Systems

23 pages, 1212 KiB

Open AccessArticle

Mapping the Complex Systems That Connects the Urban Environment to Cognitive Decline in Older Adults: A Group Model Building Study

by Ione Avila-Palencia, Leandro Garcia, Claire Cleland, Bernadette McGuinness, Joanna Mchugh Power, Amy Jayne McKnight, Conor Meehan and Ruth F. Hunter

Systems 2025, 13(7), 606; https://doi.org/10.3390/systems13070606 - 18 Jul 2025

Abstract

This study aimed to develop a Causal Loop Diagram (CLD) to visualise how urban environment factors impact dementia and cognitive decline, and potential causal mechanisms. In Group Model Building workshops with 12 researchers, a CLD was created to identify factors contributing to cognitive [...] Read more.

This study aimed to develop a Causal Loop Diagram (CLD) to visualise how urban environment factors impact dementia and cognitive decline, and potential causal mechanisms. In Group Model Building workshops with 12 researchers, a CLD was created to identify factors contributing to cognitive decline, and the dynamic interrelationships between these factors. The factors were classified in nine main themes: urban design, social environment, travel behaviours, urban design by-products, lifestyle, mental health conditions, disease/physiology, brain physiology, and cognitive decline outcomes. Five selected feedback loops illustrated some dynamics in the system. The workshops helped develop a shared language and understanding of different perspectives from an interdisciplinary team. The CLD creation was part of a comprehensive modelling approach based on experts’ knowledge which informed other research outputs such as an evidence gap map and an umbrella review, helped the identification of environmental variables for future studies and analyses, and helped to identify future possible systems-based interventions to prevent cognitive decline. The study highlights the utility of CLDs and Group Model Building workshops in interdisciplinary research projects investigating complex systems. Full article

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

11 pages, 274 KiB

Open AccessEssay

Connecting the Dots: Applying Network Theories to Enhance Integrated Paramedic Care for People Who Use Drugs

by Jennifer L. Bolster, Polly Ford-Jones, Elizabeth A. Donnelly and Alan M. Batt

Systems 2025, 13(7), 605; https://doi.org/10.3390/systems13070605 - 18 Jul 2025

Abstract

The evolving role of paramedics presents a unique opportunity to enhance care for people who use drugs, a population disproportionately affected by systemic barriers and inequities. In fragmented healthcare systems, paramedics are well-positioned to improve access through initiatives such as social prescribing and [...] Read more.

The evolving role of paramedics presents a unique opportunity to enhance care for people who use drugs, a population disproportionately affected by systemic barriers and inequities. In fragmented healthcare systems, paramedics are well-positioned to improve access through initiatives such as social prescribing and harm reduction. This theory-driven commentary explores how Network Theory and Actor Network Theory provide valuable theoretical underpinnings to conceptualize and strengthen the integration of paramedics into care networks. By emphasizing the centrality of paramedics and their connections with both human and non-human actors, these theories illuminate the relational dynamics that influence effective care delivery. We argue that leveraging paramedics’ positionality can address gaps in system navigation, improve patient outcomes, and inform policy reforms. Future work should examine the roles of other key actors, strengthen paramedic advocacy, and identify strategies to overcome barriers to care for people who use drugs. Full article

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

21 pages, 588 KiB

Open AccessArticle

Systemic Configurations of Functional Talent for Green Technological Innovation: A Fuzzy-Set QCA Study

by Mingjie Guo, Menghan Yan, Xin Yan and Yi Li

Systems 2025, 13(7), 604; https://doi.org/10.3390/systems13070604 - 18 Jul 2025

Abstract

Achieving high-level green technological innovation in heavily polluting enterprises is critical for advancing sustainable development, particularly in the context of both organizational and regional digitalization. This study adopts a configurational perspective grounded in the Technology–Organization–Environment (TOE) framework and integrates theoretical insights from resource [...] Read more.

Achieving high-level green technological innovation in heavily polluting enterprises is critical for advancing sustainable development, particularly in the context of both organizational and regional digitalization. This study adopts a configurational perspective grounded in the Technology–Organization–Environment (TOE) framework and integrates theoretical insights from resource orchestration, resource dependence, and IT capability theories. It investigates how different types of skilled talent, such as production, technical, sales, and managerial employees, contribute to green innovation under varying digital conditions. By applying fuzzy-set qualitative comparative analysis (fsQCA) to a sample of 96 publicly listed firms from China’s heavily polluting industries, this study identifies four distinct talent-based configurations that can lead to high levels of green innovation: production-centric, management-led, technical talent driven, and regionally enabled models. Each configuration reflects a specific system state in which a core group of skilled employees plays a leading role, supported by complementary functions, and shaped by the interaction between internal digital transformation and the external digital environment. This study contributes to the systems literature by elucidating the combinational roles of digital resources and talent deployment within the systemic TOE framework, and offers practical guidance for enterprises aiming to strategically utilize human capital to enhance green innovation performance amid ongoing digital transformations. Full article

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25 pages, 980 KiB

Open AccessArticle

System Factors Shaping Digital Economy Sustainability in Developing Nations

by Qigan Shao, Zhaoqin Lu, Xinlu Lin, Canfeng Chen and James J. J. H. Liou

Systems 2025, 13(7), 603; https://doi.org/10.3390/systems13070603 - 17 Jul 2025

Abstract

The gradual recovery of the economy has positioned the digital economy as a vital force driving global economic growth. However, the sustainability of this emerging economic sector is being tested by unexpected systemic shocks. There is a scarcity of research on the factors [...] Read more.

The gradual recovery of the economy has positioned the digital economy as a vital force driving global economic growth. However, the sustainability of this emerging economic sector is being tested by unexpected systemic shocks. There is a scarcity of research on the factors influencing the sustainable development of the digital economy. Therefore, developing a framework to assess the sustainability of the digital economy is significant. Building on previous research, this study established an evaluation system that extracts key indicators across four dimensions: society, the economy, the environment, and technology. Data were then collected through questionnaires and in-depth interviews with experts. Subsequently, this study employed the fuzzy Decision-Making Trial and Evaluation Laboratory–Analytical Network Process (fuzzy DANP) method to determine the weight of each indicator and used the Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) method to evaluate the sustainability of the digital economy in three cities. Sensitivity analysis was conducted to validate this comprehensive evaluation method. The results indicate that society and the economy are the two most crucial dimensions, while the regional economic development level, enterprise innovation culture, and digital divide are the top three indicators affecting the sustainable development of the digital economy industry. This work suggests that the digital economy industry should enhance regional economic levels, strengthen technological and innovative corporate cultures, and narrow the digital divide to achieve the goal of sustainable development in the digital economy sector. Full article

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

23 pages, 4086 KiB

Open AccessArticle

The County–Township–Village Station Location-Routing Problem for the Integration of Passenger and Freight Transport by Urban–Rural Buses

by Xiaoting Shang, Jiaqi Sun, Xin Cheng and Hao Sun

Systems 2025, 13(7), 602; https://doi.org/10.3390/systems13070602 - 17 Jul 2025

Abstract

The integration of passenger and freight transport by urban–rural buses is an effective approach to address two critical issues: the inefficiency of parcel delivery services and the financial struggles of public transport operators. This paper studies the county–township–village station location-routing problem for the [...] Read more.

The integration of passenger and freight transport by urban–rural buses is an effective approach to address two critical issues: the inefficiency of parcel delivery services and the financial struggles of public transport operators. This paper studies the county–township–village station location-routing problem for the integration of passenger and freight transport by urban–rural buses, aiming to develop an efficient transport network by establishing rational stations and designing optimal operation routes. A three-level county–township–village station network is proposed for the integration of passenger and freight transport, and a mixed-integer linear programming model is developed, including the constraints of location, allocation, capacity, and routing. A comprehensive series of numerical experiments is conducted on a randomly generated dataset to evaluate the feasibility and advantages of the proposed model. Lastly, key managerial insights are discussed. Full article

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21 pages, 831 KiB

Open AccessArticle

Exploring Carbon Emission Reduction Pathways: Analysis of Energy Conservation Potential in Yangtze River Economic Belt

by Weiping Cui, Rongjia Song and Zhen Li

Systems 2025, 13(7), 601; https://doi.org/10.3390/systems13070601 - 17 Jul 2025

Abstract

In response to the escalating global energy demands, the optimization of energy efficiency has emerged as a linchpin for sustainable development. This study considers the potential of energy conservation and emission reduction in one of the most economically vibrant and resource-intensive regions in [...] Read more.

In response to the escalating global energy demands, the optimization of energy efficiency has emerged as a linchpin for sustainable development. This study considers the potential of energy conservation and emission reduction in one of the most economically vibrant and resource-intensive regions in China, the Yangtze River Economic Belt, encompassing 11 provinces and cities. The SBM-Undesirable model is used to measure the energy efficiency and analyze the temporal-spatial distribution. Moran’s I is employed to analyze the overall spatial pattern and local regional differences in energy efficiency. The systematic analysis shows that the temporal fluctuation exists in the development of energy efficiency, and the average of the Yangtze River Economic Belt exhibits a development pattern of “downstream > midstream > upstream” from the spatial perspective. The upstream region would require way more effort than others to decarbonize and improve efficiency. At the municipal level, the overall energy efficiency of 11 provinces and cities fails to reach an efficient state, and potential for improvement exists. Moreover, the potential model of energy conservation and emission reduction is constructed. We further explore the pathways of energy efficiency improvement for each region in the Yangtze River Economic Belt, including pathways of “High-Efficiency Type”, “High Emission Reduction Potential”, and “Extensive Development Type”. Full article

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

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16 pages, 995 KiB

Open AccessArticle

An Upper Partial Moment Framework for Pathfinding Problem Under Travel Time Uncertainty

by Xu Zhang and Mei Chen

Systems 2025, 13(7), 600; https://doi.org/10.3390/systems13070600 - 17 Jul 2025

Abstract

Route planning under uncertain traffic conditions requires accounting for not only expected travel times but also the risk of late arrivals. This study proposes a mean-upper partial moment (MUPM) framework for pathfinding that explicitly considers travel time unreliability. The framework incorporates a benchmark [...] Read more.

Route planning under uncertain traffic conditions requires accounting for not only expected travel times but also the risk of late arrivals. This study proposes a mean-upper partial moment (MUPM) framework for pathfinding that explicitly considers travel time unreliability. The framework incorporates a benchmark travel time to measure the upper partial moment (UPM), capturing both the probability and severity of delays. By adjusting a risk parameter (

θ

), the model reflects different traveler risk preferences and unifies several existing reliability measures, including on-time arrival probability, late arrival penalty, and semi-variance. A bi-objective model is formulated to simultaneously minimize mean travel time and UPM. Theoretical analysis shows that the MUPM framework is consistent with the expected utility theory (EUT) and stochastic dominance theory (SDT), providing a behavioral foundation for the model. To efficiently solve the model, an SDT-based label-correcting algorithm is adapted, with a pre-screening step to reduce unnecessary pairwise path comparisons. Numerical experiments using GPS probe vehicle data from Louisville, Kentucky, USA, demonstrate that varying

θ

values lead to different non-dominated paths. Lower

θ

values emphasize frequent small delays but may overlook excessive delays, while higher

θ

values effectively capture the tail risk, aligning with the behavior of risk-averse travelers. The MUPM framework provides a flexible, behaviorally grounded, and computationally scalable approach to pathfinding under uncertainty. It holds strong potential for applications in traveler information systems, transportation planning, and network resilience analysis. Full article

(This article belongs to the Special Issue Data-Driven Urban Mobility Modeling)

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26 pages, 3347 KiB

Open AccessArticle

Identifying Critical Risks in Low-Carbon Innovation Network Ecosystem: Interdependent Structure and Propagation Dynamics

by Ruguo Fan, Yang Qi, Yitong Wang and Rongkai Chen

Systems 2025, 13(7), 599; https://doi.org/10.3390/systems13070599 - 17 Jul 2025

Abstract

Global low-carbon innovation networks face increasing vulnerabilities amid growing geopolitical tensions and technological competition. The interdependent structure of low-carbon innovation networks and the risk propagation dynamics within them remain poorly understood. This study investigates vulnerability patterns by constructing a two-layer interdependent network model [...] Read more.

Global low-carbon innovation networks face increasing vulnerabilities amid growing geopolitical tensions and technological competition. The interdependent structure of low-carbon innovation networks and the risk propagation dynamics within them remain poorly understood. This study investigates vulnerability patterns by constructing a two-layer interdependent network model based on Chinese low-carbon patent data, comprising a low-carbon collaboration network of innovation entities and a low-carbon knowledge network of technological components. Applying dynamic shock propagation modeling, we analyze how risks spread within and between network layers under various shocks. Our findings reveal significant differences in vulnerability distribution: the knowledge network consistently demonstrates greater susceptibility to cascading failures than the collaboration network, reaching complete system failure, while the latter maintains partial resilience, with resilience levels stabilizing at approximately 0.64. Critical node analysis identifies State Grid Corporation as a vulnerability point in the collaboration network, while multiple critical knowledge elements can independently trigger system-wide failures. Cross-network propagation follows distinct patterns, with knowledge-network failures consistently preceding collaboration network disruptions. In addition, propagation from the collaboration network to the knowledge network showed sharp transitions at specific threshold values, while propagation in the reverse direction displayed more gradual responses. These insights suggest tailored resilience strategies, including policy decentralization approaches, ensuring technological redundancy across critical knowledge domains and strengthening cross-network coordination mechanisms to enhance low-carbon innovation system stability. Full article

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

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15 pages, 2186 KiB

Open AccessArticle

Supply Chain Design Method for Introducing Floating Offshore Wind Turbines Using Network Optimization Model

by Taiga Mitsuyuki, Takahiro Shimozawa, Itsuki Mizokami and Shinnosuke Wanaka

Systems 2025, 13(7), 598; https://doi.org/10.3390/systems13070598 - 17 Jul 2025

Abstract

This paper presents a method to model and optimize the supply chain processes for floating offshore wind turbines using a network model based on Generalized Multi-Commodity Network Flows (GMCNF). The proposed method represents production bases, base ports, installation sites, component transfer areas, and [...] Read more.

This paper presents a method to model and optimize the supply chain processes for floating offshore wind turbines using a network model based on Generalized Multi-Commodity Network Flows (GMCNF). The proposed method represents production bases, base ports, installation sites, component transfer areas, and transportation routes as nodes and arcs within the network. The installation process is modeled using three transport concepts: assembling components at the base port, direct assembly and installation at the installation site, and transferring components to the installation vessel at a nearby port. These processes are expressed as a linear network model, with the objective function set to minimize total transportation and assembly costs. The optimal transportation network is derived by solving the network problem while incorporating constraints such as supply, demand, and transportation capacity. Case studies demonstrate the method’s effectiveness in optimizing the supply chain and evaluating potential new production site locations for floating foundations, considering overall supply chain optimization. Full article

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35 pages, 2924 KiB

Open AccessArticle

A Monitoring System for Measuring the Cognitive Cycle via a Continuous Reaction Time Task

by Teodor Ukov, Georgi Tsochev and Radoslav Yoshinov

Systems 2025, 13(7), 597; https://doi.org/10.3390/systems13070597 - 17 Jul 2025

Abstract

The cognitive cycle has been studied via cognitive architectures and by analyzing cognitive experiments. An emerging theoretical approach suggests that several automatic cognitive processes retrieve information, making it available to an internal agent, which in turn decides which information to access. Derived from [...] Read more.

The cognitive cycle has been studied via cognitive architectures and by analyzing cognitive experiments. An emerging theoretical approach suggests that several automatic cognitive processes retrieve information, making it available to an internal agent, which in turn decides which information to access. Derived from this view, four phases of the cognitive cycle can be formulated and reproduced within a cognitive monitoring system. This exploratory work presents a new theory, Attention as Internal Action, and proposes a hypothesis about the relationship between an iteration of the cognitive cycle and a conscious motor action. The design of a continuous reaction time task is presented as a tool for quick cognitive evaluation. Via continuously provided user responses, the computational system behind the task adapts triggering stimuli based on the suggested hypothesis. Its software implementation was employed to assess whether a previously conducted simulation of the cognitive cycle’s time range aligned with empirical data. A control group was assigned to perform a separate simple reaction time task in a sequence of five days. The analysis showed that the experimental cognitive monitoring system produced results more closely aligned with the established understanding of the timing of the cognitive cycle than the control task did. Full article

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45 pages, 9147 KiB

Open AccessArticle

Decision Analysis Data Model for Digital Engineering Decision Management

by Gregory S. Parnell, C. Robert Kenley, Devon Clark, Jared Smith, Frank Salvatore, Chiemeke Nwobodo and Sheena Davis

Systems 2025, 13(7), 596; https://doi.org/10.3390/systems13070596 - 17 Jul 2025

Abstract

Decision management is the systems engineering life cycle process for making program/system decisions. The purpose of the decision management process is: “…to provide a structured, analytical framework for objectively identifying, characterizing and evaluating a set of alternatives for a decision at any point [...] Read more.

Decision management is the systems engineering life cycle process for making program/system decisions. The purpose of the decision management process is: “…to provide a structured, analytical framework for objectively identifying, characterizing and evaluating a set of alternatives for a decision at any point in the life cycle and select the most beneficial course of action”. Systems engineers and systems analysts need to inform decisions in a digital engineering environment. This paper describes a Decision Analysis Data Model (DADM) developed in model-based systems engineering software to provide the process, methods, models, and data to support decision management. DADM can support digital engineering for waterfall, spiral, and agile development processes. This paper describes the decision management processes and provides the definition of the data elements. DADM is based on ISO/IEC/IEEE 15288, the INCOSE SE Handbook, the SE Body of Knowledge, the Data Management Body of Knowledge, systems engineering textbooks, and journal articles. The DADM was developed to establish a decision management process and data definitions that organizations and programs can tailor for their system life cycles and processes. The DADM can also be used to assess organizational processes and decision quality. Full article

(This article belongs to the Special Issue Digital and Data-Driven Systems Engineering: Bridging Theory and Practice)

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36 pages, 3524 KiB

Open AccessReview

Building Information Modeling and Big Data in Sustainable Building Management: Research Developments and Thematic Trends via Data Visualization Analysis

by Zhen Liu, Langyue Deng, Fenghong Wang, Wei Xiong, Tzuhui Wu, Peter Demian and Mohamed Osmani

Systems 2025, 13(7), 595; https://doi.org/10.3390/systems13070595 - 16 Jul 2025

Abstract

At present, the construction industry has not yet fully optimized the integration of the potential of big data. Past studies signaled the potential benefits of integrating building information management (BIM) and big data in the field of sustainable building management (SBM). However, these [...] Read more.

At present, the construction industry has not yet fully optimized the integration of the potential of big data. Past studies signaled the potential benefits of integrating building information management (BIM) and big data in the field of sustainable building management (SBM). However, these studies have a monotonous perspective in identifying the development of BIM and big data applications in SBM. Therefore, this paper aims to explore BIM and big data from various perspectives in the field of SBM to identify the aspects where additional efforts are required and provide insights into future directions, and it adopts a mixed method of quantitative and qualitative analysis, including bibliometric analysis and knowledge mapping, providing a macro-overview of the research status and development trends of BIM and big data integration for SBM from multiple bibliometric perspectives. The results indicate the following: (1) the current studies on BIM and big data integration (BBi)-aided SBM mainly focused on data integration and interoperability for collaboration, development of information technologies and emerging technologies, data analysis and presentation, and green building and sustainability assessment; (2) the longitudinal analysis of three time-slice phases (2010–2014, 2015–2018, and 2019–2024) over the past 15 years indicates that the studies on BBi-aided SBM have been expanded from the application of BIM in construction projects to the integration and interoperability of BIM with information technology, the integration of virtual models with physical buildings, and sustainable management throughout the building life cycle stages; and (3) key research gaps and emerging directions include data integration and model interoperability across the building life cycle, model transferability in the application of technology, and a comprehensive sustainability assessment framework based on the whole building life cycle stages. Full article

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

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25 pages, 864 KiB

Open AccessArticle

Effect of Network Structure on Conflict and Project Value Creation

by Cong Liu, Yuan Shan and Jiming Cao

Systems 2025, 13(7), 594; https://doi.org/10.3390/systems13070594 - 16 Jul 2025

Abstract

This study explored the impact of network structure on conflict and project value creation. Network density and network centrality are two network structure dimensions. A survey was undertaken among professionals working in Chinese construction projects. A total of 308 surveys were analyzed using [...] Read more.

This study explored the impact of network structure on conflict and project value creation. Network density and network centrality are two network structure dimensions. A survey was undertaken among professionals working in Chinese construction projects. A total of 308 surveys were analyzed using the structural equation model. The results revealed that network centrality has a negative impact on project value creation while network density has a positive impact. Network centrality has a negative impact on substantive conflicts but a positive impact on affective conflicts. The link between centrality and project value creation is weakened by substantive conflict but strengthened by affective conflict. This research gives a new direction for construction project governance and project value management. Furthermore, this research validates the constructive role of substantive conflicts, as well as the destructive impact of affective conflicts, thereby adding to the literature on conflict governance. Full article

(This article belongs to the Topic Data Science and Intelligent Management)

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25 pages, 4626 KiB

Open AccessArticle

Study on Evolution Mechanism of Agricultural Trade Network of RCEP Countries—Complex System Analysis Based on the TERGM Model

by Shasha Ding, Li Wang and Qianchen Zhou

Systems 2025, 13(7), 593; https://doi.org/10.3390/systems13070593 - 16 Jul 2025

Abstract

The agricultural products trade network is essentially a complex adaptive system formed by nonlinear interactions between countries. Based on the complex system theory, this study reveals the dynamic self-organization law of the RCEP regional agricultural products trade network by using the panel data [...] Read more.

The agricultural products trade network is essentially a complex adaptive system formed by nonlinear interactions between countries. Based on the complex system theory, this study reveals the dynamic self-organization law of the RCEP regional agricultural products trade network by using the panel data of RCEP agricultural products export trade from 2000 to 2023, combining social network analysis (SNA) and the temporal exponential random graph model (TERGM). The results show the following: (1) The RCEP agricultural products trade network presents a “core-edge” hierarchical structure, with China as the core hub to drive regional resource integration and ASEAN countries developing into secondary core nodes to deepen collaborative dependence. (2) The “China-ASEAN-Japan-Korea “riangle trade structure is formed under the RCEP framework, and the network has the characteristics of a “small world”. The leading mode of South–South trade promotes the regional economic order to shift from the traditional vertical division of labor to multiple coordination. (3) The evolution of trade network system is driven by multiple factors: endogenous reciprocity and network expansion are the core structural driving forces; synergistic optimization of supply and demand matching between economic and financial development to promote system upgrading; geographical proximity and cultural convergence effectively reduce transaction costs and enhance system connectivity, but geographical distance is still the key system constraint that restricts the integration of marginal countries. This study provides a systematic and scientific analytical framework for understanding the resilience mechanism and structural evolution of regional agricultural trade networks under global shocks. Full article

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

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23 pages, 1572 KiB

Open AccessArticle

A Systems Analysis of Reverse Channel Dynamics and Government Subsidies in Sustainable Remanufacturing

by Ting Ji, Shaofeng Wang and Xiufen Liu

Systems 2025, 13(7), 592; https://doi.org/10.3390/systems13070592 - 16 Jul 2025

Abstract

Remanufacturing in reverse logistics can not only support sustainable development but also provide a tractable way to achieve carbon neutrality. This study evaluates whether an original equipment manufacturer (OEM) should remanufacture outsource or authorize this reverse channel activity in the presence of government [...] Read more.

Remanufacturing in reverse logistics can not only support sustainable development but also provide a tractable way to achieve carbon neutrality. This study evaluates whether an original equipment manufacturer (OEM) should remanufacture outsource or authorize this reverse channel activity in the presence of government subsidies. Additionally, the model considers the equilibrium acquisition quantities, collection rates, prices, and effects of government subsidy under three reverse channel options: centralizing remanufacturing, outsourcing remanufacturing, and authorization remanufacturing. The analysis indicates that (i) a centralized approach with manufacturing and remanufacturing operations under a fixed government subsidy is always in the interest of the supply chain; (ii) that for the profit-maximizing third-party remanufacturer (3PR), the differentials in variable collection costs drive the strategy choice, and that a higher fixed scaling parameter of the collection cost favors outsourcing; and (iii) when the government aspires to reduce environmental effects and subsidy payments, the OEM and government have different reverse channel choice preferences. Surprisingly, profitability and environmental goals align under a high consumer acceptance of the remanufactured product. This paper extends the understanding of the remanufacturing strategy of an OEM and provides new insights on which reverse channel is optimal. Full article

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

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18 pages, 1583 KiB

Open AccessArticle

Developing a Dynamic Simulation Model for Point-of-Care Ultrasound Assessment and Learning Curve Analysis

by Sandra Usaquén-Perilla, Laura Valentina Bocanegra-Villegas and Jose Isidro García-Melo

Systems 2025, 13(7), 591; https://doi.org/10.3390/systems13070591 - 16 Jul 2025

Abstract

The development of new diagnostic technologies is accelerating, and budgetary constraints in the health sector necessitate a systematic decision-making process to acquire emerging technologies. Health Technology Assessment methodologies integrate technology, clinical efficacy, patient safety, and organizational and financial factors in this context. However, [...] Read more.

The development of new diagnostic technologies is accelerating, and budgetary constraints in the health sector necessitate a systematic decision-making process to acquire emerging technologies. Health Technology Assessment methodologies integrate technology, clinical efficacy, patient safety, and organizational and financial factors in this context. However, these methodologies do not include the learning curve, a critical factor in operator-dependent technologies. This study presents an evaluation model incorporating the learning curve, developed from the domains of the AdHopHTA project. Using System Dynamics (SD), the model was validated and calibrated as a case study to evaluate the use of Point-of-Care Ultrasound (POCUS) in identifying dengue. This approach allowed for the analysis of the impact of the learning curve and patient demand on the revenues and costs of the healthcare system and the cost–benefit indicator associated with dengue detection. The model assesses physician competency and how different training strategies and frequencies of use affect POCUS adoption. The findings underscore the importance of integrating the learning curve into decision-making. This study highlights the need for further investigation into the barriers that limit the effective use of POCUS, particularly in resource-limited settings. It proposes a framework to improve the integration of this technology into clinical practice for early dengue detection. Full article

(This article belongs to the Special Issue System Dynamics Modeling and Simulation for Public Health)

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31 pages, 2314 KiB

Open AccessArticle

Green and Low-Carbon Strategy of Logistics Enterprises Under “Dual Carbon”: A Tripartite Evolutionary Game Simulation

by Liping Wang, Zhonghao Ye, Tongtong Lei, Kaiyue Liu and Chuang Li

Systems 2025, 13(7), 590; https://doi.org/10.3390/systems13070590 - 15 Jul 2025

Abstract

In the low-carbon era, there is a serious challenge of climate change, which urgently needs to promote low-carbon consumption behavior in order to build sustainable low-carbon consumption patterns. The establishment of this model not only requires in-depth theoretical research as support, but also [...] Read more.

In the low-carbon era, there is a serious challenge of climate change, which urgently needs to promote low-carbon consumption behavior in order to build sustainable low-carbon consumption patterns. The establishment of this model not only requires in-depth theoretical research as support, but also requires tripartite cooperation between the government, enterprises and the public to jointly promote the popularization and practice of the low-carbon consumption concept. Therefore, by constructing a tripartite evolutionary game model and simulation analysis, this study deeply discusses the mechanism of government policy on the strategy choice of logistics enterprises. The stability strategy and satisfying conditions are deeply analyzed by constructing a tripartite evolutionary game model of the logistics industry, government, and consumers. With the help of MATLAB R2023b simulation analysis, the following key conclusions are drawn: (1) The strategic choice of logistics enterprises is affected by various government policies, including research and development intensity, construction intensity, and punishment intensity. These government policies and measures guide logistics enterprises toward low-carbon development. (2) The government’s research, development, and punishment intensity are vital in determining whether logistics enterprises adopt low-carbon strategies. R&D efforts incentivize logistics companies to adopt low-carbon technologies by driving technological innovation and reducing costs. The penalties include economic sanctions to restrain companies that do not comply with low-carbon standards. In contrast, construction intensity mainly affects the consumption behavior of consumers and then indirectly affects the strategic choice of logistics enterprises through market demand. (3) Although the government’s active supervision is a necessary guarantee for logistics enterprises to implement low-carbon strategies, more is needed. This means that in addition to the government’s policy support, it also needs the active efforts of the logistics enterprises themselves and the improvement of the market mechanism to promote the low-carbon development of the logistics industry jointly. This study quantifies the impact of different factors on the system’s evolution, providing a precise decision-making basis for policymakers and helping promote the logistics industry’s and consumers’ low-carbon transition. It also provides theoretical support for the logistics industry’s low-carbon development and green low-carbon consumption and essential guidance for sustainable development. Full article

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

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29 pages, 4762 KiB

Open AccessArticle

Evaluating Housing Policies for Migrants: A System Dynamics Approach to Rental and Purchase Decisions in China

by Yi Jiang, Jiahao Guo, Chen Geng, Xiuting Li and Jichang Dong

Systems 2025, 13(7), 589; https://doi.org/10.3390/systems13070589 - 15 Jul 2025

Abstract

This study investigates the evaluation of housing policies for migrants in China, focusing on the interplay between rental and purchase decisions under the rent-and-purchase policy (RPP) framework. Employing a system dynamics model, we simulate migrant housing choices from 2001 to 2023 and forecast [...] Read more.

This study investigates the evaluation of housing policies for migrants in China, focusing on the interplay between rental and purchase decisions under the rent-and-purchase policy (RPP) framework. Employing a system dynamics model, we simulate migrant housing choices from 2001 to 2023 and forecast market trends from 2024 to 2030. The results indicate that RPPs significantly improve housing quality and reduce costs for migrants by mitigating institutional disparities and market distortions. Scenario analyses demonstrate that a coordinated approach combining supply-side interventions (e.g., affordable housing expansion) with rights-based policies (e.g., equalizing renter and buyer rights) effectively balances affordability and demand stability. The findings emphasize the critical role of addressing rights inequalities and advocate for a holistic policy framework to tackle migrant housing challenges, offering actionable insights for policymakers in system science and urban planning. Full article

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

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23 pages, 4081 KiB

Open AccessArticle

Continuous Behavioral Biometric Authentication for Secure Metaverse Workspaces in Digital Environments

by Giluk Kang, Jihoon Park and Young-Gab Kim

Systems 2025, 13(7), 588; https://doi.org/10.3390/systems13070588 - 15 Jul 2025

Abstract

As many companies adopted hybrid work arrangements during and after the COVID-19 outbreak, interest in Metaverse applications for virtual offices grew considerably. Along with this growing interest, the risk of data breaches has also increased, as virtual offices often handle confidential documents for [...] Read more.

As many companies adopted hybrid work arrangements during and after the COVID-19 outbreak, interest in Metaverse applications for virtual offices grew considerably. Along with this growing interest, the risk of data breaches has also increased, as virtual offices often handle confidential documents for businesses. For this reason, existing studies have explored Metaverse user authentication methods; however, their methods suffer from several limitations, such as the need for additional sensors and one-time authentication. Therefore, this paper proposes a novel behavioral authentication framework for secure Metaverse workspaces. The proposed framework adopts keyboard typing behavior that is common in the office and does not cause fatigue to users as an authentication factor to afford active and continuous user authentication. Based on our evaluation, the user identification accuracy achieved an average of approximately 95% among 11 of 15 participants, with the highest-performing user reaching an accuracy of 99.77%. In addition, the proposed framework achieved an average false acceptance rate of 0.41% and a false rejection rate of 4.02%. It was also evaluated with existing studies using requirements for user authentication in the Metaverse to demonstrate its strengths. Therefore, this framework can fully ensure a secure Metaverse office by preventing unauthenticated users. Full article

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

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