Journal Description
Systems
Systems
is an international, peer-reviewed, open access journal on systems theory in practice, including fields such as systems engineering management, systems based project planning in urban settings, health systems, environmental management and complex social systems, published monthly online by MDPI. The International Society for the Systems Sciences (ISSS) is affiliated with Systems and its members receive a discount on the article processing charges.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SSCI (Web of Science), dblp, and other databases.
- Journal Rank: JCR - Q1 (Social Sciences, Interdisciplinary) / CiteScore - Q2 (Modeling and Simulation)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 17.3 days after submission; acceptance to publication is undertaken in 2.6 days (median values for papers published in this journal in the first half of 2024).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Impact Factor:
2.3 (2023);
5-Year Impact Factor:
2.5 (2023)
Latest Articles
Green Bond Issuance and the Spillover Effect of Green Technology Innovation from the Perspective of Market Attention: Evidence from China
Systems 2024, 12(10), 399; https://doi.org/10.3390/systems12100399 (registering DOI) - 26 Sep 2024
Abstract
As the green bond market in China develops and its institutional structure improves, the green bond has emerged as a pivotal element within the broader framework of the green financial system. We focus on bond issuers in China’s A-shares from the years 2010
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As the green bond market in China develops and its institutional structure improves, the green bond has emerged as a pivotal element within the broader framework of the green financial system. We focus on bond issuers in China’s A-shares from the years 2010 to 2021 and explore green bond issuance and the spillover effect of green technology innovation under the market attention perspective. Findings are that: (1) Green bond issuance can produce the spillover effect in the industry and significantly enhance peer enterprises’ green technology innovation. (2) From the viewpoint of market attention, analyst attention can significantly enhance the spillover effect of green bond issuance within the industry. The same is true for media attention and investor attention. (3) Further research shows that within the same industry, the spillover effect is more pronounced for state-owned enterprises, large-scale enterprises, and enterprises in regions with higher levels of green financial development. For the booming development of China’s green bond market and the sustainable development of enterprises, this paper provides theoretical and practical foundations.
Full article
(This article belongs to the Special Issue Business Innovation: From Management Systems to Corporate Social Responsibility)
Open AccessArticle
TriGCN: Graph Convolution Network Based on Tripartite Graph for Personalized Medicine Recommendation System
by
Huan Zhou, Sisi Liao and Fanying Guo
Systems 2024, 12(10), 398; https://doi.org/10.3390/systems12100398 (registering DOI) - 26 Sep 2024
Abstract
Intelligent medical systems have great potential to play an important role in people’s daily lives, as they can provide disease and medicine information immediately for both doctors and patients. Graph-structured data are attracting more and more attention in the artificial intelligence sector. Combining
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Intelligent medical systems have great potential to play an important role in people’s daily lives, as they can provide disease and medicine information immediately for both doctors and patients. Graph-structured data are attracting more and more attention in the artificial intelligence sector. Combining graph-structured data with a medical data set, a tripartite graph convolutional network named TriGCN is proposed. This model is able connect to disease and medicine or patient, disease, and medicine nodes, propagate information from layer to layer, and update node features at the same time. After this, calibrated label ranking is used to give personalized medicine recommendation lists to patients. The TriGCN approach has a great performance, outperforming other machine learning methods. Thus, this model has the potential to be applied in reality and will provide contributions to public health in the future.
Full article
(This article belongs to the Section Systems Practice in Social Science)
Open AccessArticle
Cybersecurity Risks Analysis in the Hospitality Industry: A Stakeholder Perspective on Sustainable Service Systems
by
Saliha Karadayi-Usta
Systems 2024, 12(10), 397; https://doi.org/10.3390/systems12100397 (registering DOI) - 26 Sep 2024
Abstract
The digital transformation age introduces cybersecurity threats into the hospitality industry by increasing the exposure and vulnerability of hospitality firms’ data and systems to hackers. The hospitality industry is a diverse segment of the service sector dedicated to the provision of services in
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The digital transformation age introduces cybersecurity threats into the hospitality industry by increasing the exposure and vulnerability of hospitality firms’ data and systems to hackers. The hospitality industry is a diverse segment of the service sector dedicated to the provision of services in areas such as accommodation, food and beverage, travel and tourism, and recreation, including hotels, restaurants, bars, travel agencies, and theme parks. Cybersecurity risks in the hospitality industry affect the data and systems of businesses such as accommodation, food, travel, and entertainment, primarily enabled by the industry’s increasing digitization. This study aims to map the principal cybersecurity risks to the main stakeholders by proposing a novel Picture Fuzzy Sets (PFSs)-based Matrix of Alliances and Conflicts: Tactics, Objectives, and Recommendations (MACTOR) approach. The purpose here is to examine each stakeholder’s position towards handling cybersecurity attacks and estimate the uncertain nature of personal judgments of industry representatives when stating their point of view. The research aimed to extract the triggering positions of the defined cybercrime risks to reach the root cause of these risks, as the point to try to mitigate first. Thus, this paper contributes to the literature in both theoretical and practical ways by proposing a new approach and by providing real industry officials’ perspectives to solve the challenges. A hospitality practitioner can easily understand their position in this service network and take action to prevent such cybercrimes.
Full article
(This article belongs to the Special Issue Cyber Security Challenges in Complex Systems)
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Open AccessSystematic Review
A Systematic Review on Extended Reality-Mediated Multi-User Social Engagement
by
Yimin Wang, Daojun Gong, Ruowei Xiao, Xinyi Wu and Hengbin Zhang
Systems 2024, 12(10), 396; https://doi.org/10.3390/systems12100396 (registering DOI) - 26 Sep 2024
Abstract
The metaverse represents a post-reality universe that seamlessly merges physical reality with digital virtuality. It provides a continuous and immersive social networking environment, enabling multi-user engagement and interaction through Extended Reality (XR) technologies, which include Virtual Reality (VR), Augmented Reality (AR), and Mixed
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The metaverse represents a post-reality universe that seamlessly merges physical reality with digital virtuality. It provides a continuous and immersive social networking environment, enabling multi-user engagement and interaction through Extended Reality (XR) technologies, which include Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR). As a novel solution distinct from traditional methods such as mobile-based applications, the technical affordance of XR technologies in shaping multi-user social experiences remains a complex, multifaceted, and multivariate issue that has not yet been thoroughly explored. Additionally, there is a notable absence of mature frameworks and guidelines for designing and developing these multi-user socio-technical systems. Enhancing multi-user social engagement through these technologies remains a significant research challenge. This systematic review aims to address this gap by establishing an analytical framework guided by the PRISMA protocol. It analyzes 88 studies from various disciplines, including computer science, social science, psychology, and the arts, to define the mechanisms and effectiveness of XR technologies in multi-user social engagement. Quantitative methods such as descriptive statistics, correlation statistics, and text mining are used to examine the manifestation of mechanisms, potential system factors, and their effectiveness. Meanwhile, qualitative case studies identify specific measures by which system factors enhance multi-user social engagement. The study provides a pioneering framework for theoretical research and offers practical insights for developing cross-spatiotemporal co-present activities in the metaverse. It also promotes critical reflection on the evolving relationship between humans and this emerging digital universe.
Full article
(This article belongs to the Special Issue Value Assessment of Product Service System Design)
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Open AccessArticle
Evaluation Research on Resilience of Coal-to-Liquids Industrial Chain and Supply Chain
by
Anbo Wu, Pingfan Li, Linhui Sun, Chang Su and Xinping Wang
Systems 2024, 12(10), 395; https://doi.org/10.3390/systems12100395 - 26 Sep 2024
Abstract
The objective of this study is to enhance the resilience of the coal-to-liquids (CTL) industrial chain and supply chain to withstand increasing shock pressures. There is an urgent need to improve the resilience of the industrial chain and supply chain. This paper identifies
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The objective of this study is to enhance the resilience of the coal-to-liquids (CTL) industrial chain and supply chain to withstand increasing shock pressures. There is an urgent need to improve the resilience of the industrial chain and supply chain. This paper identifies 21 resilience-influencing factors from 4 perspectives: absorption capacity, adaptability, recovery capacity, and self-learning capacity; it then constructs an evaluation indicator system. The Interval Type 2 Fuzzy-Decision-Making Trial and Evaluation Laboratory-Analytic Network Process (IT2F-DEMATEL-ANP) method is adopted to determine the weights of the indicator system, and a resilience evaluation is performed based on the Interval Type 2 Fuzzy-Prospect Theory-Technique for Order Preference by Similarity to an Ideal Solution (IT2F-PT-TOPSIS) method. Furthermore, in the case of the CTL industrial chain and supply chain of China Shenhua Energy Group Ningxia Coal Industry Co., Ltd. (CENC) (Ningxia, China), this study ranks the resilience level from 2018 to 2022 to identify the factors that have contributed to a reduction in resilience and to implement measures to enhance the resilience of the CTL industrial chain and supply chain. The results show that the level of the CTL industrial chain and supply chain resilience was lowest in 2020, while it was highest in 2021. Factors such as the degree of domestication of key technologies, the rationality of the CTL industry layout, and the stability of supply and demand chains are identified as significant determinants of resilience levels. This points the way to enhancing the resilience of the CTL industry and supply chain.
Full article
(This article belongs to the Special Issue Emerging Technologies in Supply Chain Management: Enhancing Traceability, Efficiency, Resilience, and Sustainability)
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Open AccessArticle
Airside Optimization Framework Covering Multiple Operations in Civil Airport Systems with a Variety of Aircraft: A Simulation-Based Digital Twin
by
Ahmad Attar, Mahdi Babaee, Sadigh Raissi and Majid Nojavan
Systems 2024, 12(10), 394; https://doi.org/10.3390/systems12100394 - 26 Sep 2024
Abstract
The airside is a principal subsystem in the intricate airport systems. This study focuses on introducing a digital twin framework for analyzing the delays and capacity of airports. This framework encompasses a diverse array of authentic features pertaining to a civil airport for
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The airside is a principal subsystem in the intricate airport systems. This study focuses on introducing a digital twin framework for analyzing the delays and capacity of airports. This framework encompasses a diverse array of authentic features pertaining to a civil airport for a mixture of both landing and departing flights. Being a decision support for the management of international airports, all sizes and weight categories of aircraft are considered permissible, each with their own unique service time and speed requirements in accordance with the global aviation regulations. The proposed discrete event simulation digital twin provides a real-time demonstration of the system performance with the possibility of predicting the future outcomes of managerial decisions. Additionally, this twin is equipped with an advanced and realistic 3D visualization that facilitates a more comprehensive understanding of the ongoing operations. To assess its efficiency in practice, the framework was implemented at an international airport. The statistical tests revealed the superior similarity between the proposed twin and the real system. Using this twin, we further optimized the studied system by analyzing its projected future performance under a set of scenarios. This resulted in a nearly 30% upgrade in the capacity of this airport while decreasing the expected delays by over 18% annually.
Full article
(This article belongs to the Special Issue Advancements in Practical Applications of Agents, Multi-Agent Systems and Digital Twins)
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Open AccessArticle
Optimal Refund and Ordering Decisions for Fresh Produce E-Commerce Platform: A Comparative Analysis of Refund Policies
by
Shouyao Xiong and Danqiong Zheng
Systems 2024, 12(10), 393; https://doi.org/10.3390/systems12100393 - 26 Sep 2024
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Different refund policies offered by e-commerce platforms provide diverse options for consumers and are crucial for enhancing after-sales service. This study constructs a refund and ordering decision model based on three typical refund policies: both basic refund and refund guarantee option (‘Policy I’),
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Different refund policies offered by e-commerce platforms provide diverse options for consumers and are crucial for enhancing after-sales service. This study constructs a refund and ordering decision model based on three typical refund policies: both basic refund and refund guarantee option (‘Policy I’), basic refund only (‘Policy II’), and refund guarantee option only (‘Policy III’). We examine scenarios where demand is influenced by price, refund policies, and stochastic factors, and returns are affected by refund policies, aiming to determine the optimal refund and ordering decisions for fresh produce e-commerce platforms. Our results indicate that, under the same parameters, the platform achieves the maximum order quantity and highest expected profit with Policy I. The return rate under Policy I is always higher than under Policy III, but not consistently higher than under Policy II. Additionally, as the sensitivity of demand to the refund policy increases, both the order quantity and basic refund price rise, while the refund guarantee option price decreases. Conversely, as the sensitivity of returns to the refund policy increases, the opposite occurs. Although market demand uncertainty does not impact the basic refund or refund guarantee option prices, the platform must increase order quantities to manage market volatility.
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Open AccessArticle
Can Institutional Openness Boost China’s Urban Economic Resilience? Evidence from Pilot Free Trade Zones
by
Xiao-Qing Ai, Hang Yang and He-Liang Zhu
Systems 2024, 12(10), 392; https://doi.org/10.3390/systems12100392 - 26 Sep 2024
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Economic resilience represents a nation’s capacity to withstand external shocks, quicken economic recovery, and attain sustainable development. Can Pilot Free Trade Zones (PFTZs), as testing fields for China’s institutional openness, boost the economic resilience of host cities? This study empirically investigates the impact
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Economic resilience represents a nation’s capacity to withstand external shocks, quicken economic recovery, and attain sustainable development. Can Pilot Free Trade Zones (PFTZs), as testing fields for China’s institutional openness, boost the economic resilience of host cities? This study empirically investigates the impact and mechanisms of establishing PFTZs on urban economic resilience. It does so by building overlapping Difference-in-Differences (DID), Propensity Score Matching DID (PSM-DID), and spatial DID models using panel data across 284 cities in China from 2007 to 2021. It is found that establishing PFTZs significantly promotes urban economic resilience, and PFTZs largely achieve this by increasing population density, consumer demand, and economic growth in host cities. Spatial heterogeneity analysis reveals that PFTZs in North, East, Central, and South China notably enhance urban economic resilience, whereas those in Northeast, Southwest, and Northwest China do not. Regarding spatial spillover effects, the establishment of PFTZs has a beneficial impact on the economic resilience of nearby cities within a radius of 100 km to 400 km. The impacts become stronger as the distance grows, peaking at a radius of 400 km. This research offers important policy implications for promoting the establishment of PFTZs, unlocking the benefits of institutional openness, and strengthening urban economic resilience.
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Open AccessArticle
A Study on the Heterogeneity of China’s Provincial Economic Growth Contribution to Carbon Emissions
by
Ruiqin Tian, Miaojie Xia, Yuqi Zhang, Dengke Xu and Shan Lu
Systems 2024, 12(10), 391; https://doi.org/10.3390/systems12100391 - 26 Sep 2024
Abstract
Achieving “dual carbon” targets by containing carbon emissions while sustaining economic growth is challenging. This study examines the varying carbon dependency levels among China’s 30 provincial-level administrative units, considering spatial correlations in emissions. Using a semi-parametric varying coefficient spatial autoregressive panel model on
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Achieving “dual carbon” targets by containing carbon emissions while sustaining economic growth is challenging. This study examines the varying carbon dependency levels among China’s 30 provincial-level administrative units, considering spatial correlations in emissions. Using a semi-parametric varying coefficient spatial autoregressive panel model on 2004–2019 panel data, this study shows the following: (i) The relationship between economic growth and carbon emissions forms an “S”-shaped curve, with the contribution decreasing as tertiary industry grows, defining three stages of carbon dependency. (ii) There is significant heterogeneity in carbon dependency across provinces, with some advancing to “weak dependency” or an “economic carbon peak” due to advantages and policies. (iii) Dependency levels shift over time, with “weak dependency” being the predominant stage, though transitions occur. (iv) A positive spatial spillover effect in emissions was noted. This study recommends tailored policies for each provincial-level administrative unit based on their carbon dependency and development stage.
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(This article belongs to the Section Systems Practice in Social Science)
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Open AccessArticle
Generative AI Assertions in UVM-Based System Verilog Functional Verification
by
Valentin Radu, Diana Dranga, Catalin Dumitrescu, Alina Iuliana Tabirca and Maria Cristina Stefan
Systems 2024, 12(10), 390; https://doi.org/10.3390/systems12100390 - 25 Sep 2024
Abstract
This paper investigates the potential of leveraging artificial intelligence to automate and optimize the verification process, particularly in generating System Verilog assertions for an Advance Peripheral Bus verification environment using Universal Verification Methodology. Generative artificial intelligence, such as ChatGPT, demonstrated its ability to
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This paper investigates the potential of leveraging artificial intelligence to automate and optimize the verification process, particularly in generating System Verilog assertions for an Advance Peripheral Bus verification environment using Universal Verification Methodology. Generative artificial intelligence, such as ChatGPT, demonstrated its ability to produce accurate and valuable assertions by employing text-based prompts and image-fed inputs, significantly reducing the required manual effort. This research presents a way of generating System Verilog assertions using the ChatGPT prompt, presenting an image to the Large Language Models, and requesting the assertions needed for the respective protocol. This approach shows the potential for artificial intelligence to revolutionize functional verification by automating complex tasks, ultimately ensuring faster and more reliable System-on-Chip development. The assertions generated by the Large Language Models are integrated into an existing Advance Peripheral Bus verification environment. This process involves running the assertions on a free EDA Playground platform with all three simulators (Cadence Incisive, Mentor Questa, and Synopsys Verilog Compiler Simulator). The main conclusions are that using ChatGPT-4.0 for generating System Verilog assertions significantly reduces the time and effort required for functional verification, demonstrating its potential to enhance efficiency and accuracy in verifying complex System-on-Chip designs.
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(This article belongs to the Section Artificial Intelligence and Digital Systems Engineering)
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Open AccessArticle
A Simulation-Based Study on Securing Data Sharing for Situational Awareness in a Port Accident Case
by
Juhani Latvakoski, Adil Umer, Topias Nykänen, Jyrki Tihinen and Aleksi Talman
Systems 2024, 12(10), 389; https://doi.org/10.3390/systems12100389 - 25 Sep 2024
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The cyber–physical systems (CPSs) of various stakeholders from the mobility, logistics, and security sectors are needed to enable smart and secure situational awareness operations in a port environment. The motivation for this research arises from the challenges caused by some unexpected events, such
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The cyber–physical systems (CPSs) of various stakeholders from the mobility, logistics, and security sectors are needed to enable smart and secure situational awareness operations in a port environment. The motivation for this research arises from the challenges caused by some unexpected events, such as accidents, in such a multi-stakeholder critical environment. Due to the scale, complexity, and cost and safety challenges, a simulation-based approach was selected as the basis for the study. Prototype-level experimental solutions for dataspaces for secure data sharing and visualization of situational awareness were developed. The secure data-sharing solution relies on the application of verifiable credentials (VCs) to ensure that data consumers have the required access rights to the data/information shared by the data prosumer. A 3D virtual digital twin model is applied for visualizing situational awareness for people in the port. The solutions were evaluated in a simulation-based execution of an accident scenario where a forklift catches fire while loading a docked ship in a port environment. The simulation-based approach and the provided solutions proved to be practical and enabled the smooth study of disaster-type situations. The realized concept of dataspaces is successfully applied here for both daily routine operations and information sharing during accidents in the simulation-based environment. During the evaluation, needs for future research related to perception, comprehension, projection, trust, and security as well as performance and quality of experience were detected. Especially, distributed and secure viewpoints of objects and stakeholders toward real-time situational awareness seem to require further studies.
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Open AccessArticle
An Approach for Multi-Item Product Sales Forecasting Based on Advancing the BCG Matrix with Matrix-Clustering and Time Modeling Techniques
by
Che-Yu Hung and Chien-Chih Wang
Systems 2024, 12(10), 388; https://doi.org/10.3390/systems12100388 - 25 Sep 2024
Abstract
Customized production has greatly diversified product categories, which has altered product life cycles and added complexity to business management. This paper introduces a matrix-clustering technique that integrates k-means clustering with the BCG Matrix, enhanced by time modeling, to offer a comprehensive framework for
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Customized production has greatly diversified product categories, which has altered product life cycles and added complexity to business management. This paper introduces a matrix-clustering technique that integrates k-means clustering with the BCG Matrix, enhanced by time modeling, to offer a comprehensive framework for multi-item product sales forecasting. The approach builds upon existing BCG Matrix outcomes, re-clustering high-selling products more precisely and redefining their relationship with other product lines more objectively. This method addresses the challenge of forecasting situations with limited historical data, providing more accurate sales predictions. Using Taiwan’s sales data, an empirical study on integrated circuit tray products demonstrated the effectiveness of the matrix clustering technique. The results showed improved data utilization, increasing from 35.93% with the original BCG analysis to 52.43% with the combined matrix-clustering and time modeling methods. This study contributes to academic research by presenting a portfolio analysis approach rooted in matrix clustering, which systematically enhances traditional BCG Matrix methods. The proposed framework is adaptable to the unique traits of different portfolios, offering businesses workflows that are efficient, reliable, sustainable, and scalable.
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(This article belongs to the Special Issue Data-Driven Modeling and Predictive Analysis for Business, Social, Economic, and Engineering Applications)
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Open AccessArticle
Influencing Factors of Sustainable Rural Entrepreneurship: A Four-Dimensional Evaluation System Encompassing Entrepreneurs, Economy, Society, and Environment
by
Qigan Shao, Changchang Jiang, Guokai Li and Guojie Xie
Systems 2024, 12(10), 387; https://doi.org/10.3390/systems12100387 - 24 Sep 2024
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The implementation of rural entrepreneurship emerges as a pivotal pathway for fostering rural economic growth. However, unsustainable entrepreneurial endeavors have posed notable ecological threats and environmental degradation. Drawing upon the triple bottom line framework, this research devised a comprehensive evaluation system for sustainable
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The implementation of rural entrepreneurship emerges as a pivotal pathway for fostering rural economic growth. However, unsustainable entrepreneurial endeavors have posed notable ecological threats and environmental degradation. Drawing upon the triple bottom line framework, this research devised a comprehensive evaluation system for sustainable rural entrepreneurship, spanning four dimensions: entrepreneurs, economic, social, and environmental aspects. Employing the fuzzy Decision-Making Trial and Evaluation Laboratory (DANP) approach, we delineated the intricate causal relationships among influencing factors and identified key determinants along with their respective weights. Our findings underscore the prominence of economic dimensions in fostering sustainable rural entrepreneurship. Specifically, entrepreneurial motivation, type of entrepreneurship, financial backing, economic value, favorable policy frameworks, and a conducive business environment emerged as pivotal indicators. Notably, the type of entrepreneurship, financial support, economic value, and favorable policies emerged as propelling factors driving sustainable rural entrepreneurial progress. Conversely, entrepreneurial motivation and the business environment manifested as dependent factors within this causal nexus. This study offers valuable managerial implications for entrepreneurial teams and pertinent government agencies, enabling decision-makers to formulate evidence-based strategies aimed at realizing sustainable rural entrepreneurship.
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Open AccessArticle
Design and Implementation of a Virtual Experimental Teaching System for Deep Energy Exploitation Based on Digital Twin Technology
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Peng Zhao and Haiyan Zhu
Systems 2024, 12(10), 386; https://doi.org/10.3390/systems12100386 - 24 Sep 2024
Abstract
The exploration and development of deep oil and gas resources are becoming the primary focus in the fossil energy sector, thereby increasing the demand for highly skilled engineers. Colleges and universities play a crucial role in cultivating talent in petroleum engineering. However, the
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The exploration and development of deep oil and gas resources are becoming the primary focus in the fossil energy sector, thereby increasing the demand for highly skilled engineers. Colleges and universities play a crucial role in cultivating talent in petroleum engineering. However, the current traditional teaching systems, particularly in experimental practices, face significant challenges, such as low efficiency, limited environments, and a disconnect between theoretical knowledge and practical application. To address these issues and enhance learners’ practical abilities and comprehension, we introduced digital twin technology into the experimental teaching of deep energy exploitation. This paper analyzes innovative pedagogical approaches, with a special emphasis on the real-time visualization of hydraulic fracturing. Supported by the National Key Laboratory of Chengdu University of Technology, our research team developed multiple digital twin platforms for both indoor and onsite hydraulic fracturing. These platforms utilize advanced algorithms and models, enabling real-time data acquisition and visualization analysis. Pilot teaching results demonstrate that the virtual experimental system based on digital twin technology encourages active learner engagement, improves their understanding of digitalization in engineering, and enhances their professional skills in deep oil and gas exploration. The digital twin-based visualization system is a valuable tool for experimental teaching in deep energy exploitation, and its application could serve as a model for other engineering disciplines.
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(This article belongs to the Section Artificial Intelligence and Digital Systems Engineering)
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Open AccessArticle
Student Perceptions of Generative Artificial Intelligence: Investigating Utilization, Benefits, and Challenges in Higher Education
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Ahmad Almassaad, Hayat Alajlan and Reem Alebaikan
Systems 2024, 12(10), 385; https://doi.org/10.3390/systems12100385 - 24 Sep 2024
Abstract
This research explores the use of Generative Artificial Intelligence (GenAI) tools among higher education students in Saudi Arabia, aiming to understand their current perceptions of these technologies. This study utilizes the Technology Acceptance Model (TAM) and the theory of Task-Technology Fit (TTF) to
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This research explores the use of Generative Artificial Intelligence (GenAI) tools among higher education students in Saudi Arabia, aiming to understand their current perceptions of these technologies. This study utilizes the Technology Acceptance Model (TAM) and the theory of Task-Technology Fit (TTF) to examine students’ utilization, perceived benefits, and challenges associated with these tools. A cross-sectional survey was conducted, yielding 859 responses. The findings indicate that 78.7% of students frequently use GenAI tools, while 21.3% do not, often due to a lack of knowledge or interest. ChatGPT emerged as the most widely used GenAI tool, utilized by 86.2% of respondents, followed by other tools like Gemini, Socratic, and CoPilot. Students primarily use these tools for defining or clarifying concepts, translation, generating ideas in writing, and summarizing academic literature. They cite benefits such as ease of access, time-saving, and instant feedback. However, they express concerns about the challenges, including subscription fees, unreliable information, plagiarism, reduced human-to-human interaction, and impacts on learning autonomy. This study underscores the need for increased awareness, ethical guidelines, and robust academic integrity measures to ensure the responsible use of GenAI tools in educational settings. These findings highlight the need for a balanced utilization of GenAI tools in higher education that maximizes benefits while addressing potential challenges and guides the development of policies, curricula, and support systems.
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(This article belongs to the Special Issue Digital Transformation in Education Systems Integrating Generative AI)
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Open AccessArticle
Research on Influencing Factors of Catch-Up in Complex Product Systems: Taking the China Manned Space Engineering Application System as an Example
by
Yuanyuan Chu and Li Xu
Systems 2024, 12(10), 384; https://doi.org/10.3390/systems12100384 - 24 Sep 2024
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In the face of escalating global competition in science and technology, complex product systems (CoPS) have emerged as a significant indicator of comprehensive national strength. The exploration of the catch-up phenomenon holds substantial implications for subsequent development of CoPS. Existing CoPS research often
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In the face of escalating global competition in science and technology, complex product systems (CoPS) have emerged as a significant indicator of comprehensive national strength. The exploration of the catch-up phenomenon holds substantial implications for subsequent development of CoPS. Existing CoPS research often focuses on a single engineering task (such as high-speed rail) and market logic (such as the telecommunications industry), examining the catch-up phenomenon from a single or hard-power perspective. However, the China Manned Space Engineering Application System (CMSEAS), with its significant international influence and dual characteristics of scientific research and engineering development, presents a different scenario. Its market value is difficult to be reflected in a short time, making the relevance of existing research limited. This study selected CMSEAS as a case, and acquired data through interviews, internal meetings, on-site observations, official websites, archives, and other forms. Based on grounded theory, open coding, axial coding, selective coding, and a saturation test were carried out, and a catch-up model of CoPS was constructed by considering various influencing factors. The results show that the catch-up is driven by five major factors: support force is the basic condition for its gradual growth; the management system, technical capability, and human resource are interdependent and serve as the direct drivers of the catch-up; and social influence plays a significant role in propelling the catch-up indirectly. Notably, the setup of a general department, interaction among different factors, cultural soft power, and social influence serve as useful complements to previous studies.
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Open AccessArticle
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
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
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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.
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(This article belongs to the Special Issue The Systems Thinking Approach to Strategic Management)
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Open AccessArticle
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
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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
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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.
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Open AccessArticle
Research on Convergence Media Ecological Model Based on Blockchain
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Hongbin Hu, Yongbin Wang and Guohui Song
Systems 2024, 12(9), 381; https://doi.org/10.3390/systems12090381 - 22 Sep 2024
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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
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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.
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Open AccessArticle
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
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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
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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.
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