Systems

30 pages, 4307 KiB

Open AccessCase Report

Design Thinking in Innovation Processes: A Market Segmentation Tool in Social Networks Research

by Richard Hartman, Roman Kvasnička, Martin Čejka and Ladislav Pilař

Systems 2024, 12(10), 444; https://doi.org/10.3390/systems12100444 - 21 Oct 2024

Viewed by 1021

This paper outlines the purposeful adaptation and utilization of the design thinking process in an innovation case involving market segmentation in social network research. Based on a case study, this paper combines the design thinking process with systems approach methods to foster innovation [...] Read more.

This paper outlines the purposeful adaptation and utilization of the design thinking process in an innovation case involving market segmentation in social network research. Based on a case study, this paper combines the design thinking process with systems approach methods to foster innovation in social network analyses. The paper details the entire process, from the initial stages to the development of a viable solution defined in the final assignment for programmers. The case study emphasizes the effective use of systems thinking tools and demonstrates the value of combining these two approaches to meet the needs of the innovation process. The paper aims to narrate the entire process and highlight critical points in a real-world case study. The focus was on the challenge of creating a market segmentation tool for researchers and marketers in the realm of social network analysis. Full article

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

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31 pages, 26175 KiB

Open AccessArticle

X-RMTV: An Integrated Approach for Requirement Modeling, Traceability Management, and Verification in MBSE

by Pengfei Gu, Yuteng Zhang, Zhen Chen, Chun Zhao, Kunyu Xie, Zhuoyi Wu and Lin Zhang

Systems 2024, 12(10), 443; https://doi.org/10.3390/systems12100443 - 20 Oct 2024

Viewed by 818

Abstract

Formal requirements modeling and traceability management are essential for effectively implementing Model-Based Systems Engineering (MBSE). However, few studies have explored the integration of requirement modeling, traceability management, and verification within MBSE-based systems engineering methodologies. Moreover, the predominant modeling language for MBSE, SysML, lacks [...] Read more.

Formal requirements modeling and traceability management are essential for effectively implementing Model-Based Systems Engineering (MBSE). However, few studies have explored the integration of requirement modeling, traceability management, and verification within MBSE-based systems engineering methodologies. Moreover, the predominant modeling language for MBSE, SysML, lacks sufficient capabilities for requirement description and traceability management and for depicting physical attributes and executable capabilities, making it challenging to verify functional and non-functional requirements collaboratively. This paper proposes an integrated approach for requirement modeling, traceability management, and verification, building on the previously proposed integrated modeling and the simulation language called X language. Our contributions primarily include defining the ReqXL specification for MBSE-oriented requirement modeling based on X language, proposing an algorithm for automatically generating requirement traces, and an integrated framework for requirements modeling, traceability management, and verification was developed by combining the X language with ReqXL. These functionalities were customized on the self-developed integrated modeling and simulation platform, XLab, which is specifically tailored for the X language. Furthermore, we showcase the efficacy and promise of our approach through a case study involving the design of an aircraft electrical system. Full article

(This article belongs to the Special Issue Advanced Model-Based Systems Engineering)

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24 pages, 892 KiB

Open AccessArticle

AI-Enabled Multi-Mode Electronic Information Innovation Practice Teaching Reform Prediction and Exploration in Application-Oriented Universities

by Ying Chen, Jianrong Bao, Geqi Weng, Yanhai Shang, Chao Liu and Bin Jiang

Systems 2024, 12(10), 442; https://doi.org/10.3390/systems12100442 - 20 Oct 2024

Viewed by 978

Abstract

In view of professional learning and practical training in traditional electronic information education of application-oriented universities, this paper constructs electronic information–innovation practice teaching reform (EI-IPTR).In this scheme, by an integrating artificial intelligence (AI)-enabled curriculum with a multi-mode integrated platform and open-style module, big [...] Read more.

In view of professional learning and practical training in traditional electronic information education of application-oriented universities, this paper constructs electronic information–innovation practice teaching reform (EI-IPTR).In this scheme, by an integrating artificial intelligence (AI)-enabled curriculum with a multi-mode integrated platform and open-style module, big data-based comprehensive education resources are optimally configured. We jointly perform the multi-mode construction of innovative practice teaching, professional education stage design, and teaching management improvement, respectively. Subsequently, new practice teaching mechanisms with information technology and its implementation and management methods are established to achieve better teaching effects. It first strengthens learning and intra-group competition to promote students’ innovation in competitions. Then, the AI technique, i.e., attention mechanism-aided long short-term memory (LSTM), is used to model individual students’ abilities. Thus, it accurately evaluates them for teachers to efficiently manage their teaching process in accordance with their aptitude. The teaching reform practice verifies that the AI-enabled big data optimization of teaching reform has a better effect by the above multi-mode innovation. It exhibits an obvious improvement in the quantity and quality of students’ professional knowledge, personal ability, teamwork, and innovative practice. It is also in accordance with the independent completion of practical course teaching in the analysis of big education data. In addition, it realizes high-quality practical teaching by combining multi-mode, multi-level, and open discipline foundations together with efficient, professional skills. Full article

(This article belongs to the Special Issue Information Systems: Discipline, Critical Research and Education)

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35 pages, 1697 KiB

Open AccessArticle

Knowledge Spillovers and Integrated Circuit Innovation Ecosystem Resilience: Evidence from China

by Shiyu Zhou, Xueguo Xu and Fengmei Liu

Systems 2024, 12(10), 441; https://doi.org/10.3390/systems12100441 - 18 Oct 2024

Viewed by 545

Abstract

A resilient innovation ecosystem is an important guarantee for enhancing industrial competitiveness. Knowledge spillover is the key driving force to enhance system resilience. Firstly, we use the MEREC-CoCoSo method to calculate the resilience level of the integrated circuit (IC) innovation ecosystem and analyze [...] Read more.

A resilient innovation ecosystem is an important guarantee for enhancing industrial competitiveness. Knowledge spillover is the key driving force to enhance system resilience. Firstly, we use the MEREC-CoCoSo method to calculate the resilience level of the integrated circuit (IC) innovation ecosystem and analyze the evolution trajectory of the resilience before and after the emergence of the “stuck-neck” problem. Secondly, based on the panel data of 30 provinces (autonomous regions and municipalities directly under the central government) in China from 2011 to 2021, this paper analyzes the mechanism of the impact of intra-regional knowledge spillovers on the resilience of IC innovation ecosystems using the fixed-effect model and analyzes the spatial effect of inter-regional knowledge spillovers on the resilience of innovation ecosystems using the spatial Durbin model under the human capital matrix. Finally, we analyze the regulating role of contractual and relational governance mechanisms and try to open the “black box” of governance. The result shows the following: (1) The polarization of innovative ecosystem resilience of integrated circuits is gradually increasing, with strong spatial agglomeration, high–high agglomeration, low–low agglomeration, and low–high dispersion, and there is an obvious “matthew effect” and “siphon effect”. (2) Both intra- and inter-regional knowledge spillovers contribute significantly to the resilience of IC innovation ecosystems. The contractual governance mechanism can effectively enhance the impact of knowledge spillovers on the resilience of innovation ecosystems in the region, and the relational governance mechanism has a positive impact on the resilience of innovation ecosystems in neighboring regions. (3) Heterogeneity results show that knowledge spillovers within the Pan-PRD region have a significant positive impact on innovation ecosystem resilience. Knowledge spillovers between regions with low innovation capacity have a double effect on innovation ecosystem resilience, and knowledge spillovers between regions with “talent highlands” have a facilitating effect on innovation ecosystem resilience. Accordingly, policy recommendations are put forward to open up channels for innovation knowledge spillover, realize effective allocation of innovation resources, and optimize the system of innovation talents. Full article

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25 pages, 1411 KiB

Open AccessArticle

Identifying Key Factors of Reputational Risk in Finance Sector Using a Linguistic Fuzzy Modeling Approach

by Uğur Hanay, Hüseyin İnce and Gürkan Işık

Systems 2024, 12(10), 440; https://doi.org/10.3390/systems12100440 - 17 Oct 2024

Viewed by 769

Abstract

Management of reputational risk is crucial for financial institutions to establish a solid foundation for strategic decisions, gain customer trust, and enhance resilience against environmental adversities, as they largely operate on digital platforms. Since this becomes even more significant as online transactions and [...] Read more.

Management of reputational risk is crucial for financial institutions to establish a solid foundation for strategic decisions, gain customer trust, and enhance resilience against environmental adversities, as they largely operate on digital platforms. Since this becomes even more significant as online transactions and digital interactions amplify the visibility and potential impact of reputational issues in the context of electronic commerce, it is essential to thoroughly investigate environmental factors to achieve a comprehensive understanding of reputational risk. However, measuring and evaluating their influence on reputational risk is challenging due to their inherent connection to human perception. This study aims to explore the factors influencing reputational risk of financial organizations to mitigate potential reputational losses by addressing uncertainties associated with concepts such as vagueness. The employed methodology integrates the Decision-Making Trial and Evaluation Laboratory and Fuzzy Cognitive Map techniques using linguistic fuzzy terms. This approach focuses on both the direct effects of factors on reputational risk and the indirect effects arising from interdependencies between factors. Linguistic fuzzy variables enable us to consider the hesitation of the experts and the vagueness of human judgment. To validate the results, factors are also weighted using the fuzzy Stepwise Weight Assessment Ratio Analysis (SWARA) method. The most influential factors identified by both methods are market value, revenue, risk culture, shareholder value, firm performance, reputation awareness, and return on equity. Additionally, factors affecting other factors include firm performance, revenue, and growth opportunities. Full article

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16 pages, 660 KiB

Open AccessArticle

Joint Choice of Fresh Food Purchase Channels and Terminal Delivery Service: A Background on Major Public Health Events

by Huiqi Zhu and Tianhua Jiang

Systems 2024, 12(10), 439; https://doi.org/10.3390/systems12100439 - 17 Oct 2024

Viewed by 597

Abstract

The paper aims to analyze the consumer joint choice behavior on fresh food purchase channels and terminal delivery services during major public health events, with the purpose of revealing the underlying influencing factors and behavioral characteristics. First, based on random utility maximization theory, [...] Read more.

The paper aims to analyze the consumer joint choice behavior on fresh food purchase channels and terminal delivery services during major public health events, with the purpose of revealing the underlying influencing factors and behavioral characteristics. First, based on random utility maximization theory, the cross-nested logit model is formulated, which takes into account the influence of socioeconomic attribute factors, service attribute factors, risk perception attribute factors and trust perception attribute factors. Second, a questionnaire survey is conducted, and the obtained data are used to estimate the model parameters and perform an elasticity analysis of the utility variables. The parameter estimation results demonstrate that in the context of major public health events, consumers consider adjusting their attitudes toward e-commerce platforms first when the utility variables are altered, and fresh food purchase channels are easily replaced for consumers who choose unmanned equipment home delivery. The elasticity analysis results suggest that consumers are more willing to buy fresh food through community group-buying channels, are more sensitive to the convenience of the purchase process and are less concerned with delivery time. Although person-to-person contact increases the risk of infection, consumers still prefer attended terminal delivery services. Furthermore, consumers least agree with the effectiveness of body temperature detection methods in public places but feel that an effective way to increase consumer trust in enterprises is to strengthen personnel protection measures. Full article

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16 pages, 5556 KiB

Open AccessArticle

Analyzing Rear-End Crash Counts on Ohio Interstate Freeways Using Advanced Multilevel Modeling

by Omar Almutairi

Systems 2024, 12(10), 438; https://doi.org/10.3390/systems12100438 - 16 Oct 2024

Viewed by 525

Abstract

This study presents a new modeling approach for rear-end crash counts on Ohio’s interstate freeways based on a dataset for 2021 that contains 2745 rear-end crashes. The analysis encompasses 20 interstate freeways, comprising 1833 homogeneous segments and extending over approximately 1313 miles. These [...] Read more.

This study presents a new modeling approach for rear-end crash counts on Ohio’s interstate freeways based on a dataset for 2021 that contains 2745 rear-end crashes. The analysis encompasses 20 interstate freeways, comprising 1833 homogeneous segments and extending over approximately 1313 miles. These interstate freeways exhibit varying safety performances, indicating a significant degree of heterogeneity. A unique rear-end crash risk rate was devised for each interstate, capturing diverse risk profiles. Three distinct models were developed: a standard negative binomial model, an uncorrelated two-level negative binomial model, and a correlated two-level negative binomial model. The correlated two-level negative binomial model demonstrated superior fit, as evidenced by the likelihood ratio test, Akaike information criterion, and Bayesian information criterion. The correlated two-level negative binomial model exhibited enhanced forecasting precision, as measured by the Root Mean Square Error. A significant finding is that the rear-end crash risk rate significantly improves the fit of the models. The study also reveals that rear-end crashes are expected to occur more frequently in urban segments of interstate freeways with high rear-end risk rates. However, rural segments experience no such significant variations in the rear-end crash risk rate. However, an increase in the inner shoulder width is associated with a decrease in expected rear-end crashes. This research offers a valuable methodology for modeling rear-end crashes on interstate freeways, providing insights into the contributing variables that could inform targeted safety improvements. Full article

(This article belongs to the Special Issue Performance Analysis and Optimization in Transportation Systems)

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17 pages, 1626 KiB

Open AccessArticle

Systems Thinking Principles for Making Change

by Martin Reynolds

Systems 2024, 12(10), 437; https://doi.org/10.3390/systems12100437 - 16 Oct 2024

Viewed by 939

Abstract

Traditionally, systems thinking support has relied on an ever-increasing plethora of systems tools, methods, and approaches. Arguably though, such support requires something different from, and more accessible than, detailed instruction on somewhat abstract laws and detailed principles and/or constitutive rules associated with conventional [...] Read more.

Traditionally, systems thinking support has relied on an ever-increasing plethora of systems tools, methods, and approaches. Arguably though, such support requires something different from, and more accessible than, detailed instruction on somewhat abstract laws and detailed principles and/or constitutive rules associated with conventional systems approaches or systems ‘tools of the trade’. For busy managers and decision makers working in often-stressful conditions, what is perhaps more valued are simple principles for enabling systems thinking in practice. Such principles should acknowledge and build on existing (multi)disciplinary skill sets and expertise, allowing for more meaningful interdisciplinary support amongst professions, as part of a nested transdisciplinary support for addressing wider social challenges. This monograph offers three principles of systems thinking in practice (STiP): relational STiP, perspective STiP, and adaptive STiP. They each have two sets of operational principles applicable to first-order and second-order practice, respectively. The three general principles are nested in an overriding principle of STiP as praxis (theory-informed action or thinking in practice) manifest in the need for being both systemic and systematic. The three principles represent a distilled expression of a systematic literacy of systems thinking, a literacy that speaks to the systemic sensibilities of Inter-relationships, Perspectives, and Boundaries (sometimes referred collectively as IPB), associated with any area of intervention. Drawing on metaphors of bricolage, conversation, and performance, and building on philosophical foundations of boundary critique, the three principles provide for a requisite systems literacy (as an emergent property of systemic sensibilities and systems thinking literacy) for enabling appropriate STiP capabilities to flourish when making a meaningful change. Full article

(This article belongs to the Special Issue The Systems Thinking Approach to Strategic Management)

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1 pages, 207 KiB

Open AccessCorrection

Correction: Spours, K. From Learning Ecologies to a Social Ecosystem Model for Learning and Skills. Systems 2024, 12, 324

by Ken Spours

Systems 2024, 12(10), 436; https://doi.org/10.3390/systems12100436 - 16 Oct 2024

Viewed by 307

Abstract

In the published article [...] Full article

20 pages, 3421 KiB

Open AccessArticle

Circular–Sustainable–Reliable Waste Management System Design: A Possibilistic Multi-Objective Mixed-Integer Linear Programming Model

by Erfan Babaee Tirkolaee

Systems 2024, 12(10), 435; https://doi.org/10.3390/systems12100435 - 16 Oct 2024

Viewed by 691

Abstract

Waste management involves the systematic collection, transportation, processing, and treatment of waste materials generated by human activities. It entails a variety of strategies and technologies to diminish environmental impacts, protect public health, and conserve resources. Consequently, providing an effective and comprehensive optimization approach [...] Read more.

Waste management involves the systematic collection, transportation, processing, and treatment of waste materials generated by human activities. It entails a variety of strategies and technologies to diminish environmental impacts, protect public health, and conserve resources. Consequently, providing an effective and comprehensive optimization approach plays a critical role in minimizing waste generation, maximizing recycling and reuse, and safely disposing of waste. This work develops a novel Possibilistic Multi-Objective Mixed-Integer Linear Programming (PMOMILP) model in order to formulate the problem and design a circular–sustainable–reliable waste management network, under uncertainty. The possibility of recycling and recovery are considered across incineration and disposal processes to address the main circular-economy principles. The objectives are to address sustainable development throughout minimizing the total cost, minimizing the environmental impact, and maximizing the reliability of the Waste Management System (WMS). The Lp-metric technique is then implemented into the model to tackle the multi-objectiveness. Several benchmarks are adapted from the literature in order to validate the efficacy of the proposed methodology, and are treated by CPLEX solver/GAMS software in less than 174.70 s, on average. Moreover, a set of sensitivity analyses is performed to appraise different scenarios and explore utilitarian managerial implications and decision aids. It is demonstrated that the configured WMS network is highly sensitive to the specific time period wherein the WMS does not fail. Full article

(This article belongs to the Section Supply Chain Management)

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23 pages, 934 KiB

Open AccessArticle

Cyber Resilience Limitations in Space Systems Design Process: Insights from Space Designers

by Syed Shahzad, Keith Joiner, Li Qiao, Felicity Deane and Jo Plested

Systems 2024, 12(10), 434; https://doi.org/10.3390/systems12100434 - 15 Oct 2024

Viewed by 787

Abstract

Space technology is integral to modern critical systems, including navigation, communication, weather, financial services, and defence. Despite its significance, space infrastructure faces unique cyber resilience challenges exacerbated by the size, isolation, cost, persistence of legacy systems, and lack of comprehensive cyber resilience engineering [...] Read more.

Space technology is integral to modern critical systems, including navigation, communication, weather, financial services, and defence. Despite its significance, space infrastructure faces unique cyber resilience challenges exacerbated by the size, isolation, cost, persistence of legacy systems, and lack of comprehensive cyber resilience engineering standards. This paper examines the engineering challenges associated with incorporating cyber resilience into space design, drawing on insights and experiences from industry experts. Through qualitative interviews with engineers, cybersecurity specialists, project managers, and testers, we identified key themes in engineering methodologies, cybersecurity awareness, and the challenges of integrating cyber resilience into space projects. Participants emphasised the importance of incorporating cybersecurity considerations from the earliest stages of design, advocating for principles such as zero-trust architecture and security by design. Our findings reveal that experts favour Model-Based Systems Engineering (MBSE) and Agile methodologies, highlighting their synergy in developing flexible and resilient systems. The study also underscores the tension between principles-based standards, which offer flexibility but can lead to inconsistent implementation, and compliance-based approaches, which provide clear measures but may struggle to adapt to evolving threats. Additionally, the research recognises significant barriers to achieving cyber resilience, including insider threats, the complexity of testing and validation, and budget constraints. Effective stakeholder engagement and innovative funding models are crucial for fostering a culture of cybersecurity awareness and investment in necessary technologies. This study highlights the need for a comprehensive cyber resilience framework that integrates diverse engineering methodologies and proactive security measures, ensuring the resilience of space infrastructure against emerging cyber threats. Full article

(This article belongs to the Special Issue Cyber Security Challenges in Complex Systems)

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36 pages, 10624 KiB

Open AccessArticle

Predicting Dependent Edges in Nonequilibrium Complex Systems Based on Overlapping Module Characteristics

by Qingyu Zou, Lin Yan, Yue Gong and Jingfei Hou

Systems 2024, 12(10), 433; https://doi.org/10.3390/systems12100433 - 14 Oct 2024

Viewed by 683

Abstract

Problem: Predicting dependency relationships in nonequilibrium systems is a critical challenge in complex systems research. Solution proposed: In this paper, we propose a novel method for predicting dependent edges in network models of nonequilibrium complex systems, based on overlapping module features. This approach [...] Read more.

Problem: Predicting dependency relationships in nonequilibrium systems is a critical challenge in complex systems research. Solution proposed: In this paper, we propose a novel method for predicting dependent edges in network models of nonequilibrium complex systems, based on overlapping module features. This approach addresses the many-to-many dependency prediction problem between nonequilibrium complex networks. By transforming node-based network models into edge-based models, we identify overlapping modular structures, enabling the prediction of many-to-many dependent edges. Experimental evaluation: This method is applied to dependency edge prediction in power and gas networks, curriculum and competency networks, and text and question networks. Results: The results indicate that the proposed dependency edge prediction method enhances the robustness of the network in power–gas networks, accurately identifies supporting relationships in curriculum–competency networks, and achieves better information gain in text–question networks. Conclusion: These findings confirm that the overlapping module-based approach effectively predicts dependencies across various nonequilibrium complex systems in diverse fields. Full article

(This article belongs to the Topic Technologies and Applications of Data-Driven Anomaly Detection in Energy Systems)

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20 pages, 768 KiB

Open AccessArticle

Partnering Implementation in SMEs: The Role of Trust

by Arvind Kumar Vidyarthy and Thyagaraj S. Kuthambalayan

Systems 2024, 12(10), 432; https://doi.org/10.3390/systems12100432 - 14 Oct 2024

Viewed by 563

Abstract

Resource Dependence Theory suggests that (a) power balance with resource interdependency, (b) formal/informal procedures for resource exchange, and (c) matching in goals and operational philosophies positively affect partnering implementation (information exchange and joint decision-making). Additionally, improved partnering implementation positive affects commitment fulfillment and [...] Read more.

Resource Dependence Theory suggests that (a) power balance with resource interdependency, (b) formal/informal procedures for resource exchange, and (c) matching in goals and operational philosophies positively affect partnering implementation (information exchange and joint decision-making). Additionally, improved partnering implementation positive affects commitment fulfillment and dispute resolution. In a setting where SMEs supply to small local retailers, the SMEs do not suffer from low bargaining power and rely on informal contracts, and both firms are compatible. The small trading partners in this study predominantly have face-to-face and telephonic interactions with each other (possible due to the small number). Knowledge of one another and a simple transaction process reduces risk and uncertainty, and leads to trust. In this study, trust is a contextual factor, and we aim to determine if there is a positive effect of (a), (b), and (c) on partnering implementation, and if the effect strengthens with an increase in the level of trust. Survey data are used to calibrate and validate a structural equation model independently. Through empirical research, we aim to identify deviations in results, determine the cause of deviation in the study characteristics, and add explanatory power to research findings. Except for the influence of trust on the positive relationship between informal procedures and partnering implementation, the finding fits with the theoretical bases. With a high level of trust, clarity in time, accuracy, and relevance of information exchanged may be lacking, compromising decision-making and adding to the ambiguity of partnering implementation with an informal agreement. Full article

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15 pages, 1021 KiB

Open AccessArticle

From Reactive to Proactive Infrastructure Maintenance: Remote Sensing Data and Practical Resilience in the Management of Leaky Pipes

by Rasmus Gahrn-Andersen and Maria Festila

Systems 2024, 12(10), 431; https://doi.org/10.3390/systems12100431 - 14 Oct 2024

Viewed by 609

Abstract

The introduction of remote sensing technologies, AI and big data analytics in the utility sector is warranted by the need to provide critical services with the least disruption to customers, but also to enable preventive maintenance, extend the life cycle of infrastructure components [...] Read more.

The introduction of remote sensing technologies, AI and big data analytics in the utility sector is warranted by the need to provide critical services with the least disruption to customers, but also to enable preventive maintenance, extend the life cycle of infrastructure components and reduce grid loss—or overall, to exhibit ‘durability’ and ‘resilience’ when faced with the certainty of breakage and decay. In this paper, we first explore the concept of ‘resilience’ and the nature of practice from a performativist perspective in order to set the scene for discussing the impact of ‘datafication’ on maintenance practices and infrastructure durability. We then describe an instance of introducing remote sensing technologies in district heating network surveillance and leak detection: drone-operated thermographic cameras and underground wire sensors. Based on insights from this case study, we discuss the specificity of data-driven infrastructure maintenance practices, and what it means to exhibit practical resilience in relation to how such practices unfold, interrelate and evolve over time. We reflect on how the use of remote sensing technologies and data analytics (1) potentially changes district heating workers’ epistemic worlds (i.e., how knowledge emerges, is negotiated and ordered in practice) and (2) provides opportunities for ‘messy’ pipe repair work to tacitly adopt proactive and preventive logics to meet continuously evolving organizational and societal needs. Full article

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24 pages, 1713 KiB

Open AccessArticle

Language Styles, Recovery Strategies and Users’ Willingness to Forgive in Generative Artificial Intelligence Service Recovery: A Mixed Study

by Dong Lv, Rui Sun, Qiuhua Zhu, Yue Cheng, Rongrong Wang and Shukun Qin

Systems 2024, 12(10), 430; https://doi.org/10.3390/systems12100430 - 14 Oct 2024

Viewed by 637

Abstract

As the prevalence of generative artificial intelligence (GenAI) in the service sector continues to grow, the impact of the language style and recovery strategies utilized during service failures remains insufficiently explored. This study, grounded in the theory of social presence and dual-process theory, [...] Read more.

As the prevalence of generative artificial intelligence (GenAI) in the service sector continues to grow, the impact of the language style and recovery strategies utilized during service failures remains insufficiently explored. This study, grounded in the theory of social presence and dual-process theory, employed a mixed-method approach combining questionnaire surveys and event-related potential (ERP) experiments to investigate the effect of different language styles (rational vs. humorous) and recovery strategies (gratitude vs. apology) on users’ willingness to forgive during the GenAI service recovery process. It further delves into the chained mediating role of perceived sincerity and social presence in this process. The findings revealed that a humorous language style was more effective in enhancing users’ willingness to forgive compared to a rational style, primarily through the enhancement of users’ perceived sincerity and sense of social presence; recovery strategies played a moderating role in this process, with the positive impact of perceived sincerity on social presence being significantly amplified when the GenAI service adopted an apology strategy. ERP results indicated that a rational language style significantly induced a larger N2 component (cognitive conflict) in apology scenarios, while a humorous style exhibited higher amplitude in the LPP component (positive emotional evaluation). This research unveils the intricate relationships between language style, recovery strategies, and users’ willingness to forgive in the GenAI service recovery process, providing important theoretical foundations and practical guidance for designing more effective GenAI service recovery strategies, and offering new insights into developing more efficacious GenAI service recovery tactics. Full article

(This article belongs to the Topic Theories and Applications of Human-Computer Interaction)

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21 pages, 1838 KiB

Open AccessReview

The Impact of Artificial Intelligence Marketing on E-Commerce Sales

by Mitra Madanchian

Systems 2024, 12(10), 429; https://doi.org/10.3390/systems12100429 - 12 Oct 2024

Viewed by 2901

Abstract

This review explores the influence of AI marketing on e-commerce sales, examining how AI-driven strategies affect key metrics such as customer acquisition and conversion rates. Given the growing importance of AI in online retail, this paper employs a critical review methodology, analyzing 50 [...] Read more.

This review explores the influence of AI marketing on e-commerce sales, examining how AI-driven strategies affect key metrics such as customer acquisition and conversion rates. Given the growing importance of AI in online retail, this paper employs a critical review methodology, analyzing 50 documents from the Scopus database. The analysis reveals that AI tools like chatbots, personalization engines, and predictive analytics significantly enhance e-commerce performance. The study provides practical and theoretical contributions, offering recommendations for businesses and suggesting future research directions. Full article

(This article belongs to the Special Issue Complex Systems for E-commerce and Business Management)

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23 pages, 680 KiB

Open AccessArticle

Risk Assessment of Employing Digital Robots in Process Automation

by Onur Dogan, Ozlem Arslan, Esra Cengiz Tirpan and Selcuk Cebi

Systems 2024, 12(10), 428; https://doi.org/10.3390/systems12100428 - 12 Oct 2024

Viewed by 598

Abstract

Using digital technologies is essential to gain a competitive advantage in the global market by adapting to new business models. While digital technologies make business processes efficient, they enable companies to make faster and more accurate decisions by automating daily and routine process [...] Read more.

Using digital technologies is essential to gain a competitive advantage in the global market by adapting to new business models. While digital technologies make business processes efficient, they enable companies to make faster and more accurate decisions by automating daily and routine process tasks. Robotic process automation (RPA) automates routine and repetitive business processes, allowing many jobs performed by humans to be performed faster. This way, advantages such as reduced error rates, reduced costs, increased production speed, and labor productivity are provided. For the successful implementation of RPA, potential risks need to be considered. In this study, failure mode and effect analysis (FMEA) based on decomposed fuzzy sets (DFSs), a new extension of intuitionistic fuzzy sets, has been used to evaluate subjectiveness in expert judgments. Differing from the other extensions of fuzzy set theory, the advantage of DFSs is to simultaneously consider decision-makers’ optimistic and pessimistic answers. Thus, the answer given by the decision-maker to the positive and negative questions on the same subject defines the indeterminacy of the decision-maker, and the method takes this indeterminacy into account in the evaluation. This study assesses and evaluates the potential risks of six digital robots in process automation. Thirteen risks were individually assessed for each automated process. This study found “Sustainability challenge” critical in three processes, “Absence of governance management” in two, and “Security“ in one. Variability in risk importance arose from process vulnerabilities. Full article

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

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24 pages, 2160 KiB

Open AccessSystematic Review

Sustainability and Information Systems in the Context of Smart Business: A Systematic Review

by Aws A. Magableh, Afnan Y. Audeh, Lana L. Ghraibeh, Mohammed Akour and Ahmed Shihab Albahri

Systems 2024, 12(10), 427; https://doi.org/10.3390/systems12100427 - 12 Oct 2024

Viewed by 601

Abstract

In recent years, calls have increased for adherence to standards that ensure sustainability, including the global initiative presented by the United Nations with 17 Sustainable Development Goals (SDGs) to ensure a more sustainable future. Achieving these goals is extremely important, as institutions have [...] Read more.

In recent years, calls have increased for adherence to standards that ensure sustainability, including the global initiative presented by the United Nations with 17 Sustainable Development Goals (SDGs) to ensure a more sustainable future. Achieving these goals is extremely important, as institutions have sought to integrate technology, especially business intelligence, into their operations to ensure their achievement. This study aims to provide a systematic literature review of the intersection of information systems and sustainability in business intelligence. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology was utilized to select high-quality studies from various databases, including ScienceDirect, IEEE Xplore, and Scopus, to be included in this review. The methodology resulted in 32 studies taxonomized into four main categories covering different aspects of the intersection of information systems and sustainability. This study discusses integrating information systems and sustainability in various sectors, such as tourism, health, urban, and other sectors, with different technologies, such as Blockchain, IoT, Industry 4.0, and other innovations. Moreover, the information system types implemented to support sustainability practices in different domains are highlighted. Full article

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

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15 pages, 9635 KiB

Open AccessArticle

An Integrated Smart Manufacturing System for Customer Design Experience

by Ying-Jiun Hsieh, Wan-Ju Huang and Li-Hung Lan

Systems 2024, 12(10), 426; https://doi.org/10.3390/systems12100426 - 12 Oct 2024

Viewed by 487

Abstract

This study focuses on the development of an integrated smart manufacturing system (ISMS) that centers on custom design experiences, utilizing virtual reality (VR) and cloud integration to enhance operational value. Through a Design for Excellence (DFX) approach, this system aims to seamlessly incorporate [...] Read more.

This study focuses on the development of an integrated smart manufacturing system (ISMS) that centers on custom design experiences, utilizing virtual reality (VR) and cloud integration to enhance operational value. Through a Design for Excellence (DFX) approach, this system aims to seamlessly incorporate customer-specific designs into the manufacturing process, thus aligning closely with consumer needs. The research contributes significantly by (1) implementing a customer-focused design system that enhances sales benefits, (2) enabling a smooth transition from design drawings to automated production, thereby increasing manufacturing efficiency, and (3) establishing a digital transformation framework that integrates design, production, and marketing to boost overall business value. Full article

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

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20 pages, 1708 KiB

Open AccessArticle

Identifying the Determinants of Academic Success: A Machine Learning Approach in Spanish Higher Education

by Ana María Sánchez-Sánchez, Jorge Daniel Mello-Román, Marina Segura and Adolfo Hernández

Systems 2024, 12(10), 425; https://doi.org/10.3390/systems12100425 - 12 Oct 2024

Viewed by 796

Abstract

Academic performance plays a key role in assessing the quality and equity of a country’s educational system. Studying the aspects or factors that influence university academic performance is an important research opportunity. This article synthesizes research that employs machine learning techniques to identify [...] Read more.

Academic performance plays a key role in assessing the quality and equity of a country’s educational system. Studying the aspects or factors that influence university academic performance is an important research opportunity. This article synthesizes research that employs machine learning techniques to identify the determinants of academic performance in first-year university students. A total of 8700 records from the Complutense University of Madrid corresponding to all incoming students in the academic year 2022–2023 have been analyzed, for which information was available on 28 variables related to university access, academic performance corresponding to the first year, and socioeconomic characteristics. The methodology included feature selection using Random Forest and Extreme Gradient Boosting (XGBoost) to identify the main predictors of academic performance and avoid overfitting in the models, followed by analysis with four different machine learning techniques: Linear Regression, Support Vector Regression, Random Forest, and XGBoost. The models showed similar predictive performance, also highlighting the coincidence in the predictors of academic performance both at the end of the first semester and at the end of the first academic year. Our analysis detects the influence of variables that had not appeared in the literature before, the admission option and the number of enrolled credits. This study contributes to understanding the factors that impact academic performance, providing key information for implementing educational policies aimed at achieving excellence in university education. This includes, for example, peer tutoring and mentoring where high- and low-performing students could participate. Full article

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26 pages, 1495 KiB

Open AccessArticle

The Influencing Mechanism of Robustness of Emergency Medical Logistics: Mediating Role of Knowledge Integration

by Jianhua Zhang, Ziao Cao, Xiaoqian Zhou, Jinyan Liu and Hongyu Jia

Systems 2024, 12(10), 424; https://doi.org/10.3390/systems12100424 - 11 Oct 2024

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Abstract

Drawing on the social capital theory, the research examines the impact of network size, network centrality, trust, and regulation on the knowledge integration and robustness of emergency medical logistics. Additionally, the research seeks to provide deeper insight into the link between the variables [...] Read more.

Drawing on the social capital theory, the research examines the impact of network size, network centrality, trust, and regulation on the knowledge integration and robustness of emergency medical logistics. Additionally, the research seeks to provide deeper insight into the link between the variables by studying how knowledge integration mediates the relationship between independent variables and the robustness of emergency medical logistics. The study utilized structural equation modeling to assess the underlying assumptions of the research model. A total of 465 valid questionnaires were collected from government departments, hospitals, social teams, and enterprises. The data processing and analysis were conducted using SPSS 23.0 and AMOS 24.0 software. The study’s outcome indicated that network size and network centrality have indirect effects on the robustness of emergency medical logistics through the intermediate variable of knowledge integration, but neither has a direct effect. Moreover, knowledge integration has a significant positive impact on the robustness of emergency medical logistics. Both trust and regulation have positive effects on the robustness of emergency medical logistics, and they also have positive effects on the robustness of emergency medical logistics through knowledge integration. This study is the inaugural exploration of the correlation between knowledge integration and the robustness of emergency medical logistics. It adds to the literature by providing evidence that knowledge integration is an essential emergency organization’s aide in promoting the robustness of emergency medical logistics. The findings of this study establish a strong theoretical foundation and practical significance for ensuring and improving the level of effectiveness in emergency medical logistics management. Full article

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14 pages, 2492 KiB

Open AccessArticle

Exponential Random Graph Model Perspective: Formation and Evolution of a Collaborative Innovation Network in China’s New Energy Vehicle Industry

by Mengxing Song, Lingling Guo and Jianwei Shen

Systems 2024, 12(10), 423; https://doi.org/10.3390/systems12100423 - 11 Oct 2024

Viewed by 645

Abstract

In light of the crucial role of collaborative R&D in advancing technology within the new energy vehicle industry, this study seeks to explore ways to overcome the barriers to technological innovation by establishing an effective collaborative innovation network. Utilizing joint patent-authorized data from [...] Read more.

In light of the crucial role of collaborative R&D in advancing technology within the new energy vehicle industry, this study seeks to explore ways to overcome the barriers to technological innovation by establishing an effective collaborative innovation network. Utilizing joint patent-authorized data from China’s new energy vehicles between 2005 and 2019, the collaborative innovation network was developed, and the Exponential Random Graph Model (ERGM) was employed to analyze its formation and evolution mechanisms. The results indicate that the network has undergone significant expansion, closely linked to strong national policy support and the active involvement of innovation participants. The network exhibits effects of expansion, transfer, and closure. External attribute analysis revealed the Matthew effect and geographical compatibility effect and found that organizational compatibility tends to foster complementary cooperation. The findings offer insights into optimizing collaborative innovation networks in the NEVs industry and suggest strategies for policymakers and industry players to promote collaborative innovation. Full article

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22 pages, 1572 KiB

Open AccessArticle

A Holistic Quality Improvement Model for Food Services: Integrating Fuzzy Kano and PROMETHEE II

by Claudia Editt Tornero Becerra, Fagner José Coutinho de Melo, Larissa de Arruda Xavier, André Philippi Gonzaga de Albuquerque, Aline Amaral Leal Barbosa, Lucas Ambrósio Bezerra de Oliveira, Raíssa Souto Maior Corrêa de Carvalho and Denise Dumke de Medeiros

Systems 2024, 12(10), 422; https://doi.org/10.3390/systems12100422 - 10 Oct 2024

Viewed by 707

Abstract

Service quality is crucial to consumer loyalty. However, it is challenging to understand and meet customer expectations effectively. Translating customer feedback into actionable insights in the service industry poses difficulties, particularly without a systematic approach that balances customer requirements with business constraints and [...] Read more.

Service quality is crucial to consumer loyalty. However, it is challenging to understand and meet customer expectations effectively. Translating customer feedback into actionable insights in the service industry poses difficulties, particularly without a systematic approach that balances customer requirements with business constraints and strategic objectives. This study proposes an approach that integrates customer perspectives into multi-criteria decision models by utilizing the fuzzy Kano model to capture service perceptions and minimize response uncertainty. It also uses 5W2H and PROMETHEE II to formulate service improvement actions and establish prioritizations, providing a structured framework for managerial implementation. When implemented in the food truck sector, this framework proves effective in addressing unique challenges, enhancing service quality, boosting customer satisfaction, and fostering loyalty. This study offers a valuable contribution to management by presenting a replicable model that aids managers in making strategic decisions, aligning customer perspectives with management efforts, and providing insights for continuously improving initiatives within the food service industry. Full article

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48 pages, 7424 KiB

Open AccessArticle

Dynamic Evolution Analysis of Digital Technology Multilayer Convergence Networks

by Qianying Wang, Tingli Liu, Tingyang Huang and Qingqing Tian

Systems 2024, 12(10), 421; https://doi.org/10.3390/systems12100421 - 9 Oct 2024

Viewed by 792

Abstract

This paper constructs a digital technology multilayer convergence network model to explore the mechanisms of digital technology convergence. The analysis is based on patent data from China’s A-share listed companies from 2012 to 2021. The results show a continuous increase in network scale [...] Read more.

This paper constructs a digital technology multilayer convergence network model to explore the mechanisms of digital technology convergence. The analysis is based on patent data from China’s A-share listed companies from 2012 to 2021. The results show a continuous increase in network scale and structural complexity, with intensified cross-domain interactions. The company collaboration subnetwork evolved from decentralization to a more centralized structure, while the technology convergence subnetwork expanded and became increasingly complex. Core technologies maintained dominant positions, and the co-evolution between companies and technologies showed sustained development. This study reveals intricate interdependencies between technological convergence and company collaboration, providing theoretical insights and practical implications for digital technology innovation and strategic decision-making. Full article

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15 pages, 2357 KiB

Open AccessArticle

Dynamic Multi-Granularity Translation System: DAG-Structured Multi-Granularity Representation and Self-Attention

by Shenrong Lv, Bo Yang, Ruiyang Wang, Siyu Lu, Jiawei Tian, Wenfeng Zheng, Xiaobing Chen and Lirong Yin

Systems 2024, 12(10), 420; https://doi.org/10.3390/systems12100420 - 9 Oct 2024

Viewed by 555

Abstract

In neural machine translation (NMT), the sophistication of word embeddings plays a pivotal role in the model’s ability to render accurate and contextually relevant translations. However, conventional models with single granularity of word segmentation cannot fully embed complex languages like Chinese, where the [...] Read more.

In neural machine translation (NMT), the sophistication of word embeddings plays a pivotal role in the model’s ability to render accurate and contextually relevant translations. However, conventional models with single granularity of word segmentation cannot fully embed complex languages like Chinese, where the granularity of segmentation significantly impacts understanding and translation fidelity. Addressing these challenges, our study introduces the Dynamic Multi-Granularity Translation System (DMGTS), an innovative approach that enhances the Transformer model by incorporating multi-granularity position encoding and multi-granularity self-attention mechanisms. Leveraging a Directed Acyclic Graph (DAG), the DMGTS utilizes four levels of word segmentation for multi-granularity position encoding. Dynamic word embeddings are also introduced to enhance the lexical representation by incorporating multi-granularity features. Multi-granularity self-attention mechanisms are applied to replace the conventional self-attention layers. We evaluate the DMGTS on multiple datasets, where our system demonstrates marked improvements. Notably, it achieves significant enhancements in translation quality, evidenced by increases of 1.16 and 1.55 in Bilingual Evaluation Understudy (BLEU) scores over traditional static embedding methods. These results underscore the efficacy of the DMGTS in refining NMT performance. Full article

(This article belongs to the Section Artificial Intelligence and Digital Systems Engineering)

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37 pages, 2995 KiB

Open AccessArticle

Quality Improvement Decisions in Service Supply Chains with Collaborative and Free-Riding Behaviors

by Wenfang Shang, Zaixin Han, Zhaoguang Xu and Tao Li

Systems 2024, 12(10), 419; https://doi.org/10.3390/systems12100419 - 8 Oct 2024

Viewed by 508

Abstract

The dominant position of a member within a service supply chain plays a crucial role in fostering a willingness to improve service quality. Consequently, this study examines a service supply chain comprising a supplier and an integrator, aiming to investigate the influence of [...] Read more.

The dominant position of a member within a service supply chain plays a crucial role in fostering a willingness to improve service quality. Consequently, this study examines a service supply chain comprising a supplier and an integrator, aiming to investigate the influence of four different power structures, namely, supplier-led, integrator-led, supplier–integrator power balance, and supplier–integrator centralized decision, on the decision-making process for service quality improvement by members. The findings highlight that the optimal willingness to improve service quality in a service supply chain is not necessarily infinitely close to 100%, and is influenced by factors such as revenue share, cost, effect, and dominant position. In cases where the collaborative improvement effect is weak, even the dominant member may display a limited willingness, rendering centralized decision-making meaningless. If the collaborative improvement effect surpasses the combined independent improvement effects, the dominant position can help strengthen willingness, although it may not always result in higher profits. Conversely, a power-balanced scenario can be advantageous in achieving the highest profit for the entire supply chain. Full article

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20 pages, 3744 KiB

Open AccessArticle

Optimal Scheduling of PV Panel Cleaning and Policy Implications Considering Uncertain Dusty Weather Conditions in the Middle East

by Abubaker Gebreil Siddig Matar and Heungjo An

Systems 2024, 12(10), 418; https://doi.org/10.3390/systems12100418 - 8 Oct 2024

Viewed by 737

Abstract

Airborne dust easily accumulates on the top of solar panel surfaces and reduces the output power in arid regions. A commonly used mitigation solution for dust deposition issues is cleaning PV panels periodically. However, cleaning frequency affects the economic viability of solar PV [...] Read more.

Airborne dust easily accumulates on the top of solar panel surfaces and reduces the output power in arid regions. A commonly used mitigation solution for dust deposition issues is cleaning PV panels periodically. However, cleaning frequency affects the economic viability of solar PV systems, resulting in a trade-off between cleaning costs and energy loss costs. To address this issue, this study relates several metrics and develops a generic framework based on simulation and optimization to determine the optimal cleaning interval. Based on the computational tests, the optimal cleaning interval in Abu Dhabi is determined to be 34 days, which is longer than the currently recommended cleaning interval of 28 days. This study also identifies that energy recovery is responsive to decreases in unit cleaning costs in the presence of high electricity tariffs, whereas total cost savings show sensitivity when electricity tariffs are low. Finally, this study discusses energy policy implications by presenting an innovative concept involving the introduction of a cleaning subsidy which could reshape energy system cost dynamics, making PV systems economically competitive beyond the conventional levelized cost of electricity. Full article

(This article belongs to the Section Systems Engineering)

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16 pages, 1921 KiB

Open AccessArticle

Investigation of Traffic System with Traffic Restriction Scheme in the Presence of Automated and Human-Driven Vehicles

by Dong Ding, Yadi Hou, Fulong Shen, Pengyun Chong and Yifeng Niu

Systems 2024, 12(10), 417; https://doi.org/10.3390/systems12100417 - 8 Oct 2024

Viewed by 573

Abstract

In the context of transportation development, the simultaneous emergence of automated vehicles (AVs) and human-driven vehicles (HDVs) can lead to varied traffic system performance. For the purpose of improving traffic systems, this paper proposes a traffic restriction scheme only for HDVs. We develop [...] Read more.

In the context of transportation development, the simultaneous emergence of automated vehicles (AVs) and human-driven vehicles (HDVs) can lead to varied traffic system performance. For the purpose of improving traffic systems, this paper proposes a traffic restriction scheme only for HDVs. We develop a variational inequality (VI) model to describe travel mode and route choices under this restriction scheme and design an algorithm to solve the model. The proposed model and algorithm are applied to a Sioux Falls network example to evaluate the effects of the traffic restriction scheme. Our findings indicate that the scheme improves overall social welfare, with a higher proportion of restricted travelers leading to greater social welfare as well as increased travel demand due to changes in capacity. However, some lower exogenous monetary factors lead to negative social welfare, as the presence of AVs may exacerbate road congestion. Additionally, advancements in technology are needed to adjust the weightings of travel time and congestion level estimates to further enhance social welfare. These results offer valuable insights for traffic demand management in traffic systems with a mix of AVs and HDVs. Full article

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27 pages, 2585 KiB

Open AccessArticle

Technology-Driven Financial Risk Management: Exploring the Benefits of Machine Learning for Non-Profit Organizations

by Hao Huang

Systems 2024, 12(10), 416; https://doi.org/10.3390/systems12100416 - 8 Oct 2024

Viewed by 1613

Abstract

This study explores how machine learning can optimize financial risk management for non-profit organizations by evaluating various algorithms aimed at mitigating loan default risks. The findings indicate that ensemble learning models, such as random forest and LightGBM, significantly improve prediction accuracy, thereby enabling [...] Read more.

This study explores how machine learning can optimize financial risk management for non-profit organizations by evaluating various algorithms aimed at mitigating loan default risks. The findings indicate that ensemble learning models, such as random forest and LightGBM, significantly improve prediction accuracy, thereby enabling non-profits to better manage financial risk. In the context of the 2008 subprime mortgage crisis, which underscored the volatility of financial markets, this research assesses a range of risks—credit, operational, liquidity, and market risks—while exploring both traditional machine learning and advanced ensemble techniques, with a particular focus on stacking fusion to enhance model performance. Emphasizing the importance of privacy and adaptive methods, this study advocates for interdisciplinary approaches to overcome limitations such as stress testing, data analysis rule formulation, and regulatory collaboration. The research underscores machine learning’s crucial role in financial risk control and calls on regulatory authorities to reassess existing frameworks to accommodate evolving risks. Additionally, it highlights the need for accurate data type identification and the potential for machine learning to strengthen financial risk management amid uncertainty, promoting interdisciplinary efforts that address broader issues like environmental sustainability and economic development. Full article

(This article belongs to the Special Issue Data-Driven Modeling and Predictive Analysis for Business, Social, Economic, and Engineering Applications)

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21 pages, 1108 KiB

Open AccessReview

The Role of Complex Systems in Predictive Analytics for E-Commerce Innovations in Business Management

by Mitra Madanchian

Systems 2024, 12(10), 415; https://doi.org/10.3390/systems12100415 - 5 Oct 2024

Viewed by 1027

Abstract

This review explores the incorporation of complex systems theory into predictive analytics in the e-commerce sector, particularly emphasizing recent advancements in business management. By analyzing the intersection of these two domains, the review emphasizes the potential of complex systems models—including agent-based modeling and [...] Read more.

This review explores the incorporation of complex systems theory into predictive analytics in the e-commerce sector, particularly emphasizing recent advancements in business management. By analyzing the intersection of these two domains, the review emphasizes the potential of complex systems models—including agent-based modeling and network theory—to improve the precision and efficacy of predictive analytics. It will provide a comprehensive overview of the applications of emergent predictive analytics techniques and tools, including real-time data analysis and machine learning, in inventory optimization, dynamic pricing, and personalization of customer experiences. In addition, this review will suggest future research directions to advance the discipline and address the technical, ethical, and practical challenges encountered during this integration phase. Full article

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Systems, Volume 12, Issue 10 (October 2024) – 61 articles

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