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Systems, Volume 13, Issue 2 (February 2025) – 55 articles

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43 pages, 812 KiB  
Article
A Networked Game Theoretic Model for Evaluating Resilience in Megaprojects: Integrating Stakeholder Interactions and Lifecycle Adaptability
by Hongsi Zhang, Shukai Jiang, Xingwu Lin, Xiang Yu and Wenjiang Zheng
Systems 2025, 13(2), 122; https://doi.org/10.3390/systems13020122 - 14 Feb 2025
Abstract
Megaprojects are complex systems comprising interdependent subsystems and diverse stakeholders, each contributing to the project’s resilience and long-term outcomes. Traditional methods for assigning stakeholder influence often assume that stakeholders operate independently when evaluating subsystem resilience. However, these approaches overlook the intricate dynamics—such as [...] Read more.
Megaprojects are complex systems comprising interdependent subsystems and diverse stakeholders, each contributing to the project’s resilience and long-term outcomes. Traditional methods for assigning stakeholder influence often assume that stakeholders operate independently when evaluating subsystem resilience. However, these approaches overlook the intricate dynamics—such as competition and collaboration—that frequently characterize stakeholder interactions in megaprojects. This study addresses this gap by introducing a novel framework based on game theory and network analysis to assess megaproject resilience. The model incorporates both stakeholder interactions and subsystem interdependencies, using a networked game approach to dynamically allocate stakeholder weights. These weights reflect cooperative and conflicting relationships among stakeholders. The framework optimizes a stakeholder’s utility function by balancing marginal benefits, costs, and interaction effects, ensuring rational and adaptive weight distribution. The resulting solution represents a unique Nash equilibrium, identified as the optimal configuration for stakeholder influence. To validate the framework, the study applies it to the Jakarta–Bandung High-Speed Railway (JBHSR) megaproject, demonstrating its capacity to integrate theoretical rigor with practical application. Through mathematical proofs and simulations, the research explores how model parameters influence two critical solution properties: order consistency and stability. Comparative analysis with established methods, such as the Analytic Hierarchy Process (AHP) and simple averaging, highlights the proposed model’s superior ability to capture stakeholder dynamics and adapt to the evolving nature of megaprojects throughout their lifecycle. The findings emphasize the model’s utility in delivering more nuanced resilience evaluations by accounting for stakeholder roles, relationships, and contributions. Specifically, this framework advances theory by merging network analysis with game theory to capture dynamic stakeholder influences, while offering practitioners a real-time mechanism to manage and optimize stakeholder interactions for improved resilience across the entire megaproject lifecycle. Its adaptability to full lifecycle assessments makes it a robust and scalable tool for managing resilience in large-scale infrastructure projects, offering valuable insights for both practitioners and researchers. Full article
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29 pages, 2118 KiB  
Article
Research on Value Co-Creation Evolution Mechanism of Cross-Border Cooperation in Intelligent Connected Vehicle Industry
by Jinhuan Tang, Yiming Chen, Dan Zhao and Shoufeng Ji
Systems 2025, 13(2), 121; https://doi.org/10.3390/systems13020121 - 13 Feb 2025
Abstract
With the continuous development of information and communication technology, “software-defined vehicle” has become the trend of the times. The intelligent connected vehicle (ICV) is becoming a new direction for the development of the automotive industry. Nevertheless, the absence of cooperative innovation in the [...] Read more.
With the continuous development of information and communication technology, “software-defined vehicle” has become the trend of the times. The intelligent connected vehicle (ICV) is becoming a new direction for the development of the automotive industry. Nevertheless, the absence of cooperative innovation in the ICV sector, the dispersal of industrial chain resources, and the absence of enduring and consistent cooperation pose significant obstacles to value co-creation. Therefore, this paper constructs a value co-creation evolutionary game model of the innovation ecosystem of the ICV industry with the automotive enterprise, an intelligent automotive solution provider and the government as players, and applies prospect theory to optimize the tripartite evolutionary game. The payment matrix is established, the expected revenue is analyzed for each player’s strategies, and the replication dynamic equation and evolutionary stability strategy are analyzed. Finally, the theoretical research is validated through numerical simulation. The aim is to promote value co-creation by analyzing the co-evolution mechanism of various stakeholder strategies in the ICV innovation ecosystem. The results show the following: (1) The best evolutionary stability strategy is the positive cross-border cooperation between the automotive enterprise and the intelligent automotive solution provider, while the government gradually does not provide subsidies. (2) The government’s subsidy support should be controlled within an appropriate range. If the subsidy is too great, the marginal effect of incentives will gradually weaken. (3) The players’ willingness to integrate across borders can be enhanced by a higher level of trust and resource complementarity between the automotive enterprise and intelligent automotive solution provider. Also, liquidated damages and opportunity loss can effectively prevent the occurrence of negative integration behaviors. (4) The greater the risk attitude coefficient and risk aversion coefficient of the automotive enterprise and intelligent automotive solution provider, the more conducive they are to the occurrence of positive integration behavior. Full article
(This article belongs to the Section Systems Practice in Social Science)
25 pages, 5724 KiB  
Article
Digital Twin Integration for Workforce Training: Transforming SMEs in the Ornamental Stone Industry
by Carlos E. Cremonini, Carlos Capela, Agostinho da Silva, Marcelo C. Gaspar and Joel C. Vasco
Systems 2025, 13(2), 120; https://doi.org/10.3390/systems13020120 - 13 Feb 2025
Abstract
Digital twin technology offers immersive and cost-effective solutions for workforce training, yet its practical implementation within SME training frameworks remains limited. This study develops and evaluates the Digital Twin Framework for Workforce Training (DT4WFT), addressing key challenges such as resource constraints and precision [...] Read more.
Digital twin technology offers immersive and cost-effective solutions for workforce training, yet its practical implementation within SME training frameworks remains limited. This study develops and evaluates the Digital Twin Framework for Workforce Training (DT4WFT), addressing key challenges such as resource constraints and precision through tools like Siemens NX Mechatronic Concept Design (MCD) and StoneCUT@Line®. Employing a mixed-methods approach, qualitative insights from managers, and quantitative analysis demonstrated the framework’s potential to enhance operator performance, improve efficiency, and reduce lead times. However, the validation was based solely on managerial perceptions, as the framework has not yet been implemented in real-world settings. Statistical analysis confirmed strong correlations between the framework’s perceived implementation and improved training outcomes, highlighting its scalability and adaptability. Future research should focus on practical implementation, cross-industry applications, and longitudinal studies to evaluate sustained impacts, ensuring the DT4WFT framework’s broader relevance and effectiveness in workforce development. Full article
(This article belongs to the Section Systems Practice in Social Science)
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24 pages, 604 KiB  
Article
Implications of Second-Order Cybernetics and Autopoiesis on Systems-of-Systems Engineering
by Jakob Axelsson
Systems 2025, 13(2), 119; https://doi.org/10.3390/systems13020119 - 13 Feb 2025
Abstract
Systems-of-systems are often characterized as systems where the constituent parts have some independence from the whole. Recent research has aimed at clarifying in more detail what this independence means. It has shown that independence requires the constituent systems to be agents that observe [...] Read more.
Systems-of-systems are often characterized as systems where the constituent parts have some independence from the whole. Recent research has aimed at clarifying in more detail what this independence means. It has shown that independence requires the constituent systems to be agents that observe the system-of-systems from within and construct internal models of it as a basis for decisions. This view on observers as parts of the system-of-systems parallels development in the field of second-order cybernetics several decades ago, yet the connection between that field and systems-of-systems has not been explored previously. This paper, therefore, summarizes key concepts from second-order cybernetics, including the subtopic autopoiesis. It then discusses what the implications are on systems-of-systems engineering through the identification of 17 concerns. These concerns relate to the physical topology, behavior, and control of the system-of-systems. This paper shows how these concerns directly relate to the theoretical concepts of second-order cybernetics and autopoiesis, and thereby, opens the door to further exploitation of this theoretical foundation. Full article
(This article belongs to the Special Issue System of Systems Engineering)
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24 pages, 1345 KiB  
Article
iEVEM: Big Data-Empowered Framework for Intelligent Electric Vehicle Energy Management
by Siyan Guo and Cong Zhao
Systems 2025, 13(2), 118; https://doi.org/10.3390/systems13020118 - 13 Feb 2025
Abstract
Recent years have witnessed an unprecedented boom of Electric Vehicles (EVs). However, EVs’ further development confronts critical bottlenecks due to EV Energy (EVE) issues like battery hazards, range anxiety, and charging inefficiency. Emerging data-driven EVE Management (EVEM) is a promising solution but still [...] Read more.
Recent years have witnessed an unprecedented boom of Electric Vehicles (EVs). However, EVs’ further development confronts critical bottlenecks due to EV Energy (EVE) issues like battery hazards, range anxiety, and charging inefficiency. Emerging data-driven EVE Management (EVEM) is a promising solution but still faces fundamental challenges, especially in terms of reliability and efficiency. This article presents iEVEM, the first big data-empowered intelligent EVEM framework, providing systematic support to the essential driver-, enterprise-, and social-level intelligent EVEM applications. Particularly, a layered data architecture from heterogeneous EVE data management to knowledge-enhanced intelligent solution design is provided, and an edge–cloud collaborative architecture for the networked system is proposed for reliable and efficient EVEM, respectively. We conducted a proof-of-concept case study on a typical EVEM task (i.e., EV energy consumption outlier detection) using real driving data from 4000+ EVs within three months. The experimental results show that iEVEM achieves a significant boost in reliability and efficiency (i.e., up to 47.48% higher in detection accuracy and at least 3.07× faster in response speed compared with the state-of-art approaches). As the first intelligent EVEM framework, iEVEM is expected to inspire more intelligent energy management applications exploiting skyrocketing EV big data. Full article
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28 pages, 1820 KiB  
Article
Synergistic Evolution in the Digital Transformation of the Whole Rural E-Commerce Industry Chain: A Game Analysis Using Prospect Theory
by Yanling Wang and Junqian Xu
Systems 2025, 13(2), 117; https://doi.org/10.3390/systems13020117 - 12 Feb 2025
Abstract
In the big data era, global business competition focuses on industrial chain coordination. The whole rural e-commerce industry chain, as an advanced system characterized by digital transformation, is experiencing rapid growth. This paper aims to explore the evolutionary mechanism of collaborative behavior in [...] Read more.
In the big data era, global business competition focuses on industrial chain coordination. The whole rural e-commerce industry chain, as an advanced system characterized by digital transformation, is experiencing rapid growth. This paper aims to explore the evolutionary mechanism of collaborative behavior in the digital transformation of platform enterprises and participating enterprises across the whole rural e-commerce industry chain. To achieve this, this paper combines prospect theory and evolutionary game theory, introduces the value function and decision weight of prospect theory, and constructs a two-party game model between platform enterprises and participating enterprises. Based on the demonstration of the impact of individual changes in major objective factors, such as the cooperative innovation benefit coefficient, as well as major behavioral characteristic factors, such as decision-makers’ risk attitude coefficients, on enterprises’ strategic choices, we further reveal the influence of the interaction of key factors on the evolutionary results through case simulations. The findings indicate that when the behavior characteristics of the players are introduced, the threshold interval of the cost–benefit ratio of the two sides to reach the optimal state of decision-making is obviously reduced. Under moderate risk attitudes and degrees of loss sensitivity, enhancing the resource absorption capacity of enterprises in the chain and reducing the potential risk loss of platform enterprises to alleviate the influence of subjective behavior characteristics on cooperation willingness are effective measures. Improving innovation ability is the key factor in alleviating the negative impact of uncertainty on the decision-making of both parties. This paper is one of the few studies to integrate prospect theory with evolutionary game analysis in examining the collaborative behaviors between platform enterprises and participating enterprises. Effective strategies are proposed to promote enterprises achieving synergy. Full article
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27 pages, 679 KiB  
Article
How Intelligent Transformation Empowers Innovation Quality Improvement in Manufacturing Enterprises: A Resource Orchestration Perspective
by Xinyi Liu, Qinghao Zheng, Yang Deng and Zongjun Wang
Systems 2025, 13(2), 116; https://doi.org/10.3390/systems13020116 - 12 Feb 2025
Abstract
The rise of Industry 4.0 has led more manufacturers to embrace the concept of intelligent transformation. Understanding this relationship improves both transformation efficiency and the quality of innovation. This study, based on resource orchestration theory, empirically tests a sample of Chinese A-share listed [...] Read more.
The rise of Industry 4.0 has led more manufacturers to embrace the concept of intelligent transformation. Understanding this relationship improves both transformation efficiency and the quality of innovation. This study, based on resource orchestration theory, empirically tests a sample of Chinese A-share listed manufacturing companies from 2007 to 2022. The key findings are as follows: (1) intelligent transformation significantly enhances the innovation quality of manufacturing firms, particularly in the eastern region, non-state-owned enterprises, and non-high-tech enterprises; (2) intelligent transformation, as a vital means of resource orchestration, optimizes resource allocation, thereby strengthening corporate financing, organizational resilience, and risk-taking capabilities, ultimately empowering the improvement in innovation quality; (3) the three sub-dimensions of intelligent transformation—intelligent sensing technology, intelligent production and manufacturing, and intelligent strategic layout—all significantly contribute to the enhancement of innovation quality in manufacturing firms. These conclusions provide new insights for manufacturing enterprises to utilize intelligent transformation for resource orchestration and offer valuable implications for the improvement in their innovation quality. Full article
(This article belongs to the Section Systems Practice in Social Science)
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23 pages, 1290 KiB  
Article
Corporate Financialization and Innovation Investment in China: Disentangling the Crowding-Out Effect and Reservoir Effect Under Economic Policy Uncertainty
by Jing Tian
Systems 2025, 13(2), 115; https://doi.org/10.3390/systems13020115 - 12 Feb 2025
Abstract
This study investigates the relationship between corporate financialization and innovation investment in Chinese manufacturing firms under the backdrop of economic policy uncertainty (EPU). We systematically examine the dual mechanisms through which financialization simultaneously supports and constrains innovation via its reservoir and crowding-out effects. [...] Read more.
This study investigates the relationship between corporate financialization and innovation investment in Chinese manufacturing firms under the backdrop of economic policy uncertainty (EPU). We systematically examine the dual mechanisms through which financialization simultaneously supports and constrains innovation via its reservoir and crowding-out effects. Our findings reveal a robust inverted U-shaped relationship between financialization and R&D expenditure, which is significantly moderated by EPU. Notably, financialization predominantly enhances R&D expenditure for most firms in our sample, challenging conventional perspectives on the financialization–real investment nexus. Further analyses indicate that alleviating financing constraints serves as a fundamental mechanism through which financialization fosters innovation investment. However, elevated EPU exacerbates financing constraints, attenuating the reservoir effects of financialization on innovation activities. Full article
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26 pages, 5718 KiB  
Article
Enhancing Software Sustainability: Leveraging Large Language Models to Evaluate Security Requirements Fulfillment in Requirements Engineering
by Ahmad F. Subahi
Systems 2025, 13(2), 114; https://doi.org/10.3390/systems13020114 - 12 Feb 2025
Abstract
In the digital era, cybersecurity is integral for preserving national security, digital privacy, and social sustainability. This research emphasizes the role of non-functional equirements (NFRs) in developing secure software systems that enhance societal wellbeing by ensuring data protection, user privacy, and system robustness. [...] Read more.
In the digital era, cybersecurity is integral for preserving national security, digital privacy, and social sustainability. This research emphasizes the role of non-functional equirements (NFRs) in developing secure software systems that enhance societal wellbeing by ensuring data protection, user privacy, and system robustness. Specifically, this study introduces a proof-of-concept approach by leveraging machine learning (ML) models to classify NFRs and identify security-related issues early in the software development lifecycle. Two experiments were conducted to assess the effectiveness of different models for binary and multi-class classification tasks. In Experiment 1, BERT-based models and artificial neural networks (ANNs) were fine-tuned to classify NFRs into security and non-security categories using a dataset of 803 statements. BERT-based models outperformed ANNs, achieving higher accuracy, precision, recall, and ROC-AUC scores, with hyperparameter tuning further enhancing the results. Experiment 2 assessed logistic regression (LR), a support vector machine (SVM), and XGBoost for the multi-class classification of security-related NFRs into seven categories. The SVM and XGBoost showed strong performance, achieving high precision and recall in specific categories. The findings demonstrate the effectiveness of advanced ML models in automating NFR classification, improving software security, and supporting social sustainability. Future work will explore hybrid approaches to enhance scalability and accuracy. Full article
(This article belongs to the Section Systems Engineering)
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19 pages, 348 KiB  
Article
The Role of Digital Infrastructure and Skills in Enhancing Labor Productivity: Insights from Industry 4.0 in the European Union
by Ofelia Ema Aleca and Florin Mihai
Systems 2025, 13(2), 113; https://doi.org/10.3390/systems13020113 - 12 Feb 2025
Abstract
The adoption of Industry 4.0 technologies supports the digital transformation of production processes, making them more efficient. This study examines how digital infrastructure, digital skills, and the use of cloud technologies influence labor productivity in European Union countries. Using econometric methods, including linear [...] Read more.
The adoption of Industry 4.0 technologies supports the digital transformation of production processes, making them more efficient. This study examines how digital infrastructure, digital skills, and the use of cloud technologies influence labor productivity in European Union countries. Using econometric methods, including linear regressions and fixed-effects panel regressions, the analysis highlights the important role digital skills play in boosting productivity. It also identifies the adoption of cloud solutions as a catalyst for process efficiency, while widespread high-speed internet coverage supports the connectivity of smart systems. However, variations in the development of digital infrastructure and workforce readiness across EU member states present challenges to overall labor productivity. The study concludes that strategic investments in automation and digital infrastructure, along with improving the workforce’s digital skills, are essential to making Industry 4.0 a key pillar of economic competitiveness. By examining how workforce digital skills and certain Industry 4.0 technologies affect labor productivity, this research adds valuable insights to the specialized literature. Full article
28 pages, 1347 KiB  
Article
Intelligent Assessment of Personal Credit Risk Based on Machine Learning
by Chuansheng Wang and Hang Yu
Systems 2025, 13(2), 112; https://doi.org/10.3390/systems13020112 - 12 Feb 2025
Abstract
In the 21st-century global economy, the rapid growth of the finance industry, particularly in personal credit, fuels economic growth and market prosperity. However, the rapid expansion of personal credit business has brought explosive growth in the amount of data, which puts forward higher [...] Read more.
In the 21st-century global economy, the rapid growth of the finance industry, particularly in personal credit, fuels economic growth and market prosperity. However, the rapid expansion of personal credit business has brought explosive growth in the amount of data, which puts forward higher requirements for the risk management of financial institutions. To solve this problem, this paper constructs an intelligent evaluation model of personal credit risk under the background of big data. Firstly, based on the forest optimization feature selection algorithm, combined with initialization based on chi-square check, adaptive global seeding, and greedy search strategies, key risk factors are accurately identified from high-dimensional data. Then, the XGBoost algorithm is used to evaluate the credit risk level of customers, and the traditional Sparrow Search Algorithm is improved by using Tent chaotic mapping, sine and cosine search, reverse learning, and Cauchy mutation strategy to improve the optimization performance of algorithm parameters. Finally, using the Lending Club dataset for empirical analysis, the experiment shows that the model improves the accuracy of personal credit risk assessment and enhances the ability of risk control. Full article
(This article belongs to the Special Issue AI-Empowered Modeling and Simulation for Complex Systems)
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18 pages, 1720 KiB  
Article
Fine-Grained Sentiment Analysis Based on SSFF-GCN Model
by Yuexu Zhao, Junjie Fang and Shaolong Jin
Systems 2025, 13(2), 111; https://doi.org/10.3390/systems13020111 - 11 Feb 2025
Abstract
The research on aspect-based sentiment analysis (ABSA) mostly relies on a single attention mechanism or grammatical semantic information, which makes it less effective in dealing with complex language structures. To address the challenges in fine-grained sentiment analysis tasks, this paper establishes a novel [...] Read more.
The research on aspect-based sentiment analysis (ABSA) mostly relies on a single attention mechanism or grammatical semantic information, which makes it less effective in dealing with complex language structures. To address the challenges in fine-grained sentiment analysis tasks, this paper establishes a novel model of syntax and semantics based on feature fusion together with a graph convolutional network (SSFF-GCN), which includes a dual-channel information extraction layer by combining syntactic dependency graphs and semantic information, and consists of three important modules: the syntactic feature enhancement module, semantic feature extraction module, and feature fusion module. In the grammar feature enhancement module, this model uses dependency trees to capture the structural relationship between emotional words and target words and adds a dual affine attention module to enhance grammar learning ability. In the semantic feature extraction module, aspect-aware attention combined with self-attention is used to extract semantic associations in sentences, which ensures effective capture of long-distance dependency information. The feature fusion module dynamically combines the enhanced syntactic and semantic information through a gated mechanism; therefore, it enhances the model’s ability to express emotional features. The empirical results show that the SSFF-GCN model is generally superior to existing models on several publicly available datasets. Full article
(This article belongs to the Section Artificial Intelligence and Digital Systems Engineering)
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24 pages, 6895 KiB  
Article
Panoramic Video Synopsis on Constrained Devices for Security Surveillance
by Palash Yuvraj Ingle and Young-Gab Kim
Systems 2025, 13(2), 110; https://doi.org/10.3390/systems13020110 - 11 Feb 2025
Abstract
As the global demand for surveillance cameras increases, the digital footage data also explicitly increases. Analyzing and extracting meaningful content from footage is a resource-depleting and laborious effort. The traditional video synopsis technique is used for constructing a small video by relocating the [...] Read more.
As the global demand for surveillance cameras increases, the digital footage data also explicitly increases. Analyzing and extracting meaningful content from footage is a resource-depleting and laborious effort. The traditional video synopsis technique is used for constructing a small video by relocating the object in the time and space domains. However, it is computationally expensive, and the obtained synopsis suffers from jitter artifacts; thus, it cannot be hosted on a resource-constrained device. In this research, we propose a panoramic video synopsis framework to address and solve the problems of the efficient analysis of objects for better governance and storage. The surveillance system has multiple cameras sharing a common homography, which the proposed method leverages. The proposed method constructs a panorama by solving the broad viewpoints with significant deviations, collisions, and overlapping among the images. We embed a synopsis framework on the end device to reduce storage, networking, and computational costs. A neural network-based model stitches multiple camera feeds to obtain a panoramic structure from which only tubes with abnormal behavior were extracted and relocated in the space and time domains to construct a shorter video. Comparatively, the proposed model achieved a superior accuracy matching rate of 98.7% when stitching the images. The feature enhancement model also achieves better peak signal-to-noise ratio values, facilitating smooth synopsis construction. Full article
(This article belongs to the Special Issue Digital Solutions for Participatory Governance in Smart Cities)
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23 pages, 7083 KiB  
Article
Economic Optimal Dispatch of Networked Hybrid Renewable Energy Microgrid
by Xiaoqin Ye and Peng Yang
Systems 2025, 13(2), 109; https://doi.org/10.3390/systems13020109 - 10 Feb 2025
Abstract
With the increasing importance of renewable energy in the global energy transition, the microgrid has attracted wide attention as an efficient and flexible power solution. However, there are some problems in current networked microgrid systems, such as complex structure, numerous parameters, and significant [...] Read more.
With the increasing importance of renewable energy in the global energy transition, the microgrid has attracted wide attention as an efficient and flexible power solution. However, there are some problems in current networked microgrid systems, such as complex structure, numerous parameters, and significant fluctuations in generation capacity. Aiming at the parameter optimization problem of networked microgrids integrating multiple energy generation and energy storage forms, this paper constructs a multi-objective microgrid structure decision-making model. The model comprehensively considers operation and maintenance costs, fuel costs, power abandonment and lack-of-power punishment costs, power transaction costs, and pollution treatment costs, aiming to realize the joint optimization of economic benefits and environmental sustainability. Furthermore, an improved multi-objective particle swarm optimization (IMOPSO) algorithm is designed to solve the model. In order to verify the effectiveness of the model in the scenarios of distributed energy and energy load fluctuation, this paper uses the scenario analysis method to realize the data analysis of 2000 scenarios, and obtains four typical deterministic scenarios for simulation experiments. The experimental results show that, compared with the traditional microgrid, when the capacity configuration is determined by the number of wind driven generators, photovoltaic panels, diesel generators, and batteries being 5, 189, 2, and 107, respectively, the proposed net-connected economic dispatch optimization method based on hybrid renewable energy in this paper reduces the generation cost and environmental cost of the system by 96.76 ¥ to 428.19 ¥, and keeps the load loss rate stable between 0.34% and 4.56%. The utilization rate of renewable energy has been raised to about 95%. Full article
(This article belongs to the Section Complex Systems and Cybernetics)
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37 pages, 1584 KiB  
Article
Manufacturer Channel-Selection Strategy Considering Information Sharing Under Uncertain Demand
by Fang Huang, Yi Pan, Zhi Zhao, Han Song and Yuying Liu
Systems 2025, 13(2), 108; https://doi.org/10.3390/systems13020108 - 10 Feb 2025
Abstract
Taking into account retailers’ resistance and operational costs, manufacturer enterprises are facing the optimal decision-making problem of whether and what kind of direct sales channels to open. Meanwhile, against the backdrop of asymmetric demand information, how does retailers’ information sharing affect manufacturers’ channel [...] Read more.
Taking into account retailers’ resistance and operational costs, manufacturer enterprises are facing the optimal decision-making problem of whether and what kind of direct sales channels to open. Meanwhile, against the backdrop of asymmetric demand information, how does retailers’ information sharing affect manufacturers’ channel selection? Based on this, this study considers three types of sales channels for manufacturers in the context of asymmetric demand information: a traditional channel, online direct sales channel, and subsidiary direct sales channel. Six supply chain game models are established under the retailer’s information strategy, and the manufacturer’s channel-selection decision and the retailer’s information-sharing decision are analyzed. The study demonstrates that when information is shared, the online direct sales channel represents the optimal choice. Conversely, when information sharing is absent, the manufacturer will select the subsidiary direct channel when the subsidiary sales channel opening cost is minimal, and the unit direct selling cost of online direct sales channels is moderate. Furthermore, we discover that retailers lack motivation to share demand information. Therefore, we propose an information-sharing incentive system to encourage retailers to voluntarily share information with manufacturers, aiming for Pareto optimization in the supply chain. Full article
(This article belongs to the Section Supply Chain Management)
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31 pages, 7861 KiB  
Article
Modelling and Analysis of Emergency Scenario Evolution System Based on Generalized Stochastic Petri Net
by Yinghua Song, Hongqian Xu, Danhui Fang and Xiaoyan Sang
Systems 2025, 13(2), 107; https://doi.org/10.3390/systems13020107 - 10 Feb 2025
Abstract
Emergency scenario characterization and analysis is an essential approach to describing and understanding the future development of emergencies and assisting in response decision-making. This paper aims to develop a method for emergency evolution analysis in a scenario-based way to improve “scenario response” decision-making. [...] Read more.
Emergency scenario characterization and analysis is an essential approach to describing and understanding the future development of emergencies and assisting in response decision-making. This paper aims to develop a method for emergency evolution analysis in a scenario-based way to improve “scenario response” decision-making. A systematic conceptual framework for emergency scenario evolution (ESE) analysis has been developed based on the domain knowledge of emergency management and the disaster system, combined with the representational ability of the knowledge element model. In addition, a modelling approach for ESE based on the generalized stochastic Petri net (ESEGSPN) is proposed to depict the evolutionary uncertainty through basic control flow and to optimize the parameter uncertainty using fuzzy theory. Finally, the COVID-19 pandemic is used as a case study to show how ESEGSPN works. The results indicate that ESEGSPN can simulate the emergency evolution process, identify critical states and trigger actions, present the evolution trend of typical scenario elements, and assist decision-makers in deploying more targeted emergency responses in dynamically changing situations. Full article
(This article belongs to the Section Systems Practice in Social Science)
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27 pages, 3309 KiB  
Article
Integrating Lean Principles into Lean Robotics Systems for Enhanced Production Processes
by Stelian Brad and Eyas Deeb
Systems 2025, 13(2), 106; https://doi.org/10.3390/systems13020106 - 10 Feb 2025
Abstract
Integrating lean principles into lean robotics systems emerges as a transformative path for production processes. This paper addresses the question of what are the best practices of integrating lean principles within robotics systems to enhance production processes in manufacturing systems through a comprehensive [...] Read more.
Integrating lean principles into lean robotics systems emerges as a transformative path for production processes. This paper addresses the question of what are the best practices of integrating lean principles within robotics systems to enhance production processes in manufacturing systems through a comprehensive literature review, direct engagement with robotics engineers, and generating a Voice of Use Table Performance analysis (VOT) and Key Performance Indicators (KPIs) to illuminate the advantages realized from lean principles within robotics systems and draw attention to the current gap of how robotics systems can become lean in manufacturing to maximize their value in production processes. The paper focuses on the key findings of the possible influence on the development of the principles of lean, as well as the precision and accuracy of robotics systems for improved production processes in manufacturing systems. Full article
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31 pages, 994 KiB  
Article
Artificial Intelligence and the New Quality Productive Forces of Enterprises: Digital Intelligence Empowerment Paths and Spatial Spillover Effects
by Xiumin Li, Haojian Tang and Zishuo Chen
Systems 2025, 13(2), 105; https://doi.org/10.3390/systems13020105 - 9 Feb 2025
Abstract
The 20th CPC Central Committee stressed that the key to high-quality economic development is to cultivate new quality productive forces, and AI plays a key role in cultivating new quality productive forces. This paper takes A-share listed enterprises in China from 2013 to [...] Read more.
The 20th CPC Central Committee stressed that the key to high-quality economic development is to cultivate new quality productive forces, and AI plays a key role in cultivating new quality productive forces. This paper takes A-share listed enterprises in China from 2013 to 2022 as a sample, constructs comprehensive level indicators of AI from the strategic side, application side, and innovation side of enterprises’ AI, and empirically examines the impact, mechanism, and spatial spillover effect of AI development on enterprises’ new quality productive forces from the perspective of digital intelligence empowerment and the spatial perspective. The results of this study show that AI can significantly promote the development of new productivity, and the development of AI within enterprises can promote the improvement of new productivity levels of neighboring enterprises or regions. At the same time, the role of AI in promoting the development of new quality productive forces is more obvious when the enterprise is a private enterprise, the managers have a digital background, and the enterprise is located in an industry with fierce market competition or a strategic industry. The purpose of this paper is to reveal the mechanism and spatial spillover effect of AI in promoting the new quality productive forces of enterprises and to provide a new theoretical basis and research perspective for enterprises to cultivate new quality productive forces. Full article
(This article belongs to the Special Issue Sustainable Business Model Innovation in the Era of Industry 4.0)
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41 pages, 1469 KiB  
Article
Evaluation and Analysis of Industrial Internet Maturity for Power Enterprises in the Digital Transformation
by Yan Jia, Zengqiang Wang and Qianying Li
Systems 2025, 13(2), 104; https://doi.org/10.3390/systems13020104 - 9 Feb 2025
Abstract
The industrial Internet plays a vital role in promoting the digital transformation of enterprises, especially in the core application field of the power industry. Evaluating the maturity of the industrial Internet of power enterprises and finding the weak points in the construction of [...] Read more.
The industrial Internet plays a vital role in promoting the digital transformation of enterprises, especially in the core application field of the power industry. Evaluating the maturity of the industrial Internet of power enterprises and finding the weak points in the construction of the industrial Internet are of great significance for the digital transformation of power enterprises. Firstly, this paper reviews the existing literature and analyzes the evaluation situation of industrial Internet maturity. Research has found that there is relatively little research on the maturity evaluation of the industrial Internet for the power industry, and existing maturity models have difficulty meeting industry-specific needs. Therefore, it is very important and necessary to build a maturity evaluation model of the industrial Internet suitable for the power industry. Subsequently, based on the specific characteristics of the power industry, while referring to the authoritative literature and industry standards, this paper constructs a three-level index system covering key elements such as equipment networking, information network infrastructure construction, supply chain management, and intelligent production and simultaneously expounds the quantitative collection methods and scoring principles of indices. Then, introducing the Analytic Hierarchy Process (AHP) to determine subjective weights and the Entropy Weight Method (EWM) to quantify the objective weights of indices, a maturity evaluation method that combines subjective judgment and objective data support is formed. Later, the calculation method for the comprehensive score of indices and the criteria for classifying maturity levels are explained. Finally, a specific power enterprise is selected as a case study, and the evaluation results are analyzed to verify the feasibility of the evaluation method. Full article
(This article belongs to the Section Systems Practice in Social Science)
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17 pages, 1807 KiB  
Article
Research on the Incentive Mechanism of Environmental Responsibility of Polluting Enterprises Considering Fairness Preference
by Gedi Ji, Qisheng Wang and Qing Chang
Systems 2025, 13(2), 103; https://doi.org/10.3390/systems13020103 - 8 Feb 2025
Abstract
More and more attention has been paid to the environmental problems brought about by the development of the global economy. Based on the principal–agent theory, this paper constructs an incentive model for the government and polluting enterprises and explores the incentive problem of [...] Read more.
More and more attention has been paid to the environmental problems brought about by the development of the global economy. Based on the principal–agent theory, this paper constructs an incentive model for the government and polluting enterprises and explores the incentive problem of the government and polluting enterprises in undertaking environmental responsibility. At present, the research on the incentive of polluting enterprises focuses on the hypothesis of ‘rational man’, and less on the fairness preference of polluting enterprises. However, in other research fields, it has been proved that fairness preference has a great influence on the incentive mechanism. Fairness preference is introduced into the incentive model, and the incentive effect of polluting enterprises before and after considering fairness preference is compared and analyzed. This study found that the reward and punishment mechanism considering fairness preference can increase the behavior of polluting enterprises to assume environmental responsibility and limit the behavior of not assuming environmental responsibility. The stronger the fairness preference of polluting enterprises, the stronger the role of incentive mechanism; after considering the fairness preference, the government’s subsidies and penalties for polluting enterprises will increase with the increase in the fairness preference of polluting enterprises, and the expected benefits of polluting enterprises and the government will also increase; under the same incentive mechanism, the income of polluting enterprises with strong fairness preference is higher, but the government’s income is lower. Adopting the same incentive mechanism for different polluting enterprises will cause the loss of social benefits. After considering the fairness preference, the incentive strategy set up to a certain extent promotes the polluting enterprises to assume environmental responsibility and realize the coordinated development of the economy and the environment. Therefore, the government should set reasonable subsidy and punishment policies according to the fairness preference of polluting enterprises to encourage enterprises to fulfill their environmental responsibilities, improve environmental quality and reduce pollution. Full article
(This article belongs to the Special Issue Systems Analysis of Enterprise Sustainability)
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29 pages, 2776 KiB  
Article
Research on Dynamic Monitoring and Early Warning for Innovation Ecosystem Resilience: Evidence from China
by Xin Wang
Systems 2025, 13(2), 102; https://doi.org/10.3390/systems13020102 - 8 Feb 2025
Abstract
Innovation ecosystem resilience (IER) is the maximum tolerance of an innovation ecosystem to accidents, crises, and other external shocks. Developing such resilience involves stages such as risk diversification, impact mitigation, recovery and reconstruction, and innovative development. This study first constructs an evaluation index [...] Read more.
Innovation ecosystem resilience (IER) is the maximum tolerance of an innovation ecosystem to accidents, crises, and other external shocks. Developing such resilience involves stages such as risk diversification, impact mitigation, recovery and reconstruction, and innovative development. This study first constructs an evaluation index system for IER with the dimensions of diversity, evolvability, fluidity, and buffering. Secondly, a coupling coordination degree model is used to evaluate and monitor IER, and the early warning levels are further subdivided with the help of an alertness degree model. Finally, through an obstacle degree model, the main obstacles to IER are determined. The research findings are as follows: First, the development trend of China’s IER is relatively stable. Second, the regional heterogeneity of IER is obvious. Third, the IER in most regions of the country is at the early warning stage. Fourth, the number of enterprises with R&D activities, the number of patents granted, the proportion of foreign funds contributing to internal R&D expenditure, and hydropower generation are the greatest obstacles to diversity, evolvability, fluidity, and buffering, respectively. The main obstacles are slightly different in different regions. This research establishes a monitoring and early warning system for IER, which is conducive to discovering weak links in an innovation ecosystem in time and sounding the alarm. This will help government departments formulate scientific and reasonable graded response plans, reduce the risk of emergencies in society and national security, and ensure the resilience and stability of the innovation ecosystems. Full article
(This article belongs to the Special Issue Research and Practices in Technological Innovation Management Systems)
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29 pages, 2223 KiB  
Article
Integrating HR, Intellectual Capital, Ambidextrous Innovation, and Environmental Regulation for Sustainable Success in Bangladesh’s Manufacturing Industry
by Muhammad Khalequzzaman, Shuxiang Wang, Nana Zhang and Liya Wang
Systems 2025, 13(2), 99; https://doi.org/10.3390/systems13020099 - 7 Feb 2025
Abstract
This study examines how environmental regulation (ER), green intellectual capital (GIC), green human resource management (GHRM), and green ambidextrous innovation (GAI) contribute to enhancing the sustainable performance (SP) of manufacturing firms. Using a quantitative approach, data from 472 managers of green garment manufacturing [...] Read more.
This study examines how environmental regulation (ER), green intellectual capital (GIC), green human resource management (GHRM), and green ambidextrous innovation (GAI) contribute to enhancing the sustainable performance (SP) of manufacturing firms. Using a quantitative approach, data from 472 managers of green garment manufacturing firms in Bangladesh were analyzed with SmartPLS4 software. The results indicate that GHRM and GIC positively impact SP, with GIC exerting a stronger influence on GAI—encompassing green exploitative innovation (EIGI) and green exploratory innovation (ERGI)—compared to GHRM. Additionally, GAI positively affects SP and serves as a partial mediator in the GIC-SP relationship but not in the GHRM-SP relationship. ER negatively moderates the GHRM-SP and GHRM-GAI links, while it positively moderates the GIC-GAI relationship, albeit weakly in the GIC-SP connection. This study highlights GAI’s mediating roles in the GHRM-SP (specifically, GHRM-EIGI-SP and GHRM-ERGI-SP) and GIC-SP (specifically, GIC-EIGI-SP and GIC-ERGI-SP) relationships within a regulatory context. By introducing fresh perspectives, this research advances green management studies, offering valuable insights for academics and industry professionals. It provides a strategic framework for firms to navigate regulations, foster innovation, optimize human and intangible resources, and enhance sustainable performance, thereby positioning themselves as leaders in the global market. Full article
(This article belongs to the Section Systems Practice in Social Science)
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19 pages, 1312 KiB  
Article
The Population Health Impacts of Changes to the National Health Service Health Check Programme: A System Dynamics Modelling Approach in a Local Authority in England
by Abraham George, Padmanabhan Badrinath, Stephanie Newton, Amy Hooper, Aaron Bhavsar, Mark Chambers, Peter Lacey, Rutuja Kulkarni-Johnston and Harry Whitlow
Systems 2025, 13(2), 101; https://doi.org/10.3390/systems13020101 - 7 Feb 2025
Abstract
Health checks aim to improve the health of the population by identifying individuals with risk factors earlier and intervening to prevent disease. The role of commissioners is to ensure health checks provide as much benefit as possible for taxpayer funds invested into them. [...] Read more.
Health checks aim to improve the health of the population by identifying individuals with risk factors earlier and intervening to prevent disease. The role of commissioners is to ensure health checks provide as much benefit as possible for taxpayer funds invested into them. As such, evidence of the potential impacts of different commissioning choices is beneficial in this decision-making process. System dynamics modelling can be used to provide this evidence by modelling the health check programme using a pre-existing cohort model of a given population. This modelling considers local data, literature findings, and stakeholder views, from which nine different scenarios of a local health check programme have been tested. These scenarios found that extending the duration of health checks to 20 years and improving treatment uptake for those with high blood pressure or high cholesterol reduced rates of cardiovascular disease, improved healthy life expectancy and reduced years lived in ill health. In contrast, improving attendance in the most deprived quintile of the population made very little change to the health of the population overall, although a larger effect was observed in the most deprived areas. These findings helped guide local commissioning decisions by showing the long-term impact of different health check scenarios. Full article
(This article belongs to the Special Issue System Dynamics Modeling and Simulation for Public Health)
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29 pages, 6608 KiB  
Article
A Study on Platform Supply Chain Model Selection and Pricing Considering Precision Marketing
by Jianhua Wang and Yuchen Zhang
Systems 2025, 13(2), 100; https://doi.org/10.3390/systems13020100 - 7 Feb 2025
Abstract
This study constructs a Stackelberg competitive model that includes manufacturers, e-commerce platforms, and third-party marketing platforms to explore the impact of precision marketing services on the strategic balance of all parties involved. The article proposes three strategies, including a platform marketing model, third-party [...] Read more.
This study constructs a Stackelberg competitive model that includes manufacturers, e-commerce platforms, and third-party marketing platforms to explore the impact of precision marketing services on the strategic balance of all parties involved. The article proposes three strategies, including a platform marketing model, third-party marketing model, and differentiated marketing model. Research has found that manufacturers tend to choose marketing services with lower costs, especially when marketing costs are low. The cost and expenses of precision marketing services are key factors in manufacturers’ decision-making. When the commission rate is at a moderate level, manufacturers tend to choose e-commerce platforms, while platforms tend to provide precision marketing services with lower service sensitivity. Full article
(This article belongs to the Section Supply Chain Management)
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27 pages, 12270 KiB  
Article
Pricing Decision-Making Considering Ambiguity Tolerance in Consumers: Evidence from Recycled Building Material Enterprises
by Jie Peng, Yuxi Zou, Hao Zhang, Lianghui Zeng, Yuhan Wang and Xingwei Li
Systems 2025, 13(2), 98; https://doi.org/10.3390/systems13020098 - 5 Feb 2025
Abstract
Globally, recycled building materials have attracted much attention, but the ambiguity of the use of recycled building materials makes it difficult for the building material remanufacturer (BMR) to compete with the building material manufacturer (BMM). Brand building is an important strategic tool for [...] Read more.
Globally, recycled building materials have attracted much attention, but the ambiguity of the use of recycled building materials makes it difficult for the building material remanufacturer (BMR) to compete with the building material manufacturer (BMM). Brand building is an important strategic tool for enterprises to increase product competitiveness. From the new perspective of the supply chain, this paper aims to examine the decision-making behavior of enterprises under two scenarios of consumer ambiguity neutrality and ambiguity tolerance and to analyze the impact of ambiguity tolerance on the pricing decisions of building materials supply chains in a brand-building scenario. This paper constructs a building material supply chain game model consisting of the BMM and BMR, according to the cognitive–affective personality system (CAPS) theory and through the Stackelberg game. The main findings are as follows. (1) Strengthening brand building can mitigate the negative impact of ambiguity tolerance on new product pricing. The selling price of recycled building materials is positively related to ambiguity tolerance. (2) When the BMM has higher brand value, there is a U-shaped trend between profit and ambiguity tolerance at a cost coefficient above the threshold value of 0.61. (3) When the BMR has higher brand value, profit is negatively related to ambiguity tolerance at operational inefficiencies and cost coefficients below the threshold value of 0.45. Otherwise, profits and ambiguity tolerance follow a U-shaped trend. This paper not only expands the research on brand building and ambiguity tolerance but also provides theoretical guidance for enterprises to make effective decisions in response to consumers’ ambiguity psychology. Full article
(This article belongs to the Section Supply Chain Management)
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21 pages, 1173 KiB  
Article
Systemic Approaches to Coopetition: Technology and Service Integration in Dynamic Ecosystems Among SMEs
by Agostinho da Silva and Antonio J. Marques Cardoso
Systems 2025, 13(2), 97; https://doi.org/10.3390/systems13020097 - 5 Feb 2025
Abstract
In the globalized, technologically advanced landscape, coopetition—simultaneously cooperating and competing—has become a key strategy for innovation and enhanced value creation. This research focuses on the impact of technology-driven coopetition networks in the Portuguese ornamental stone sector, using a framework based on Service-Dominant Logic [...] Read more.
In the globalized, technologically advanced landscape, coopetition—simultaneously cooperating and competing—has become a key strategy for innovation and enhanced value creation. This research focuses on the impact of technology-driven coopetition networks in the Portuguese ornamental stone sector, using a framework based on Service-Dominant Logic (S-D Logic). It emphasizes the importance of resource integration, service exchange, and institutional arrangements in successful coopetition. Employing a two-phase experimental approach with selected small and medium enterprises (SMEs), this study assesses customer perceptions of product quality under traditional best practices versus those enabled by technology-driven coopetition networks. The results indicate a notable improvement in the customer-perceived quality and outcome consistency. The statistical analysis shows that these networks allow firms to better align with customer expectations, optimize resource allocation, and improve operational coordination. The findings highlight the strategic potential of coopetition networks, particularly when augmented by advanced technologies like IoT-based systems. These networks facilitate sustainable value co-creation and operational resilience by enabling firms to share expertise, distribute tasks, and synchronize efforts. This research contributes to the coopetition and S-D Logic literature by offering a practical framework for firms aiming to boost competitiveness and sustain growth in dynamic service ecosystems. Full article
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22 pages, 8432 KiB  
Article
Multi-Step Peak Passenger Flow Prediction of Urban Rail Transit Based on Multi-Station Spatio-Temporal Feature Fusion Model
by Jianan Sun, Xiaofei Ye, Xingchen Yan, Tao Wang and Jun Chen
Systems 2025, 13(2), 96; https://doi.org/10.3390/systems13020096 - 3 Feb 2025
Abstract
Accurate prediction of station passenger flow is crucial for optimizing rail transit efficiency, but peak passenger flow in urban rail transit (URT) is often disrupted by random events, making predictions challenging. In this paper, in order to solve this challenge, the Bi-graph Graph [...] Read more.
Accurate prediction of station passenger flow is crucial for optimizing rail transit efficiency, but peak passenger flow in urban rail transit (URT) is often disrupted by random events, making predictions challenging. In this paper, in order to solve this challenge, the Bi-graph Graph Convolutional Spatio-Temporal Feature Fusion Network (BGCSTFFN)-based model is introduced to capture complex spatio-temporal correlations. A combination of a graph convolutional neural network and a Transformer is used. The model separately inputs land use (point of interest, POI) and station adjacency information as features into the BGCSTFFN model, using the Pearson correlation coefficient matrix, which is evaluated on real passenger flow dataset from 1 to 25 January 2019 in Hangzhou. The results showed that the model consistently provided the best prediction results across different datasets and prediction tasks compared to other baseline models. In addition, in tasks involving predictions with different combinations of inputs and prediction steps, the model showed superior performance at multiple prediction steps. Its practical application is validated by comparing the results of passenger flow prediction for different types of stations. In addition, the impact of these features on the prediction accuracy and the generalization ability of the model were verified by designing ablation experiments and testing on different datasets. Full article
(This article belongs to the Section Artificial Intelligence and Digital Systems Engineering)
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21 pages, 9737 KiB  
Article
Crowd Management at Turnstiles in Metro Stations: A Pilot Study Based on Observation and Microsimulation
by Sebastian Seriani, Vicente Aprigliano, Alvaro Peña, Alexis Garrido, Bernardo Arredondo, Vinicius Minatogawa, Claudio Falavigna and Taku Fujiyama
Systems 2025, 13(2), 95; https://doi.org/10.3390/systems13020095 - 1 Feb 2025
Abstract
Crowd management at turnstiles in metro stations is a critical task for ensuring safety, efficiency, and comfort for passengers. A methodology based on observation and microsimulation provides an advanced understanding and optimization of crowd flow through these turnstiles. The aim is to optimize [...] Read more.
Crowd management at turnstiles in metro stations is a critical task for ensuring safety, efficiency, and comfort for passengers. A methodology based on observation and microsimulation provides an advanced understanding and optimization of crowd flow through these turnstiles. The aim is to optimize crowd management and prevent overcrowding and delays at metro turnstiles through innovative solutions. The methodology is based on simulating passenger movements through turnstiles to observe and optimize crowd behavior. The results show that passenger decisions (e.g., choosing which turnstile to use, adjusting pace) are based on perceived crowd density, level of service, and usage of space. For instance, the number of turnstiles, their location, and the layout are important variables to be considered in the decision-making sequence. These decisions can be influenced by parameters like turnstile availability, walking paths, and real-time data (e.g., density of passengers). The methodology can help metro operators decide where to place additional turnstiles or adjust operational schedules. By simulating crowd behavior, operators can make informed decisions to reduce congestion and improve the efficiency of turnstile usage. This methodology could be implemented in various metro systems to optimize operations during different crowd conditions and peak times, ensuring smooth, safe, and efficient passenger flow. Full article
(This article belongs to the Special Issue Optimization-Based Decision-Making Models in Rail Systems Engineering)
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19 pages, 353 KiB  
Article
System-Level Critical Success Factors for BIM Implementation in Construction Management: An AHP Approach
by Filippo Maria Ottaviani, Giovanni Zenezini, Francesca Saba, Alberto De Marco and Lorenzo Gavinelli
Systems 2025, 13(2), 94; https://doi.org/10.3390/systems13020094 - 31 Jan 2025
Abstract
Digital tools are transforming the construction industry, reshaping how projects are designed, managed, and delivered. Building Information Modeling (BIM), a cornerstone of this transformation, requires a systemic approach because its implementation spans several organization functions, involves multiple stakeholders, and encompasses all phases of [...] Read more.
Digital tools are transforming the construction industry, reshaping how projects are designed, managed, and delivered. Building Information Modeling (BIM), a cornerstone of this transformation, requires a systemic approach because its implementation spans several organization functions, involves multiple stakeholders, and encompasses all phases of the project life cycle. While extensive literature examines BIM adoption, there is no consensus on its key enablers and barriers nor a ranking of their impact on implementation success. This study investigates the system-level critical success factors (CSFs) for BIM adoption in construction management. First, it reviews earlier literature, identifying 18 CSFs across six dimensions: change management, process efficiency, regulatory compliance, strategic alignment, technology integration, and user training and support. Next, it utilizes the AHP method to rank the CSFs based on the data collected from 31 construction professionals. Results highlight the importance of aligning BIM initiatives with organizational strategies, streamlining workflows, fostering collaboration, and ensuring compliance with evolving regulations. The research concludes that effective BIM implementation requires holistic strategies that emphasize leadership, scalable technology integration, comprehensive training, and adaptability. By addressing these system-level CSFs, organizations can enhance efficiency, drive innovation, and strengthen resilience in an evolving construction landscape. Full article
(This article belongs to the Special Issue Systems Approach to Innovation in Construction Projects)
25 pages, 1712 KiB  
Article
Pricing and Service Decision in a Dual-Channel System Considering Zone of Service Tolerance
by Qingren He, Xinru Lei and Ping Wang
Systems 2025, 13(2), 93; https://doi.org/10.3390/systems13020093 - 31 Jan 2025
Abstract
In the dual-channel retail industry, excessive enthusiasm in offline retailers’ services often extends beyond the customer’s “interpersonal distance zone”, leading to psychological discomfort for customers and a subsequent loss of demand. This situation can trap retailers in a dilemma known as the “service [...] Read more.
In the dual-channel retail industry, excessive enthusiasm in offline retailers’ services often extends beyond the customer’s “interpersonal distance zone”, leading to psychological discomfort for customers and a subsequent loss of demand. This situation can trap retailers in a dilemma known as the “service trap”. To address this issue, we introduce the concept of the zone of service tolerance, which encompasses desired and adequate levels of service, into a dual-channel supply chain consisting of an online channel manufacturer and an offline retailer. We incorporate the zone of service tolerance into the demand function of the offline retailer and establish its profit function, a dynamic game theory to demonstrate the existence of a linkage mechanism between the optimal selling price and service level, providing the conditions for such a mechanism to exist. Additionally, we establish conditions for offline retailers to avoid over-servicing or under-servicing and consider the impacts of these conditions, and we reveal the stability conditions of the offline retailers’ service decisions. Our findings indicate that both over- and under-servicing can lead to customer churn. For newly launched products, offline retailers risk losing customers by adopting a sales strategy focused on high profits and moderate sales (under-servicing). Similarly, for products nearing removal from the shelves, they risk losing customers by adopting a sales strategy focused on low profits and high sales (over-servicing). Furthermore, under certain ranges for the service sensitivity factor, desired service, or adequate service, the optimal service provided by offline retailers remains robust regardless of the manufacturer’s optimal selling price. This greatly simplifies the offline retailer’s decision-making process regarding service levels, as they can directly focus on providing the desired service without factoring in the manufacturer’s pricing strategy. Full article
(This article belongs to the Special Issue Complex Systems for E-commerce and Business Management)
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