Systems

20 pages, 5296 KiB

Open AccessArticle

Vit-Traj: A Spatial–Temporal Coupling Vehicle Trajectory Prediction Model Based on Vision Transformer

by Rongjun Cheng, Xudong An and Yuanzi Xu

Systems 2025, 13(3), 147; https://doi.org/10.3390/systems13030147 - 21 Feb 2025

Accurately predicting the future trajectory of road users around autonomous vehicles is crucial for path planning and collision avoidance. In recent years, data-driven vehicle trajectory prediction models have become a significant research focus, and various spatial–temporal neural network models, based on spatial–temporal data, [...] Read more.

Accurately predicting the future trajectory of road users around autonomous vehicles is crucial for path planning and collision avoidance. In recent years, data-driven vehicle trajectory prediction models have become a significant research focus, and various spatial–temporal neural network models, based on spatial–temporal data, have been proposed. However, some existing spatial–temporal models segregate time and space, neglecting the inherent coupling of time and space. To address this issue, an end-to-end spatial–temporal feature fusion model, based on the Vision Transformer (Vit), is proposed in this paper, which can couple stereoscopic features of diverse spatial regions and time periods. Specifically, we propose an end-to-end spatiotemporal feature coupling model based on visual Transformer, Vit-Traj, which extracts spatiotemporal features through 2D convolution and uses Vit and SENet to complete feature fusion. Experimental results on the NGSIM and HighD datasets indicate that, compared to State-of-the-Art models, the proposed model exhibits better performance. The root mean squared error (RMSE) is 2.72 m on the NGSIM dataset and 0.86 m on the HighD dataset when the prediction horizon is 5 s. Furthermore, ablation experiments are conducted to evaluate the performance of each module, affirming the efficacy of ViT in modeling spatial–temporal data. Full article

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

24 pages, 1235 KiB

Open AccessArticle

Patent Openness Decisions and Investment Propensities of Frontier Enterprises in Asymmetric Competition

by Chen Liu, Daiqing Yan, Zihao Song, Gandang Shi, Wentao Zhan and Minghui Jiang

Systems 2025, 13(3), 146; https://doi.org/10.3390/systems13030146 - 21 Feb 2025

Abstract

The patent openness decisions of frontier enterprises and the consequent investment tendencies of laggard enterprises play a significant role in their profitability. Despite the benefits resulting from directly using open patents, in order to capture market share and surpass frontier enterprises, laggard enterprises [...] Read more.

The patent openness decisions of frontier enterprises and the consequent investment tendencies of laggard enterprises play a significant role in their profitability. Despite the benefits resulting from directly using open patents, in order to capture market share and surpass frontier enterprises, laggard enterprises must decide whether they are going to invest in R&D or expansion. In this context, based on evolutionary game theory and the operational behaviors of both frontier and laggard enterprises, this study constructed a model of enterprise revenue under asymmetric competition, exploring the impact of patent openness with and without government subsidies on enterprise revenue. This study discovered that: (1) when the industry scale is small, frontier enterprises gain significant social effects through patent openness, while laggard enterprises invest in expansion; (2) as the industry scale gradually expands, frontier enterprises tend to prefer not to open their patents, and laggard enterprises gradually shift from imitation to independent innovation when the return on R&D investment increases more than that on expansion investment; and (3) when the R&D costs of laggard enterprises are high, frontier enterprises usually choose not to open their patents, forcing laggard enterprises to turn to investment in expansion. This allows frontier enterprises to reduce the losses from patent openness while enjoying the benefits of reduced industry production costs. This study provides new perspectives on patent openness and investment tendencies with the help of an evolutionary game mechanism and offers managerial policy recommendations. Full article

(This article belongs to the Special Issue Decision Making in Uncertain Environments via Advanced Analytical Methods)

26 pages, 2428 KiB

Open AccessArticle

Digital Finance, Digital Usage Divide, and Urban–Rural Income Gap: Evidence from China

by Yanfei Xiao, Mengli Yin, Huilin Wang and Yunbo Xiang

Systems 2025, 13(3), 145; https://doi.org/10.3390/systems13030145 - 21 Feb 2025

Abstract

Digital finance can reduce the urban–rural income gap, but the digital divide may limit this effect. This study develops a theoretical framework to explore the interactions between digital finance, the digital usage gap, and income disparity. Using data from 274 Chinese cities, the [...] Read more.

Digital finance can reduce the urban–rural income gap, but the digital divide may limit this effect. This study develops a theoretical framework to explore the interactions between digital finance, the digital usage gap, and income disparity. Using data from 274 Chinese cities, the research applies a two-way fixed-effects and threshold effect model. The results indicate that disparities in digital usage not only diminish but may also distort the convergence benefits of digital finance, producing a U-shaped relationship that exhibits variability across dimensions and regions. Additionally, traditional financial systems appear to moderate this U-shaped pattern by delaying the point at which digital finance begins to widen the urban–rural income gap. However, the extent of this alleviation is influenced by the digital usage is divisive. Once digital technology adoption exceeds a threshold, the negative effect becomes positive, narrowing the urban–rural income gap. Consequently, policy initiatives should prioritize improving financial conditions in rural areas, accelerating the digital transformation of conventional finance, bolstering digital education in rural regions, and addressing the disparities in digital usage. Full article

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

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35 pages, 1054 KiB

Open AccessArticle

AI Product Factors and Pro-Environmental Behavior: An Integrated Model with Hybrid Analytical Approaches

by Chi-Horng Liao

Systems 2025, 13(3), 144; https://doi.org/10.3390/systems13030144 - 21 Feb 2025

Abstract

Based on three theories—the Technology Acceptance Model (TAM), the Unified Theory of Acceptance and Use of Technology (UTAUT), and Responsible Environmental Behavior (REB)—the present study proposes a model of AI product factors and pro-environmental behavior. This study aims to investigate AI product factors [...] Read more.

Based on three theories—the Technology Acceptance Model (TAM), the Unified Theory of Acceptance and Use of Technology (UTAUT), and Responsible Environmental Behavior (REB)—the present study proposes a model of AI product factors and pro-environmental behavior. This study aims to investigate AI product factors that promote pro-environmental behavior by examining behavioral intentions to use AI technology. Unlike previous research, which predominantly focused on external variables such as social norms, cost, and inconvenience, or individual variables like demographic and psychological factors, this study emphasizes the underexplored role of technological factors. It integrates the Fuzzy Decision-Making Trial and Evaluation Laboratory (F-DEMATEL), Structural Equation Modeling (SEM), and Artificial Neural Network (ANN) approaches to assess the relationships among constructs. For the F-DEMATEL, opinions were collected from 20 experts in the environmental field, while SEM and ANN data were gathered from 1726 participants in Taiwan. F-DEMATEL results demonstrated causal relationships between external factors (perceived trust, self-efficacy, and perceived awareness) and the main variables of the TAM. Likewise, SEM results revealed that perceived trust (PT), self-efficacy (SE), and perceived awareness (PA) influence the main variables of TAM. However, the direct relationships between PT and behavioral intention (BI) and PA and BI were not significant. PT and PA indirectly influence BI through perceived usefulness (PU) and perceived ease of use (PEOU). The results also established that BI positively influences pro-environmental behavior. The author has also outlined how stakeholders aiming to encourage sustainable environmental behaviors can utilize the study’s findings to protect the environment. Full article

27 pages, 4426 KiB

Open AccessArticle

Conceptual Modeling for Understanding and Communicating Complexity During Human Systems Integration in Manned–Unmanned Systems: A Case Study

by Tommy Langen, Kristin Falk and Gerrit Muller

Systems 2025, 13(3), 143; https://doi.org/10.3390/systems13030143 - 21 Feb 2025

Abstract

Informal soft system methodologies hold a significant role in developing complex systems. They bridge system knowledge and sensemaking among heterogeneous stakeholders. This article investigates the application of conceptual models to support such communication and understanding among transdisciplinary stakeholders, ensuring the translation of customer [...] Read more.

Informal soft system methodologies hold a significant role in developing complex systems. They bridge system knowledge and sensemaking among heterogeneous stakeholders. This article investigates the application of conceptual models to support such communication and understanding among transdisciplinary stakeholders, ensuring the translation of customer requirements and needs into suitable engineered systems. This article presents a case study incorporating observations, interviews, and a review of conceptual models utilized by an aerospace and defense case company for the development of future Manned–Unmanned Systems. It explores how practitioners employ conceptual modeling to support the Human Systems Integration (HSI) aspects of technological, organizational, and human elements of Manned–Unmanned Teaming (MUM-T) systems. The results indicate that practitioners utilize a mix of informal and formal types of conceptual models when developing Human Systems Integration aspects of the system. Formal models, such as sequence diagrams, requirement overviews, and functional flow models, are applied when addressing technology-focused aspects. Organization-centered modeling leverages representations like stakeholder maps and swimlane diagrams, while people-centered aspects rely more on informal techniques such as storytelling and user personas. The findings suggest a potential underestimation by practitioners of the value of quantification in conceptual modeling for Manned–Unmanned Systems development. This study highlights the important role that conceptual modeling methods play, particularly focusing on the informal aspects. These methods are instrumental in enhancing effective communication and understanding among transdisciplinary stakeholders. Furthermore, they facilitate mutual understanding, which is essential for fostering collaboration and shared vision in the development of complex systems. This facilitates deeper insights and reasoning into HSI for MUM-T applications. Full article

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

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Conceptual modeling framework: An Illustration of five key aspects. These aspects, labeled from (a) to (e), include conceptual models, the purpose, key drivers and qualities, multi-level abstraction, and the knowledge pyramid. Full article ">Figure 2
Review of models represented in aerospace and defense case studies investigating HSI in MUM-T applications. Full article ">Figure 3
Abstract–formality diagram [<a href="#B26-systems-13-00143" class="html-bibr">26</a>]: Showing the classification of conceptual model types, divided into eight sections (A–H) according to their degree of formality (horizontal axis) and level of abstraction (vertical axis). Full article ">Figure 4
Raw data of the survey mapping of the TOP from one participant. The colors blue, yellow, and pink represent T, O, and P, respectively. (The red circle indicates the participant’s preferred degree of abstraction and formality in their modeling practice). Full article ">Figure 5
Results from the survey indicate the number of individuals who used the various conceptual models for the CAFCR and TOP views, respectively. (For CAFCR max = 3 individuals, while for TOP max = 5 individuals). Full article ">Figure 6
Illustration of Storytelling and Visual ConOps from the case study observation and exploration. Full article ">Figure 7
Percentage of respondents and articles mentioning the various models (x-axis), as derived from the case company and literature review, respectively. Full article ">

35 pages, 9453 KiB

Open AccessArticle

A Two-Layer Causal Knowledge Network Construction Method Based on Quality Problem-Solving Data

by Yubin Wang, Shirong Qiang, Xin Yue, Tao Li and Keyong Zhang

Systems 2025, 13(3), 142; https://doi.org/10.3390/systems13030142 - 20 Feb 2025

Abstract

“Cause analysis” constitutes an indispensable component in quality management systems, serving to systematically identify the causes of quality defects, thereby enabling the development of targeted improvement strategies that concurrently address surface-level manifestations and fundamental drivers. However, relying solely on personal experience makes it [...] Read more.

“Cause analysis” constitutes an indispensable component in quality management systems, serving to systematically identify the causes of quality defects, thereby enabling the development of targeted improvement strategies that concurrently address surface-level manifestations and fundamental drivers. However, relying solely on personal experience makes it challenging to conduct a comprehensive and in-depth analysis of quality problems. The reason is that, when analyzing the causes of quality problems, it is essential not only to consider the specific context in which the problems occur. This enables “specific problems” to be “specifically analyzed” for the formulation of temporary containment measures. Additionally, the context of the problem needs to be stripped. This allows for a general and in-depth analysis of the “class problem” or the causal linkages underlying the problem, thereby determining the root cause of the problem and formulating a corresponding long-term program. The analysis of the causes of quality problems exhibits “duality” characteristics. Based on this, this study proposes and constructs a two-layer causal knowledge network by leveraging the causal knowledge generated and applied in the process of quality problem solving to address the “duality” characteristic of the cause analysis of quality problems. The proposed network can assist front-line employees in analyzing the quality problems of products from diverse perspectives and overcome the challenge of relying solely on personal experience to comprehensively and profoundly analyze the causal relationships of quality problems. Our method not only contributes to enhancing the efficiency of quality problem solving but also makes a valuable contribution to the advancement of theories and methods related to quality management and knowledge management. Full article

(This article belongs to the Special Issue Data-Driven Methods in Business Process Management)

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21 pages, 4715 KiB

Open AccessArticle

Development of a Functional and Logical Reference System Architecture in Automotive Engineering

by Jonas Krog, Caner Akbas, Bastian Nolte and Thomas Vietor

Systems 2025, 13(3), 141; https://doi.org/10.3390/systems13030141 - 20 Feb 2025

Abstract

The automobile is evolving from a mechanically dominated to a cyber-physical, software-defined system. Future complex functionalities, such as autonomous driving, require multidisciplinary, interconnected systems. Hence, interdisciplinary architecture development based on Systems Engineering principles becomes essential, leading to a methodology for vehicle system architecture [...] Read more.

The automobile is evolving from a mechanically dominated to a cyber-physical, software-defined system. Future complex functionalities, such as autonomous driving, require multidisciplinary, interconnected systems. Hence, interdisciplinary architecture development based on Systems Engineering principles becomes essential, leading to a methodology for vehicle system architecture with the RFLP-Framework. For its application in the automotive industry, building upon the established mechanical and electronical platform approaches, the methodology incorporates the concept of a Reference System Architecture. This is defined as a basic architecture that sets out the common architectural specifications to support the efficient and systemic interdisciplinary architecture development across multiple projects. Its corresponding characteristics and quality criteria are defined and the understanding of the functional and logical reference architecture view, based on the RFLP-Framework, is described. Based on this understanding, an exemplary functional and logical Reference System Architecture for passenger vehicles is proposed. Its methodical user-oriented and knowledge-based development within the scientific circumstances is discussed and concluded. Full article

(This article belongs to the Section Systems Engineering)

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14 pages, 698 KiB

Open AccessArticle

Barriers to Leveraging Valuable Health Data for Collaborative Patient Care: How Will We Integrate Family Health Histories?

by Laura Hays, Jordan Weaver, Matthew Gauger, Nickie Buckner, Brett Bailey, Ashley Stone and Lori A. Orlando

Systems 2025, 13(3), 140; https://doi.org/10.3390/systems13030140 - 20 Feb 2025

Abstract

We sought to incorporate a community-based solution with a family health history (FHH) clinical support program (MeTree) integrated into well-patient appointments with the novel partnership of a public health state-level health information exchange (HIE). The Arkansas—Making History pilot project tested informatics compatibility among [...] Read more.

We sought to incorporate a community-based solution with a family health history (FHH) clinical support program (MeTree) integrated into well-patient appointments with the novel partnership of a public health state-level health information exchange (HIE). The Arkansas—Making History pilot project tested informatics compatibility among these systems and the patients’ electronic medical record (EPIC) in a rural clinic in the north central region of the state, having the state HIE as a means for patients to store and share their FHHs across multiple healthcare providers with updates in real time. We monitored for unexpected issues during the pilot and asked for the perspectives of patients and healthcare providers throughout the project to have a clear understanding of how to implement this project on a larger scale. The greatest barrier to project implementation was the inability of the state HIE to host or share the FHH data. We compensated for the lack of systems compatibility and documented valuable information about patient acceptability and usability of the MeTree platform, as well as gleaning important clinical outcome data from those who completed MeTree FHH accounts in an underserved area. Rural patients need additional technological support in the larger scaling of this project, both in available linkages to community clinics with patient-controlled options for how their data is stored and shared and in Internet connectivity and software options available for ease of use. Full article

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

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25 pages, 359 KiB

Open AccessArticle

Strategic Alignment of Technological Innovation for Sustainable Development: Efficiency Evaluation and Spatial Analysis in China’s Advanced Manufacturing Industry

by Zhenghan Chen, Quan Zhang, Tianzhen Tang and Mingran Deng

Systems 2025, 13(3), 139; https://doi.org/10.3390/systems13030139 - 20 Feb 2025

Abstract

Technological innovation is essential to promoting sustainable development in emerging economies as it drives regional coordination and industry upgrading. In order to address the understudied connection between regional coordination and industrial structural transformation, this study examines the spatial dynamics of technological innovation efficiency [...] Read more.

Technological innovation is essential to promoting sustainable development in emerging economies as it drives regional coordination and industry upgrading. In order to address the understudied connection between regional coordination and industrial structural transformation, this study examines the spatial dynamics of technological innovation efficiency (TIE) in China’s advanced manufacturing industry (AMI) along the Yangtze River Economic Belt (YREB) from 2007 to 2022. Through a Data Envelopment Analysis (DEA) and Spatial Durbin Model (SDM), we systematically evaluated TIE patterns using panel data from 11 provinces. Our empirical analysis reveals three key findings. (1) The temporal distribution of TIE in AMI in the YREB showed an annual increasing trend. The spatial distribution characteristics showed a gradient distribution disparity between the eastern, central, and western regions, but the regional gap of TIE in AMI is gradually closing. (2) Through the examination of Moran’s I, the spatial spillover effect of TIE in AMI was observed, that is, the TIE is spreading from high-performance provinces to other regions, suggesting that interregional collaboration and knowledge exchange may be beneficial. (3) According to the factor identification study, the main factors affecting the spatial distribution of TIE in AMI are industrialization, human capital, and innovation capability. Interestingly, the effects of information technology and economic progress are not statistically significant, suggesting that cautious government actions are required. By optimizing technological innovation processes and spatial arrangements, this study adds to the expanding body of knowledge on the spatial aspects of technological innovation and provides valuable insights for policymakers looking to enhance global competitiveness and foster sustainable economic growth in the AMI. The findings advance our knowledge of how to support sustainable economic development in emerging nations by highlighting the critical role that innovation and technology management play in removing regional development obstacles and encouraging the modernization of industrial structures. Full article

(This article belongs to the Special Issue Research and Practices in Technological Innovation Management Systems)

21 pages, 5171 KiB

Open AccessArticle

A “C³-TOPSIS-Pareto” Based Model for Identifying Critical Nodes in Complex Networks

by Ziqiang Zeng, Weiye Zhang and Hongling Jin

Systems 2025, 13(2), 138; https://doi.org/10.3390/systems13020138 - 19 Feb 2025

Abstract

This study addresses the critical challenge of identifying key nodes in complex networks, an essential task for optimizing network stability, efficiency, and resilience. Traditional approaches often rely on single-dimensional metrics, which may fail to fully capture the multifaceted roles that nodes play in [...] Read more.

This study addresses the critical challenge of identifying key nodes in complex networks, an essential task for optimizing network stability, efficiency, and resilience. Traditional approaches often rely on single-dimensional metrics, which may fail to fully capture the multifaceted roles that nodes play in maintaining network functionality. To overcome this limitation, a novel framework was proposed, integrating the C³ dimensions (Cohesion, Connectivity, Conciseness) with the TOPSIS method and Pareto dominated set (PDS) to enable a comprehensive, multi-dimensional evaluation of node importance. The method introduces an optimized parameter α for relative conciseness, validated through area-under-curve (AUC) minimization, ensuring adaptability across diverse networks. Scalability analysis demonstrates its feasibility for large-scale systems, with computational complexity managed through approximation algorithms. The method was applied to eight real-world networks including transportation systems, power grids, and social networks. Results demonstrated that the PDS-based STS method outperformed traditional centrality measures, such as degree centrality and betweenness centrality, particularly during the early stages of network degradation. The framework effectively identified critical nodes in highly connected systems, with the conciseness metric proving instrumental in highlighting irreplaceable nodes whose removal would severely disrupt network functionality. This study concludes that the “C³-TOPSIS-Pareto” based model provides a more accurate and robust approach for critical node identification, offering a reliable tool for enhancing network design and resilience, particularly in systems with complex interdependencies. Limitations in fragmented networks are discussed, with future directions proposed for dynamic weight adaptation and functional dynamics integration. Full article

(This article belongs to the Section Complex Systems and Cybernetics)

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28 pages, 16929 KiB

Open AccessArticle

Spatial–Temporal Coupling and Interactive Effects of Reclaimed Water Usage Efficiency and High-Quality Development of the Financial Sector

by Ying Zhou, Fengping Wu, Gen Li and Chen Feng

Systems 2025, 13(2), 137; https://doi.org/10.3390/systems13020137 - 19 Feb 2025

Abstract

In China, the current policy of the financial sector on water conservation and management is being vigorously pursued; therefore, efficient synergy between the two systems is of great significance. In this study, the coupling and coordination degree (CCD) between reclaimed water usage efficiency [...] Read more.

In China, the current policy of the financial sector on water conservation and management is being vigorously pursued; therefore, efficient synergy between the two systems is of great significance. In this study, the coupling and coordination degree (CCD) between reclaimed water usage efficiency (RWUE) and high-quality development of the financial sector (HQDFS) was assessed using a coupling coordination model with panel data from 27 provinces in China during 2010–2021, and a more in-depth coupling and coordination relationship (CCR) was carried out using a spatiotemporal evolution methodology and PVAR model. The results of this study show the following: (1) CCD exhibits a continuous upward trajectory. At the end of the study period, the eastern, central, western, and northeastern regions moved to the primary coordination level. (2) The eastern and northeastern regions show an increasing trend in absolute differences and polarization. Meanwhile, the central region experiences a gradual rise in polarization. (3) The elliptical plot of the CCD’s standard deviation tends toward a circular shape with a positive aspect ratio. An expanding trend of absolute differences and polarization is observed in the eastern and northeastern regions. (4) The PVAR results show that the two systems can promote each other in the early stages and have a negative impact in the later stages. This study provides policy recommendations for a balanced development of the two systems and the formulation of regional development strategies based on the state of coupling and coordination between the two. Full article

(This article belongs to the Special Issue Data Analytics for Social, Economic and Environmental Issues)

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9 pages, 246 KiB

Open AccessOpinion

The Systemic Unity in Mathematics and Science: Beyond Techno-Science Myths

by Giuseppe Longo

Systems 2025, 13(2), 136; https://doi.org/10.3390/systems13020136 - 19 Feb 2025

Abstract

Dualistic views in mathematics and natural sciences are severely reducing the scope of science. It began by claiming, more than one century ago, that, in mathematical theories, “a formal list of signs“ (the axioms and rules of inference, independent from meaning) could allow [...] Read more.

Dualistic views in mathematics and natural sciences are severely reducing the scope of science. It began by claiming, more than one century ago, that, in mathematical theories, “a formal list of signs“ (the axioms and rules of inference, independent from meaning) could allow one to consistently and completely deduce all “true” theorems. It continues today by claiming that “we can control evolution by re-writing the instructions of life written in the four signs of DNA” or mimicking completely human cognition in “sequences of 0 and 1s”, independently of our biological body and brain and their historicity. The damages of and the alternatives to these views will be briefly hinted. Full article

(This article belongs to the Special Issue Theoretical Issues on Systems Science)

23 pages, 4600 KiB

Open AccessArticle

Bridging the Gender Gap in Climate-Resilient Sweet Potato Farming: A Case Study from Goromonzi District, Zimbabwe

by Jean-Claude Baraka Munyaka, Olivier Gallay, Jérôme Chenal, Edward Mutandwa, Ximena Salgado, Tariro Pindayi, Davison Gondo, Herbert Pfuma, Rumbidzai Mhembere, Tinotenda Tamanikwa and Shawn Chipise

Systems 2025, 13(2), 135; https://doi.org/10.3390/systems13020135 - 19 Feb 2025

Abstract

This study delves into the gender-specific challenges and opportunities in sweet potato farming in Goromonzi District, Zimbabwe, against the backdrop of escalating droughts. Through a blend of surveys, expert analysis, and high-resolution satellite imagery, the research uncovers critical factors shaping sweet potato production—ranging [...] Read more.

This study delves into the gender-specific challenges and opportunities in sweet potato farming in Goromonzi District, Zimbabwe, against the backdrop of escalating droughts. Through a blend of surveys, expert analysis, and high-resolution satellite imagery, the research uncovers critical factors shaping sweet potato production—ranging from land access and cultivation techniques to harvesting and market dynamics. By leveraging the multi-Criteria Decision-Making (MCDM) framework, the study evaluates these factors’ importance and presents innovative, gender-inclusive strategies to foster climate resilience. Remote sensing tools map the severity of droughts, while data analysis reveals the interconnected challenges faced by farmers. The findings spotlight the urgent need for equitable resource access and support systems to empower both female farmers, paving the way for sustainable agriculture in an era of climate uncertainty. Full article

(This article belongs to the Special Issue Multi-criteria Decision Making in Supply Chain Management)

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28 pages, 566 KiB

Open AccessArticle

The Effect of Human Resource Analytics on Organizational Performance: Insights from Ethiopia

by Shimelis Adugna Tessema, Shuai Yang and Chiyin Chen

Systems 2025, 13(2), 134; https://doi.org/10.3390/systems13020134 - 18 Feb 2025

Abstract

Strategic human resource management plays a crucial role in fostering long-term organizational performance through data-driven decision-making. Human Resource Analytics (HRA), using advanced business intelligence and integrated reporting tools, provides insights that optimize decision-making and strategy alignment. Despite its potential, the impact of HRA [...] Read more.

Strategic human resource management plays a crucial role in fostering long-term organizational performance through data-driven decision-making. Human Resource Analytics (HRA), using advanced business intelligence and integrated reporting tools, provides insights that optimize decision-making and strategy alignment. Despite its potential, the impact of HRA on organizational performance remains insufficiently explored. This study addresses this gap by examining the effects of HRA on organizational performance in Ethiopian organizations. A quantitative research design was employed, utilizing a survey method to collect data from 269 valid responses across 55 organizations in Addis Ababa, Ethiopia. Structural Equation Modeling (SEM) via SmartPLS 3.0 software was used for data analysis. The findings reveal that HRA significantly enhances organizational performance, with this relationship mediated by strategic alignment between HR and organizational goals. Additionally, firm size was found to moderate the impact of HRA on performance, with larger firms deriving greater benefits. The results suggest that HRA serves as a powerful driver of enhanced organizational performance, with larger firms potentially reaping even greater benefits from its implementation. These results also underscore the importance of strategic alignment in leveraging HRA for improved performance, particularly in the context of Ethiopian organizations, where HRA adoption is still evolving. This study offers practical implications for organizations seeking to enhance workforce management and performance through data-driven HR strategies. Full article

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

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23 pages, 6735 KiB

Open AccessArticle

Passenger Flow Simulation of Airport Terminal Subway Station Based on System Dynamics

by Wei Chen and Yi Ai

Systems 2025, 13(2), 133; https://doi.org/10.3390/systems13020133 - 18 Feb 2025

Abstract

Grasping the effective carrying capacity of airport hub subway stations in real-time serves as the foundation for enhancing the safety assurance capability of the hub. Starting from the perspectives of multiple subsystems, including people, stations, and trains, and combining passenger flow, system structure, [...] Read more.

Grasping the effective carrying capacity of airport hub subway stations in real-time serves as the foundation for enhancing the safety assurance capability of the hub. Starting from the perspectives of multiple subsystems, including people, stations, and trains, and combining passenger flow, system structure, and multiple attributes of trains, a system dynamics (SD) model for passenger travel in airport hub subway stations is established. The model is simulated using Vensim PLE 5.9d to analyze the effective carrying capacity of the transfer system under the existing configuration and layout of transfer facilities and equipment in the hub. The model features a modular architecture and interface, enabling quick and easy model establishment, and adapts to various configurations and operational characteristics of airport hub subway stations in a user-friendly manner. Multiple sensitivity simulation analysis experiments are designed to analyze changes in passenger flow density from multiple perspectives. This method can calculate the effective carrying capacity of airport hub subway stations, providing a scientific basis for planning, construction, and operational management. The effectiveness of the model is verified by analyzing the Pudong International Airport terminal subway station. Full article

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

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20 pages, 4433 KiB

Open AccessArticle

Evaluating Spatial Allocation of Resilient Medical Facilities in Megacities: A Case Study of Shanghai, China

by Peng Gao, Yuchen He and Xinyue Zhang

Systems 2025, 13(2), 132; https://doi.org/10.3390/systems13020132 - 18 Feb 2025

Abstract

In response to public health emergencies, the importance of resilient medical facilities—such as large exhibition centers and sports venues that can be rapidly converted into temporary emergency hospitals—has become increasingly evident. This study focuses on these potential medical resources within megacities, using Shanghai [...] Read more.

In response to public health emergencies, the importance of resilient medical facilities—such as large exhibition centers and sports venues that can be rapidly converted into temporary emergency hospitals—has become increasingly evident. This study focuses on these potential medical resources within megacities, using Shanghai as a case study. Employing advanced analytical tools including the kernel density two-step floating catchment area method, Lorenz curves, and Gini coefficient, we systematically evaluated the spatial allocation of 36 resilient medical facilities in Shanghai. The findings indicate that Shanghai’s resilient medical facilities ensure 4.5 emergency beds per thousand residents, with large exhibition centers and sports venues demonstrating exceptional conversion capabilities far surpassing those of ordinary public venues. However, the study also uncovers significant disparities in spatial allocation: these facilities are predominantly concentrated in the city center, leading to notable deficiencies in accessibility and equity for suburban areas. The opportunity for residents to access emergency medical services decreases progressively from the city center outward, a trend consistent across various travel time scenarios. The calculated Gini coefficient underscores an extremely uneven spatial configuration of resilient medical facilities, well beyond the warning threshold, suggesting substantial service disparities between different regions during emergencies, which poses potential risks to public health. Our research provides valuable insights for megacities aiming to more effectively address future public health challenges and enhance societal resilience. Full article

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

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37 pages, 4287 KiB

Open AccessArticle

An AI-Based Decision Support System Utilizing Bayesian Networks for Judicial Decision-Making

by Zlatan Morić, Vedran Dakić and Siniša Urošev

Systems 2025, 13(2), 131; https://doi.org/10.3390/systems13020131 - 17 Feb 2025

Abstract

Judicial decision-making in continental law systems requires carefully evaluating complex, interdependent evidence while ensuring consistency and fairness. This study investigates the application of Bayesian networks in structuring legal evidence within an AI-based decision support system. The primary research objective is to assess the [...] Read more.

Judicial decision-making in continental law systems requires carefully evaluating complex, interdependent evidence while ensuring consistency and fairness. This study investigates the application of Bayesian networks in structuring legal evidence within an AI-based decision support system. The primary research objective is to assess the enhancement of transparency, minimization of cognitive overload, and reduced bias in judicial processes through probabilistic reasoning. The proposed system dynamically updates outcome probabilities as new evidence is introduced, enabling real-time monitoring of case likelihoods. AI-generated recommendations are aligned with judicial precedents by integrating Conditional Probability Tables (CPTs) and historical case data in this adaptive approach. The interpretability and effectiveness of Bayesian inference in legal decision support are analyzed methodologically, emphasizing its capacity to refine probability distributions in response to evolving courtroom inputs. The findings address a key research gap by demonstrating how structured AI-driven heuristics can supplement judicial reasoning while maintaining decision accountability and transparency. The system is suggested to enhance consistency and fairness in legal judgments while preserving judicial autonomy. This study contributes to the growing intersection of AI and legal decision-making, with an emphasis placed on the role of machine learning in supporting judicial heuristics while maintaining procedural integrity. Full article

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

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34 pages, 15713 KiB

Open AccessArticle

Evolutional Game Analysis of Quality Regulation of a Blockchain Platform for Emergency Material Security in Emergencies Based on Prospect Theory

by Xiaoliang Long, Liqi Lan, Wenjing Ma and Li Xiong

Systems 2025, 13(2), 130; https://doi.org/10.3390/systems13020130 - 17 Feb 2025

Abstract

To enhance the security and supervision of emergency materials from their source to transport, thus preventing safety incidents, a tripartite evolution model integrating the government, material production enterprises, and logistics entities is proposed. This model, situated within the framework of a government-established blockchain [...] Read more.

To enhance the security and supervision of emergency materials from their source to transport, thus preventing safety incidents, a tripartite evolution model integrating the government, material production enterprises, and logistics entities is proposed. This model, situated within the framework of a government-established blockchain platform, combines evolutionary game theory and prospect theory. It examines the strategy evolution of emergency material’s security subjects amid diverse government reward punishment measures and enterprise risk perceptions. Our findings indicate that employing dynamic reward–punishment measures not only conserves government regulatory resources but also incentivizes enterprises to enhance the quality of emergency materials security. This dynamic approach effectively encourages responsible behavior, averting rebellious tendencies or speculative mindsets in enterprises with deviating risk perceptions regarding emergency materials security. Full article

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

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27 pages, 908 KiB

Open AccessArticle

Social Identification in Open Innovation Projects: Role of Knowledge Collaboration and Resource Interdependence

by Shaoze Fang and Yanjun Qin

Systems 2025, 13(2), 129; https://doi.org/10.3390/systems13020129 - 17 Feb 2025

Abstract

In open innovation projects (OIPs), project members from different participating organizations often have dual social identifications, namely, project identification and organizational identification. While such dual identifications may align or conflict in shaping collaborative behaviors, their micro-level psychological mechanisms and performance implications remain underexplored, [...] Read more.

In open innovation projects (OIPs), project members from different participating organizations often have dual social identifications, namely, project identification and organizational identification. While such dual identifications may align or conflict in shaping collaborative behaviors, their micro-level psychological mechanisms and performance implications remain underexplored, as prior research predominantly adopts a firm-centric perspective. This study examines how dual social identifications affect OIP performance. The investigation considers mediating role of knowledge collaboration and the moderating role of resource interdependence. Data were collected through a questionnaire survey targeting the OIPs in major high-tech industrial development zones in China. The results show that project identification drives participating organizations to collaborate deeply (e.g., sharing core expertise) and broadly (e.g., involving diverse partners), both of which boost OIP performance. By contrast, organizational identification prioritizes expanding collaboration breadth over deep collaboration, which risks superficial engagement. Too many partners initially help but eventually harm OIP performance, whereas deeper collaboration consistently improves OIP performance. In addition, resource interdependence strengthens the positive effects of project identification on breadth and depth of knowledge collaboration but does little for organizational identification. This study extends social identity theory to the open innovation field and offers novel insights into practices of social psychological reality in OIPs, revealing how dual identifications interact with resource interdependence to shape OIP performance. Additionally, it offers actionable strategies for balancing knowledge collaboration breadth and depth while leveraging resource interdependence in OIP governance. Full article

(This article belongs to the Special Issue Research and Practices in Technological Innovation Management Systems)

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