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Volume 12
Issue 9
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Systems, Volume 12, Issue 9 (September 2024) – 66 articles

Cover Story (view full-size image): The growing relevance of Socio-Ecological Systems (SESs) thinking reflects both the challenges of an anthropogenic poly crisis and attempts to understand the complexities of societal development in an era of globalisation. The article develops a variant of SESs thinking through a review of the literature on ‘Learning Ecologies’ to assess the strengths and limitations of this human ecological approach. Perceived limitations are addressed by developing a Social Ecosystem Model (SEM), which adds a ‘political economy and ecology’ dimension to the learning ecologies concept. The expanded human ecosystem model is then applied to an analysis of learning and skills in the English context, in support of an inclusive and place-based approach to vocational education and training. View this paper
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23 pages, 579 KiB  
Article
Prioritizing Factors to Foster Improvement of Sales Operations in Small- and Medium-Sized Industrial Organizations
by Luis A. Vásquez-Ruiz, Juan E. Núñez-Ríos and Jacqueline Y. Sánchez-García
Systems 2024, 12(9), 383; https://doi.org/10.3390/systems12090383 - 23 Sep 2024
Viewed by 918
Abstract
Small- and medium-sized companies depend heavily on their internal configuration to achieve their goals, generate profit, and remain competitive. The performance of the sales department is often crucial for this. Decision-makers need to understand how to coordinate the sales force’s operations while considering [...] Read more.
Small- and medium-sized companies depend heavily on their internal configuration to achieve their goals, generate profit, and remain competitive. The performance of the sales department is often crucial for this. Decision-makers need to understand how to coordinate the sales force’s operations while considering team members’ communication and commitment. This article presents an approach to prioritize factors that will improve the operations of the sales department in small- and medium-sized companies in the industrial sector. To achieve this, we adopted the soft modeling approach by (1) outlining a conceptual model that identifies the factors that can lead to improvements based on the literature and (2) using the analytical hierarchy process to validate a construct and prioritize the factors. This study is focused on the organizational domain and involves the participation of sixty employees from medium-sized Mexican companies with at least five years of experience. The results indicate that the factors that foster improvement in sales department operations are communication improvement, failure prevention, workload alignment, and adequate integration of human efforts with technology without neglecting coordination and management mechanisms. This article could encourage academics and practitioners to adopt the soft modeling approach to adopt new courses of action based on continuous learning and improve organizational cohesion. Full article
(This article belongs to the Special Issue The Systems Thinking Approach to Strategic Management)
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17 pages, 3772 KiB  
Article
A Methodological Framework for New Product Development in Fuzzy Environments
by Chun-Ming Yang, Shiyao Li, Kuen-Suan Chen, Mingyuan Li and Wei Lo
Systems 2024, 12(9), 382; https://doi.org/10.3390/systems12090382 - 22 Sep 2024
Cited by 2 | Viewed by 987
Abstract
New product development (NPD) is crucial for helping companies to maintain competitive advantages. In this study, a methodological framework is presented combining a novel Kano model and fuzzy axiomatic design (FAD) for improving the product development capability in the whole NPD process. In [...] Read more.
New product development (NPD) is crucial for helping companies to maintain competitive advantages. In this study, a methodological framework is presented combining a novel Kano model and fuzzy axiomatic design (FAD) for improving the product development capability in the whole NPD process. In the Kano model, a novel mixed-class classification method is presented to classify each evaluation indicator agreed on by the majority, and to calculate the affiliation value based on category strength (CS) to display the degree to which the indicator belongs to a certain attribute. A new importance ratio is also proposed to adjust the importance of each indicator attribute. This helps to achieve higher customer satisfaction and improve the attractiveness of the product or service. FAD is then used to measure the gap between customer satisfaction and the company’s expected levels of satisfaction in terms of product functions. This enables the company to obtain more comprehensive information for decision-making. A case study is provided to verify the practicability of the proposed method. Sensitivity analysis proves the robustness of the results based on the number of respondents. Finally, comparative analysis with existing approaches demonstrates the strengths of the proposed method. Full article
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23 pages, 3630 KiB  
Article
Research on Convergence Media Ecological Model Based on Blockchain
by Hongbin Hu, Yongbin Wang and Guohui Song
Systems 2024, 12(9), 381; https://doi.org/10.3390/systems12090381 - 22 Sep 2024
Viewed by 606
Abstract
Currently, the media industry is in the rapid development stage of media integration, which has brought about great changes in content production mode, presentation form, communication mechanism, operation and maintenance management, etc. At the same time, it is also faced with problems such [...] Read more.
Currently, the media industry is in the rapid development stage of media integration, which has brought about great changes in content production mode, presentation form, communication mechanism, operation and maintenance management, etc. At the same time, it is also faced with problems such as difficult information traceability, declining industry credibility, low data circulation quality and efficiency, difficult data security and user privacy protection, etc. Utilizing blockchain’s characteristics can solve these problems that the media industry is currently facing. This paper designs a convergence media ecology model based on blockchain (CMEM-BC), focusing on the basic elements of the model, node operation and maintenance system, node management mechanism, value circulation mechanism, and storage mechanism, trying to establish a decentralized, traceable, and immutable convergence media ecosystem. On this basis, this paper summarizes the ecological framework and ecological model of CMEM-BC. Finally, the paper describes the verification of the effectiveness of CMEM-BC in key links through simulation experiments, verifying that CMEM-BC has high originality and is more suitable for the application of convergence media ecology through model analysis and comparison. Full article
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18 pages, 763 KiB  
Article
Learning to Score: A Coding System for Constructed Response Items via Interactive Clustering
by Lingjing Luo, Hang Yang, Zhiwu Li and Witold Pedrycz
Systems 2024, 12(9), 380; https://doi.org/10.3390/systems12090380 - 21 Sep 2024
Viewed by 673
Abstract
Constructed response items that require the student to give more detailed and elaborate responses are widely applied in large-scale assessments. However, the hand-craft scoring with a rubric for massive responses is labor-intensive and impractical due to rater subjectivity and answer variability. The automatic [...] Read more.
Constructed response items that require the student to give more detailed and elaborate responses are widely applied in large-scale assessments. However, the hand-craft scoring with a rubric for massive responses is labor-intensive and impractical due to rater subjectivity and answer variability. The automatic response coding method, such as the automatic scoring of short answers, has become a critical component of the learning and assessment system. In this paper, we propose an interactive coding system called ASSIST to efficiently score student responses with expert knowledge and then generate an automatic score classifier. First, the ungraded responses are clustered to generate specific codes, representative responses, and indicator words. The constraint set based on feedback from experts is taken as training data in metric learning to compensate for machine bias. Meanwhile, the classifier from responses to code is trained according to the clustering results. Second, the experts review each coded cluster with the representative responses and indicator words to score a rating. The coded cluster and score pairs will be validated to ensure inter-rater reliability. Finally, the classifier is available for scoring a new response with out-of-distribution detection, which is based on the similarity between response representation and class proxy, i.e., the weight of class in the last linear layer of the classifier. The originality of the system developed stems from the interactive response clustering procedure, which involves expert feedback and an adaptive automatic classifier that can identify new response classes. The proposed system is evaluated on our real-world assessment dataset. The results of the experiments demonstrate the effectiveness of the proposed system in saving human effort and improving scoring performance. The average improvements in clustering quality and scoring accuracy are 14.48% and 18.94%, respectively. Additionally, we reported the inter-rater reliability, out-of-distribution rate, and cluster statistics, before and after interaction. Full article
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12 pages, 1397 KiB  
Article
Supply Chain Sustainability: Influencing Factors and Empirical Study from a Marxist Political Economy Perspective
by Kun Zhang, Mei He, Jimei Yang and Hanping Hou
Systems 2024, 12(9), 379; https://doi.org/10.3390/systems12090379 - 20 Sep 2024
Viewed by 1182
Abstract
Marxist political economy provides a theoretical framework for sustainable supply chains, while the implementation of sustainable supply chains embodies and deepens the practical application of Marxist principles. This paper studies supply chain sustainability from the perspective of Marxist political economy, proposing a novel [...] Read more.
Marxist political economy provides a theoretical framework for sustainable supply chains, while the implementation of sustainable supply chains embodies and deepens the practical application of Marxist principles. This paper studies supply chain sustainability from the perspective of Marxist political economy, proposing a novel analytical framework to address sustainability challenges. The primary research focuses on (1) Identifying Influencing Factors: Influencing factors of Marxist political economy and supply chain sustainability are categorized into four main areas: society and government, environment, economy, and the supply chain itself. Through classification analysis, 16 key factors influencing sustainable supply chain implementation are identified. (2) DEMATEL Analysis (Decision-Making Trial and Evaluation Laboratory Method): Data are gathered through investigations and questionnaires to construct a direct influence matrix. Subsequently, a decision test method quantitatively analyzes the interactions among these factors, resulting in a comprehensive influence matrix and a cause–effect diagram. To enhance the overall benefits of supply chain sustainability and foster sustainable development. Full article
(This article belongs to the Special Issue New Trends in Sustainable Operations and Supply Chain Management)
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21 pages, 601 KiB  
Article
The Functional Mechanisms through Which Artificial Intelligence Influences the Innovation of Green Processes of Enterprises
by Jue Wang, Xiao Wang, Feng Sun and Xinyu Li
Systems 2024, 12(9), 378; https://doi.org/10.3390/systems12090378 - 19 Sep 2024
Viewed by 1094
Abstract
Green process innovation is an important strategy in the high-quality development of enterprises. Digital technology is becoming a key factor in helping businesses address environmental issues and contributes to their green process innovation and sustainable growth. Nevertheless, there is a lack of studies [...] Read more.
Green process innovation is an important strategy in the high-quality development of enterprises. Digital technology is becoming a key factor in helping businesses address environmental issues and contributes to their green process innovation and sustainable growth. Nevertheless, there is a lack of studies on how particular digital technology categories affect corporate green process innovation. Artificial intelligence (AI) is an important part of digitalization as it can provide new technical means and guidance for enterprise’s innovation of green processes. This study aims to fills this research gap by revealing the logical relationship between digital technology and the green development of enterprises. Using China’s A-share-listed companies as the research object from 2013 to 2022, this study employed a two-way fixed-effects model and investigated the impact of artificial intelligence (AI) on corporate green process innovation and the moderating effect of multidimensional intellectual capital. The results revealed that AI positively impacts corporate green process innovation. Human capital, structural capital, employed capital, and relational capital strengthen this positive effect. Robustness tests validated these conclusions. This study expands the literature on digital technology and corporate green innovation and provides a reference for enterprises to implement green practices using digital technology. Full article
(This article belongs to the Special Issue Systems Analysis of Enterprise Sustainability)
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11 pages, 4193 KiB  
Article
One-Bit In, Two-Bit Out: Network-Based Metrics of Papers Can Be Largely Improved by Including Only the External Citation Counts without the Citation Relations
by Jianlin Zhou, Zhesi Shen and Jinshan Wu
Systems 2024, 12(9), 377; https://doi.org/10.3390/systems12090377 - 17 Sep 2024
Viewed by 786
Abstract
Many ranking algorithms and metrics have been proposed to identify high-impact papers. Both the direct citation counts and the network-based PageRank-like algorithms are commonly used. Ideally, the more complete the data on the citation network, the more informative the ranking. However, obtaining more [...] Read more.
Many ranking algorithms and metrics have been proposed to identify high-impact papers. Both the direct citation counts and the network-based PageRank-like algorithms are commonly used. Ideally, the more complete the data on the citation network, the more informative the ranking. However, obtaining more data on citation relations is often costly and challenging. In some cases, obtaining the citation counts can be relatively simple. In this paper, we look into using the additional citation counts but without additional citation relations to form more informative metrics for identifying high-impact papers. As an example, we propose enhancing the original PageRank algorithm by combining the local citation network with the additional citation counts from a more complete data source. We apply this enhanced method to American Physical Society (APS) papers to verify its effectiveness. The results indicate that the proposed ranking algorithm is robust against missing data and can improve the identification of high-quality papers. This shows that it is possible to enhance the effectiveness of a network-based metric calculated on a relatively small citation network by including only the additional data of the citation counts, without the additional citation relations. Full article
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15 pages, 1512 KiB  
Article
Nash–Cournot Equilibrium and Its Impact on Network Transmission Congestion
by María de los Ángeles Sánchez Galván, Jaime Robles García, David Romero Romero and Mohamed Badaoui
Systems 2024, 12(9), 376; https://doi.org/10.3390/systems12090376 - 17 Sep 2024
Viewed by 640
Abstract
This paper evaluates the impact of congestion on transmission lines when the operation cost is minimized using economic dispatch (ED), comparing the results obtained with the Nash–Cournot Equilibrium (NCE). A methodology is developed for the optimal power flow solution through the NCE, considering [...] Read more.
This paper evaluates the impact of congestion on transmission lines when the operation cost is minimized using economic dispatch (ED), comparing the results obtained with the Nash–Cournot Equilibrium (NCE). A methodology is developed for the optimal power flow solution through the NCE, considering the network topology (upper and lower generation limits, upper and lower limits of the transmission lines, and power balance) for a nine-node system without and considering two bilateral power transactions. The results show that the operation cost is higher when the NCE is implemented than ED. However, the problem of congestion in the transmission lines is reduced due to the equilibrium obtained in the power dispatch against minimizing the operation cost in the dispatch; the transmission lines with the most significant participation tend to become congested when additional bilateral transactions occur. Finally, the above is verified by obtaining the mean and median of the transmission line percentages used in the two simulations. Full article
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22 pages, 4577 KiB  
Article
Integrating System Perspectives to Optimize Ecosystem Service Provision in Urban Ecological Development
by Wenbo Cai and Chengji Shu
Systems 2024, 12(9), 375; https://doi.org/10.3390/systems12090375 - 17 Sep 2024
Viewed by 890
Abstract
System-based approaches are critical for addressing the complex and interconnected nature of urban ecological development and restoration of ecosystem services. This study adopts a system perspective to investigate the spatiotemporal drivers of key ecosystem services, including carbon sequestration, water conservation, sediment reduction, pollution [...] Read more.
System-based approaches are critical for addressing the complex and interconnected nature of urban ecological development and restoration of ecosystem services. This study adopts a system perspective to investigate the spatiotemporal drivers of key ecosystem services, including carbon sequestration, water conservation, sediment reduction, pollution mitigation, and stormwater regulation, within the Yangtze River Delta Eco-Green Integrated Development Demonstration Area (YRDDA) from 2000 to 2020. We propose a novel framework for defining enhanced-efficiency ecosystem service management regions (EESMR) to guide targeted restoration. Our analysis revealed the complex interplay of 11, 9, 6, 6, and 10 driving factors for selected ecosystem services, highlighting the spatiotemporal heterogeneity of these drivers. By overlaying these key factors, we identified high-efficiency restoration priority areas for EESMR that ensure high returns on investment and the efficient restoration of ecosystem functions. This system-oriented approach provided critical spatial guidance for integrated ecological restoration, green development, and eco-planning. These findings offer valuable insights for policymakers and planners in the Yangtze River Delta and other rapidly urbanizing regions, supporting the formulation of effective land-use policies that balance environmental sustainability and urban growth. Full article
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27 pages, 1550 KiB  
Systematic Review
A Study of the Main Mathematical Models Used in Mobility, Storage, Pickup and Delivery in Urban Logistics: A Systematic Review
by Renan Paula Ramos Moreno, Rui Borges Lopes, José Vasconcelos Ferreira, Ana Luísa Ramos and Diogo Correia
Systems 2024, 12(9), 374; https://doi.org/10.3390/systems12090374 - 17 Sep 2024
Viewed by 896
Abstract
This systematic review investigates the main mathematical models applied in urban logistics, focusing on routing, location and transshipment problems. The study addresses the growing demand for efficient and sustainable logistics solutions driven by population growth and the expansion of e-commerce. A thorough analysis [...] Read more.
This systematic review investigates the main mathematical models applied in urban logistics, focusing on routing, location and transshipment problems. The study addresses the growing demand for efficient and sustainable logistics solutions driven by population growth and the expansion of e-commerce. A thorough analysis of 57 scientific articles was carried out, covering deterministic and stochastic methodologies, as well as heuristic and exact solutions. This review revealed that heuristic methods are predominant due to their computational efficiency. Combining exact methods with heuristics has proven effective for complex logistics scenarios, increasing accuracy and efficiency. Synchronization and intermediate stops have also emerged as critical factors in optimizing logistics operations. This review highlights the diversity of methodologies and the need for sustainable and efficient models. The integration of stochastic simulations remains limited, representing a research gap where stochastic models have been shown to provide more robust solutions in addressing the uncertainties inherent in logistics operations. This integration can increase the robustness and applicability of logistics solutions in urban environments. By highlighting the strengths and limitations of current approaches, it paves the way for future research to develop more robust and adaptable solutions to urban logistics challenges, emphasizing interdisciplinary collaboration and the use of real-world data. Full article
(This article belongs to the Section Supply Chain Management)
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21 pages, 1093 KiB  
Article
The Influence of Machine Learning on Enhancing Rational Decision-Making and Trust Levels in e-Government
by Ayat Mohammad Salem, Serife Zihni Eyupoglu and Mohammad Khaleel Ma’aitah
Systems 2024, 12(9), 373; https://doi.org/10.3390/systems12090373 - 16 Sep 2024
Viewed by 1978
Abstract
The rapid growth in the use of AI techniques, mainly machine learning (ML), is revolutionizing different industries by significantly enhancing decision-making processes through data-driven insights. This study investigates the influence of using ML, particularly supervised and unsupervised learning, on rational decision-making (RDM) within [...] Read more.
The rapid growth in the use of AI techniques, mainly machine learning (ML), is revolutionizing different industries by significantly enhancing decision-making processes through data-driven insights. This study investigates the influence of using ML, particularly supervised and unsupervised learning, on rational decision-making (RDM) within Jordanian e-government, focusing on the mediating role of trust. By analyzing the experiences of middle-level management within e-government in Jordan, the findings underscore that ML positively impacts the rational decision-making process in e-government. It enables more efficient and effective data gathering, improves the accuracy of data analysis, enhances the speed and accuracy of evaluating decision alternatives, and improves the assessment of potential risks. Additionally, this study reveals that trust plays a critical role in determining the effectiveness of ML adoption for decision-making, acting as a pivotal mediator that can either facilitate or impede the integration of these technologies. This study provides empirical evidence of how trust not only enhances the utilization of ML but also amplifies its positive impact on governance. The findings highlight the necessity of cultivating trust to ensure the successful deployment of ML in public administration, thereby enabling a more effective and sustainable digital transformation. Despite certain limitations, the outcomes of this study offer substantial insights for researchers and government policymakers alike, contributing to the advancement of sustainable practices in the e-government domain. Full article
(This article belongs to the Special Issue Navigating Digital Transformation: Leadership and Decision Making in Today’s Systems)
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26 pages, 1206 KiB  
Article
Does Government Digital Transformation Drive High-Quality Urban Economic Development? Evidence from E-Government Platform Construction
by Li Xiong, Xiaoyu Wang, Zijie Liu and Xiaoliang Long
Systems 2024, 12(9), 372; https://doi.org/10.3390/systems12090372 - 15 Sep 2024
Viewed by 1072
Abstract
Digitalization represents a pivotal global development trend and serves as a significant force propelling economic and social transformation. This manuscript uses the global Malmquist–Luenberger (GML) model to estimate green total factor productivity (GTFP) across 284 Chinese cities from 2003 to 2018, taking the [...] Read more.
Digitalization represents a pivotal global development trend and serves as a significant force propelling economic and social transformation. This manuscript uses the global Malmquist–Luenberger (GML) model to estimate green total factor productivity (GTFP) across 284 Chinese cities from 2003 to 2018, taking the pilot policy of “construction and application of e-government public platforms based on cloud computing” as an example to assess the impact of government digital transformation on the qualitative development of the economy by using a difference-in-differences model to explore the path of its role and driving mechanism. The results reveal that government digital transformation promotes the qualitative improvement of the city’s economic development, and its driving effect shows a marginal incremental law. Moreover, government digital transformation can contribute to the formation of a “latecomer advantage” in the lagging regions, which creates a “catch-up effect” on the regions with favorable development foundations, excellent geographical conditions, high urban ranking, and high education quality. Additionally, government digital transformation boosts economic and social development quality through both innovation spillover and structural optimization. Full article
(This article belongs to the Topic AI and IoT for Promoting Green Operation and Sustainable Environment)
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25 pages, 2029 KiB  
Article
Differential Games of Supply Chain on Consideration of Low-Carbon Reference Effect under Different Carbon Quota Allocation Methods
by Anbo Wu, Ronglin Zhang, Yue Sun, Linhui Sun, Shuhan Wang and Xinping Wang
Systems 2024, 12(9), 371; https://doi.org/10.3390/systems12090371 - 15 Sep 2024
Cited by 1 | Viewed by 920
Abstract
The carbon quota allocation method serves as the foundation for the design of the carbon trading mechanism, which has a significant impact on supply chain production decisions and the operational efficiency of the carbon trading market. To analyze the behavioral decision problem of [...] Read more.
The carbon quota allocation method serves as the foundation for the design of the carbon trading mechanism, which has a significant impact on supply chain production decisions and the operational efficiency of the carbon trading market. To analyze the behavioral decision problem of supply chain members under different carbon quota allocation methods, the low-carbon reference effect is introduced to characterize the effect of consumers’ low-carbon preference on market demand. On this basis, three differential game models are constructed, namely, no emissions penalty, trading under the grandfathering principle, and trading under the benchmarking principle. The results indicate that the implementation of carbon trading policies enhances consumers’ low-carbon reference levels, the carbon emission reduction levels of manufacturers, and the low-carbon publicity levels of retailers. Moreover, the enhancement of the low-carbon reference effect becomes a positive driver of profit growth. Manufacturers are observed to make more efforts in carbon reduction under the benchmarking principle compared to the grandfathering principle. In contrast, the level of low-carbon publicity by retailers remains unchanged. The above findings can provide a scientific basis for the decision-making of emission reduction in low-carbon supply chain enterprises, which has certain theoretical significance. Full article
(This article belongs to the Special Issue Multi-criteria Decision Making in Supply Chain Management)
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22 pages, 7166 KiB  
Article
An Improved Driving Safety Field Model Based on Vehicle Movement Uncertainty for Highway Ramp Influence Areas
by Yueru Xu, Wei Ye, Yalin Luan and Bingbo Cui
Systems 2024, 12(9), 370; https://doi.org/10.3390/systems12090370 - 14 Sep 2024
Viewed by 766
Abstract
Road traffic accidents result in numerous fatalities and injuries annually. Advanced driving assistance systems (ADASs) have garnered significant attention to mitigate these harms. An accurate safety assessment can significantly improve the effectiveness and credibility of ADASs. However, a real-time safety assessment remains a [...] Read more.
Road traffic accidents result in numerous fatalities and injuries annually. Advanced driving assistance systems (ADASs) have garnered significant attention to mitigate these harms. An accurate safety assessment can significantly improve the effectiveness and credibility of ADASs. However, a real-time safety assessment remains a key challenge due to the complex interactions among humans, vehicles, and the road environment. Traditional safety assessment methods, relying on crash data and surrogate safety measures (SSMs), face limitations in real-time applicability and scenario coverage, especially in freeway ramp areas with frequent merging and lane changing. To address these gaps, this paper develops a driving safety field based on the uncertainty of vehicle movements, which integrates the characteristics of driving behaviors, vehicles, and the road environment. The proposed method is validated with a simulation of driving scenarios and ROC curves obtained from the NGSIM dataset. The results demonstrate that our proposed driving safety field effectively quantifies the real-time risk in ramp influence areas and outperforms Time to Collision (TTC), making it suitable for integration into collision warning systems of ADASs. Full article
(This article belongs to the Special Issue Application of System Engineering and Complex Theory in Transportation)
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22 pages, 3020 KiB  
Article
Text-to-Model Transformation: Natural Language-Based Model Generation Framework
by Aditya Akundi, Joshua Ontiveros and Sergio Luna
Systems 2024, 12(9), 369; https://doi.org/10.3390/systems12090369 - 14 Sep 2024
Viewed by 935
Abstract
System modeling language (SysML) diagrams generated manually by system modelers can sometimes be prone to errors, which are time-consuming and introduce subjectivity. Natural language processing (NLP) techniques and tools to create SysML diagrams can aid in improving software and systems design processes. Though [...] Read more.
System modeling language (SysML) diagrams generated manually by system modelers can sometimes be prone to errors, which are time-consuming and introduce subjectivity. Natural language processing (NLP) techniques and tools to create SysML diagrams can aid in improving software and systems design processes. Though NLP effectively extracts and analyzes raw text data, such as text-based requirement documents, to assist in design specification, natural language, inherent complexity, and variability pose challenges in accurately interpreting the data. In this paper, we explore the integration of NLP with SysML to automate the generation of system models from input textual requirements. We propose a model generation framework leveraging Python and the spaCy NLP library to process text input and generate class/block definition diagrams using PlantUML for visual representation. The intent of this framework is to aid in reducing the manual effort in creating SysML v1.6 diagrams—class/block definition diagrams in this case. We evaluate the effectiveness of the framework using precision and recall measures. The contribution of this paper to the systems modeling domain is two-fold. First, a review and analysis of natural language processing techniques for the automated generation of SysML diagrams are provided. Second, a framework to automatically extract textual relationships tailored for generating a class diagram/block diagram that contains the classes/blocks, their relationships, methods, and attributes is presented. Full article
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15 pages, 599 KiB  
Article
Intuitionistic Linguistic EDAS Method with New Score Function: Case Study on Evaluating Universities’ Innovation and Entrepreneurship Education
by Chunyu Zhao, Haiyang Hou and Hui Yan
Systems 2024, 12(9), 368; https://doi.org/10.3390/systems12090368 - 14 Sep 2024
Viewed by 682
Abstract
Intuitionistic linguistic numbers (ILNs) describe expert evaluation information by representing semantic assessment values and reflecting the confidence level and hesitation of decision-makers. ILNs are widely used to handle uncertain and incomplete information. The Evaluation Based on Distance from Average Solution (EDAS) method selects [...] Read more.
Intuitionistic linguistic numbers (ILNs) describe expert evaluation information by representing semantic assessment values and reflecting the confidence level and hesitation of decision-makers. ILNs are widely used to handle uncertain and incomplete information. The Evaluation Based on Distance from Average Solution (EDAS) method selects the optimal solution based on the distance of each alternative from the average solution, making it suitable for multi-attribute decision-making with conflicting attributes. This study proposes a new scoring function for ILNs and develops an evaluation method combining ILNs with EDAS (IL-EDAS). Experts’ evaluations of each alternative’s indices are expressed using ILNs, and the EDAS method ranks the alternatives to select the optimal solution. We apply this method to assess innovation and entrepreneurship education capabilities in universities, and compare the results with those from other methods to verify their applicability and practicality. Full article
(This article belongs to the Special Issue Information Systems: Discipline, Critical Research and Education)
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19 pages, 555 KiB  
Article
Developing a Maturity Rating System for Project Management Offices
by Abdullah M. Alshabragi, Abdulmohsen S. Almohsen and Abdulrahman A. Bin Mahmoud
Systems 2024, 12(9), 367; https://doi.org/10.3390/systems12090367 - 14 Sep 2024
Viewed by 895
Abstract
Effective project management is crucial for organizations to achieve strategic objectives and maintain competitiveness in today’s market. The project management office (PMO) has emerged as a key enabler in enhancing project management effectiveness through centralized oversight, support, and standardization. However, evaluating the effectiveness [...] Read more.
Effective project management is crucial for organizations to achieve strategic objectives and maintain competitiveness in today’s market. The project management office (PMO) has emerged as a key enabler in enhancing project management effectiveness through centralized oversight, support, and standardization. However, evaluating the effectiveness of PMOs and identifying areas for improvement remain challenging. This paper aims to provide a comprehensive overview of project management effectiveness and the role of PMOs in achieving organizational success by establishing a maturity rating system. The research objectives include identifying critical success factors relevant to sustainable PMO effectiveness, reviewing existing literature on project management maturity models, analyzing data through literature review and questionnaires, developing a rating system based on identified success factors, and contributing to the existing literature on PMOs. The literature review and thematic analysis identified five critical themes—organizational culture, governance, competence, project controls, and engagement—each with corresponding success factors. Questionnaires were used to assess the maturity levels and relative importance of these factors, where the AHP analysis determined the weighted importance of each success factor and category. The results highlight the critical success factors for PMOs: collaboration, effective leadership, alignment with organizational goals, knowledge management, project planning, risk management, stakeholder satisfaction, and communication. By establishing a standardized and objective approach to evaluating sustainable PMO effectiveness, organizations can enhance their sustainable project management practices, improve project success rates, and address the challenges associated with evaluating PMO performance. Ultimately, adopting a systems approach enables PMOs to align strategies with organizational goals and foster a culture of continuous improvement. Full article
(This article belongs to the Special Issue Sustainable Project Management in Business)
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23 pages, 1491 KiB  
Article
Digital Transformation: A Challenge for the Romanian Health System
by Nicu Rotaru and Eduard Edelhauser
Systems 2024, 12(9), 366; https://doi.org/10.3390/systems12090366 - 14 Sep 2024
Viewed by 737
Abstract
This study analyzes the current status of the digitalization of the Romanian Health System (RHS). Data were collected from 135 active public and private health professionals using an online questionnaire with 102 items. The results of the analysis show that, if the qualification [...] Read more.
This study analyzes the current status of the digitalization of the Romanian Health System (RHS). Data were collected from 135 active public and private health professionals using an online questionnaire with 102 items. The results of the analysis show that, if the qualification level and the experience of managers are high, seniority in management positions is an essential factor in the adoption of digital technologies, the digitalization of health services increases the efficiency and quality of medical and management services, and the success of the implementation of digital technologies is conditioned by the harmonization of a variety of factors because there are differences between the public and private sectors in terms of the economic efficiency determined by the adoption of digital technologies. There are also differences in the implementation of digital technologies between the national and worldwide levels, there are specific technologies that positively influence managerial performance, and the innovation process is conditioned by the management level. Because Romanian health service managers are updated with new technologies, they can ensure the implementation of digital technologies, considering that economic efficiency and managerial performance are directly related to the level of adoption and the type of technologies implemented. Full article
(This article belongs to the Special Issue Advances in the Modeling and Analytics of Health and Healthcare Systems)
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40 pages, 1390 KiB  
Article
Governance of Corporate Greenwashing through ESG Assurance
by Meiwen Bu, Xin Liu, Bin Zhang, Saddam A. Hazaea, Run Fan and Zijian Wang
Systems 2024, 12(9), 365; https://doi.org/10.3390/systems12090365 - 14 Sep 2024
Viewed by 1547
Abstract
This study utilizes data from Chinese A-share listed companies from 2014 to 2022 to theoretically analyze and empirically test the governance effect of ESG assurance on corporate greenwashing behavior, as well as the role played by the legal environment and management shareholding in [...] Read more.
This study utilizes data from Chinese A-share listed companies from 2014 to 2022 to theoretically analyze and empirically test the governance effect of ESG assurance on corporate greenwashing behavior, as well as the role played by the legal environment and management shareholding in this context. The impacts of ownership and the governance mechanism of ESG assurance on corporate greenwashing behavior are also explored. This study employs text mining, OLS, PSM, IV-LIML, treatment effect models, feasible generalized least squares, placebo tests, bootstrap methods, etc., to conduct empirical analysis and conclude the following results: ESG assurance has a significant inhibitory effect on corporate greenwashing behavior, playing a crucial role in resource allocation, particularly in non-state-owned enterprises. The legal environment has a certain substitution effect on ESG assurance in inhibiting corporate greenwashing behavior, meaning that when the legal environment is weak, ESG assurance is more effective in curbing such behavior. Management shareholding also has a certain substitution effect on ESG assurance in inhibiting corporate greenwashing behavior, indicating that when management shareholding is low, ESG assurance is better at curbing such behavior. Further research reveals that corporate ESG performance plays a mediating role between ESG assurance and corporate greenwashing governance. This article provides policy references and empirical evidence for strengthening ESG assurance and enhancing corporate ESG performance and greenwashing governance to promote high-quality corporate development. Full article
(This article belongs to the Special Issue Business Innovation: From Management Systems to Corporate Social Responsibility)
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20 pages, 1432 KiB  
Article
Explaining Crisis Situations via a Cognitive Model of Attention
by Georgi Tsochev and Teodor Ukov
Systems 2024, 12(9), 364; https://doi.org/10.3390/systems12090364 - 14 Sep 2024
Viewed by 676
Abstract
Decision making in critical situations is a complex process. There are many processes to consider. This paper describes a theoretical approach to researching attentional processes and automatic unconscious processes in terms of metacognition. An application of the approach is presented to explain decision [...] Read more.
Decision making in critical situations is a complex process. There are many processes to consider. This paper describes a theoretical approach to researching attentional processes and automatic unconscious processes in terms of metacognition. An application of the approach is presented to explain decision making and metacognition as a solution for ineffective cognitive biases during a crisis situation. Evidence is presented from studies on neuropsychology, cognitive control, and cognitive architectures. An application of the recently formulated semiotic methodology is implemented that allows the design of conceptual models of Attention as Action. The formulation of a general model of attentional processes is based on a set of rules. The crisis phenomenon, as the crisis situation trigger, is semiotically described and applied as insight for a crisis information system design that prompts its users toward self-aware internal decision making. The research conducted evidently shows how the approach can explain the design of several cognitive architectures. Pointing toward metacognition as a solution to a crisis phenomenon and cognitive biases, the paper shows that understanding human cognitive and behavioral processes can significantly improve management in a critical infrastructure crisis situation. Full article
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20 pages, 690 KiB  
Article
Intellectual Capital, Board Diversity, and Firms’ Financial Performance: A Complex System Perspective
by Yu Gao, Xinyu Tian and Jian Xu
Systems 2024, 12(9), 363; https://doi.org/10.3390/systems12090363 - 12 Sep 2024
Viewed by 732
Abstract
The objective of this study is to analyze the impact of intellectual capital (IC) and its components on firm financial performance using data from Chinese agricultural listed companies during 2015–2020. The moderating role of board diversity in the relationship between IC and firm [...] Read more.
The objective of this study is to analyze the impact of intellectual capital (IC) and its components on firm financial performance using data from Chinese agricultural listed companies during 2015–2020. The moderating role of board diversity in the relationship between IC and firm financial performance is also tested. The modified value-added intellectual coefficient (MVAIC) model is used to measure IC, and board diversity is measured by several indicators, such as diversity in gender, experience, professional background, and educational background. The results suggest that the overall IC and only one element (human capital) positively influence firm financial performance. Diversity in gender, professional background, and educational background positively moderate the relationship between IC and financial performance, while experience diversity has a negative moderating effect. Among IC components, experience diversity, and educational background diversity negatively moderate the relationship between human capital and financial performance. In addition, gender diversity and experience diversity have a negative moderating effect on the relationship between physical capital and financial performance, while professional background diversity and educational background diversity have a positive moderating effect. This study can provide some new insights for managers to devise strategies to improve IC performance and strengthen corporate governance in order to achieve sustainable development of the agricultural industry. It also can guide policymakers in making policies to improve IC efficiency and firm performance. Full article
(This article belongs to the Section Systems Practice in Social Science)
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26 pages, 3488 KiB  
Article
Interaction Mechanism between Inter-Organizational Relationship Cognition and Engineering Project Value Added from the Perspective of Dynamic Impact
by Mengyu Xu, Xun Liu, Zhen Bian and Yufan Wang
Systems 2024, 12(9), 362; https://doi.org/10.3390/systems12090362 - 12 Sep 2024
Viewed by 590
Abstract
Projects involve inter-organizational relationship cognition, which is central to collaborative engineering project value added. Interest in value added in the project lifecycle is mounting and gaining increasing attention in the research literature. However, little is known about how inter-organizational relationship cognition facilitates value [...] Read more.
Projects involve inter-organizational relationship cognition, which is central to collaborative engineering project value added. Interest in value added in the project lifecycle is mounting and gaining increasing attention in the research literature. However, little is known about how inter-organizational relationship cognition facilitates value added and how such cognition pushes a project toward higher end-states of value. The existing literature mainly analyzes and studies value added on functional analysis and cost control. There are predominantly static analyses of the factors that influence value added in studies. The guiding role of value added has not been adequately explored in the studies on the influencing factors of value added. Utilizing a combination of Structural Equation Modeling (SEM) and Fuzzy Cognitive Maps (FCMs), this study addresses how inter-organizational relationship cognition influences engineering project value added, identifying complex structures of interaction and cognition dynamics. Results indicate that: (1) A hybrid SEM–FCM method can be able to model dynamic interactions between inter-organizational relationship cognition and value added; (2) trust and shared vision have positive effects on in-role behavior and extra-role behavior. Shared vision has a negative effect on opportunistic behavior. In-role behavior and extra-role behavior have a positive impact on value added, while opportunistic behavior has a negative impact. Organizational behavior is an important mediating variable to explain the interaction between inter-organizational relationship cognitions and value added. This hybrid method explores the potential mechanisms of inter-organizational relationship cognition on project value added from novel perspectives on construction project management practices, proposing practical advice for further project management. Full article
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49 pages, 1337 KiB  
Article
Diagnosing Market Capitalism: A Metacybernetic View
by Maurice Yolles
Systems 2024, 12(9), 361; https://doi.org/10.3390/systems12090361 - 11 Sep 2024
Viewed by 1279
Abstract
This multidisciplinary paper contributes to political economy, social cybernetics, and philosophy by examining distinctions in market capitalist ideologies through a metacybernetic approach. It explores reflexive processes, akin to Adam Smith’s invisible and visible hands, and their impact on market ideologies. The study highlights [...] Read more.
This multidisciplinary paper contributes to political economy, social cybernetics, and philosophy by examining distinctions in market capitalist ideologies through a metacybernetic approach. It explores reflexive processes, akin to Adam Smith’s invisible and visible hands, and their impact on market ideologies. The study highlights the evolutifon of these ideologies in balancing egoism and altruism, revealing insights into sociocultural shifts. Some ideologies are more prone to pathologies like market hegemony, which disrupts market viability and social welfare. Diagnosing these ideologies is essential to address issues of market hegemony like platform capitalism, technofeudalism, and surveillance capitalism. After a comparative analysis of capitalist ideologies, the paper focuses on neoliberal and stakeholder capitalism, due to their dominance, contrasting philosophies, policy influence, and roles in global challenges. A metacybernetic perspective is adopted, modelling the market as a complex adaptive system with agency, using Mindset Agency Theory (MAT). MAT distinguishes agency into subagencies of affect and cognition. Recognising the role of spirit, a spirit subagency is configured into MAT to enable explicit consideration of attributes like ethics and the greater good within the market, relationally improving transparency and promoting sustainable and inclusive economic practices. MAT is applied to the evolution of capitalist ideologies, examining their viability and sustainability under changing conditions. With its now triadic interactive subagency structure, MAT identifies eight distinct types of mindset, each characterised by 21 parameters that combine to deliver unique variations, in neoliberal and stakeholder capitalism, of the market ideologies. Full article
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23 pages, 382 KiB  
Article
Complex Business Environment Systems and Corporate Innovation
by Yu Gao, Xiaojie Sun, Na Liu, Wenyu Zhang and Jian Xu
Systems 2024, 12(9), 360; https://doi.org/10.3390/systems12090360 - 11 Sep 2024
Viewed by 755
Abstract
Sustainable development has become a corporate goal all over the world, and innovation as a crucial prerequisite for sustainable development has attracted much attention. This study investigates the relationship between the business environment and corporate innovation in Chinese A-share listed enterprises from 2017 [...] Read more.
Sustainable development has become a corporate goal all over the world, and innovation as a crucial prerequisite for sustainable development has attracted much attention. This study investigates the relationship between the business environment and corporate innovation in Chinese A-share listed enterprises from 2017 to 2020. We use a complex indicator to measure the business environment and use multiple regression models to conduct the analysis. The findings suggest that a favorable business environment promotes corporate innovation by reducing financing constraints and environmental uncertainty. Compared to non-state-owned enterprises, the positive impact of the business environment on corporate innovation is enhanced in state-owned enterprises. Concentrated ownership enhances the positive impact of a favorable business environment on corporate innovation. Our study provides a new analytical perspective on the relationship between the business environment and corporate innovation in the context of China. Full article
(This article belongs to the Section Systems Practice in Social Science)
25 pages, 1154 KiB  
Article
Digital Transformation and Innovation: The Influence of Digital Technologies on Turnover from Innovation Activities and Types of Innovation
by Anca Antoaneta Vărzaru and Claudiu George Bocean
Systems 2024, 12(9), 359; https://doi.org/10.3390/systems12090359 - 11 Sep 2024
Viewed by 5733
Abstract
In today’s competitive and globalized world, innovation is essential for organizational survival, offering a means for companies to address environmental impacts and social challenges. As innovation processes accelerate, managers need to rethink the entire value-creation chain, with digital transformation emerging as a continuous [...] Read more.
In today’s competitive and globalized world, innovation is essential for organizational survival, offering a means for companies to address environmental impacts and social challenges. As innovation processes accelerate, managers need to rethink the entire value-creation chain, with digital transformation emerging as a continuous process of organizational adaptation to the evolving societal landscape. The research question focuses on how digital technologies—such as artificial intelligence, Big Data, cloud computing, industrial and service robots, and the Internet of Things—influence innovation-driven revenues among enterprises within the European Union (EU). The paper examines, using neural network analysis, the specific impact of each digital technology on innovation revenues while exploring how these technologies affect various types of social innovation within organizations. Through cluster analysis, the study identifies patterns among EU countries based on their digital technology adoption, innovation expenditures, and revenues and the proportion of enterprises engaged in innovation activities. The findings highlight the central role of digital technologies in enhancing innovation and competitiveness, with significant implications for managers and policymakers. These results underscore the necessity for companies to strategically integrate digital technologies to sustain long-term competitiveness in the rapidly evolving digital landscape of the EU. Full article
(This article belongs to the Special Issue Digital Transformation and Processes Innovation)
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22 pages, 5332 KiB  
Article
Category Mapping of Emergency Supplies Classification Standard Based on BERT-TextCNN
by Qiuxia Zhang, Hanping Hou, Yingjie Ju, Jiandong Yuan, Kun Zhang, Huanhuan Wang and Junhe Chen
Systems 2024, 12(9), 358; https://doi.org/10.3390/systems12090358 - 10 Sep 2024
Viewed by 881
Abstract
In recent years, the escalation in emergency occurrences has underscored the pressing need for expedient responses in delivering essential supplies. Efficient integration and precise allocation of emergency resources under joint government–enterprise stockpiling models are pivotal for enhancing emergency response effectiveness and minimizing economic [...] Read more.
In recent years, the escalation in emergency occurrences has underscored the pressing need for expedient responses in delivering essential supplies. Efficient integration and precise allocation of emergency resources under joint government–enterprise stockpiling models are pivotal for enhancing emergency response effectiveness and minimizing economic repercussions. However, current research predominantly focuses on contract coordination and cost-sharing within these joint reserve modes, overlooking significant discrepancies in emergency supply classification standards between government and enterprise sectors, as well as the asymmetry in cross-sectoral and cross-regional supply information. This oversight critically impedes the timeliness and accuracy of emergency supply responses. In practice, manual judgment has been used to match the same materials under differing classification standards between government and enterprise reserves. Still, this approach is inefficient and prone to high error rates. To mitigate these challenges, this study proposes a methodology leveraging the BERT pre-trained language model and TextCNN neural network to establish a robust mapping relationship between these classification criteria. The approach involves abstracting textual representations of both taxonomical classes, generating comparable sentence vectors via average pooling, and calculating cosine similarity scores to facilitate precise classification mapping. Illustrated with China’s Classification and Coding of Emergency Supplies standards and Global Product Classification standards, empirical validation on annotated data demonstrates the BERT-TextCNN model’s exceptional accuracy of 98.22%, surpassing other neural network methodologies such as BERT-CNN, BERT-RNN, BERT-BiLSTM, etc. This underscores the potential of advanced neural network techniques in enhancing emergency supply management across diverse sectors and regions. Full article
(This article belongs to the Section Supply Chain Management)
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17 pages, 1197 KiB  
Review
Resilience Metrics for Socio-Ecological and Socio-Technical Systems: A Scoping Review
by Patrick Steinmann, Hilde Tobi and George A. K. van Voorn
Systems 2024, 12(9), 357; https://doi.org/10.3390/systems12090357 - 10 Sep 2024
Viewed by 729
Abstract
An increased interest in the resilience of complex socio-ecological and socio-technical systems has led to a variety of metrics being proposed. An overview of these metrics and their underlying concepts would support identifying useful metrics for applications in science and engineering. This study [...] Read more.
An increased interest in the resilience of complex socio-ecological and socio-technical systems has led to a variety of metrics being proposed. An overview of these metrics and their underlying concepts would support identifying useful metrics for applications in science and engineering. This study undertakes a scoping review of resilience metrics for systems straddling the societal, ecological, and technical domains to determine how resilience has been measured, the conceptual differences between the proposed approaches, and how they align with the domains of their case studies. We find that a wide variety of resilience metrics have been proposed in the literature. Conceptually, ten different quantification approaches were identified. Four different disturbance types were observed, including sudden, continuous, multiple, and abruptly ending disturbances. Surprisingly, there is no strong pattern regarding socio-ecological systems being studied using the “ecological resilience” concept and socio-technical systems being studied using the “engineering resilience” concept. As a result, we recommend that researchers use multiple resilience metrics in the same study, ideally following different conceptual approaches, and compare the resulting insights. Furthermore, the used metrics should be mathematically defined, the included variables explained and their units provided, and the chosen functional form justified. Full article
(This article belongs to the Special Issue Data-Driven Decision Making for Complex Systems)
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23 pages, 2773 KiB  
Article
Using Blockchain Evidence in China’s Digital Copyright Legislation to Enhance the Sustainability of Legal Systems
by Lin Zou and Dike Chen
Systems 2024, 12(9), 356; https://doi.org/10.3390/systems12090356 - 9 Sep 2024
Viewed by 1153
Abstract
To achieve sustainable development of social systems, it is necessary to modernize the legal system, which is the foundation of any society, to increase the efficiency of resources and simultaneously optimize the performance of the environment and society. The immutable and timestamped features [...] Read more.
To achieve sustainable development of social systems, it is necessary to modernize the legal system, which is the foundation of any society, to increase the efficiency of resources and simultaneously optimize the performance of the environment and society. The immutable and timestamped features of blockchain offer a robust solution for tracking and authenticating digital copyright evidence, thereby enhancing the integrity and transparency of judicial systems. This ensures that the integration of blockchain into legal systems not only advances technological efficiency but also promotes environmental consciousness. Through comprehensive analyses that integrate questionnaires, interviews, case studies and legislative assessments, this research reveals that there are still problems in the application of blockchain evidence in China’s judicial practice, such as insufficient and stable credibility, inadequate database storage, deficient original rights mechanisms, and the imperfect application of rules of evidence. These problems can be solved by enhancing correspondence legal systems, such as establishing an officially trusted copyright certificate blockchain, creating a blockchain copyright certificate technology supervision system and formulating specific laws and regulations on the application and identification of blockchain evidence. As such, our study contributes to aligning blockchain with judicial records, supporting the sustainable development goals of social systems, fostering institutional justice and social progress. Full article
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30 pages, 5751 KiB  
Article
Method for Developing the System Architecture of Existing Industrial Objects for Digital Representation Tasks
by Vladimir Badenko, Vladimir Yadykin, Vladimir Kamsky, Arina Mohireva, Andrey Bezborodov, Egor Melekhin and Nikolay Sokolov
Systems 2024, 12(9), 355; https://doi.org/10.3390/systems12090355 - 9 Sep 2024
Viewed by 868
Abstract
This paper presents a method for creating the system architecture of existing industrial objects based on Model-Based Systems Engineering (MBSE) principles. The method aims to form a digital representation of physical objects, which is crucial in the digital transformation of industrial enterprises. It [...] Read more.
This paper presents a method for creating the system architecture of existing industrial objects based on Model-Based Systems Engineering (MBSE) principles. The method aims to form a digital representation of physical objects, which is crucial in the digital transformation of industrial enterprises. It allows for the accurate reflection of all components, processes, functions, and interrelationships within an object. The methodology includes stages of data collection, structuring, development of ontological models, and the integration of a comprehensive system architecture into the digital space. This method was tested using a small hydroelectric power plant, revealing its key advantages and disadvantages and identifying areas for further improvement. The main findings indicate a significant improvement in understanding the system architecture for scenario modeling and digital operation of the objects. Despite challenges such as the need for multiple iterations and high data requirements, the methodology demonstrates the potential for applying MBSE in the digital transformation of existing industrial objects. Full article
(This article belongs to the Special Issue Advanced Model-Based Systems Engineering)
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20 pages, 610 KiB  
Article
Integrating Order Splitting and Acceptance with Batch Delivery in Parallel Machine Scheduling
by Hanxing Cui, Qilan Zhao, Huanhuan Wang, Yuliang Guo and Junjie Guo
Systems 2024, 12(9), 354; https://doi.org/10.3390/systems12090354 - 8 Sep 2024
Viewed by 587
Abstract
Multiple production lines can work together to efficiently manufacture certain products. Thus, when capacity is insufficient, it is necessary to decide whether to develop new production lines to ensure the timely completion of all orders. For example, running a new production line for [...] Read more.
Multiple production lines can work together to efficiently manufacture certain products. Thus, when capacity is insufficient, it is necessary to decide whether to develop new production lines to ensure the timely completion of all orders. For example, running a new production line for a small number of orders is not cost-effective. Therefore, decision-making involves choosing between paying tardiness costs for a few orders, abandoning some orders, or developing new production lines to maximize efficiency. Additionally, the timely transportation of completed orders is crucial and depends on vehicle usage efficiency. From a transportation perspective, fully loading vehicles is the most efficient, but this may impact the timeliness of orders, leading to potential tardiness costs. By comprehensively considering these aspects, a multi-machine production model is constructed that incorporates transportation batch sequences and uses heuristic algorithms to solve the problem. Finally, designed case examples validate the effectiveness of the model and algorithm. Full article
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