Systems

22 pages, 8432 KiB

Open AccessArticle

Multi-Step Peak Passenger Flow Prediction of Urban Rail Transit Based on Multi-Station Spatio-Temporal Feature Fusion Model

by Jianan Sun, Xiaofei Ye, Xingchen Yan, Tao Wang and Jun Chen

Systems 2025, 13(2), 96; https://doi.org/10.3390/systems13020096 (registering DOI) - 3 Feb 2025

Viewed by 102

Abstract

Accurate prediction of station passenger flow is crucial for optimizing rail transit efficiency, but peak passenger flow in urban rail transit (URT) is often disrupted by random events, making predictions challenging. In this paper, in order to solve this challenge, the Bi-graph Graph [...] Read more.

Accurate prediction of station passenger flow is crucial for optimizing rail transit efficiency, but peak passenger flow in urban rail transit (URT) is often disrupted by random events, making predictions challenging. In this paper, in order to solve this challenge, the Bi-graph Graph Convolutional Spatio-Temporal Feature Fusion Network (BGCSTFFN)-based model is introduced to capture complex spatio-temporal correlations. A combination of a graph convolutional neural network and a Transformer is used. The model separately inputs land use (point of interest, POI) and station adjacency information as features into the BGCSTFFN model, using the Pearson correlation coefficient matrix, which is evaluated on real passenger flow dataset from 1 to 25 January 2019 in Hangzhou. The results showed that the model consistently provided the best prediction results across different datasets and prediction tasks compared to other baseline models. In addition, in tasks involving predictions with different combinations of inputs and prediction steps, the model showed superior performance at multiple prediction steps. Its practical application is validated by comparing the results of passenger flow prediction for different types of stations. In addition, the impact of these features on the prediction accuracy and the generalization ability of the model were verified by designing ablation experiments and testing on different datasets. Full article

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

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21 pages, 1908 KiB

Open AccessArticle

Crowd Management at Turnstiles in Metro Stations: A Pilot Study Based on Observation and Microsimulation

by Sebastian Seriani, Vicente Aprigliano, Alvaro Peña, Alexis Garrido, Bernardo Arredondo, Vinicius Minatogawa, Claudio Falavigna and Taku Fujiyama

Systems 2025, 13(2), 95; https://doi.org/10.3390/systems13020095 (registering DOI) - 1 Feb 2025

Viewed by 323

Abstract

Crowd management at turnstiles in metro stations is a critical task for ensuring safety, efficiency, and comfort for passengers. A methodology based on observation and microsimulation provides an advanced understanding and optimization of crowd flow through these turnstiles. The aim is to optimize [...] Read more.

Crowd management at turnstiles in metro stations is a critical task for ensuring safety, efficiency, and comfort for passengers. A methodology based on observation and microsimulation provides an advanced understanding and optimization of crowd flow through these turnstiles. The aim is to optimize crowd management and prevent overcrowding and delays at metro turnstiles through innovative solutions. The methodology is based on simulating passenger movements through turnstiles to observe and optimize crowd behavior. The results show that passenger decisions (e.g., choosing which turnstile to use, adjusting pace) are based on perceived crowd density, level of service, and usage of space. For instance, the number of turnstiles, their location, and the layout are important variables to be considered in the decision-making sequence. These decisions can be influenced by parameters like turnstile availability, walking paths, and real-time data (e.g., density of passengers). The methodology can help metro operators decide where to place additional turnstiles or adjust operational schedules. By simulating crowd behavior, operators can make informed decisions to reduce congestion and improve the efficiency of turnstile usage. This methodology could be implemented in various metro systems to optimize operations during different crowd conditions and peak times, ensuring smooth, safe, and efficient passenger flow. Full article

(This article belongs to the Special Issue Optimization-Based Decision-Making Models in Rail Systems Engineering)

19 pages, 358 KiB

Open AccessArticle

System-Level Critical Success Factors for BIM Implementation in Construction Management: An AHP Approach

by Filippo Maria Ottaviani, Giovanni Zenezini, Francesca Saba, Alberto De Marco and Lorenzo Gavinelli

Systems 2025, 13(2), 94; https://doi.org/10.3390/systems13020094 (registering DOI) - 31 Jan 2025

Viewed by 402

Abstract

Digital tools are transforming the construction industry, reshaping how projects are designed, managed, and delivered. Building Information Modeling (BIM), a cornerstone of this transformation, requires a systemic approach because its implementation spans several organization functions, involves multiple stakeholders, and encompasses all phases of [...] Read more.

Digital tools are transforming the construction industry, reshaping how projects are designed, managed, and delivered. Building Information Modeling (BIM), a cornerstone of this transformation, requires a systemic approach because its implementation spans several organization functions, involves multiple stakeholders, and encompasses all phases of the project life cycle. While extensive literature examines BIM adoption, there is no consensus on its key enablers and barriers nor a ranking of their impact on implementation success. This study investigates the system-level critical success factors (CSFs) for BIM adoption in construction management. First, it reviews earlier literature, identifying 18 CSFs across six dimensions: change management, process efficiency, regulatory compliance, strategic alignment, technology integration, and user training and support. Next, it utilizes the AHP method to rank the CSFs based on the data collected from 31 construction professionals. Results highlight the importance of aligning BIM initiatives with organizational strategies, streamlining workflows, fostering collaboration, and ensuring compliance with evolving regulations. The research concludes that effective BIM implementation requires holistic strategies that emphasize leadership, scalable technology integration, comprehensive training, and adaptability. By addressing these system-level CSFs, organizations can enhance efficiency, drive innovation, and strengthen resilience in an evolving construction landscape. Full article

(This article belongs to the Special Issue Systems Approach to Innovation in Construction Projects)

25 pages, 1301 KiB

Open AccessArticle

Pricing and Service Decision in a Dual-Channel System Considering Zone of Service Tolerance

by Qingren He, Xinru Lei and Ping Wang

Systems 2025, 13(2), 93; https://doi.org/10.3390/systems13020093 (registering DOI) - 31 Jan 2025

Viewed by 309

Abstract

In the dual-channel retail industry, excessive enthusiasm in offline retailers’ services often extends beyond the customer’s “interpersonal distance zone”, leading to psychological discomfort for customers and a subsequent loss of demand. This situation can trap retailers in a dilemma known as the “service [...] Read more.

In the dual-channel retail industry, excessive enthusiasm in offline retailers’ services often extends beyond the customer’s “interpersonal distance zone”, leading to psychological discomfort for customers and a subsequent loss of demand. This situation can trap retailers in a dilemma known as the “service trap”. To address this issue, we introduce the concept of the zone of service tolerance, which encompasses desired and adequate levels of service, into a dual-channel supply chain consisting of an online channel manufacturer and an offline retailer. We incorporate the zone of service tolerance into the demand function of the offline retailer and establish its profit function, a dynamic game theory to demonstrate the existence of a linkage mechanism between the optimal selling price and service level, providing the conditions for such a mechanism to exist. Additionally, we establish conditions for offline retailers to avoid over-servicing or under-servicing and consider the impacts of these conditions, and we reveal the stability conditions of the offline retailers’ service decisions. Our findings indicate that both over- and under-servicing can lead to customer churn. For newly launched products, offline retailers risk losing customers by adopting a sales strategy focused on high profits and moderate sales (under-servicing). Similarly, for products nearing removal from the shelves, they risk losing customers by adopting a sales strategy focused on low profits and high sales (over-servicing). Furthermore, under certain ranges for the service sensitivity factor, desired service, or adequate service, the optimal service provided by offline retailers remains robust regardless of the manufacturer’s optimal selling price. This greatly simplifies the offline retailer’s decision-making process regarding service levels, as they can directly focus on providing the desired service without factoring in the manufacturer’s pricing strategy. Full article

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

24 pages, 1389 KiB

Open AccessArticle

Optimization of EMS Station Layout Based on a New Decision Support Framework

by Peng Yang, Bozheng Zhang and Jingrong Yang

Systems 2025, 13(2), 92; https://doi.org/10.3390/systems13020092 (registering DOI) - 31 Jan 2025

Viewed by 258

Abstract

The layout of emergency medical services (EMS) is of vital importance. A well-planned layout significantly impacts the timeliness of response and operational efficiency, which are crucial for saving lives and mitigating injury severity. This paper presents a novel decision support framework for optimizing [...] Read more.

The layout of emergency medical services (EMS) is of vital importance. A well-planned layout significantly impacts the timeliness of response and operational efficiency, which are crucial for saving lives and mitigating injury severity. This paper presents a novel decision support framework for optimizing EMS station layout. Employing the k-means clustering algorithm in combination with the elbow method and silhouette coefficient method, we conduct a clustering analysis on a patient call record dataset. Comprising 166,161 emergency center call records in the Shanghai area over one year, this dataset serves as the basis for our analysis. The analysis results are applied to determine EMS station locations, with the average ambulance patient pickup time as the evaluation criterion. A simulation model is utilized to validate the effectiveness and reliability of the decision-making framework. An experimental analysis reveals that compared with the existing EMS station layout, the proposed framework reduces the average patient pickup time from 11.033 min to 9.661 min, marking a 12.441% decrease. Furthermore, a robustness test of the proposed scheme is carried out. The results indicate that even when some first-aid sites fail, the average response time can still be effectively controlled within 9.9 min. Through this robustness analysis, the effectiveness and reliability of the decision framework are demonstrated, offering more efficient and reliable support for the EMS system. Full article

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

18 pages, 1780 KiB

Open AccessArticle

Enhancing Efficiency in the Healthcare Sector Through Multi-Objective Optimization of Freight Cost and Delivery Time in the HIV Drug Supply Chain Using Machine Learning

by Amirkeyvan Ghazvinian, Bo Feng and Junwen Feng

Systems 2025, 13(2), 91; https://doi.org/10.3390/systems13020091 - 31 Jan 2025

Viewed by 395

Abstract

The purpose of this paper is to examine the optimization of the HIV drug supply chain, with a dual focus on minimizing freight costs and delivery times. With the help of a dataset containing 10,325 instances of supply chain transactions, key variables, including [...] Read more.

The purpose of this paper is to examine the optimization of the HIV drug supply chain, with a dual focus on minimizing freight costs and delivery times. With the help of a dataset containing 10,325 instances of supply chain transactions, key variables, including “Country”, “Vendor INCO Term”, and “Shipment Mode”, were examined in order to develop a predictive model using Artificial Neural Networks (ANN) employing a Multi-Layer Perceptron (MLP) architecture. A set of ANN models were trained to forecast “freight cost” and “delivery time” based on four principal design variables: “Line Item Quantity”, “Pack Price”, “Unit of Measure (Per Pack)”, and “Weight (Kilograms)”. According to performance metrics analysis, these models demonstrated predictive accuracy following training. An optimization algorithm, configured with an “active-set” algorithm, was then used to minimize the combined objective function of freight cost and delivery time. Both freight costs and delivery times were significantly reduced as a result of the optimization. This study illustrates the potent application of machine learning and optimization algorithms to the enhancement of supply chain efficiency. This study provides a blueprint for cost reduction and improved service delivery in critical medication supply chains based on the methodology and outcomes. Full article

(This article belongs to the Special Issue Systems Methodology in Sustainable Supply Chain Resilience)

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20 pages, 2656 KiB

Open AccessArticle

An All-Hazards Return on Investment (ROI) Model to Evaluate U.S. Army Installation Resilient Strategies

by Gregory S. Parnell, Robert M. Curry, Eric Specking, Anthony Beger, Randy Buchanan, Susan Wolters, John P. Richards and Patrick R. Ables

Systems 2025, 13(2), 90; https://doi.org/10.3390/systems13020090 - 31 Jan 2025

Viewed by 406

Abstract

The paper describes our project to develop, verify, and deploy an All-Hazards Return of Investment (ROI) model for the U. S. Army Engineer Research and Development Center (ERDC) to provide army installations with a decision support tool for evaluating strategies to make existing [...] Read more.

The paper describes our project to develop, verify, and deploy an All-Hazards Return of Investment (ROI) model for the U. S. Army Engineer Research and Development Center (ERDC) to provide army installations with a decision support tool for evaluating strategies to make existing installation facilities more resilient. The need for increased resilience to extreme weather caused by climate change was required by U.S. code and DoD guidance, as well as an army strategic plan that stipulated an ROI model to evaluate relevant resilient strategies. During the project, the ERDC integrated the University of Arkansas designed model into a new army installation planning tool and expanded the scope to evaluate resilient options from climate to all hazards. Our methodology included research on policy, data sources, resilient options, and analytical techniques, along with stakeholder interviews and weekly meetings with installation planning tool developers. The ROI model uses standard risk analysis and engineering economics terms and analyzes potential installation hazards and resilient strategies using data in the installation planning tool. The ROI model calculates the expected net present cost without the resilient strategy, the expected net present cost with the resilient strategy, and ROI for each resilient strategy. The minimum viable product ROI model was formulated mathematically, coded in Python, verified using hazard scenarios, and provided to the ERDC for implementation. Full article

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

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25 pages, 2361 KiB

Open AccessArticle

How Does Rural Resilience Affect Return Migration: Evidence from Frontier Regions in China

by Yiqing Su, Meiqi Hu and Xiaoyin Zhang

Systems 2025, 13(2), 89; https://doi.org/10.3390/systems13020089 - 31 Jan 2025

Viewed by 336

Abstract

An important way to realize urban–rural integration and regional coordinated development is to attract labor forces back to rural areas. Most of the existing studies consider the impact of individual factors on population migration, they lack a systematic framework to analyze the combined [...] Read more.

An important way to realize urban–rural integration and regional coordinated development is to attract labor forces back to rural areas. Most of the existing studies consider the impact of individual factors on population migration, they lack a systematic framework to analyze the combined impact of different factors on rural return migration. Furthermore, in practice, the interaction within the rural social ecosystem as an important driver of return migration is always ignored. Using data from 131 villages in 14 cities in Guangxi, China, combined with the Coupled Infrastructure System framework and the sustainable livelihoods framework, this paper analyzes the comprehensive impact of internal components of the rural social ecosystem on return migration. Qualitative comparative analysis is used to identify four condition combinations that can effectively promote return migration and five condition combinations that make return migration vulnerable. The main conclusions are as follows. First, high-level public infrastructure providers are an important driving factor for labor return to rural areas, and a substitution effect exists between them and livelihood capitals. Second, sufficient human capital and social capital are crucial for return migration, highlighting the importance of the structure of rural members and the collective atmosphere. Third, natural capital and economic capital emphasized by previous research are not key conditions for forming a high level of return migration. Fourth, the vulnerability of return migration is mainly caused by the decline of social capital, the loss of public infrastructure providers, and excessive dependence on economic or physical capital input. To attract return migration, rural areas need to pay attention to the integration and synergy of multi-dimensional capital and public infrastructure providers, and special emphasis should be placed on the cultivation of public leadership to promote the enhancement of human capital and social capital. This paper provides a more comprehensive and instrumental analytical perspective for understanding and promoting rural return migration. While deepening the understanding of the dynamic relationship between rural social ecosystem and labor mobility, it also offers policy insights for developing countries to achieve integrated urban–rural development. Full article

(This article belongs to the Topic Sustainable Development and Coordinated Governance of Urban and Rural Areas under the Guidance of Ecological Wisdom)

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23 pages, 3249 KiB

Open AccessArticle

A Generalized Framework for Adversarial Attack Detection and Prevention Using Grad-CAM and Clustering Techniques

by Jeong-Hyun Sim and Hyun-Min Song

Systems 2025, 13(2), 88; https://doi.org/10.3390/systems13020088 - 31 Jan 2025

Viewed by 315

Abstract

Through advances in AI-based computer vision technology, the performance of modern image classification models has surpassed human perception, making them valuable in various fields. However, adversarial attacks, which involve small changes to images that are hard for humans to perceive, can cause classification [...] Read more.

Through advances in AI-based computer vision technology, the performance of modern image classification models has surpassed human perception, making them valuable in various fields. However, adversarial attacks, which involve small changes to images that are hard for humans to perceive, can cause classification models to misclassify images. Considering the availability of classification models that use neural networks, it is crucial to prevent adversarial attacks. Recent detection methods are only effective for specific attacks or cannot be applied to various models. Therefore, in this paper, we proposed an attention mechanism-based method for detecting adversarial attacks. We utilized a framework using an ensemble model, Grad-CAM and calculated the silhouette coefficient for detection. We applied this method to Resnet18, Mobilenetv2, and VGG16 classification models that were fine-tuned on the CIFAR-10 dataset. The average performance demonstrated that Mobilenetv2 achieved an F1-Score of 0.9022 and an accuracy of 0.9103, Resnet18 achieved an F1-Score of 0.9124 and an accuracy of 0.9302, and VGG16 achieved an F1-Score of 0.9185 and an accuracy of 0.9252. The results demonstrated that our method not only detects but also prevents adversarial attacks by mitigating their effects and effectively restoring labels. Full article

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

23 pages, 3802 KiB

Open AccessArticle

Enhancing Invoice Processing Automation Through the Integration of DevOps Methodologies and Machine Learning

by Oana-Alexandra Dragomirescu, Pavel-Cristian Crăciun and Ana Ramona Bologa

Systems 2025, 13(2), 87; https://doi.org/10.3390/systems13020087 - 31 Jan 2025

Viewed by 293

Abstract

In today’s rapidly evolving digital landscape, organizations are increasingly seeking systemic approaches to optimize their financial operations, particularly in invoice processing. Traditional methods of invoice management, which are heavily reliant on manual labor, not only incur significant costs but also contribute to inefficiencies, [...] Read more.

In today’s rapidly evolving digital landscape, organizations are increasingly seeking systemic approaches to optimize their financial operations, particularly in invoice processing. Traditional methods of invoice management, which are heavily reliant on manual labor, not only incur significant costs but also contribute to inefficiencies, delays, and resource wastage. This article presents an integrated framework that combines DevOps methodologies and machine learning (ML) to transform invoice processing into a scalable and sustainable operation. By leveraging system dynamics and automation, the proposed Proof of Concept (PoC) addresses interconnected challenges, such as reducing labor dependency, enhancing operational intelligence, and minimizing environmental impact. The PoC framework includes dynamic model training, testing, deployment, and monitoring, enabling adaptive and resilient solutions aligned with evolving business needs. Findings from a survey highlight the potential of these integrated approaches to streamline processes, reduce errors, and optimize resource utilization while also identifying barriers to widespread adoption. By combining ML’s predictive power with DevOps’ agility, the framework not only advances automation but also provides a path toward sustainable financial operations in an interconnected and data-driven economy. Full article

(This article belongs to the Special Issue Systemic Optimization in Sustainable Business Operations: Theory and Practice)

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21 pages, 2707 KiB

Open AccessReview

Integrating Evidence and Causal Mapping of Factors Which Influence Medication-Taking Behavior of Pregnant Women at Risk of Hypertensive Disorder: A Scoping Review

by Yin Jien Lee, Anita Taft, Melody Moua, David K. Stevenson and Gary L. Darmstadt

Systems 2025, 13(2), 86; https://doi.org/10.3390/systems13020086 - 31 Jan 2025

Viewed by 306

Abstract

Preeclampsia is a form of gestational hypertension that usually appears after the 20th week of pregnancy. Evidence suggests that low-dose aspirin (LDA) effectively reduces the risk of developing preeclampsia, but the uptake rate remains low. This scoping review aims to synthesize and integrate [...] Read more.

Preeclampsia is a form of gestational hypertension that usually appears after the 20th week of pregnancy. Evidence suggests that low-dose aspirin (LDA) effectively reduces the risk of developing preeclampsia, but the uptake rate remains low. This scoping review aims to synthesize and integrate existing knowledge domains relevant to the factors that influence women’s medication decisions during pregnancy, and to develop a causal explanation for at-risk women’s LDA uptake decisions. We introduced systems thinking to map the variables and develop causal loops to show variable interactions and causal explanations guided by the Theory of Planned Behavior. We extracted 65 variables, and grouped them into provider- (n = 19), patient- (n = 39), and system-level (n = 7) factors. By identifying variable interactions, we built a theory to explain various causal pathways leading to LDA treatment uptake. Mapping the variables and supporting the relationships of these variables with theories and concepts increases our study’s generalizability to medication decisions for other pregnancy complications. Full article

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

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16 pages, 1259 KiB

Open AccessArticle

Electoral Districts in Chile: Optimizing Socio-Economic Homogeneity and Demographic Balance

by Rodrigo Rebolledo, Maykol Reinoso, Óscar Cornejo, Carlos Obreque and Felipe Baesler

Systems 2025, 13(2), 85; https://doi.org/10.3390/systems13020085 - 30 Jan 2025

Viewed by 384

Abstract

This article addresses the problem of unequal representation in Chile, where the current districting does not effectively consider its socio-economic diversity. An innovative methodology is proposed that uses the socio-economic dissimilarity distance (SED) obtained using a cluster analysis to create more homogeneous electoral [...] Read more.

This article addresses the problem of unequal representation in Chile, where the current districting does not effectively consider its socio-economic diversity. An innovative methodology is proposed that uses the socio-economic dissimilarity distance (SED) obtained using a cluster analysis to create more homogeneous electoral districts. This SED is incorporated into a mathematical programming model for (re)districting and seat allocation, taking into account criteria such as the demographic balance, contiguity and compactness. The application of this methodology in the Santiago Metropolitan Region shows a significant improvement in both the socio-economic homogeneity and demographic balance of the districts. This research has relevant implications for electoral justice in Chile, as it proposes a way to improve the representativeness and ensure that the needs of each social group are reflected in the decision-making process. Full article

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16 pages, 338 KiB

Open AccessArticle

The Effects of Enterprises’ E-Business Adoptions on Cross-Border Firm Internationalization

by Yan Xu and Haiying Pan

Systems 2025, 13(2), 84; https://doi.org/10.3390/systems13020084 - 29 Jan 2025

Viewed by 407

Abstract

Nowadays, in the complex business network system, the interaction of firms across borders is facing several challenges. Many studies in the literature also suggest numerous approaches to overcome these challenges. However, a few of the obstacles for internationalizing firms were studied and the [...] Read more.

Nowadays, in the complex business network system, the interaction of firms across borders is facing several challenges. Many studies in the literature also suggest numerous approaches to overcome these challenges. However, a few of the obstacles for internationalizing firms were studied and the challenges are increasing against firms’ growth opportunities cross-border. Taking this into account, the present research emphasized the roles of enterprises’ e-business adoptions of countries on cross-border firms’ internationalization by drawing from network theory and technology–organization–environment frames. By employing a fixed effect model to 365 enterprises, leaders’ attitudes of preferring technology-intensive firms, network infrastructure, risk-averting attitudes, country’s market size, multilingual services, e-government status, threats from competitors, reliable utility sources, human capital quality, costs of adoptions and telecom services enrichments, and costs of adopting different online services need to be taken into account before internationalization of born global companies. Full article

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

26 pages, 848 KiB

Open AccessArticle

Economics of Cybersecurity Investment and Information Sharing: Firm Decision Making under Policy Constraints

by Liurong Zhao, Xinshuo Wu, Jiao Li and Huagang Tong

Systems 2025, 13(2), 83; https://doi.org/10.3390/systems13020083 - 29 Jan 2025

Viewed by 368

Abstract

With an increasing number of firms in cybersecurity information-sharing platforms, the potential cyber risks become a critical challenge during the exchanging of information. How to balance economic benefits and security requirements is an important topic for both firms and the government. By developing [...] Read more.

With an increasing number of firms in cybersecurity information-sharing platforms, the potential cyber risks become a critical challenge during the exchanging of information. How to balance economic benefits and security requirements is an important topic for both firms and the government. By developing a game-theoretic model, the firms’ optimal strategies are discussed considering their absorptive capacity for security information under different policy constrains. The results show that the value of security information, intrusion loss, the level of cybersecurity vulnerability, the negative impact coefficient of platform security information disclosure, and the absorptive capacity for security information are key factors impacting firms’ decisions. The value of security information and intrusion loss are constrained by the marginal utility of cybersecurity investment and security information sharing. Firms prefer to increase their security investment or security information sharing only if the value of security information and intrusion loss are positively related to the marginal utility of cybersecurity investment or cybersecurity information sharing. Specifically, in the case without policy constrains, the optimal strategies of n firms are discussed, and it is found that they are consistent with those of two firms and that the utility of any firm in the platform decreases as the number of firms increases. Full article

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

25 pages, 956 KiB

Open AccessArticle

It’s Scary to Use It, It’s Scary to Refuse It: The Psychological Dimensions of AI Adoption—Anxiety, Motives, and Dependency

by Adi Frenkenberg and Guy Hochman

Systems 2025, 13(2), 82; https://doi.org/10.3390/systems13020082 - 29 Jan 2025

Viewed by 836

Abstract

The current study examines the psychological factors shaping AI adoption, focusing on anxiety, motivation, and dependency. It identifies two dimensions of AI anxiety: anticipatory anxiety, driven by fears of future disruptions, and annihilation anxiety, reflecting existential concerns about human identity and autonomy. We [...] Read more.

The current study examines the psychological factors shaping AI adoption, focusing on anxiety, motivation, and dependency. It identifies two dimensions of AI anxiety: anticipatory anxiety, driven by fears of future disruptions, and annihilation anxiety, reflecting existential concerns about human identity and autonomy. We demonstrate a U-shaped relationship between AI anxiety and usage, where moderate engagement reduces anxiety, and high or low levels increase it. Perceived utility, interest, and attainment significantly correlate with AI engagement, while frequent AI usage is linked to high dependency but not to anxiety. These findings highlight the dual role of psychological factors in hindering and alleviating AI usage. This study enriches the understanding of emotional and motivational drivers in AI adoption and highlights the importance of balanced implementation strategies to foster sustainable and effective AI integration while mitigating the risks of over-reliance. Full article

(This article belongs to the Special Issue Navigating Digital Transformation: Leadership and Decision Making in Today’s Systems)

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16 pages, 1213 KiB

Open AccessArticle

Supplier Selection Model Considering Sustainable and Resilience Aspects for Mining Industry

by Pablo Becerra and Javier Diaz

Systems 2025, 13(2), 81; https://doi.org/10.3390/systems13020081 - 29 Jan 2025

Viewed by 471

Abstract

Supplier selection plays a pivotal role in the mining industry, forming a key component of the supply chain management. It has been established that the integration of sustainability and resilience into this process can significantly enhance the industry’s ability to withstand economic, environmental, [...] Read more.

Supplier selection plays a pivotal role in the mining industry, forming a key component of the supply chain management. It has been established that the integration of sustainability and resilience into this process can significantly enhance the industry’s ability to withstand economic, environmental, and social shocks. Despite a large body of literature investigating supplier selection, there is a notable gap in research specifically addressing the incorporation of sustainability and resilience criteria in the mining industry. The objective of this research is to bridge this knowledge gap and contribute to the understanding of sustainable and resilient supplier selection in the mining industry. A constructive research approach was employed, identifying both practical and theoretical problems and proposing a construction—a mathematical model. This model was developed in collaboration with industry key actors, ensuring its practical applicability and validity. The main result of this research is an optimization mathematical programming model that allows practitioners to evaluate and select suppliers considering both sustainability and resilience criteria. The model facilitates a comprehensive assessment of suppliers, incorporating a wide range of factors beyond cost, including environmental impact, social responsibility, and the ability to maintain supply under various potential disruptions. Full article

(This article belongs to the Special Issue New Trends in Sustainable Operations and Supply Chain Management)

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19 pages, 753 KiB

Open AccessArticle

Improving Ride-Hailing Platform Operations in Dynamic Markets: A Drivers’ Switching Perspective

by Xingguang Chen and Hepu Deng

Systems 2025, 13(2), 80; https://doi.org/10.3390/systems13020080 - 28 Jan 2025

Viewed by 426

Abstract

Improving the performance of the operations of ride-hailing platforms (RHPs) by adequately considering drivers’ switching behaviors is becoming crucial for their profitability and sustainability. This study explores how to optimize the operations of RHPs by investigating the impact of commission rates on drivers’ [...] Read more.

Improving the performance of the operations of ride-hailing platforms (RHPs) by adequately considering drivers’ switching behaviors is becoming crucial for their profitability and sustainability. This study explores how to optimize the operations of RHPs by investigating the impact of commission rates on drivers’ switching behaviors in a dynamic mobility market. Two queue-theory-based mathematical models have been developed to explore the relationship between commission rates, drivers’ switching behaviors, and critical platform parameters in optimizing the operations of RHPs. Numerical examples are presented to demonstrate the applicability of such models in determining the best commission rate to optimize the operations of RHPs in duopoly and fully competitive market conditions. The findings suggest that understanding the intricate relationship between commission rates, drivers’ switching behaviors, and critical platform parameters is significant for RHPs in formulating appropriate strategies and policies to ensure their sustainable operations. Full article

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

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21 pages, 1149 KiB

Open AccessArticle

Effects of AI Virtual Anchors on Brand Image and Loyalty: Insights from Perceived Value Theory and SEM-ANN Analysis

by Yu-Peng Zhu, Lina Xin, Huimin Wang and Han-Woo Park

Systems 2025, 13(2), 79; https://doi.org/10.3390/systems13020079 - 27 Jan 2025

Viewed by 522

Abstract

AI virtual anchors are an emerging innovation that are gaining significant attention, as they hold promising applications across various fields. This study examines how users perceive live product selling by AI virtual anchors and its impact on brand image and brand loyalty. A [...] Read more.

AI virtual anchors are an emerging innovation that are gaining significant attention, as they hold promising applications across various fields. This study examines how users perceive live product selling by AI virtual anchors and its impact on brand image and brand loyalty. A two-stage PLS-SEM and ANN approach was employed to analyze data from a sample of 336 individuals in China who had experienced and utilized AI virtual anchors for purchases during branded live streaming sessions. The findings indicate that perceived usefulness, perceived enjoyment, and novelty positively impact brand image, with artificial neural network (ANN) analysis identifying brand image as the primary predictor. Furthermore, brand image acts as a mediator between these user perceptions and brand loyalty. These insights offer brand managers a strategic approach to utilize AI virtual anchors for fostering a positive brand image and building loyal customer bases. The study also contributes to the academic understanding of consumer behavior and brand management in the context of AI. Full article

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

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29 pages, 5400 KiB

Open AccessArticle

The Coordinated Development and Identification of Obstacles in the Manufacturing Industry Based on Economy–Society–Resource–Environment Goals

by Jiaojiao Yang, Ting Wang, Min Zhang, Yujie Hu and Xinran Liu

Systems 2025, 13(2), 78; https://doi.org/10.3390/systems13020078 - 26 Jan 2025

Viewed by 355

Abstract

Given the deficiencies in the definition of connotation, the construction of index systems, and the coordination of targets within the research on sustainable development in the manufacturing industry, an evaluation index system for sustainable development has been established. This system includes economic benefits, [...] Read more.

Given the deficiencies in the definition of connotation, the construction of index systems, and the coordination of targets within the research on sustainable development in the manufacturing industry, an evaluation index system for sustainable development has been established. This system includes economic benefits, social benefits, resource management, and environmental goals and is built upon a clear definition of the concept’s connotation. The CRITIC–entropy–TOPSIS–CCDM approach is employed for the computation of the coordinated development level of the manufacturing industry. To identify the main factors influencing the coupling coordination degree (CCD) from a mechanistic and compositional point of view, a logarithmic mean divisia index (LMDI) is used. Furthermore, the obstacle degree model analyzes the factors that restrict subsystem development. The results show the following. (1) The coordinated development level of the Chinese manufacturing industry has been maintained at 0.6–0.7, while the CCD of Hainan, Qinghai, and Xinjiang remains to be enhanced. (2) The key factor affecting the CCD is the coupling degree. The evaluation value of the economy and employment system determines the trend of coordinated development in the regional manufacturing industry. (3) The economic and employment scenarios in most provinces (cities) led to a significant decrease in the CCD compared to the baseline scenario, with average growth rates of −10.55% and −12.69%. This suggests that policymakers’ priorities significantly influence the CCD. The research presents a theoretical framework for assessing the sustainability of the manufacturing industry, offering valuable insights to guide the industry towards more sustainable practices. Full article

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

24 pages, 2143 KiB

Open AccessArticle

Simulation Evaluation and Case Study Verification of Equipment System of Systems Support Effectiveness

by Gang Ding, Lijie Cui, Feng Zhang, Chao Shi, Xinhe Wang and Xiang Tai

Systems 2025, 13(2), 77; https://doi.org/10.3390/systems13020077 - 26 Jan 2025

Viewed by 291

Abstract

As the scale of missions continues to expand, equipment support has emerged as a critical component of military combat effectiveness. Consequently, the supportability of a system of systems (SOS) for equipment has become as essential quality requirement alongside its performance metrics. This study [...] Read more.

As the scale of missions continues to expand, equipment support has emerged as a critical component of military combat effectiveness. Consequently, the supportability of a system of systems (SOS) for equipment has become as essential quality requirement alongside its performance metrics. This study systematically assessed the effectiveness of equipment SOS support through a task-driven methodology. Initially, a model for generating equipment support tasks was developed to translate the operational requirements into a sequence of support tasks. Subsequently, a simulation model was constructed to evaluate the equipment SOS support system, and solutions were derived for the corresponding SOS-level support effectiveness indexes. Finally, the feasibility and characteristics of the proposed models and simulation methodology were validated through a case study involving an emergency operational mission for an air combat group formation. The results indicate that the increased reliability of the equipment system correlates with a reduced failure rate and lower resource consumption for maintenance and support per device, thereby improving support efficiency. The methodology presented in this article provides a framework for evaluating the effectiveness of equipment SOS support while facilitating informed decision-making in information warfare conditions. Full article

(This article belongs to the Section Systems Engineering)

31 pages, 2107 KiB

Open AccessArticle

Operational Risk Assessment of Commercial Banks’ Supply Chain Finance

by Wenying Xie, Juan He, Fuyou Huang and Jun Ren

Systems 2025, 13(2), 76; https://doi.org/10.3390/systems13020076 - 24 Jan 2025

Viewed by 287

Abstract

Supply chain finance (SCF) operations require extensive activities and a high level of information transparency, making them vulnerable to operational issues that pose significant risks of financial loss for commercial banks. Accurately assessing operational risks is crucial for ensuring market stability. This research [...] Read more.

Supply chain finance (SCF) operations require extensive activities and a high level of information transparency, making them vulnerable to operational issues that pose significant risks of financial loss for commercial banks. Accurately assessing operational risks is crucial for ensuring market stability. This research aims to provide a reliable operational risk assessment tool for commercial banks’ SCF businesses and to deeply examine the features of operational risk events. To achieve these goals, the study explores the dependency structure of risk cells and proposes a quantitative measurement framework for operational risk in SCF. The loss distribution analysis (LDA) is improved to align with the marginal loss distribution of segmented operational risks at both high and low frequencies. A tailored copula function is developed to capture the dependency structure between various risk cells, and the Monte Carlo algorithm is utilized to compute operational risk values. An empirical investigation is conducted using SCF loss data from commercial banks, creating a comprehensive database documenting over 400 entries of SCF loss events from 2012 to 2022. This database is analyzed to identify behaviors, trends, frequencies, and the severity of loss events. The results indicate that fraud risk and compliance risk are the primary sources of operational risks in SCF. The proposed approach is validated through backtesting, revealing a value at risk of CNY 179.3 million and an expected shortfall of CNY 204.9 million at the 99.9% significance level. This study pioneers the measurement of SCF operational risk, offering a comprehensive view of operational risks in SCF and providing an effective risk management tool for financial institutions and policymakers. Full article

(This article belongs to the Special Issue New Trends in Sustainable Operations and Supply Chain Management)

26 pages, 569 KiB

Open AccessArticle

The Impact of Digital Transformation on Organizational Resilience: The Role of Innovation Capability and Agile Response

by Jingyi Zhang, Hanxi Li and Hong Zhao

Systems 2025, 13(2), 75; https://doi.org/10.3390/systems13020075 - 24 Jan 2025

Viewed by 766

Abstract

In the face of a VUCA environment, organizational resilience has become a critical factor in sustaining enterprise performance. This study explores how digital transformation influences organizational resilience through its impact on the key components of organizational systems, specifically innovation capability and agile response. [...] Read more.

In the face of a VUCA environment, organizational resilience has become a critical factor in sustaining enterprise performance. This study explores how digital transformation influences organizational resilience through its impact on the key components of organizational systems, specifically innovation capability and agile response. Using data from Chinese A-share listed firms over the period 2007–2023, the study finds that digital transformation significantly enhances organizational resilience, with robust results across various tests. The analysis highlights that digital transformation strengthens resilience by optimizing innovation capability and improving agility within organizational systems. Heterogeneity tests reveal that these effects are particularly strong in firms located in eastern and central regions, operating in capital-intensive industries, and at growth or maturity stages. These findings underscore the systemic role of digital transformation in building adaptive, resilient organizations that can better navigate uncertainty and complexity. This study contributes to understanding the dynamic interplay between digital technologies and organizational systems, offering practical insights for enterprises aiming to leverage digital transformation for sustainable growth and high-quality economic development. Full article

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

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18 pages, 315 KiB

Open AccessArticle

Nexus Between Fair Pay and Say-on-Pay Votes

by Ahmad Alqatan and Muhammad Arslan

Systems 2025, 13(2), 74; https://doi.org/10.3390/systems13020074 - 23 Jan 2025

Viewed by 358

Abstract

This study explores the magnitude of shareholders’ say-on-pay (SOP) votes and its impact on CEO compensation. This study draws its sample from US Russell 3000 companies, the largest US companies, from 2011 to 2019. By creating a dummy variable, we further divided our [...] Read more.

This study explores the magnitude of shareholders’ say-on-pay (SOP) votes and its impact on CEO compensation. This study draws its sample from US Russell 3000 companies, the largest US companies, from 2011 to 2019. By creating a dummy variable, we further divided our sample into Russell 3000 and S&P 500 for peer comparison. This study employs descriptive statistics, correlation analysis, and pooled OLS regression and finds that CEO compensation has a significant negative association with pay gap opposition. The coefficient and t-statistic were greater for the S&P 500 than for the Russell group. The study also finds that the CEO-to-employee pay ratio (CTE) is positively correlated with the number of shareholders’ dissenting votes. The coefficient and t-statistic were greater for the Russell group than for the S&P 500 group. Each additional point of CTE increases shareholder dissent votes by 1.4% for the Russell 3000 companies. This study has important implications for corporate directors, investors, and policymakers. The study contributes to the corporate governance literature, particularly on executive compensation. Our findings support the perspective of social comparison theory and contend that shareholders view CEO compensation as a biased evaluation of their contribution to the firm. We have developed a unique measure of the CEO-to-employee pay ratio, which is based on SEC methodology. Our findings provide empirical evidence for investors and policymakers in the U.S. and other jurisdictions. Full article

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

24 pages, 7034 KiB

Open AccessArticle

An Approach Integrating Model-Based Systems Engineering, IoT, and Digital Twin for the Design of Electric Unmanned Autonomous Vehicles

by Clara A. Ramirez, Priyanshu Agrawal and Amy E. Thompson

Systems 2025, 13(2), 73; https://doi.org/10.3390/systems13020073 - 23 Jan 2025

Viewed by 455

Abstract

This article proposes a novel methodology aimed at streamlining the system’s development process. By examining existing state-of-the-art approaches and the capabilities inherent in Model-Based Systems Engineering (MBSE) tools, the article introduces a methodology centered around transforming a descriptive Systems Modeling Language (SysML) model [...] Read more.

This article proposes a novel methodology aimed at streamlining the system’s development process. By examining existing state-of-the-art approaches and the capabilities inherent in Model-Based Systems Engineering (MBSE) tools, the article introduces a methodology centered around transforming a descriptive Systems Modeling Language (SysML) model into a digital twin. This virtual representation of the physical asset leverages real-time data and simulations to mirror its behavior and characteristics. When integrated with MBSE, this synergy allows for a comprehensive and dynamic approach, enhancing innovation by providing a holistic and adaptable framework for designing, analyzing, and optimizing complex systems throughout their lifecycle. The practical application of this Real-Time Communication and Data Acquisition (RT-CDA) methodology is implemented in a context and operational scenario of an electric unmanned autonomous vehicle employing both Software-in-the-Loop (SITL) and Hardware-in-the-Loop (HITL) approaches. The methodology empowers systems engineers to iteratively update and refine their system model’s fidelity based on real-world testing insights. The article specifically demonstrates the real-time communication capabilities achieved between an electric unmanned autonomous vehicle (a physical asset) and a descriptive (SysML) model, illustrating the real-time data aspect integral to the concept of a digital twin. This study serves as a foundation for future endeavors, envisioning real-time communication among virtual and physical models to construct comprehensive digital twins of complex systems to predict behavior and performance. Full article

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

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39 pages, 24264 KiB

Open AccessArticle

Digital Health Transformation: Leveraging a Knowledge Graph Reasoning Framework and Conversational Agents for Enhanced Knowledge Management

by Abid Ali Fareedi, Muhammad Ismail, Stephane Gagnon, Ahmad Ghazanweh and Zartashia Arooj

Systems 2025, 13(2), 72; https://doi.org/10.3390/systems13020072 - 22 Jan 2025

Viewed by 553

Abstract

The research focuses on the limitations of traditional systems in optimizing information flow in the healthcare domain. It focuses on integrating knowledge graphs (KGs) and utilizing AI-powered applications, specifically conversational agents (CAs), particularly during peak operational hours in emergency departments (EDs). Leveraging the [...] Read more.

The research focuses on the limitations of traditional systems in optimizing information flow in the healthcare domain. It focuses on integrating knowledge graphs (KGs) and utilizing AI-powered applications, specifically conversational agents (CAs), particularly during peak operational hours in emergency departments (EDs). Leveraging the Cross Industry Standard Process for Data Mining (CRISP-DM) framework, the authors tailored a customized methodology, CRISP-knowledge graph (CRISP-KG), designed to harness KGs for constructing an intelligent knowledge base (KB) for CAs. This KG augmentation empowers CAs with advanced reasoning, knowledge management, and context awareness abilities. We utilized a hybrid method integrating a participatory design collaborative methodology (CM) and Methontology to construct a domain-centric robust formal ontological model depicting and mapping information flow during peak hours in EDs. The ultimate objective is to empower CAs with intelligent KBs, enabling seamless interaction with end users and enhancing the quality of care within EDs. The authors leveraged semantic web rule language (SWRL) to enhance inferencing capabilities within the KG framework further, facilitating efficient information management for assisting healthcare practitioners and patients. This innovative assistive solution helps efficiently manage information flow and information provision during peak hours. It also leads to better care outcomes and streamlined workflows within EDs. Full article

(This article belongs to the Special Issue Integration of Cybersecurity, AI, and IoT Technologies)

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24 pages, 559 KiB

Open AccessArticle

Understanding User Acceptance of AI-Driven Chatbots in China’s E-Commerce: The Roles of Perceived Authenticity, Usefulness, and Risk

by Rob Kim Marjerison, Hang Dong, Jong-Min Kim, Hanyi Zheng, Youran Zhang and George Kuan

Systems 2025, 13(2), 71; https://doi.org/10.3390/systems13020071 - 21 Jan 2025

Viewed by 728

Abstract

This study examines users’ perceptions of Chatbots in China, with a particular focus on the factors influencing their acceptance and usage. Grounded in the Technology Acceptance Model (TAM), we analyze data from 542 online responses to explore the roles of Perceived Authenticity, usefulness, [...] Read more.

This study examines users’ perceptions of Chatbots in China, with a particular focus on the factors influencing their acceptance and usage. Grounded in the Technology Acceptance Model (TAM), we analyze data from 542 online responses to explore the roles of Perceived Authenticity, usefulness, and risk in shaping user behavior toward AI-driven Chatbots. Using linear regression and mediation analyses, our findings indicate that both Perceived Authenticity and Perceived Usefulness positively impact users’ behavioral intentions, while Perceived Risk has a negative influence. Notably, Perceived Usefulness serves as a mediator between behavioral intentions and both Perceived Authenticity and Perceived Risk. These results contribute to the growing body of research on AI and e-commerce by providing empirical evidence of the key factors affecting Chatbot adoption. The study offers valuable implications for developers and marketers, suggesting that enhancing Perceived Authenticity and usefulness while addressing Perceived Risks can improve user acceptance. These insights are particularly pertinent for AI practitioners aiming to refine Chatbot technology and expand its application across various sectors. Full article

(This article belongs to the Special Issue Innovation Management and Digitalization of Business Models)

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31 pages, 2001 KiB

Open AccessArticle

A Reference Architecture for Smart Car Parking Management Systems

by Mert Ozkaya and Alper Turunc

Systems 2025, 13(2), 70; https://doi.org/10.3390/systems13020070 - 21 Jan 2025

Viewed by 453

Abstract

Smart car parking management systems (SPMSs) have gained an ever-increasing popularity for the digital management of car parking processes. While various techniques and technologies have been proposed for SPMSs, the literature lacks in any generic software architecture design that can be reused systematically [...] Read more.

Smart car parking management systems (SPMSs) have gained an ever-increasing popularity for the digital management of car parking processes. While various techniques and technologies have been proposed for SPMSs, the literature lacks in any generic software architecture design that can be reused systematically for the specifications of quality SPMS architectures. To bridge this gap, we propose a reference architecture (RA) for the SPMS product family after performing a comprehensive domain analysis. Our RA design offers a feature model that consists of the common and varying features for SPMSs. We offer multiple viewpoints for our RA, including context, module, component and connector, and allocation. The context viewpoint focuses on the stakeholders, the module viewpoint focuses on the software units, the component and connector viewpoint focuses on the layered architecture of SPMSs, and the allocation viewpoint focuses on mapping software units into the physical components. Each viewpoint can be re-used for specifying the application architecture of any SPMSs. We validated our RA with a real SPMS scenario specification and prototype development, where the former measures the reusability of RA and the latter measures the development performance. The RA design for SPMSs is expected to be useful for several stakeholders who research, develop, and sell SPMS solutions. Full article

(This article belongs to the Section Systems Engineering)

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40 pages, 13421 KiB

Open AccessArticle

Applying the PRiSM™ Methodology to Raise Awareness of the Importance of Using Sustainable Project Management Practices in Organizations

by Ana Moutinho, Paulo Sousa and Anabela Tereso

Systems 2025, 13(2), 69; https://doi.org/10.3390/systems13020069 - 21 Jan 2025

Viewed by 543

Abstract

Sustainability has become crucial in today’s business landscape. Customers, suppliers, partners, and investors are increasingly demanding that companies be aware of their impacts on the environment and society. Achieving sustainability in business operations, including social, economic, and environmental aspects, is one of the [...] Read more.

Sustainability has become crucial in today’s business landscape. Customers, suppliers, partners, and investors are increasingly demanding that companies be aware of their impacts on the environment and society. Achieving sustainability in business operations, including social, economic, and environmental aspects, is one of the major challenges for companies today. Integrating sustainability into project management fosters the development of more sustainable and responsible projects, considering environmental, social, and economic aspects. This integration allows for benefits such as risk and operational cost reduction, strengthening of the company’s reputation, and gaining stakeholders’ trust. This study takes an exploratory approach, focusing on a pilot test to investigate how the PRiSM™ (Projects Integrating Sustainable Methods) methodology can be applied in a business context to assess the level of maturity of sustainable project management practices and thus raise awareness of the importance of these issues. PRiSM™ was developed by GPM^® Global (Global Project Management, Lees Summit, MO, USA) in 2013 to help organizations integrate project processes with sustainable initiatives and it is based on the P5 Standard, which incorporates tangible tools and methods to manage the balance between finite resources, social responsibility, and delivery of sustainable project outcomes. Based on the PRiSM™ methodology and the P5 Standard (2nd Edition), a comprehensive questionnaire was developed under the Portuguese Project Management Observatory^® to assist companies in assessing their performance in terms of sustainable practices, resulting in a sustainable maturity level. The questionnaire aimed to evaluate companies in four impact categories: product/process impacts, social impacts, economic impacts, and environmental impacts. The results, obtained from 30 respondents, indicated that the majority of organizations achieved medium-level ratings, with an overall average of 65%. However, some still showed unsatisfactory performance, with a minimum score of 14%, indicating there is still a long way to go for the full integration of sustainability. Based on participants’ feedback, the study found that many recognized the importance of sustainability but were unaware of how to integrate sustainability practices into their project management activities, highlighting the importance of promoting education and raising awareness about sustainable project management practices. The findings, while based on a limited sample, provide valuable initial insights into the potential of PRiSM™ to foster sustainability in project management. This research underscores the need for further studies to expand and validate these preliminary conclusions. Full article

(This article belongs to the Special Issue Sustainable Project Management in Business)

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29 pages, 1602 KiB

Open AccessArticle

Financing Mechanisms and Preferences of Technology-Driven Small- and Medium-Sized Enterprises in the Digitalization Context

by Jing Hu, Lianming Huang, Weifu Li and Hongyi Xu

Systems 2025, 13(2), 68; https://doi.org/10.3390/systems13020068 - 21 Jan 2025

Viewed by 632

Abstract

In the context of digitalization, this study investigated the financing mechanisms and preferences of technology-driven small and medium-sized enterprises (TDSMEs) listed on the National Equities Exchange and Quotations (NEEQ) in China. Its primary objective was to identify the factors influencing financing decisions and [...] Read more.

In the context of digitalization, this study investigated the financing mechanisms and preferences of technology-driven small and medium-sized enterprises (TDSMEs) listed on the National Equities Exchange and Quotations (NEEQ) in China. Its primary objective was to identify the factors influencing financing decisions and to elucidate how TDSMEs choose their financing options in a rapidly evolving digital environment. To achieve this goal, we constructed a panel regression model using financial data from 41 TDSMEs (2017–2023), identifying the key determinants of financing decisions while examining the impact of regional heterogeneity and validating the model’s robustness. The empirical findings indicated that various independent variables, including a firm’s capital structure, significantly influenced both internal and external financing. Additionally, six machine learning (ML) algorithms were employed to predict financing preferences. Among them, the random forest (RF) model achieved the best financing preferences performance, with an average F1 score of 0.814, indicating its robust predictive capability for TDSMEs’ financing preferences. To further validate the proposed models, we conducted a case study on a TDSME newly recognized in 2024 (named TS Pharmaceutical). Both the Lasso and RF models demonstrated outstanding predictive accuracy, confirming the practicality of the ML models. These results provide valuable insights into navigating the ever-changing digital financing landscape, offering recommendations for policymakers and financial institutions to better support TDSMEs. The key innovation of this study lies in its novel integration of conventional panel regression analysis and ML techniques, thereby bridging the gap between digital transformation and financing strategies while contributing both theoretically and practically to the field. Full article

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

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Systems, Volume 13, Issue 2 (February 2025) – 29 articles

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