energy structure transformation in the identification of macroeconomic performance and environmental outcomes, but have neglected its impact on ecosystem resilience. This paper exploits the implementation of the New Energy Demonstration City pilot policy as a quasi-natural experiment. Using panel data of Chinese prefecture-level cities from 2010 to 2022, it constructs a multidimensional evaluation system of urban ecosystem resilience and employs a difference-in-differences (DID) model to empirically examine the impact of energy structure transformation on urban ecosystem resilience. It is found that energy structure transition significantly enhances urban ecosystem resilience, and this conclusion is verified through a series of robustness tests. Mechanism analysis shows that energy structure transformation comprehensively enhances urban ecosystem resilience through strengthening institutional regulation, optimizing resource allocation, promoting energy substitution, and enhancing public awareness. Heterogeneity analysis indicates that the strengthening effect of energy structure transition on urban ecosystem resilience is inclusive, and that this positive effect is greater in cities characterized by lower resource endowment and weaker governance capacity. This paper reveals the intrinsic mechanism of urban energy transition for ecological resilience enhancement, and provides an energy transition path for building more resilient urban ecosystems. Full article

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16 pages, 978 KB

Open AccessArticle

Optimizing Agricultural Supply Chain Subsidy Strategies Incorporating Farm Size and Budgetary Constraints

by Xirou Huang and Wenbin Cao

Systems 2025, 13(8), 708; https://doi.org/10.3390/systems13080708 - 18 Aug 2025

Viewed by 332

Abstract

This study models a three-level supply chain (farmer–retailer–government) incorporating farmer risk aversion. Under land capacity and fiscal budget constraints, it analyzes two subsidy strategies: area-based subsidies to farmers (SF) and volume-based subsidies to retailers (SR). Key findings include that when farmer land capacity [...] Read more.

This study models a three-level supply chain (farmer–retailer–government) incorporating farmer risk aversion. Under land capacity and fiscal budget constraints, it analyzes two subsidy strategies: area-based subsidies to farmers (SF) and volume-based subsidies to retailers (SR). Key findings include that when farmer land capacity exceeds a critical threshold and the fiscal budget is constrained, SF yields superior performance to SR. Conversely, with sufficient budgets, SR outperforms SF under high land capacity. Under moderate land capacity and unlimited budgets, both strategies exhibit equivalent effects. When land capacity falls below a critical threshold, government subsidies become unnecessary. The SF strategy demonstrates greater resilience against output uncertainty compared to SR. Under constrained budgets, SF is preferable; SR becomes more advantageous with abundant budgets. Critically, increasing risk aversion significantly reduces social welfare under both SF and SR strategies. This indicates neither subsidy mechanism effectively mitigates the adverse effects of farmer risk aversion. Full article

(This article belongs to the Section Supply Chain Management)

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27 pages, 711 KB

Open AccessArticle

The Alignment Between Digital Servitization Strategies and Digital Servitization Capabilities in Chinese Manufacturing Enterprises: A Multi-Case Study

by Le Zhang, Juhong Chen and Hailin Dong

Systems 2025, 13(8), 707; https://doi.org/10.3390/systems13080707 - 18 Aug 2025

Viewed by 524

Abstract

Grounded in the dynamic capability theory, this study selects three typical manufacturing enterprises as the research subjects. Through longitudinal and cross-case analyses, it delves into the dynamic alignment between the digital servitization capabilities and strategies of manufacturing enterprises, as well as the mechanism [...] Read more.

Grounded in the dynamic capability theory, this study selects three typical manufacturing enterprises as the research subjects. Through longitudinal and cross-case analyses, it delves into the dynamic alignment between the digital servitization capabilities and strategies of manufacturing enterprises, as well as the mechanism through which this alignment influences firm performance. The findings indicate that—within the framework of capabilities, such as the strategy alignment model—among six potential alignment scenarios, only three configurations exert a significantly positive impact on firm performance: the alignment of service data integration capabilities/service demand exploration capabilities with product-centric digital servitization strategies and the alignment of digital service orchestration capabilities with ecosystem-centric strategies. The former bolsters efficiency advantages through value-added product servitization, while the latter unlocks ecological dividends by capitalizing on network effects. By uncovering the stage-specific patterns of capability–strategy alignment, this study enriches the dynamic capability theory with a micro-level explanation in the context of digital servitization. It also offers a staged transformation roadmap for manufacturing enterprises to mitigate the risk of misalignment between strategic choices and their existing capabilities. Full article

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24 pages, 10345 KB

Open AccessArticle

Dynamic Evolution and Driving Mechanism of a Multi-Agent Green Technology Cooperation Innovation Network: Empirical Evidence Based on Exponential Random Graph Model

by Jing Ma, Lihua Wu and Jingxuan Hu

Systems 2025, 13(8), 706; https://doi.org/10.3390/systems13080706 - 18 Aug 2025

Viewed by 490

Abstract

As a crucial vehicle for green technological innovation, cooperative networks significantly promote resource integration and knowledge sharing. Yet, their dynamic evolution and micro-mechanism remain underexplored. Drawing on data from the joint applications of green invention patents between 2006 and 2021, this study constructed [...] Read more.

As a crucial vehicle for green technological innovation, cooperative networks significantly promote resource integration and knowledge sharing. Yet, their dynamic evolution and micro-mechanism remain underexplored. Drawing on data from the joint applications of green invention patents between 2006 and 2021, this study constructed a multi-agent GTCIN involving multiple stakeholders, such as enterprises, universities, and research institutions, and analyzed the topological structure and evolutionary characteristics of this network; an exponential random graph model (ERGM) was introduced to elucidate its endogenous and exogenous driving mechanisms. The results indicate that while innovation connections increased significantly, the connection density decreased. The network evolved from a “loose homogeneity” to “core aggregation” and then to “outward diffusion”. State-owned enterprises in the power industry and well-known universities are located at the core of the network. Preferential attachment and transitive closure as endogenous mechanisms exert strong and continuous positive effects by reinforcing local clustering and cumulative growth. The effects of exogenous forces exhibit stage-specific characteristics. State ownership and regional location become significant positive drivers only in the mid-to-late stages. The impact of green innovation capability is nonlinear, initially promoting but later exhibiting a significant inhibitory effect. In contrast, green knowledge diversity exerts an opposite pattern, having a negative effect in the early stage due to integration difficulties that turns positive as technical standards mature. Geographical, technological, social, and institutional proximity all have a positive promoting effect on network evolution, with technological proximity being the most influential. However, organizational proximity exerts a significant inhibitory effect in the later stages of GTCIN evolution. This study reveals the shifting influence of endogenous and exogenous mechanisms across different evolutionary phases, providing theoretical and empirical insights into the formation and development of green innovation networks. Full article

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28 pages, 2198 KB

Open AccessArticle

A Dual-Level Model of AI Readiness in the Public Sector: Merging Organizational and Individual Factors Using TOE and UTAUT

by Rok Hržica, Katja Debelak and Primož Pevcin

Systems 2025, 13(8), 705; https://doi.org/10.3390/systems13080705 - 17 Aug 2025

Viewed by 1285

Abstract

Artificial intelligence (AI) is increasingly transforming the public sector, although the willingness of organizations to adopt such technologies varies widely. Existing models, such as the technology–organization–environment (TOE) model, highlight systemic drivers and barriers but overlook the individual-level factors that are also critical to [...] Read more.

Artificial intelligence (AI) is increasingly transforming the public sector, although the willingness of organizations to adopt such technologies varies widely. Existing models, such as the technology–organization–environment (TOE) model, highlight systemic drivers and barriers but overlook the individual-level factors that are also critical to successful adoption. To address this gap, we propose a decision model that combines the TOE model with the unified theory of acceptance and use of technology (UTAUT) and combines the dimensions of technology, organization, environment, and individual readiness. The model was developed using the Analytic Hierarchy Process (AHP) and supports group decision-making by combining the pairwise comparison matrices of multiple experts into a consolidated priority structure. Specifically, many expert judgments were used to create a group matrix for the four main categories and four additional group matrices for the criteria within each category. This structured approach allows for a systematic assessment of whether a public sector organization is ready for AI adoption. The results show the importance of both systemic factors (such as data, technology, innovation, and readiness for change) and individual factors (such as social influence and voluntariness of use). The final model provides a comprehensive and practical decision-making tool for public sector organizations to assess readiness, identify gaps, and guide the strategic adoption of AI. Full article

(This article belongs to the Special Issue Data-Driven Decision Making for Complex Systems)

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32 pages, 3363 KB

Open AccessArticle

Pre- and Post-Disaster Allocation Strategies of Relief Items in the Presence of Resilience

by Fanshun Zhang, Yucan Liu, Hao Yun, Cejun Cao and Xiaoqian Liu

Systems 2025, 13(8), 704; https://doi.org/10.3390/systems13080704 - 17 Aug 2025

Viewed by 439

Abstract

Pre-disaster and post-disaster allocation strategies are widely investigated as the single optimization problem in humanitarian supply chain management, while integrated decisions including the above two problems are seldom discussed in the existing literature. Here, this paper proposes a mixed-integer programming model to determine [...] Read more.

Pre-disaster and post-disaster allocation strategies are widely investigated as the single optimization problem in humanitarian supply chain management, while integrated decisions including the above two problems are seldom discussed in the existing literature. Here, this paper proposes a mixed-integer programming model to determine these decisions, including the location of central warehouses and emergency storage points and the quantities of relief items pre-deployed and distributed. Specially, two preferences regarding costs and cost-resilience are considered, and a comparison of two models concerning the above preferences is performed. The results are as follows: (i) When the impact of disasters is at a relatively low or moderate level, the cost-oriented model can reduce the government’s financial burden and increase the coverage of relief items. However, when the severity of the disaster is high, the cost resilience-oriented model can respond to the needs of victims within the shortest time, although these needs cannot be completely met. (ii) Increasing the initial inventory level of emergency storage points and enhancing the victims’ tolerance time through social support can effectively reduce the total costs, while increasing the transportation speed can effectively reduce the response delay time. (iii) Adjusting the unit penalty cost can make the total penalty costs and transportation costs decline within a certain range, but such an adjustment has no influence on the response delay time. This paper not only proposes an integrated framework for pre- and post-disaster allocation decisions but also highlights the importance of incorporating resilience into relief item allocation in disaster contexts. Full article

(This article belongs to the Special Issue Scheduling and Optimization in Production and Transportation Systems)

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18 pages, 1669 KB

Open AccessArticle

Kill Chain Search and Evaluation of Weapon System of Systems Based on GAT-DFS

by Yongquan You, Xin Zhang, Huafeng He, Qi Zhang and Xiang Liu

Systems 2025, 13(8), 703; https://doi.org/10.3390/systems13080703 - 16 Aug 2025

Viewed by 484

Abstract

To address the insufficient utilization of network model features and low search efficiency in kill chain analysis for Weapon System of Systems (WSoS), a complex network model of WSoS based on OODA loop was constructed, which converts the indicator system into attribute features [...] Read more.

To address the insufficient utilization of network model features and low search efficiency in kill chain analysis for Weapon System of Systems (WSoS), a complex network model of WSoS based on OODA loop was constructed, which converts the indicator system into attribute features embedded in network nodes, and analyzes the kill chain mode through the metapath. Subsequently, a Depth First Search (DFS) algorithm combined with Graph Attention Network (GAT) is proposed for kill chain search evaluation. The algorithm utilizes GAT to extract topological information and node attribute features from graph data to obtain node-embedding vectors, and optimizes the DFS algorithm process by computing the cosine similarity of node-embedding vectors. Simulation results demonstrated that the proposed algorithm achieves high search efficiency and accuracy, providing robust support for combat decision-making. Full article

(This article belongs to the Section Systems Engineering)

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26 pages, 442 KB

Open AccessArticle

Unlocking AI’s Radical Innovation Potential: The Contingent Roles of Digital Foundation and Government Subsidy

by Zongjun Wang, Xian Zhang, Xiying Song and Jinrong Huang

Systems 2025, 13(8), 702; https://doi.org/10.3390/systems13080702 - 15 Aug 2025

Viewed by 504

Abstract

Over the past decade, artificial intelligence (AI) has been increasingly used in firm innovation. While AI has contributed to innovation improvement, direct evidence of its effectiveness in radical innovation is limited. This study fills this gap by empirically investigating the impact of AI [...] Read more.

Over the past decade, artificial intelligence (AI) has been increasingly used in firm innovation. While AI has contributed to innovation improvement, direct evidence of its effectiveness in radical innovation is limited. This study fills this gap by empirically investigating the impact of AI on radical innovation and how this relationship is shaped by digital foundation and government subsidy from the perspectives of technological synergy and the external institutional environment. Using panel data from Chinese A-share listed firms from 2007 to 2023, this study empirically tests hypotheses through regression analyses. The findings reveal that AI adoption significantly promotes radical innovation, and this relationship is moderated by the characteristics of a firm’s digital foundation (i.e., degree and rate) as well as government subsidy. Specifically, a high degree of digital foundation hinders AI-driven radical innovation, while a fast rate enhances it. In addition, government subsidy strengthens the positive impact of AI adoption on radical innovation. A heterogeneity analysis further shows that both the timing (early vs. late) and pace (fast vs. slow) of AI adoption exert nuanced impacts: firms that adopt AI later and at a slower pace tend to achieve greater gains in radical innovation. This study advances research on radical innovation in the era of intelligence and provides managerial implications regarding the interplay of AI with internal digital foundation and external government subsidy. Full article

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

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27 pages, 1308 KB

Open AccessArticle

A Systems Perspective on Customer Segmentation as a Strategic Tool for Sustainable Development Within Slovakia’s Postal Market

by Radovan Madlenak, Pawel Drozdziel, Malgorzata Zysinska and Lucia Madlenakova

Systems 2025, 13(8), 701; https://doi.org/10.3390/systems13080701 - 15 Aug 2025

Viewed by 506

Abstract

Customer segmentation is a foundation of Customer Relationship Management (CRM) and is widely regarded as a key to business development success. As the principles of sustainable development become increasingly central to business strategy, it is necessary that social, environmental, and economic considerations be [...] Read more.

Customer segmentation is a foundation of Customer Relationship Management (CRM) and is widely regarded as a key to business development success. As the principles of sustainable development become increasingly central to business strategy, it is necessary that social, environmental, and economic considerations be incorporated into customer segmentation—even in regulated markets such as the postal market. The article develops and applies a three-dimensional (3D) segmentation model of business customers in the Slovak postal market, utilizing cluster analysis within STATISTICA analytical software for operationalization of the segmentation criteria. The 3D model reacts to the three pillars of sustainable development and is verified under real conditions at Slovak Post, plc. By adopting a systems perspective, the research places customer segmentation as an integral component of the entire socio-technical system, emphasizing the interrelatedness of organizational, social, and environmental considerations. The study illustrates how a systems-based approach to segmentation enables postal operators to uncover key customer segments, optimize resource allocation, and support competitiveness and sustainability goals. The practical applicability of the model is illustrated by its potential for application in other regulated service industries, providing a solid framework for sustainable customer management and strategic decision-making in complex environments. The research underscores the critical role of systems thinking in addressing the complex challenges of sustainable development in regulated industries. Full article

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28 pages, 1878 KB

Open AccessArticle

Introducing the Manufacturing Digital Passport (MDP): A New Concept for Realising Digital Thread Data Sharing in Aerospace and Complex Manufacturing

by Mohammed M. Mabkhot, Roy S. Kalawsky and Amer Liaqat

Systems 2025, 13(8), 700; https://doi.org/10.3390/systems13080700 - 15 Aug 2025

Viewed by 759

Abstract

In the current data-driven era, effective data sharing is set to unlock billions in value for aerospace and complex manufacturing and their supply chains by enhancing product quality, boosting manufacturing and operational efficiency, and generating new value streams. However, current practices are hindered [...] Read more.

In the current data-driven era, effective data sharing is set to unlock billions in value for aerospace and complex manufacturing and their supply chains by enhancing product quality, boosting manufacturing and operational efficiency, and generating new value streams. However, current practices are hindered by fragmented data ecosystems, isolated silos, and reliance on paper-based documentation. Although the Digital Thread (DTh) initiative holds promise, its implementation remains impractical due to interoperability challenges, security and intellectual property risks, and the inherent difficulty of capturing and managing the overwhelming volume of data in such complex products as a holistic thread. This paper introduces the Manufacturing Digital Passport (MDP), a novel industry-driven concept that employs a product-centric, system-independent digital carrier to facilitate targeted, structured sharing of technical product data across the supply chain. The conceptual contribution of this work is the analytical formalisation of the MDP as a value-oriented carrier that shifts DTh thinking from costly, system-wide interoperability toward an incremental, ROI-driven record of lifecycle data. Rooted in real-world challenges and built on foundational principles of modularity, value creation, and model-based structures, the MDP, by design, enhances traceability, security, and trust through a bottom-up, incremental, use case-driven approach. The paper outlines its benefits through core design principles, definition, practical features, and integration strategies with legacy systems, laying the groundwork for a structured adoption roadmap in high-value manufacturing ecosystems. Full article

(This article belongs to the Special Issue Management and Simulation of Digitalized Smart Manufacturing Systems)

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20 pages, 1045 KB

Open AccessArticle

Linking Life Satisfaction to Settlement Intention: The Moderating Role of Urban Regeneration Budget Execution in South Korea

by Min-Woo Lee and Kuk-Kyoung Moon

Systems 2025, 13(8), 699; https://doi.org/10.3390/systems13080699 - 15 Aug 2025

Viewed by 627

Abstract

This study investigates urban life satisfaction and residents’ settlement intention as emergent outcomes of interconnected urban systems and examines the moderating role of urban regeneration budget execution as a systemic policy input. Drawing on the bottom-up spillover perspective and policy feedback theory, this [...] Read more.

This study investigates urban life satisfaction and residents’ settlement intention as emergent outcomes of interconnected urban systems and examines the moderating role of urban regeneration budget execution as a systemic policy input. Drawing on the bottom-up spillover perspective and policy feedback theory, this study posits that satisfaction with core aspects of urban living—such as housing, transportation, and public safety—reflects the functioning of multiple interrelated urban subsystems, which accumulate into a global sense of well-being that influences settlement intention. Furthermore, when urban regeneration budgets are visibly and fully executed, they operate as institutional feedback mechanisms, leading residents to attribute their life satisfaction to effective system performance and reinforcing their desire to stay. Using survey data from Incheon Metropolitan City and Gyeonggi Province in South Korea, the study employs stereotype logistic regression to test the proposed model. The findings reveal that urban life satisfaction significantly predicts stronger settlement intention, and this effect is amplified in municipalities with higher levels of budget execution. These results contribute to theoretical understanding by linking subjective well-being with institutional performance and offer practical guidance for South Korean local governments seeking to strengthen community resilience through transparent and outcome-driven urban policy delivery. Full article

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

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23 pages, 848 KB

Open AccessArticle

Research on the Dynamic Relationship Between the Growth of Innovation Activity and Entrepreneurial Activity in China

by Song Lin and Haiyao Liu

Systems 2025, 13(8), 698; https://doi.org/10.3390/systems13080698 - 14 Aug 2025

Viewed by 330

Abstract

This study aims to empirically investigate the contemporaneous, bidirectional causal relationship between innovation and entrepreneurial activities in China by constructing a dynamic simultaneous equation system. Using panel data from 31 provincial administrative regions from 2000 to 2022, our empirical results demonstrate a robust [...] Read more.

This study aims to empirically investigate the contemporaneous, bidirectional causal relationship between innovation and entrepreneurial activities in China by constructing a dynamic simultaneous equation system. Using panel data from 31 provincial administrative regions from 2000 to 2022, our empirical results demonstrate a robust two-way causal relationship: vigorous innovation activities significantly stimulate the emergence and subsequent growth of entrepreneurial ventures, while entrepreneurial dynamism similarly promotes regional innovation. These findings remain stable and consistent after rigorous robustness checks. Further, employing a Panel Vector Autoregression (PVAR) approach in extended analyses, we find clear evidence of a stable positive feedback loop between innovation and entrepreneurship, characterized by progressive and cumulative effects. Additionally, regional heterogeneity analysis indicates that macroeconomic disparities significantly influence the bidirectional relationship between innovation and entrepreneurship. Specifically, differences in regional resource endowments and economic conditions largely account for variations in innovation–entrepreneurship dynamics across regions. Consequently, local governments should tailor innovation and entrepreneurship policies to regional contexts to maximize economic outcomes effectively under China’s current development paradigm. Full article

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

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23 pages, 1506 KB

Open AccessArticle

Dynamic Risk Assessment Framework for Tanker Cargo Operations: Integrating Game-Theoretic Weighting and Grey Cloud Modelling with Port-Specific Empirical Validation

by Lihe Feng, Binyue Xu, Chaojun Ding, Hongxiang Feng and Tianshou Liu

Systems 2025, 13(8), 697; https://doi.org/10.3390/systems13080697 - 14 Aug 2025

Viewed by 410

Abstract

The complex interdependencies among numerous safety risk factors influencing oil tanker loading/unloading operations constitute a focal point in academic research. To enhance safety management in oil port operations, this study conducts a risk analysis of oil tanker berthing and cargo transfer safety. Initially, [...] Read more.

The complex interdependencies among numerous safety risk factors influencing oil tanker loading/unloading operations constitute a focal point in academic research. To enhance safety management in oil port operations, this study conducts a risk analysis of oil tanker berthing and cargo transfer safety. Initially, safety risk factors are identified based on the Wu-li Shi-li Ren-li (WSR) systems methodology. Subsequently, a hybrid weighting approach integrating the Fuzzy Analytic Hierarchy Process (FAHP), G2 method, and modified CRITIC technique is employed to calculate indicator weights. These weights are then synthesised into a combined weight (GVW) using cooperative game theory and variable weight theory. Further, by integrating grey theory with the cloud model (GCM), a risk assessment is performed using Tianjin Port as a case study. Results indicate that the higher-risk indicators for Tianjin Port include vessel traffic density, safety of berthing/unberthing operations, safety of cargo transfer operations, safety of pipeline transfer operations, psychological resilience, proficiency of pilots and captains, and emergency management capability. The overall comprehensive risk evaluation value for Tianjin Port is 0.403, corresponding to a “Moderate Risk” level. Comparative experiments demonstrate that the results generated by this model align with those obtained through Fuzzy Comprehensive Evaluation Methods. However, the proposed GVW-GCM framework provides a more objective and accurate reflection of safety risks during tanker operations. Based on the computational outcomes, targeted recommendations for risk mitigation are presented. The integrated weighting model—incorporating game theory and variable weight concepts—coupled with the grey cloud methodology, establishes an interpretable and reusable analytical framework for the safety assessment of oil port operations under diverse port conditions. This approach provides critical decision support for constructing comprehensive management systems governing oil tanker loading/unloading operations. Full article

(This article belongs to the Special Issue Modeling and Simulation Innovations for Advanced Logistics Systems Management)

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27 pages, 1955 KB

Open AccessArticle

How Industry–University–Research Integration Promotes Green Technology Innovation in Chinese Enterprises: The Dual Mediating Pathways and Nonlinear Effects

by Chuang Li, Xin Zhang and Liping Wang

Systems 2025, 13(8), 696; https://doi.org/10.3390/systems13080696 - 14 Aug 2025

Viewed by 571

Abstract

This study examines 3256 Chinese A-share-listed companies from 2011 to 2022 to investigate the facilitative role and impact mechanism of industry–university–research (IUR) integration on corporate green technology innovation (GTI). The findings indicate that (1) the collaboration among IUR substantially enhances enterprises’ GTI, and [...] Read more.

This study examines 3256 Chinese A-share-listed companies from 2011 to 2022 to investigate the facilitative role and impact mechanism of industry–university–research (IUR) integration on corporate green technology innovation (GTI). The findings indicate that (1) the collaboration among IUR substantially enhances enterprises’ GTI, and this conclusion remains robust following various tests; (2) the integration of IUR can enhance GTI by mitigating managerial myopia and augmenting media attention; (3) integrating IUR into state-owned enterprises (SOEs) and large enterprises (LEs) has a stronger role in promoting GTI, according to a heterogeneity test; (4) further research shows that the impact of the depth and breadth of IUR cooperation on GTI presents an inverted U-shaped relationship from the promotion effect to the inhibition effect. Full article

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

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14 pages, 550 KB

Open AccessArticle

Systemic Governance of Rural Revitalization: Social Capital Transfer Through State-Owned Enterprise Interventions in China

by Xinhui Wu, Minsheng Li and Yaofu Huang

Systems 2025, 13(8), 695; https://doi.org/10.3390/systems13080695 - 14 Aug 2025

Viewed by 660

Abstract

This study investigates how state-owned enterprises (SOEs) contribute to rural revitalization in China through systemic interventions that enable the transfer of social capital. Addressing the gap between external resource inputs and internal development needs, the study adopts a systems thinking framework to conceptualize [...] Read more.

This study investigates how state-owned enterprises (SOEs) contribute to rural revitalization in China through systemic interventions that enable the transfer of social capital. Addressing the gap between external resource inputs and internal development needs, the study adopts a systems thinking framework to conceptualize social capital as comprising structural, relational, and cognitive components. Drawing on multi-case evidence from assistance projects led by China Southern Power Grid, this study selects 11 assistance projects from a broader pool of 199 cases, to demonstrate how SOEs act as institutional nodes to reshape rural governance systems. They rebuild local organizational networks (structural capital), establish long-term trust through “strong commitment–weak contract” mechanisms (relational capital), and localize technical knowledge to align with rural contexts (cognitive capital). These interlinked processes form an integrated system that enhances rural governance capacity and promotes sustainable development. The findings highlight that SOEs are not merely resource providers but systemic catalysts that support cross-scalar collaboration and social infrastructure building. The study contributes a novel perspective by integrating social capital theory with a systemic governance lens and offer a actionable insights into the institutional design of assistance models for the future interventions by SOEs and similar entities in underdeveloped areas. Full article

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

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26 pages, 819 KB

Open AccessArticle

Critical Success Factors in Agile-Based Digital Transformation Projects

by Meiying Chen, Xinyu Sun and Meixi Liu

Systems 2025, 13(8), 694; https://doi.org/10.3390/systems13080694 - 13 Aug 2025

Viewed by 920

Abstract

Digital transformation (DT) requires organizations to navigate complex technological and organizational changes, often under conditions of uncertainty. While agile methodologies are widely adopted to address the iterative and cross-functional nature of DT, limited attention has been paid to identifying critical success factors (CSFs) [...] Read more.

Digital transformation (DT) requires organizations to navigate complex technological and organizational changes, often under conditions of uncertainty. While agile methodologies are widely adopted to address the iterative and cross-functional nature of DT, limited attention has been paid to identifying critical success factors (CSFs) from a socio-technical systems (STS) perspective. This study addresses that gap by integrating and prioritizing CSFs as interdependent elements within a layered socio-technical framework. Drawing on a systematic review of 17 empirical and conceptual studies, we adapt Chow and Cao’s agile success model and validate a set of 14 CSFs across five domains—organizational, people, process, technical, and project—through a Delphi-informed Analytic Hierarchy Process (AHP). The findings reveal that organizational and people-related enablers, particularly management commitment, team capability, and organizational environment, carry the greatest weight in agile-based DT contexts. These results inform a three-layered framework—comprising organizational readiness, agile delivery, and project artefacts—which reflects how social, technical, and procedural factors interact systemically. The study contributes both theoretically, by operationalizing STS theory in the agile DT domain, and practically, by providing a prioritized CSF model to guide strategic planning and resource allocation in transformation initiatives. Full article

(This article belongs to the Special Issue Advancing Project Management Through Digital Transformation)

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