Systems

27 pages, 1825 KiB

Open AccessArticle

Multi-Layered Security Framework Combining Steganography and DNA Coding

by Bhavya Kallapu, Avinash Nanda Janardhan, Rama Moorthy Hejamadi, Krishnaraj Rao Nandikoor Shrinivas, Saritha, Raghunandan Kemmannu Ramesh and Lubna A. Gabralla

Systems 2025, 13(5), 341; https://doi.org/10.3390/systems13050341 (registering DOI) - 1 May 2025

Abstract

With the rapid expansion of digital communication and data sharing, ensuring robust security for sensitive information has become increasingly critical, particularly when data are transmitted over public networks. Traditional encryption techniques are increasingly vulnerable to evolving cyber threats, making single-layer security mechanisms less [...] Read more.

With the rapid expansion of digital communication and data sharing, ensuring robust security for sensitive information has become increasingly critical, particularly when data are transmitted over public networks. Traditional encryption techniques are increasingly vulnerable to evolving cyber threats, making single-layer security mechanisms less effective. This study proposes a multi-layered security approach that integrates cryptographic and steganographic techniques to enhance data protection. The framework leverages advanced methods such as encrypted data embedding in images, DNA sequence coding, QR codes, and least significant bit (LSB) steganography. To evaluate its effectiveness, experiments were conducted using text messages, text files, and images, with security assessments based on PSNR, MSE, SNR, and encryption–decryption times for text data. Image security was analyzed through visual inspection, correlation, entropy, standard deviation, key space analysis, randomness, and differential analysis. The proposed method demonstrated strong resilience against differential cryptanalysis, achieving high NPCR values (99.5784%, 99.4292%, and 99.5784%) and UACI values (33.5873%, 33.5149%, and 33.3745%), indicating robust diffusion and confusion properties. These results highlight the reliability and effectiveness of the proposed framework in safeguarding data integrity and confidentiality, providing a promising direction for future cryptographic research. Full article

(This article belongs to the Special Issue Cybersecurity and Secure Information Systems: Challenges and Solutions in Digital Environment)

28 pages, 26458 KiB

Open AccessArticle

Spatiotemporal Changes and Driving Forces of the Ecosystem Service Sustainability in Typical Watertown Region of China from 2000 to 2020

by Zhenhong Zhu, Chen Xu, Jianwan Ji, Liang Wang, Wanglong Zhang, Litao Wang, Eshetu Shifaw and Weiwei Zhang

Systems 2025, 13(5), 340; https://doi.org/10.3390/systems13050340 (registering DOI) - 1 May 2025

Abstract

Quantitative assessment of the ability of the ecosystem service (ES) and its driving forces is of great significance for achieving regional SDGs. In view of the scarcity of existing research that evaluates the sustainability of multiple ES types over a long time series [...] Read more.

Quantitative assessment of the ability of the ecosystem service (ES) and its driving forces is of great significance for achieving regional SDGs. In view of the scarcity of existing research that evaluates the sustainability of multiple ES types over a long time series at the township scale in a typical Watertown Region, this study aims to address two key scientific questions: (1) what are the spatiotemporal changes in the ecosystem service supply–demand index (ESSDI) and ecosystem service sustainability index (ESSI) of a typical Watertown Region? and (2) what are the key factors driving the changes in ESSI? To answer the above two questions, this study takes the Yangtze River Delta Integrated Demonstration Zone (YRDIDZ) as the study area, utilizing multi-source remote sensing and other spatiotemporal geographical datasets to calculate the supply–demand levels and sustainable development ability of different ES in the YRDIDZ from 2000 to 2020. The main findings were as follows: (1) From 2000 to 2020, the mean ESSDI values for habitat quality, carbon storage, crop production, water yield, and soil retention all showed a declining trend. (2) During the same period, the mean ESSI exhibited a fluctuating downward trend, decreasing from 0.31 in 2000 to 0.17 in 2020, with low-value areas expanding as built-up areas grew, while high-value areas were mainly distributed around Dianshan Lake, Yuandang, and parts of ecological land. (3) The primary driving factors within the YRDIDZ were human activity factors, including POP and GDP, with their five-period average explanatory powers being 0.44 and 0.26, whereas the explanatory power of natural factors was lower. However, the interaction of POP and soil showed higher explanatory power. The results of this study could provide actionable ways for regional sustainable governance: (1) prioritizing wetland protection and soil retention in high-population-density areas based on targeted land use quotas; (2) integrating ESSI coldspots (built-up expansion zones) into ecological redline adjustments, maintaining high green infrastructure coverage in new urban areas; and (3) establishing a population–soil co-management framework in agricultural–urban transition zones. Full article

(This article belongs to the Special Issue Applying Systems Thinking to Enhance Ecosystem Services)

14 pages, 1247 KiB

Open AccessArticle

Enhancing Small-Business Ecosystems Through Local Currency Designs in South Korea: A Choice Experiment Approach

by Myoungjin Oh, Geunyoung Lee, Donghyun Lee, Joongha Ahn and Jungwoo Shin

Systems 2025, 13(5), 339; https://doi.org/10.3390/systems13050339 - 1 May 2025

Abstract

Local governments have introduced local currency systems to stimulate regional economies by encouraging local spending and preventing financial outflows. Since the success of a local currency depends on residents’ active participation, understanding consumer preferences is essential for designing effective systems. This study used [...] Read more.

Local governments have introduced local currency systems to stimulate regional economies by encouraging local spending and preventing financial outflows. Since the success of a local currency depends on residents’ active participation, understanding consumer preferences is essential for designing effective systems. This study used a choice experiment and stated preference data to identify the features that most influence local currency adoption. Using the conditional logit model, the analysis revealed that purchase limits, merchant coverage, number of service businesses, local infrastructure, and incentives significantly impact users’ willingness to participate. The scenario analysis further highlighted the necessity of regional differentiation in currency platforms. By adopting an urban analytics approach, these results offer evidence-based insights for policymakers aiming to establish robust, spatially differentiated local currency platforms that bolster regional economic vitality across diverse urban contexts. Full article

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

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23 pages, 4413 KiB

Open AccessArticle

A Novel Method for Holistic Collision Risk Assessment in the Precautionary Area Using AIS Data

by Yu Zhong, Hongzhu Zhou, Manel Grifoll, Agustí Martín, Yusheng Zhou, Jiao Liu and Pengjun Zheng

Systems 2025, 13(5), 338; https://doi.org/10.3390/systems13050338 - 1 May 2025

Abstract

Ship collisions pose a significant threat to maritime safety, especially in congested precautionary areas with high vessel traffic density. Traditional collision risk assessment methods, such as distance to closest point of approach (DCPA) and time to closest point of approach (TCPA), often overlook [...] Read more.

Ship collisions pose a significant threat to maritime safety, especially in congested precautionary areas with high vessel traffic density. Traditional collision risk assessment methods, such as distance to closest point of approach (DCPA) and time to closest point of approach (TCPA), often overlook environmental uncertainties and variations in human response. To address these limitations, this study proposes a novel approach for collision risk assessment using automatic identification system (AIS) data. AIS data from vessels in precautionary areas are resampled to synchronize their temporal frameworks, enabling the systematic identification of ship encounters. Each encounter is analyzed by evaluating critical parameters, including the minimum ship encounter distance (MSED), relative azimuth angles, and trajectories, within a customized ship domain model that incorporates vessel characteristics such as ship length and course. Key metrics, such as intrusion depth and time, are calculated based on vessels’ entry and exit points during each encounter. A set of collision risk indices, which integrates both intrusion depth and time, is introduced, with particular emphasis on intrusion depth due to its heightened sensitivity to proximity danger and constrained maneuvering space. An extensive analysis of vessel interactions in the precautionary area establishes a holistic collision risk index. A case study using AIS data from Ningbo–Zhoushan Port, involving a dataset of 1000 ship encounters, demonstrates the effectiveness of the proposed method. Specifically, the holistic collision risk in the No.2 precautionary area is 0.456, while the No.3 precautionary area shows a risk value of 0.443. These results confirm the effectiveness and feasibility of the proposed method for evaluating and classifying collision risks, offering a more precise and reliable framework for collision risk assessment in complex navigational environments. Full article

(This article belongs to the Section Systems Theory and Methodology)

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29 pages, 444 KiB

Open AccessArticle

Enhancing Greenness and Performance of Agricultural Supply Chains with Nash Bargaining Contract Under Consumer Environmental Awareness

by Guangxing Wei, Xinyue Zhang and Binta Bary

Systems 2025, 13(5), 337; https://doi.org/10.3390/systems13050337 - 1 May 2025

Abstract

To enhance product greenness and operational performance, this study designs a Nash bargaining contract incorporating consumer environmental awareness in an agricultural supply chain consisting of one manufacturer and one retailer. The manufacturer invests in green technologies and the retailer shares partial green costs [...] Read more.

To enhance product greenness and operational performance, this study designs a Nash bargaining contract incorporating consumer environmental awareness in an agricultural supply chain consisting of one manufacturer and one retailer. The manufacturer invests in green technologies and the retailer shares partial green costs to improve greenness and efficiency. Using game theory, theoretical models for competitive scenario without Nash bargaining, local cooperative scenario with given ratio, and global cooperative scenario with Nash bargaining are constructed. Through comparison and sensitivity analysis, the enhancements from Nash bargaining are explored, and the effects of consumer environmental awareness on these enhancements are examined. The findings reveal several key insights. First, the process of bargaining determines the optimal contract ratio, which also depends on the magnitude of price sensitivity, marginal green costs, and consumer environmental awareness. Second, the Nash bargaining contract significantly improves product greenness, increases retail prices, and boosts profits for both the manufacturer and the retailer. Finally, consumer environmental awareness amplifies the effectiveness of the Nash bargaining contract, leading to greener products, higher prices, and greater overall supply chain profits. This research contributes to agricultural supply chain management by providing a theoretically rigorous Nash bargaining mechanism alongside a real-world case study, which harmonizes environmental stewardship and economic viability in agricultural supply chains. The findings offer actionable insights for supply chain managers and policymakers seeking to promote green innovation while maintaining profitability. Full article

(This article belongs to the Section Supply Chain Management)

22 pages, 1133 KiB

Open AccessArticle

Market Entry or Outsourcing? Game Analyzing Coastal Piggybacking Within Horizontal Competition

by Naimeng Liu, Rong Zhang and Bin Liu

Systems 2025, 13(5), 336; https://doi.org/10.3390/systems13050336 - 1 May 2025

Abstract

The shipping industry employs various strategies for outsourcing between freight forwarders and ocean shipping (OS) companies, including consignment and turnkey strategies. Freight forwarders often have a competitive edge in cargo canvassing, but many OS companies still engage in this practice. With China’s new [...] Read more.

The shipping industry employs various strategies for outsourcing between freight forwarders and ocean shipping (OS) companies, including consignment and turnkey strategies. Freight forwarders often have a competitive edge in cargo canvassing, but many OS companies still engage in this practice. With China’s new policy liberalizing coastal shipping rights, OS companies are presented with two coastal shipping tactics: coastal transition and coastal piggyback (CPB). The interaction between OS companies and freight forwarders in the context of this policy change raises important strategic questions. This study examines the coastal piggyback business model within a three-tier shipping supply chain, involving a freight forwarder and two competing OS companies (OS1, which does not qualify for the coastal piggyback policy, and OS2, which does) using game theory. Through game analysis, we find that CPB may represent a myopic equilibrium. Specifically, when the freight forwarder’s cargo-canvassing capability is higher than a certain threshold, CPB is not advantageous for OS2’s market entry. Conversely, if the freight forwarder’s capability is relatively low, both OS companies can benefit from CPB. Additionally, OS companies enter the market when entry costs are low and avoid it when costs are high. With moderate costs, their strategy depends on the other OS company’s actions. Interestingly, the forwarder can deter market entry by enhancing cargo canvassing and adjusting outsourcing tactics. Notably, OS companies’ market entry may boost the forwarder’s payoffs in a horizontally competitive supply chain. Furthermore, this research examines the economic sustainability of coastal piggyback policy by analyzing its impacts on the profitability of all supply chain members. Full article

(This article belongs to the Special Issue Systems Approaches in Sustainable Logistics and Supply Chain Management)

20 pages, 8834 KiB

Open AccessReview

Human Digital Healthcare Engineering for Enhancing the Health and Well-Being of Seafarers and Offshore Workers: A Comprehensive Review

by Meng-Xuan Cui, Kun-Hou He, Fang Wang and Jeom-Kee Paik

Systems 2025, 13(5), 335; https://doi.org/10.3390/systems13050335 - 1 May 2025

Abstract

With over 50,000 merchant vessels and nearly two million seafarers operating globally, more than 12,000 maritime incidents in the past decade underscore the urgent need for proactive safety measures to ensure the structural integrity of aging ships and safeguard the well-being of seafarers, [...] Read more.

With over 50,000 merchant vessels and nearly two million seafarers operating globally, more than 12,000 maritime incidents in the past decade underscore the urgent need for proactive safety measures to ensure the structural integrity of aging ships and safeguard the well-being of seafarers, who face harsh ocean environments in remote locations. The Digital Healthcare Engineering (DHE) framework offers a proactive solution to these challenges, comprising five interconnected modules: (1) real-time monitoring and measurement of health parameters, (2) transmission of collected data to land-based analytics centers, (3) data analytics and simulations leveraging digital twins, (4) AI-driven diagnostics and recommendations for remedial actions, and (5) predictive health analysis for optimal maintenance planning. This paper reviews the core technologies required to implement the DHE framework in real-world settings, with a specific focus on the well-being of seafarers and offshore workers, referred to as Human DHE (HDHE). Key technical challenges are identified, and practical solutions to address these challenges are proposed for each individual module. This paper also outlines future research directions to advance the development of an HDHE system, aiming to enhance the safety, health, and overall well-being of seafarers operating in demanding maritime environments. Full article

(This article belongs to the Special Issue AI-Driven Transportation Systems: Innovations, Challenges, and Future Mobility)

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27 pages, 2096 KiB

Open AccessArticle

How to Ensure System Sustainability: Paradoxical Cognition and Adaptive Strategies for the Value Creation Process of Megaprojects

by Faping Shui, Guangyu Chen, Ruoshui He, Duosi Luo and Xiaolong Wang

Systems 2025, 13(5), 334; https://doi.org/10.3390/systems13050334 - 1 May 2025

Abstract

A megaproject is a complex technological-social-natural system, and its “double-edged sword” effect raises significant attention in research on system sustainability. However, prior studies often overlook the long-term characteristics of megaprojects, while paradox provides an effective lens for explaining their long-term evolution. Guided by [...] Read more.

A megaproject is a complex technological-social-natural system, and its “double-edged sword” effect raises significant attention in research on system sustainability. However, prior studies often overlook the long-term characteristics of megaprojects, while paradox provides an effective lens for explaining their long-term evolution. Guided by a “context-cognition-action” analytical frame, this study employs an inductive and longitudinal case study approach to investigate the value creation process of a typical megaproject, focusing on paradoxical cognition, adaptive strategies, and core drivers of system sustainability. The findings reveal that “macro demand-tension cognition-adaptive governance” is an efficient pathway for value creation under dynamic contexts. Importantly, paradoxical cognition uncovers multi-level tensions (macro, meso, micro) in value creation, with a complex shift from a single layer to a nested structure as macro demands intensify. Correspondingly, adaptive strategies exhibit distinct logic: from reactive strategies to proactive strategies. This shift drives the evolution from the “Project–City–Environment” composite system to the “Project–City–Environment–Region” complex giant system. Furthermore, the evolution of responsibility is the core driver of system sustainability, characterized by a transition from intragenerational equity to intergenerational obligations driven by technological advancements. This study advances theoretical understanding of value creation and provides practical insights into the sustainable development of future megaprojects. Full article

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

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20 pages, 1579 KiB

Open AccessArticle

Artificial Intelligence as a Catalyst for Sustainable Tourism: A Case Study from China

by Dandan Song and Hongwen Chen

Systems 2025, 13(5), 333; https://doi.org/10.3390/systems13050333 - 1 May 2025

Abstract

The tourism industry’s explosive growth has triggered severe carbon emission issues, making enhancing tourism carbon efficiency (TCE) a pressing concern for achieving sustainable tourism development. The widespread application of artificial intelligence (AI) in tourism presents new opportunities. This study applies the Environmental Kuznets [...] Read more.

The tourism industry’s explosive growth has triggered severe carbon emission issues, making enhancing tourism carbon efficiency (TCE) a pressing concern for achieving sustainable tourism development. The widespread application of artificial intelligence (AI) in tourism presents new opportunities. This study applies the Environmental Kuznets Curve (EKC) theory to examine the pathways and mechanisms of AI’s impact on TCE, with a focus on China. The findings reveal that AI significantly enhances TCE, where improvements in tourism labor productivity, the rationalization of the tourism industry structure, and advancements in tourism technology are the key channel mechanisms. Heterogeneity tests indicate that AI substantially boosts TCE in eastern developed regions and areas with deficient tourism resource endowments. Furthermore, AI exhibits significant spatial spillover effects, enhancing both local and neighboring regions’ TCE. These insights provide crucial policy implications for utilizing AI to promote China’s sustainable tourism industry. Full article

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

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18 pages, 576 KiB

Open AccessArticle

Driving Green Transformation in Equipment Manufacturing Enterprises: The Role of Digital Technologies

by Weiyang Xu, Jianzhong Xu and Wei Zhang

Systems 2025, 13(5), 332; https://doi.org/10.3390/systems13050332 - 1 May 2025

Abstract

As digital technologies are increasingly applied in the equipment manufacturing industry, they play an increasingly important role in the green transformation of business development models. Digital technologies have gradually become a key driving force behind the green transformation and development of equipment manufacturing [...] Read more.

As digital technologies are increasingly applied in the equipment manufacturing industry, they play an increasingly important role in the green transformation of business development models. Digital technologies have gradually become a key driving force behind the green transformation and development of equipment manufacturing enterprises. Using empirical data from 2013 to 2022 on publicly listed equipment manufacturing companies in China’s A-share market, this study explores the mechanisms through which digital technologies influence the green transformation of these enterprises. The empirical results show that the application of digital technologies in equipment manufacturing enterprises effectively promotes their green transformation. Mechanism tests reveal that digital technologies contribute to green transformation through channels such as fostering green innovation and optimizing the market environment. The findings provide empirical support for the green transformation of equipment manufacturing enterprises. These companies should further enhance their application of digital technologies, while the government should actively introduce relevant supportive policies to create a favorable market environment, strengthen digital infrastructure, and provide extensive support for the application of digital technologies, thereby promoting the coordinated advancement of digital and green transformations in enterprises. Full article

(This article belongs to the Special Issue Innovation Management and Digitalization of Business Models)

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19 pages, 614 KiB

Open AccessArticle

Empirical Analysis of Hierarchical Pathfinding in Lifelong Multi-Agent Pathfinding with Turns

by László Z. Varga

Systems 2025, 13(5), 331; https://doi.org/10.3390/systems13050331 - 1 May 2025

Abstract

Lifelong multi-agent pathfinding has two interrelated aspects: one is to find conflict-free paths for the agents, and the other is to resolve the conflicts among the agents in the best possible way. We focus on the first aspect by investigating three hierarchical pathfinding [...] Read more.

Lifelong multi-agent pathfinding has two interrelated aspects: one is to find conflict-free paths for the agents, and the other is to resolve the conflicts among the agents in the best possible way. We focus on the first aspect by investigating three hierarchical pathfinding approaches, while we apply the same conflict resolution method. We formally present the three pathfinding options: map reduction using fixed waypoints, map reduction using dynamic waypoints, and the classic grid region-based approach. We point out the problem of emerging conflicts in lifelong multi-agent pathfinding with turns. We describe how we evaluate the proposed solutions to example scenarios from the League of Robot Runners competition, and we formulate the goals of the empirical analysis. Based on the experimental results, we point out the need to find the sweet spot between response time and throughput. Full article

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

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15 pages, 2502 KiB

Open AccessArticle

Fault Detection and Diagnosis in Air-Handling Unit (AHU) Using Improved Hybrid 1D Convolutional Neural Network

by Prince, Byungun Yoon and Prashant Kumar

Systems 2025, 13(5), 330; https://doi.org/10.3390/systems13050330 - 1 May 2025

Abstract

The air-handling unit (AHU) is an essential component of heating, ventilation, and air-conditioning (HVAC) systems. Hence, detecting the faults in AHUs is essential for maintaining continuous HVAC operation and preventing system breakdowns. The advent of artificial intelligence has transformed the AHU fault diagnosis [...] Read more.

The air-handling unit (AHU) is an essential component of heating, ventilation, and air-conditioning (HVAC) systems. Hence, detecting the faults in AHUs is essential for maintaining continuous HVAC operation and preventing system breakdowns. The advent of artificial intelligence has transformed the AHU fault diagnosis techniques. Specifically, deep learning has obviated the necessity for manual feature extraction and selection, thereby streamlining the fault diagnosis process. While conventional convolutional neural networks (CNNs) effectively detect defects, incorporating more spatial variables could enhance their performance further. This paper presents a hybrid architecture combining a CNN model with a long short-term memory (LSTM) model to diagnose the faults in AHUs. The advantages of the LSTM model and convolutional layers are combined to identify significant patterns in the input data, which considerably facilitates the detection of AHU defects. The hybrid design enhances the network’s capability to capture both local and global characteristics, thus improving its ability to differentiate between normal and abnormal circumstances. The proposed approach achieves strong diagnostic accuracy, exhibiting high sensitivity to nuanced fault patterns. Furthermore, its efficacy is corroborated through comparisons with state-of-the-art AHU fault identification techniques. Full article

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

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17 pages, 3527 KiB

Open AccessArticle

Research on the Effectiveness of Driving Simulation Systems in Risky Traffic Environments

by Liang Chen, Jie Fang, Jingyan Li and Jiming Xie

Systems 2025, 13(5), 329; https://doi.org/10.3390/systems13050329 - 29 Apr 2025

Abstract

Conducting research on the effectiveness of driving simulators is of great significance for enhancing the availability of driving simulator systems. However, in risky environments, traditional methods have the limitation of making it difficult to conduct real vehicle experiments. Therefore, this study proposes a [...] Read more.

Conducting research on the effectiveness of driving simulators is of great significance for enhancing the availability of driving simulator systems. However, in risky environments, traditional methods have the limitation of making it difficult to conduct real vehicle experiments. Therefore, this study proposes a method based on driver physiological indicators to evaluate the effectiveness of driving simulators in risky environments. On the one hand, the two-dimensional extended time to collision theoretical model (2D-TTC) was used to calculate the risk degree. Then, the similarity between the risk degree and the drivers’ electrocardiogram (ECG), electromyogram (EMG), and electrodermal activity (EDA) data sequences was calculated based on the dynamic time warping (DTW) model. On the other hand, we used the complexity and sample entropy of ECG and EMG as indicators to assess the drivers’ physiological load. This paper used intersections as risk scenarios to conduct driving simulation experiments to verify the feasibility of the above method. It was found that changes in drivers’ physiological indicators were consistent with changes in risk degree, with the DTW values of risk degree and drivers’ EDA tending to become smaller and the two sequence values closer to being similar. It was also found that the complexity and the sample entropy of the driver’s ECG and EMG showed higher values in the simulated poor sight intersection scenario compared to the intersection with good sight. In addition, in the simulated heavy traffic intersection scenario, physiological parameters such as EMG complexity and sample entropy, as well as ECG complexity, were higher than in the low traffic flow intersection. These findings are highly consistent with the characteristics of physiological responses in real driving environments, fully demonstrating the effectiveness of the test-driving simulation system in simulating risky traffic scenarios. The method proposed in this paper overcomes the limitations of traditional approaches and effectively validates the effectiveness of driving simulation systems in risky environments. The research results can drive further development and application of driving simulation technology. Full article

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

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19 pages, 704 KiB

Open AccessArticle

An AHP-Based Assessment of the Relative Importance of Risk Factors in Project Management: Designing a Bid Preparation Checklist

by Liang-Sheng Hsiao, Chi-Jan Huang, Hsiang-Te Liu and I-Long Lin

Systems 2025, 13(5), 328; https://doi.org/10.3390/systems13050328 - 29 Apr 2025

Abstract

This study primarily aims to evaluate the relative importance of factors influencing project risk management. In particular, we seek to identify and prioritize the key factors affecting the bidding process within the cross-strait political and economic context. This research employs the analytic hierarchy [...] Read more.

This study primarily aims to evaluate the relative importance of factors influencing project risk management. In particular, we seek to identify and prioritize the key factors affecting the bidding process within the cross-strait political and economic context. This research employs the analytic hierarchy process (AHP) to calculate the relative weights of project risk factors. This study conducted AHP questionnaire interviews with 15 experts, including industry professionals, government project management executives with over 15 years of experience, and professors specializing in project risk management. Through pairwise comparisons across three hierarchical levels and twelve factors, this study identified the key influencing factors that account for 70% of the cumulative eigenvector weight. Based on seven key risk factors identified, namely, political factors, lack of professional skills among subcontractors, lack of professional skills among personnel, resident protests, insufficient project duration, insufficient manpower, and lowest bid awarded, a project management bid preparation checklist is developed. Political ideology is identified as the most significant risk factor for contractors. Implementing this checklist can effectively control approximately 70% of the identified risks. Full article

(This article belongs to the Special Issue Risk Management in Project Management—How Two Major Dimensions (Relational and Processual) Influence Risk Management in Project Management)

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26 pages, 2903 KiB

Open AccessArticle

ArchiMate-Based System of Systems Resilience Evaluation Approach

by Huanjun Zhang and Yutaka Matsubara

Systems 2025, 13(5), 327; https://doi.org/10.3390/systems13050327 - 28 Apr 2025

Abstract

The system of systems (SoS) is essential for integrating independent systems to meet increasing service demands. However, its growing complexity leads to disruptions that are difficult to predict and mitigate, making resilience analysis a critical aspect of SoS development. Resilience reflects an SoS’s [...] Read more.

The system of systems (SoS) is essential for integrating independent systems to meet increasing service demands. However, its growing complexity leads to disruptions that are difficult to predict and mitigate, making resilience analysis a critical aspect of SoS development. Resilience reflects an SoS’s ability to absorb and adapt to disruptions, yet its quantitative assessment remains challenging due to diverse stakeholders. To address this, we propose a model-based approach leveraging ArchiMate for SoS visualization and quantitative modeling, combined with a resilience indicator derived from model simulations. This indicator identifies critical constituent systems (CSs) and informs resilient design strategies. Using Mobility as a Service (MaaS) as a case study, we demonstrate how the proposed method can be implemented in a specific SoS. Full article

(This article belongs to the Special Issue System of Systems Engineering)

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23 pages, 8176 KiB

Open AccessArticle

Container Truck High-Risk Events Prediction and Its Influencing Factors Analyses Based on Trajectory Data

by Zhihao Zhu, Yuan Meng and Rongjun Cheng

Systems 2025, 13(5), 326; https://doi.org/10.3390/systems13050326 - 27 Apr 2025

Abstract

With the prosperity of the economy and the continuous expansion of the port area, container trucks have become the main means of transportation on port roads. Traditional traffic flow research mainly focuses on passenger cars. In view of the unique characteristics of container [...] Read more.

With the prosperity of the economy and the continuous expansion of the port area, container trucks have become the main means of transportation on port roads. Traditional traffic flow research mainly focuses on passenger cars. In view of the unique characteristics of container truck traffic flow and the lack of research on conflict-influencing factors for this traffic flow, this paper is committed to filling this research gap. This paper uses drones and YOLOv8 technology to construct a vehicle trajectory dataset in the container truck traffic flow scenario and extracts relevant features of container truck traffic flow from vehicle trajectory data from a macro perspective. For the trajectory data after denoising, the time to collision (TTC) indicator is used to identify conflict events, and then the synthetic minority oversampling technique (SMOTE) is used to obtain four datasets. Machine learning and related classification models are selected for conflict prediction. It is worth noting that the XGBoost model performs better than other models on the four datasets, with an accuracy of 0.86 and an AUC value of 0.933. The Shapley additive explanation (SHAP) theory is used to explain and analyze the model results and compare them with existing studies. The results show that in container truck traffic flow, traffic density is the most important factor affecting conflicts, and conflicts occur more frequently when the traffic density is between 50 and 70 vehicles/km, followed by lane change rate. In contrast, for general traffic flows, studies have shown that speed is the main factor affecting conflicts. Full article

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

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26 pages, 740 KiB

Open AccessArticle

Leveraging Text Mining Techniques for Civil Aviation Service Improvement: Research on Key Topics and Association Rules of Passenger Complaints

by Huali Cai, Tao Dong, Pengpeng Zhou, Duo Li and Hongtao Li

Systems 2025, 13(5), 325; https://doi.org/10.3390/systems13050325 - 27 Apr 2025

Abstract

Airline customers will often complain to the relevant authorities if they encounter an unpleasant flight experience. The specific complaint information can directly reflect the various service problems encountered, so conducting in-depth research on public air transport passenger complaints can reveal important details for [...] Read more.

Airline customers will often complain to the relevant authorities if they encounter an unpleasant flight experience. The specific complaint information can directly reflect the various service problems encountered, so conducting in-depth research on public air transport passenger complaints can reveal important details for improving service. Therefore, by analyzing the passenger complaint data of relevant civil aviation departments in China, we propose a method for identifying key topics of passenger complaints based on text mining. We organically integrate sentiment analysis, topic modeling and association rule mining. A new complaint text analysis framework is constructed, which provides new perspectives and ideas for complaint text analysis and related application fields. First, we calculate the sentiment orientation of the complaint text based on the sentiment dictionary method and filter complaint texts with strong negative sentiment. Then, we compare the two topic modeling methods of LDA (Latent Dirichlet Allocation) and LSA (Latent Semantic Analysis). Finally, we select the better LDA method to extract the main topics hidden in the passenger complaint text with high negative emotional intensity. We use the Apriori algorithm to mine the association rules between the complaint topic words and the service problem classification labels on the complaint text. We use the FP-growth algorithm to mine the association rules between the complaint subject words and the service problem classification labels on the complaint text. By comparing the Apriori algorithm with the FP-growth algorithm, the results of mining the support, confidence and promotion of the association rules show that the Apriori algorithm is more efficient. Finally, we analyze the causes of specific service problems and suggest improvement strategies for airlines and airports. Full article

(This article belongs to the Section Systems Theory and Methodology)

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26 pages, 630 KiB

Open AccessArticle

The Effect of Resource Restructuring on Supply Chain Resilience in the Context of Digital Transformation

by Huayu Long, Huiying Zhang, Tongzhen Wu and Jiarui Han

Systems 2025, 13(5), 324; https://doi.org/10.3390/systems13050324 - 27 Apr 2025

Abstract

In the BANI context, organizations can utilize digital technologies to implement flexible resource allocation strategies to help them address unpredictable situations, which is crucial for enhancing supply chain resilience. However, the existing research lacks an in-depth exploration of the mechanisms underlying supply chain [...] Read more.

In the BANI context, organizations can utilize digital technologies to implement flexible resource allocation strategies to help them address unpredictable situations, which is crucial for enhancing supply chain resilience. However, the existing research lacks an in-depth exploration of the mechanisms underlying supply chain resilience development in the practice of enterprise resource restructuring. Therefore, the purpose of this study is to investigate how companies can enhance supply chain resilience through resource restructuring in the context of digital transformation. Taking Compaks as its research object, this study adopted the exploratory single-case study method. Through open, axial, and selective coding based on the proceduralized grounded theory and following the research logic of “resource orchestration motivation—digital transformation—resource orchestration under digital transformation”, this study comprehensively investigates the improvement of supply chain resilience via enterprise resource restructuring in the context of digital transformation. The results show that (1) resource orchestration motivation includes two dimensions of risk perception, supply-side and demand-side (2) in the context of digital transformation, restructuring supply chain resources (redundant, technological, and internal and external resources) through capability transformation (manufacturing, digital platform, and innovation capability) positively impacts supply chain resilience (both active and passive). This research contributes to the theory of supply chain resilience and provides reference and guidance for traditional enterprise resource orchestration and optimizing supply chain resilience. Full article

(This article belongs to the Special Issue Emerging Technologies in Supply Chain Management: Enhancing Traceability, Efficiency, Resilience, and Sustainability)

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26 pages, 14005 KiB

Open AccessArticle

Unveiling the Technological Dynamics of Banking Systems: A Network Analysis of Chinese and Global Banking Innovation

by Chuhan Zhang and Xiuting Li

Systems 2025, 13(5), 323; https://doi.org/10.3390/systems13050323 - 27 Apr 2025

Abstract

Utilizing nearly 80,000 patent records and over 540,000 patent references from within China’s banking industry, spanning from 2000 to July 2021, this paper employs network analysis and the main path method to examine the technological evolution of both Chinese and global banks. The [...] Read more.

Utilizing nearly 80,000 patent records and over 540,000 patent references from within China’s banking industry, spanning from 2000 to July 2021, this paper employs network analysis and the main path method to examine the technological evolution of both Chinese and global banks. The contributions of this study encompass the comprehensive collection of 21 years of patent data, the introduction of a distinctive analytical framework for networks, and addressing a research gap in Chinese banking innovation. The research delves into the sources of innovation of China’s banking industry, maps its development, and identifies cutting-edge technologies of the global banking system, with a specific emphasis on the burgeoning role of blockchain. Additionally, this paper presents a valuable list of recent global patents identified by the main path algorithm, serving as a valuable reference for governments and regulatory bodies worldwide. Full article

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

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