Systems

34 pages, 2070 KiB

Open AccessArticle

Urban Scenic Spot Activity Center Investment: Strategic Construction Company Selection Using the Grey System-II Thinking Compromise Ranking of Alternatives from Distance to Ideal Solution Multi-Criteria Decision-Making Method

by Shuo Zhang and Moses Olabhele Esangbedo

Systems 2025, 13(1), 67; https://doi.org/10.3390/systems13010067 - 20 Jan 2025

Viewed by 567

Abstract

Investing in urban scenic spots is a complex process that requires careful consideration of multiple criteria to ensure sustainability and efficiency. In the post-pandemic era, the uncertainty of future trends necessitates effective risk management and informed investment decisions. Revitalizing urban scenic spots while [...] Read more.

Investing in urban scenic spots is a complex process that requires careful consideration of multiple criteria to ensure sustainability and efficiency. In the post-pandemic era, the uncertainty of future trends necessitates effective risk management and informed investment decisions. Revitalizing urban scenic spots while maintaining profitability, along with the construction of multi-purpose activity centers, requires a thorough evaluation of construction companies. This study addresses the selection of the most suitable contractor for constructing multi-purpose activity chain centers as a Multi-Criteria Decision-Making (MCDM) problem. We address the intricacies of contractor selection by integrating MCDM and system thinking approaches, emphasizing the alignment of investment strategies with broader urban development goals. First, a time delay was introduced between the first and second rounds of administering the weighting questionnaire to capture decision-makers’ preferences for the evaluation criteria as System-2 thinking, then the Grey System-2 Thinking (GS2T) weighting method was proposed for group decision-making. Second, the Compromise Ranking of Alternatives from Distance to Ideal Solution (CRADIS) method was incorporated into the Grey Systems Theory (GST), resulting in the development of the Grey-CRADIS method, which was applied to rank seven contractors for constructing activity centers across four urban scenic spots. Using the proposed GS2T with the developed Grey-CRADIS method in conjunction with the decision-makers’ preferences, Company-2 was found to be the best contractor for the construction project. Finally, classical MCDM methods such as theWeighted Sum Model (WSM) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) were employed to confirm the top-ranking contractor. Full article

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

► Show Figures

Figure 1

26 pages, 1736 KiB

Open AccessArticle

Supplier Encroachment Channel Selection on an Online Retail Platform

by Zongyu Mou, Kaixin Ding, Yaping Fu and Hao Sun

Systems 2025, 13(1), 66; https://doi.org/10.3390/systems13010066 - 20 Jan 2025

Viewed by 446

Abstract

Online retail platforms offer encroachment opportunities for suppliers to directly sell products to consumers on the online market. However, how to select appropriate encroachment channels poses a significant challenge for suppliers. To solve this problem, we take one supplier selling products through an [...] Read more.

Online retail platforms offer encroachment opportunities for suppliers to directly sell products to consumers on the online market. However, how to select appropriate encroachment channels poses a significant challenge for suppliers. To solve this problem, we take one supplier selling products through an indirect reselling channel on a third-party online retail platform (TORP) as the base model, and further consider that the supplier can choose TORP agency selling, the owned channel, or both to encroach onto the online market. We hereby establish game-theoretical models to analyze the optimal strategy of supplier encroachment, the TORP preference, and the equilibrium channel strategy. The findings show that the supplier is always willing to encroach onto the online market through its own channel. Additionally, when the commission rate is low, the supplier will further encroach via the TORP agency selling channel. The TORP provides the agency selling channel for the supplier only when the commission rate exceeds a certain threshold. If the channel competition is not very fierce (the competition intensity is lower than 0.852) and the commission rate is moderate, dual-channel encroachment is the equilibrium channel strategy; otherwise, supplier-owned-channel encroachment is the equilibrium strategy. We extend our main models by incorporating supplier blockchain adoption and the cost differences between both parties to enhance practical applicability. Full article

(This article belongs to the Section Supply Chain Management)

► Show Figures

Figure 1

23 pages, 5424 KiB

Open AccessArticle

Integrated Dairy Production and Cattle Healthcare Management Using Blockchain NFTs and Smart Contracts

by Saravanan Krishnan and Lakshmi Prabha Ganesan

Systems 2025, 13(1), 65; https://doi.org/10.3390/systems13010065 - 20 Jan 2025

Viewed by 696

Abstract

Efficient cattle healthcare management is vital for ensuring productivity and welfare in dairy production, yet traditional record-keeping methods often lack transparency, security, and efficiency, leading to challenges in livestock product quality and healthcare. This study introduces a novel framework leveraging Zero Knowledge (ZK)-Rollups-enhanced [...] Read more.

Efficient cattle healthcare management is vital for ensuring productivity and welfare in dairy production, yet traditional record-keeping methods often lack transparency, security, and efficiency, leading to challenges in livestock product quality and healthcare. This study introduces a novel framework leveraging Zero Knowledge (ZK)-Rollups-enhanced Layer 2 blockchain and Non-Fungible Tokens (NFTs) to address these issues. NFTs serve as secure digital certificates for individual cattle health records, ensuring transparency and traceability. ZK-Rollups on the Layer 2 blockchain enhance scalability, privacy, and cost-efficiency, while smart contracts automate key processes such as veterinary scheduling, medication delivery, and insurance claims, minimizing administrative overhead. Performance evaluations reveal significant advancements, with transaction delays of 4.1 ms, throughput of 249.8 TPS, gas costs reduced to 26,499.76 Gwei, and a time-to-finality of 1.1 ms, achieved through ZK-SNARKs (ZK-Succinct Non-Interactive Arguments of Knowledge) integration. These results demonstrate the system’s potential to revolutionize cattle healthcare management by combining transparency, security, and operational efficiency. Full article

► Show Figures

Figure 1

22 pages, 5972 KiB

Open AccessArticle

Evaluation and Optimization Research on the Spatial Distribution of Automated External Defibrillators Based on a Genetic Algorithm: A Case Study of Central Urban District of Nanjing, China

by Ge Shi, Jiahang Liu, Chuang Chen, Jingran Zhang, Jinghai Xu, Yu Chen, Jiaming Na and Wei Chen

Systems 2025, 13(1), 64; https://doi.org/10.3390/systems13010064 - 20 Jan 2025

Viewed by 521

Abstract

Automated external defibrillators (AEDs) are portable emergency medical devices critical for resuscitating individuals experiencing sudden cardiac arrest. The installation of AEDs in public spaces is essential for enhancing society’s emergency response capabilities. However, many cities in China currently face issues such as inadequate [...] Read more.

Automated external defibrillators (AEDs) are portable emergency medical devices critical for resuscitating individuals experiencing sudden cardiac arrest. The installation of AEDs in public spaces is essential for enhancing society’s emergency response capabilities. However, many cities in China currently face issues such as inadequate AEDs deployment and uneven distribution. This study aims to explore a rational layout plan for AEDs through systematic site optimization. Initially, this paper evaluates the current spatial configuration of AEDs in the central urban district of Nanjing using various spatial analysis methods. Subsequently, a coverage model is constructed to simulate the coverage capacity of potential emergency needs for new facilities, and a genetic algorithm is utilized to solve it. Finally, an AED site selection experiment is conducted, and the site selection results are discussed and analyzed in conjunction with practical conditions. The research conclusions are as follows: (1) AED distribution in Nanjing’s central urban district is clustered, with some areas lacking facilities, and the coverage rate of AEDs within 100 m and 200 m ranges is relatively low, particularly across different types of venues; and (2) the optimization experiment, with 90 new site selection points, effectively addressed AED distribution gaps, significantly improved coverage, and ameliorated the overall distribution across various public venues. This study provides a scientific basis for the rational placement of AEDs in urban public spaces through systematic analysis and optimization experiments. It enhances the efficiency of current AED deployment in the main urban areas of Nanjing and offers significant insights for the optimization of urban emergency resource allocation. Full article

(This article belongs to the Special Issue Advances in the Modeling and Analytics of Health and Healthcare Systems)

► Show Figures

Figure 1

19 pages, 14691 KiB

Open AccessArticle

Quality of Pedestrian Networks Around Metro Stations: An Assessment Based on Approach Routes

by Qiyao Yang, Zheng Zhang, Jun Cai, Mengzhen Ding, Lemei Li, Shaohua Zhang, Zhenang Song, Feiyang Chen and Yi Ling

Systems 2025, 13(1), 63; https://doi.org/10.3390/systems13010063 - 20 Jan 2025

Viewed by 570

Abstract

Walking is the primary mode of reaching metro stations, yet the quality of pedestrian networks around these stations has not been well researched. Considering the objective physical characteristics of pedestrian networks and the subjective assessments of walkers on the routes, this study developed [...] Read more.

Walking is the primary mode of reaching metro stations, yet the quality of pedestrian networks around these stations has not been well researched. Considering the objective physical characteristics of pedestrian networks and the subjective assessments of walkers on the routes, this study developed an evaluation model that integrated the Analytic Hierarchy Process and Entropy Weight Method with human–machine adversarial scoring and cosine similarity to validate the reliability. Nineteen indicators concerning four fundamental criteria, including accessibility, convenience, safety, and comfort, were applied with data acquired from eight stations in Tianjin, China. Results reveal that accessibility and safety indicators weigh more than convenience and comfort indicators. The quality of pedestrian networks around the public-service and comprehensive stations scores higher than that around residential stations, while walking environment quality near commercial stations shows significant disparities. These findings highlight the importance of prioritizing accessibility and safety while enhancing convenience and comfort in the renewal of the pedestrian network in Tianjin. The assessment model provides a valuable tool for urban policymakers and planners, enabling the formulation of sound pedestrian-network policies, facilitating higher-quality walking access and egress trips to stations, and encouraging transit-oriented development. Full article

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

► Show Figures

Figure 1

4 pages, 168 KiB

Open AccessEditorial

Introduction to the Topic of AI and IoT for Promoting Green Operation and Sustainable Environment

by Nan Zhang, Wei Liu and Chia-Huei Wu

Systems 2025, 13(1), 62; https://doi.org/10.3390/systems13010062 - 20 Jan 2025

Viewed by 455

Abstract

In the current era, green operation has become a key strategic direction for firm development, with its core being the realization of a win–win situation for economic and environmental benefits through environmentally friendly production processes [...] Full article

(This article belongs to the Topic AI and IoT for Promoting Green Operation and Sustainable Environment)

21 pages, 2219 KiB

Open AccessArticle

Selection of Production Strategies for New Energy Vehicles: An Analysis of the Impact of Government Intervention Policies

by Yingxi Ge and Kehong Chen

Systems 2025, 13(1), 61; https://doi.org/10.3390/systems13010061 - 19 Jan 2025

Viewed by 772

Abstract

The aim of this study was to analyze the strategic choices and profit variations of a monopolistic automobile manufacturer capable of producing both traditional fuel vehicles and new energy vehicles, with a particular focus on government interventions. Using a theoretical model, the research [...] Read more.

The aim of this study was to analyze the strategic choices and profit variations of a monopolistic automobile manufacturer capable of producing both traditional fuel vehicles and new energy vehicles, with a particular focus on government interventions. Using a theoretical model, the research examined firm-level production decisions by incorporating consumer preferences and market competition under three policy scenarios: no government intervention, government subsidies, and tax policies. The key findings are as follows: (1) In the absence of government intervention, the firm’s production strategy is influenced by consumer preferences for new energy vehicles. Specifically, the firm prioritizes the production of new energy vehicles when consumer preference is high, fuel vehicles when preference is low, and both types when preference is moderate. (2) Government subsidies substantially reduce the production of fuel vehicles while promoting the production of new energy vehicles. However, excessively high subsidies may lead the firm to revert to fuel vehicle production. (3) Tax policies influence production strategies in a manner similar to subsidy policies. (4) When government intervention is weak and competition between fuel vehicles and new energy vehicles is intense, subsidy policies are more effective; however, when competition is less intense, tax policies may be more beneficial. Under strong government intervention, subsidy policies are found to be more effective. This research contributes to the literature by providing a theoretical foundation for government policymaking in the new energy vehicle sector, offering insights into firm-level production decisions under various policy environments. The originality of this study lies in its comparison of the effectiveness of subsidy and tax policies in promoting new energy vehicle production, which helps guide policymakers in designing optimal policy interventions. Full article

(This article belongs to the Section Supply Chain Management)

► Show Figures

Figure 1

35 pages, 7662 KiB

Open AccessArticle

Towards Smart and Resilient City Networks: Assessing the Network Structure and Resilience in Chengdu–Chongqing Smart Urban Agglomeration

by Rui Li, Yuhang Wang, Zhiyue Zhang and Yi Lu

Systems 2025, 13(1), 60; https://doi.org/10.3390/systems13010060 - 19 Jan 2025

Viewed by 784

Abstract

The mobility and openness of smart cities characterize them as particularly complex networks, necessitating the resilience enhancement of smart city regions from a network structure perspective. Taking the Chengdu–Chongqing urban agglomeration as a case study, this research constructs economic, information, population, and technological [...] Read more.

The mobility and openness of smart cities characterize them as particularly complex networks, necessitating the resilience enhancement of smart city regions from a network structure perspective. Taking the Chengdu–Chongqing urban agglomeration as a case study, this research constructs economic, information, population, and technological intercity networks based on the complex network theory and gravity model to evaluate their spatial structure and resilience over five years. The main conclusions are as follows: (1) subnetworks exhibit a ‘core/periphery’ structure with a significant evolution trend, particularly the metropolitan area integration degree of capital cities has significantly improved; (2) the technology network is the most resilient but was the most affected by COVID-19, while the population and information networks are the least resilient, resulting from poor hierarchy, disassortativity, and agglomeration; (3) network resilience can be improved through system optimization and node enhancement. System optimization should focus more on improving the coordinated development of population, information, and technology networks due to their low synergistic level of resilience, while node optimization should adjust strategies according to the dominance, redundancy, and network role of nodes. This study provides a reference framework to assess the resilience of smart cities, and the assessment results and enhancement strategies can provide valuable regional planning information for resilience building in smart city regions. Full article

► Show Figures

Figure 1

24 pages, 1119 KiB

Open AccessArticle

Maximizing Information Dissemination in Social Network via a Fast Local Search

by Lijia Tian, Xingjian Ji and Yupeng Zhou

Systems 2025, 13(1), 59; https://doi.org/10.3390/systems13010059 - 19 Jan 2025

Viewed by 344

Abstract

In recent years, social networks have become increasingly popular as platforms for personal expression, commercial transactions, and government management. The way information propagates on these networks influences the quality and expenses of social network activities, garnering substantial interest. This study addresses the enhancement [...] Read more.

In recent years, social networks have become increasingly popular as platforms for personal expression, commercial transactions, and government management. The way information propagates on these networks influences the quality and expenses of social network activities, garnering substantial interest. This study addresses the enhancement of information spread in large-scale social networks constrained by resources, by framing the issue as a unique weighted k-vertex cover problem. To tackle this complex NP-hard optimization problem, a rapid local search algorithm named FastIM is introduced. A fast constructive heuristic is initially used to quickly find a starting solution, while a sampling selection method is incorporated to minimize complexity during the local search. When the algorithm stalls in local optima, a random walk operator reorients the search towards unexplored regions. Comparative tests highlight the proposed method’s robustness, scalability, and efficacy in maximizing information distribution across social networks. Moreover, strategy validation trials confirm that each element of the framework enhances its overall performance. Full article

(This article belongs to the Section Complex Systems and Cybernetics)

► Show Figures

Figure 1

27 pages, 4747 KiB

Open AccessArticle

From Location Advantage to Innovation: Exploring Interprovincial Co-Funding Networks in Mainland China

by Feifei Wang, Hanbai Wang, Yuxuan An, Rui Xue, Yuanke Zhang and Tianqi Hao

Systems 2025, 13(1), 58; https://doi.org/10.3390/systems13010058 - 19 Jan 2025

Viewed by 417

Abstract

This study examines the regional co-funding network as a novel framework for advancing high-quality fundamental research amid systemic reforms in science funding. Based on provincial joint funding data from Mainland China retrieved via the WoS-SCIE and SSCI databases (2013–2022), an interprovincial co-funding network [...] Read more.

This study examines the regional co-funding network as a novel framework for advancing high-quality fundamental research amid systemic reforms in science funding. Based on provincial joint funding data from Mainland China retrieved via the WoS-SCIE and SSCI databases (2013–2022), an interprovincial co-funding network was constructed. Social network analysis, kernel density estimation, and fixed-effects regression analysis were employed to explore the evolution of regional location advantages and their impact on technological innovation. The findings reveal that the co-funding network has become increasingly balanced over time, significantly enhancing the location-based innovation advantages of individual provinces and strengthening the network’s overall capacity to foster innovation. This improved equilibrium has positively influenced regional scientific output, demonstrating that a province’s position within the co-funding network—particularly its individual location advantage—plays a pivotal role in advancing technological progress. However, persistent disparities in regional collaboration and development remain, underscoring the need for more coordinated strategies to address uneven growth dynamics. By introducing the co-funding network as an analytical lens, this study uncovers the hidden channels of resource synergy and their influence on regional innovation. The results provide actionable insights for optimizing co-funding mechanisms and enhancing interprovincial collaboration to maximize innovation potential in China. Full article

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

► Show Figures

Figure 1

16 pages, 1433 KiB

Open AccessArticle

Multimodal Recommendation System Based on Cross Self-Attention Fusion

by Peishan Li, Weixiao Zhan, Lutao Gao, Shuran Wang and Linnan Yang

Systems 2025, 13(1), 57; https://doi.org/10.3390/systems13010057 - 17 Jan 2025

Viewed by 563

Abstract

Recent advances in graph neural networks (GNNs) have enhanced multimodal recommendation systems’ ability to process complex user–item interactions. However, current approaches face two key limitations: they rely on static similarity metrics for product relationship graphs and they struggle to effectively fuse information across [...] Read more.

Recent advances in graph neural networks (GNNs) have enhanced multimodal recommendation systems’ ability to process complex user–item interactions. However, current approaches face two key limitations: they rely on static similarity metrics for product relationship graphs and they struggle to effectively fuse information across modalities. We propose MR-CSAF, a novel multimodal recommendation algorithm using cross-self-attention fusion. Building on FREEDOM, our approach introduces an adaptive modality selector that dynamically weights each modality’s contribution to product similarity, enabling more accurate product relationship graphs and optimized modality representations. We employ a cross-self-attention mechanism to facilitate both inter- and intra-modal information transfer, while using graph convolution to incorporate updated features into item and product modal representations. Experimental results on three public datasets demonstrate MR-CSAF outperforms eight baseline methods, validating its effectiveness in providing personalized recommendations, advancing the field of personalized recommendation in complex multimodal environments. Full article

► Show Figures

Figure 1

16 pages, 771 KiB

Open AccessArticle

The Mechanism of Entrepreneurial Resource Bricolage on Entrepreneurial Behavior in Underdeveloped Regions

by Sheng Ouyang, Linji Luo, Kaili Chen and Zhaoyang Liu

Systems 2025, 13(1), 56; https://doi.org/10.3390/systems13010056 - 17 Jan 2025

Viewed by 450

Abstract

Entrepreneurial resources are crucial to the success of ventures in underdeveloped regions. Leveraging limited resources to enhance entrepreneurial effectiveness and contribute to poverty alleviation through entrepreneurship has attracted significant academic interest. In this study, a conceptual model is developed, incorporating resource bricolage, entrepreneurial [...] Read more.

Entrepreneurial resources are crucial to the success of ventures in underdeveloped regions. Leveraging limited resources to enhance entrepreneurial effectiveness and contribute to poverty alleviation through entrepreneurship has attracted significant academic interest. In this study, a conceptual model is developed, incorporating resource bricolage, entrepreneurial involvement, entrepreneurial action learning, and entrepreneurial behavior. Through an empirical analysis of data collected from 230 startup founders in the Wuling Mountain Area, the results indicate that resource bricolage positively influences entrepreneurial behavior, while entrepreneurial involvement partially mediates the relationship between resource bricolage and entrepreneurial behavior. However, the findings also suggest that entrepreneurial action learning negatively moderates the relationship between resource bricolage and entrepreneurial involvement and that entrepreneurial involvement exerts a significant moderated mediation effect on the relationship between resource bricolage and entrepreneurial behavior. This study advances our understanding of resource bricolage and its implication for the resource environment in underdeveloped regions, providing valuable insights into how entrepreneurs can effectively adapt to resource-constrained settings. Full article

► Show Figures

Figure 1

18 pages, 894 KiB

Open AccessArticle

The Impact of VR Exhibition Experiences on Presence, Interaction, Immersion, and Satisfaction: Focusing on the Experience Economy Theory (4Es)

by Sungbok Chang and Jungho Suh

Systems 2025, 13(1), 55; https://doi.org/10.3390/systems13010055 - 16 Jan 2025

Viewed by 554

Abstract

This study systematically analyzes and emphasizes the importance of VR exhibition experiences, a relatively under-researched area. It examines the effects of VR exhibition experiences on presence and interaction and the influence of interaction on presence. Additionally, how these factors impact user immersion and [...] Read more.

This study systematically analyzes and emphasizes the importance of VR exhibition experiences, a relatively under-researched area. It examines the effects of VR exhibition experiences on presence and interaction and the influence of interaction on presence. Additionally, how these factors impact user immersion and satisfaction is explored, and the relationship between exhibition immersion and satisfaction is analyzed. Specifically, this study investigates how virtual exhibition experiences, similar to those in physical galleries, provide a sense of reality, leading to immersion in the artwork and ultimately resulting in satisfaction. The findings reveal that, among the VR exhibition experience factors, entertainment, escapism, and aesthetic experiences positively (+) affected interaction, while educational experiences negatively (−) influenced it. Furthermore, entertainment, escapism, and educational experiences positively influenced presence, whereas aesthetic experiences did not significantly impact it. Interaction significantly affected presence and positively influenced both immersion and satisfaction. Presence positively affected immersion but did not significantly affect satisfaction. Finally, immersion positively affected satisfaction. This study suggests that strategies that enhance interaction and presence are crucial in designing VR exhibition experiences. They also provide an important foundation for future research by systematically analyzing the relationships between presence, interaction, immersion, and satisfaction in VR exhibition experiences. Full article

► Show Figures

Figure 1

24 pages, 1588 KiB

Open AccessArticle

A New Model of Emergency Supply Management for Swift Transition from Peacetime to Emergency Considering Demand Urgency and Supplier Evaluation

by Jiaqi Fang, Lvjiangnan Ye, Wenli Zhou and Lihui Xiong

Systems 2025, 13(1), 54; https://doi.org/10.3390/systems13010054 - 16 Jan 2025

Viewed by 426

Abstract

In recent years, the increasing complexity of natural disasters has highlighted the limitations of existing emergency material assistance systems. To address these challenges, this study proposes a collaborative adaptation mechanism for “peacetime and emergency integration” and develops a supplier evaluation framework. The framework [...] Read more.

In recent years, the increasing complexity of natural disasters has highlighted the limitations of existing emergency material assistance systems. To address these challenges, this study proposes a collaborative adaptation mechanism for “peacetime and emergency integration” and develops a supplier evaluation framework. The framework incorporates multi-dimensional indicators such as profit, business credit, regional advantages, and emergency capability. Using a DEMATEL-ANP-based model, supplier L2 is identified as the optimal choice with a weight of 0.285. A fuzzy comprehensive assessment approach is applied to classify emergency materials based on demand urgency, identifying drinking water, rescue tools, medical supplies, and other critical items as priority resources. The evaluation vectors for these materials range from 0.1540 to 0.9909. This study enhances emergency material management through improved information systems, a better control of critical processes, and a unified assurance strategy. It provides theoretical support and practical guidance for more scientific and standardized disaster management practices. Full article

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

► Show Figures

Figure 1

22 pages, 3298 KiB

Open AccessArticle

Stages of Systems Engineering: An Analysis and Characterization of Systems Engineering Approaches

by Iris Graessler and Benedikt Grewe

Systems 2025, 13(1), 53; https://doi.org/10.3390/systems13010053 - 16 Jan 2025

Viewed by 711

Abstract

In the engineering of complex technical systems, Systems Engineering (SE) is a key approach that is becoming increasingly relevant in more and more industries due to the ever-increasing complexity of systems. Over the decades of practical application and research, various specializations and forms [...] Read more.

In the engineering of complex technical systems, Systems Engineering (SE) is a key approach that is becoming increasingly relevant in more and more industries due to the ever-increasing complexity of systems. Over the decades of practical application and research, various specializations and forms of the Systems Engineering approach have developed, but there has so far been a lack of an overarching context and positioning in meaningful stages for the introduction of Systems Engineering in companies. For this reason, this research will systematize common Systems Engineering approaches and bring them together in a stage model for Systems Engineering. Based on a systematic literature review, use cases are identified for each approach and stage, which support companies in selecting an approach suitable for their own organization. Full article

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

► Show Figures

Figure 1

42 pages, 2540 KiB

Open AccessSystematic Review

Recent Trends in Information and Cyber Security Maturity Assessment: A Systematic Literature Review

by Alenka Brezavšček and Alenka Baggia

Systems 2025, 13(1), 52; https://doi.org/10.3390/systems13010052 - 15 Jan 2025

Viewed by 975

Abstract

This work represents a comprehensive and systematic literature review (SLR) that follows the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines for research assessing information and cyber security maturity. The period from 2012 to 2024 was considered and the final collection [...] Read more.

This work represents a comprehensive and systematic literature review (SLR) that follows the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines for research assessing information and cyber security maturity. The period from 2012 to 2024 was considered and the final collection of 96 studies was taken into account. Our findings were summarised in two stages, a quantitative analysis and a qualitative synthesis. In the first part, various quantitative indicators were used to analyse the evolution of the information and cyber security maturity assessment domain over the last twelve years. The qualitative synthesis, which was limited to 36 research papers, categorises the studies into three key areas: the development of new maturity models, the implementation of established models and frameworks, and the advancement of methodologies to support maturity assessments. The findings reveal significant progress in sector-specific customisation, the growing importance of lightweight models for small and medium-sized enterprises (SMEs), and the integration of emerging technologies. This study provides important insights into the evolving landscape of information and cyber security maturity assessment and provides actionable recommendations for academia and industry to improve security resilience and support the adoption of tailored, effective maturity models. Full article

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

► Show Figures

Figure 1

30 pages, 4205 KiB

Open AccessArticle

Forecasting Renewable Energy Consumption Using a Novel Fractional Grey Reverse Accumulation Model

by Yipeng Zhang and Huiping Wang

Systems 2025, 13(1), 51; https://doi.org/10.3390/systems13010051 - 15 Jan 2025

Viewed by 427

Abstract

The accumulation operation is the most fundamental method for processing data in grey models, playing a decisive role in the accuracy of model predictions. However, the traditional forward accumulation method does not adhere to the principle of prioritizing new information. Therefore, we propose [...] Read more.

The accumulation operation is the most fundamental method for processing data in grey models, playing a decisive role in the accuracy of model predictions. However, the traditional forward accumulation method does not adhere to the principle of prioritizing new information. Therefore, we propose a novel fractional reverse accumulation, which increases the accumulation coefficient for new data to fully utilize the new information carried by the latest data. This led to the development of a novel grey model, termed the FGRM(1,1). This model was validated using renewable energy consumption data from France, Spain, the UK, and Europe, and the results demonstrated that the FGRM(1,1) outperformed other models in terms of simulation error, prediction error, and comprehensive error. The predictions indicated significant growth in renewable energy consumption for France and Spain, moderate growth for the UK, and robust growth for Europe overall. These findings highlight the effectiveness of the proposed model in utilizing new information and provide insights into energy transition and emission reduction potential in Europe. Full article

► Show Figures

Figure 1

19 pages, 1056 KiB

Open AccessArticle

Proposal of a Correlation Model Integrating FDRM and CLSCM Practices and Performance Measures: A Case Study from the Automotive Battery Industry in Brazil

by Antonio Marco-Ferreira, Reginaldo Fidelis, Francielle Cristina Fenerich, Rafael Henrique Palma Lima, Pedro Paulo De Andrade Junior and Diogo José Horst

Systems 2025, 13(1), 50; https://doi.org/10.3390/systems13010050 - 15 Jan 2025

Viewed by 643

Abstract

The field of closed-loop supply chain management (CLSCM) seeks to replace the linear flow of materials and energy with a cyclical model in which the outputs of the production system become inputs to the same system, thus closing the cycle of materials and [...] Read more.

The field of closed-loop supply chain management (CLSCM) seeks to replace the linear flow of materials and energy with a cyclical model in which the outputs of the production system become inputs to the same system, thus closing the cycle of materials and energy within the supply chain. Current literature on CLSCM reports a wide variety of practices, and combining these practices with environmental performance measures is an ongoing challenge, mainly because results from these practices are often diffuse and linking them with performance results is not a straightforward task. This paper addresses this problem by proposing a model to prioritize CLSCM practices and performance measures. The correlation model integrating the fuzzy direct rating method (FDRM) and CLSCM practices and performance measures was tested in a real company that is part of a closed-loop supply chain that recycles lead obtained from automotive batteries in Brazil. The results allowed the identification of which management practices are more relevant to the organization by correlating their impact with performance measures. The most relevant practices for the company under study were demand forecasting, with 21.68% of relative importance, followed by reverse logistics practices (21.15%) and production planning and control (18.16%). Another relevant finding is that upstream performance measures account for 77.72% of the company’s CLSCM performance. Full article

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

► Show Figures

Figure 1

29 pages, 10143 KiB

Open AccessArticle

Identifying Key Nodes and Enhancing Resilience in Grain Supply Chains Under Drought Conditions

by Shuiwang Zhang and Chuansheng Zhou

Systems 2025, 13(1), 49; https://doi.org/10.3390/systems13010049 - 14 Jan 2025

Viewed by 751

Abstract

Grain supply chains remain stable in the face of natural disasters, and the resilience of the grain supply chain plays an important role. In a complex scenario of exposure to shocks, it is significant to identify the critical nodes of the grain supply [...] Read more.

Grain supply chains remain stable in the face of natural disasters, and the resilience of the grain supply chain plays an important role. In a complex scenario of exposure to shocks, it is significant to identify the critical nodes of the grain supply chain and propose countermeasures accordingly to enhance the resilience of the grain supply chain. In this paper’s study, firstly, a triangular model of contradictory events is used to describe complex scenarios and obtain Bayesian network nodes. Secondly, the fragmentation of the scenario is based on the description of the scene, the scene stream is constructed, the event network is obtained, and the Bayesian network structure is built on the basis. Then, combining expert knowledge and D–S evidence theory, the Bayesian network parameters are determined, and the Bayesian network model is built. Finally, the key nodes of the grain supply chain are identified in the context of the 2022 drought data in the Yangtze River Basin in China, and, accordingly, a strategy for improving the resilience of the grain supply chain is proposed in stages. This study provides a new research perspective on issues related to grain supply-chain resilience and enriches the theoretical foundation of research related to supply-chain resilience. Full article

► Show Figures

Figure 1

30 pages, 1605 KiB

Open AccessArticle

Risk Analysis of Digital Twin Project Operation Based on Improved FMEA Method

by Longyu Li, Jianxin You and Tao Xu

Systems 2025, 13(1), 48; https://doi.org/10.3390/systems13010048 - 13 Jan 2025

Viewed by 535

Abstract

With the advent of digitization, digital twin technology is gradually becoming one of the core technologies of the Industry 4.0 era, highlighting the increasing importance of digital twin project management. Despite its potential, DT projects face significant risks during implementation, stemming from technical, [...] Read more.

With the advent of digitization, digital twin technology is gradually becoming one of the core technologies of the Industry 4.0 era, highlighting the increasing importance of digital twin project management. Despite its potential, DT projects face significant risks during implementation, stemming from technical, managerial, and operational complexities. To address these challenges, this study proposes an improved failure mode and effect analysis (FMEA) framework by integrating double hierarchy hesitant fuzzy linguistic term sets (DHHFLTSs) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). This framework converts qualitative assessments into quantitative metrics and calculates weights using a hybrid approach, enabling more precise risk prioritisation. Application of the model to an automotive manufacturing company’s DT project identified key risks, particularly in the iteration and upgrade phase, emphasising the importance of cross-departmental collaboration and robust digital infrastructure. The proposed model provides a systematic framework for enterprises to assess and mitigate risks, ensuring the successful deployment of DT projects. Full article

► Show Figures

Figure 1

23 pages, 2775 KiB

Open AccessArticle

Artificial Intelligence as a Catalyst for Management System Adaptability, Agility and Resilience: Mapping the Research Agenda

by Ion Popa, Simona Cătălina Ștefan, Andrei Josan, Corina-Elena Mircioiu and Nicoleta Căruceru

Systems 2025, 13(1), 47; https://doi.org/10.3390/systems13010047 - 12 Jan 2025

Viewed by 1161

Abstract

Artificial intelligence (AI) is an increasingly notable presence in society, industries, and organizations, making its necessity felt more in managerial decisions and practices. This paper aims to outline the importance of the topic related to the increase in the adaptability, agility, and resilience [...] Read more.

Artificial intelligence (AI) is an increasingly notable presence in society, industries, and organizations, making its necessity felt more in managerial decisions and practices. This paper aims to outline the importance of the topic related to the increase in the adaptability, agility, and resilience of the management system as a result of AI integration, resorting to a bibliometric type of research. A total of 107 papers from the period 2007–2024 exported from the Web of Science Core Collection database were analyzed, with support of Biblioshiny software. This topic is proving to be one of heightened global interest, being comprehensively addressed by world leaders in AI research and technologies such as the United States, China, Great Britain, France, India, and beyond. Collaborative relationships established between geographic regions are captured, noting the power and expansion of the theme on all continents of the globe. Likewise, its thematic and strategic evolution is characterized as a surprising one, managing to incorporate and relate concepts with a strong technical and IT character such as feature extraction, machine learning, reinforcement learning with concepts of a managerial nature as supporting customer-tailored interaction, employee skills development, company productivity, and innovation. Full article

(This article belongs to the Special Issue Strategic Management in Digital Transformation Era)

► Show Figures

Figure 1

19 pages, 3805 KiB

Open AccessArticle

Driver Takeover Performance Prediction Based on LSTM-BiLSTM-ATTENTION Model

by Lijie Chen, Daofei Li, Tao Wang, Jun Chen and Quan Yuan

Systems 2025, 13(1), 46; https://doi.org/10.3390/systems13010046 - 11 Jan 2025

Viewed by 720

Abstract

Ensuring the driver’s readiness to take over before a takeover request is issued by an autonomous driving system is crucial for a safe takeover. However, current takeover prediction models suffer from poor prediction accuracy and do not consider the time dependence of input [...] Read more.

Ensuring the driver’s readiness to take over before a takeover request is issued by an autonomous driving system is crucial for a safe takeover. However, current takeover prediction models suffer from poor prediction accuracy and do not consider the time dependence of input features. In this regard, this study proposes a hybrid LSTM-BiLSTM-ATTENTION algorithm for driver takeover performance prediction. By building a takeover scenario and conducting experiments in the driving simulation experimental platform under the human–machine co-driving environment, the relevant state indicators in the 15 s per second before the takeover request is sent are extracted from three perspectives, namely, driver state, traffic environment, and personal attributes, as model inputs, and the level of takeover performance was labeled; the hybrid LSTM-BiLSTM-ATTENTION algorithm is used to construct a driver takeover performance prediction model and compare it with other five algorithms. The results show that the algorithm proposed in this study performs optimally, with an accuracy of 93.11%, a precision of 93.02%, a recall of 93.28%, and an F1 score of 93.12%. This study provides new ideas and methods for realizing the accurate prediction of driver takeover performance, and it can provide a decision basis for the safe design of self-driving vehicles. Full article

► Show Figures

Figure 1

26 pages, 1122 KiB

Open AccessArticle

How Can China’s Autonomous Vehicle Companies Use Digital Empowerment to Improve Innovation Quality?—The Role of Digital Platform Capabilities and Boundary-Spanning Search

by Mu Li, Yingqi Liu and Ruiyu Feng

Systems 2025, 13(1), 45; https://doi.org/10.3390/systems13010045 - 10 Jan 2025

Viewed by 502

Abstract

The acquisition, integration, and exchange of digital technologies considerably contribute to the improvement of corporate innovation quality, as autonomous vehicles are a complex amalgamation of multiple industrial chains. In order to address the intense global competition in the autonomous vehicles industry and help [...] Read more.

The acquisition, integration, and exchange of digital technologies considerably contribute to the improvement of corporate innovation quality, as autonomous vehicles are a complex amalgamation of multiple industrial chains. In order to address the intense global competition in the autonomous vehicles industry and help China’s enterprises establish a prominent position in technological innovation, this study innovatively integrates the concepts of digital empowerment, digital platform capabilities, and boundary-spanning search into a cohesive framework, examines the pathways of influence, and methodically builds a multiple-chain mediation model. It employs various quantitative models, such as reliability and validity testing, confirmatory factor analysis, common method bias testing, mediation effect analysis, and robustness testing. The study focuses on over a hundred companies related to autonomous vehicles in China, employing software such as SPSS26.0, AMOS26.0, PROCESS4.0, and MPLUS8.3 to conduct this analysis. The findings indicate that digital empowerment is a critical factor in the improvement of innovation quality within autonomous vehicle companies. The relationship between digital empowerment and innovation quality is partially mediated by digital platform capabilities, and the boundary-spanning search also functions as a partial intermediary. Additionally, the quality of innovation and digital empowerment are mediated by the boundary-spanning search and the capabilities of digital platforms. The results of this study provide valuable insights on how to accurately empower the high-quality development of the autonomous vehicle sector with digital technologies, revealing new perspectives on the innovation quality enhancement pathways for autonomous vehicle companies in China, offering pivotal insights amidst the escalating competition within the global autonomous vehicle sector. Full article

► Show Figures

Figure 1

25 pages, 2103 KiB

Open AccessArticle

A Study on the Impact of Watershed Compensation Policies on Green Technology Innovation Ecosystems

by Mo Li, Jianhua Zhu and Hua Dong

Systems 2025, 13(1), 44; https://doi.org/10.3390/systems13010044 - 10 Jan 2025

Viewed by 393

Abstract

This study uses the implementation of the watershed compensation policy as a quasi-natural experiment and selects a sample of 53 cities located within the four major watersheds from 2005 to 2022. By employing a staggered difference-in-differences model and a synthetic control difference-in-differences model, [...] Read more.

This study uses the implementation of the watershed compensation policy as a quasi-natural experiment and selects a sample of 53 cities located within the four major watersheds from 2005 to 2022. By employing a staggered difference-in-differences model and a synthetic control difference-in-differences model, the study investigates how watershed compensation policies influence green technology innovation ecosystems and delves into the underlying mechanisms that are responsible for these impacts. The research reveals the following findings: (1) The introduction of the watershed compensation policy markedly boosts the development of green technology innovation ecosystems in the pilot cities, and this finding remains consistent following a series of robustness checks. (2) An analysis of the mechanisms indicates that the watershed compensation policy exerts its impact on the advancement of green technology innovation ecosystems through a reduction in carbon emission intensity and the enhancement of wastewater treatment efficiency. (3) The influence of the watershed compensation policy on green technology innovation ecosystems varies according to the level of public financial expenditure and labor productivity. This research offers a factual foundation for comprehending the effects of watershed compensation policies on the innovation of green technologies within China. Full article

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

► Show Figures

Figure 1

21 pages, 4598 KiB

Open AccessArticle

Digital Transformation and Innovation Performance in Small- and Medium-Sized Enterprises: A Systems Perspective on the Interplay of Digital Adoption, Digital Drive, and Digital Culture

by Shaofeng Wang and Hao Zhang

Systems 2025, 13(1), 43; https://doi.org/10.3390/systems13010043 - 9 Jan 2025

Viewed by 1032

Abstract

Small- and medium-sized enterprises (SMEs) face complex systemic challenges in managing digital transformation while pursuing innovation in an increasingly interconnected business environment. This study adopts a systems theory perspective to investigate how digitalization enhances Innovation Performance by examining the dynamic interrelationships among digital [...] Read more.

Small- and medium-sized enterprises (SMEs) face complex systemic challenges in managing digital transformation while pursuing innovation in an increasingly interconnected business environment. This study adopts a systems theory perspective to investigate how digitalization enhances Innovation Performance by examining the dynamic interrelationships among digital adoption, digital drive, digital culture, and Innovation Performance. Through an empirical analysis of 201 Chinese SMEs using PLS-SEM, IPMA, and ANFIS approaches, we reveal that digital drive fully mediates the relationship between digital adoption and Innovation Performance, highlighting the systemic nature of digital transformation processes. Digital culture emerges as a critical moderator, positively influencing the relationships between digital adoption and digital drive, as well as between digital drive and Innovation Performance. These findings demonstrate how different elements of digital transformation form an integrated system where components interact to produce innovation outcomes. This study contributes to systems theory by illuminating the complex interdependencies in digital transformation and offers practical implications for managing systemic change in SMEs. Full article

► Show Figures

Figure 1

23 pages, 3649 KiB

Open AccessArticle

A Real Estate Price Index Forecasting Scheme Based on Online News Sentiment Analysis

by Tao Xu, Yingying Zhao and Jie Yu

Systems 2025, 13(1), 42; https://doi.org/10.3390/systems13010042 - 8 Jan 2025

Viewed by 588

Abstract

The real estate price index serves as a crucial indicator reflecting the operational status of the real estate market in China. However, it often lags until mid-next month, hindering stakeholders from grasping market trends in real time. Moreover, the real estate market has [...] Read more.

The real estate price index serves as a crucial indicator reflecting the operational status of the real estate market in China. However, it often lags until mid-next month, hindering stakeholders from grasping market trends in real time. Moreover, the real estate market has an extremely complex operating mechanism, which makes it difficult to accurately assess the impact of various policy and economic factors on the real estate price index. Therefore, we hope, from the perspective of data science, to explore the emotional fluctuations of the public towards the real estate market and to reveal the dynamic relationship between the real estate price index and online news sentiment. Leveraging massive online news data, we propose a forecasting scheme for the real estate price index that abandons complex policy and economic data dependence and is solely based on common and easily obtainable online news data. This scheme involves crawling historical online real estate news data in China, employing a BERT-based sentiment analysis model to identify news sentiment, and subsequently aggregating the monthly Real Estate Sentiment (RES) index for Chinese cities. Furthermore, we construct a Vector Autoregression (VAR) model using the historical RES index and housing price index to forecast future housing price indices. Extensive empirical research has been conducted in Beijing, Shanghai, Guangzhou, and Shenzhen, China, to explore the dynamic interaction between the RES index and both the new housing price index and the second-hand housing price index. Experimental results showcase the unique features of the proposed RES index in various cities and demonstrate the effectiveness and utility of our proposed forecasting scheme for the real estate price index. Full article

► Show Figures

Figure 1

23 pages, 5761 KiB

Open AccessArticle

A Follow-Up Risk Identification Model Based on Multi-Source Information Fusion

by Shuwei Guo, Yunyu Bo, Jie Chen, Yanan Liu, Jiajia Chen and Huimin Ge

Systems 2025, 13(1), 41; https://doi.org/10.3390/systems13010041 - 8 Jan 2025

Viewed by 473

Abstract

To address poor real-time performance and low accuracy in car-following risk identification, a model based on autoencoders is proposed. Using the SHRP2 natural driving dataset, this paper constructs a car-following risk identification model in two stages. In Stage 1, a deep feedforward neural [...] Read more.

To address poor real-time performance and low accuracy in car-following risk identification, a model based on autoencoders is proposed. Using the SHRP2 natural driving dataset, this paper constructs a car-following risk identification model in two stages. In Stage 1, a deep feedforward neural network autoencoder reconstructs preprocessed multi-source heterogeneous indicators of human-vehicle-road-environment. The high-dimensional latent space feature representation is used as input for Stage 2, enhancing the basic model’s performance. Eight basic models and sixteen models with autoencoders are compared using multiple evaluation indicators. A simulated driving test verifies the model’s generalization and robustness. Results show improved accuracy in car-following risk identification, with the optimized AutoEncoder_LR performing best at 91.33% for risk presence and 70.14% for risk levels. These findings can aid in safe driving and rear-end accident prevention. Full article

► Show Figures

Figure 1

21 pages, 499 KiB

Open AccessArticle

Research on the Cross-Regional Traveling Welcome Short Messaging Service During the COVID-19 Pandemic: A Survey from Mobile Users’ Perspective

by Zhiyuan Yu and Chi Zhang

Systems 2025, 13(1), 40; https://doi.org/10.3390/systems13010040 - 7 Jan 2025

Viewed by 642

Abstract

Based on spatiotemporal sensing techniques, the cross-regional traveling welcome short messaging service (TW-SMS) has been adopted in China and has become popular, typically being used when travelers pass through or arrive in cities. In this service, governmental institutions in combination with telecom operators [...] Read more.

Based on spatiotemporal sensing techniques, the cross-regional traveling welcome short messaging service (TW-SMS) has been adopted in China and has become popular, typically being used when travelers pass through or arrive in cities. In this service, governmental institutions in combination with telecom operators send welcome messages with the local characteristics. As a typical location-based service for mobile users, the TW-SMS includes reminders or alerts related to COVID-19 prevention and control. In this paper, we investigate the perceptions and behavior of mobile users regarding this special TW-SMS through mixed-methods research. An online survey was conducted among mobile users who engaged in intercity travel. After analyzing samples of TW-SMS data collected during the COVID-19 pandemic, we found that the respondents exhibited a relatively positive overall attitudes and recognized the necessity and helpfulness of the TW-SMS with its trusted content. For content analysis, we found that more than 70% of the messages transmitted by the TW-SMS were released by official departments (e.g., the COVID-19 Prevention and Control Office). Reminders about traveling registration and nucleic acid testing were assigned the highest importance, as they offer convenience in communicating the most up-to-date prevention and control information to mobile users during intercity travel. Through this study, we provide insights into epidemic prevention and control experiences during public health emergencies in cities. Full article

► Show Figures

Figure 1

27 pages, 586 KiB

Open AccessArticle

Enabling Digital Capabilities with Technologies: A Multiple Case Study of Manufacturing Supply Chains in Disruptive Times

by Marco Ardolino, Anna Bino, Maria Pia Ciano and Andrea Bacchetti

Systems 2025, 13(1), 39; https://doi.org/10.3390/systems13010039 - 7 Jan 2025

Viewed by 907

Abstract

In the rapidly changing digital economy, manufacturing companies are under growing pressure to adopt new approaches to business management by developing digital capabilities. This research explores the role of digital technologies in enabling these capabilities, using the Digital Capability Model (DCM) as a [...] Read more.

In the rapidly changing digital economy, manufacturing companies are under growing pressure to adopt new approaches to business management by developing digital capabilities. This research explores the role of digital technologies in enabling these capabilities, using the Digital Capability Model (DCM) as a guiding framework. While previous research often focused on theoretical perspectives, this study operationalizes the DCM by identifying specific applications of digital technologies that enhance business processes. Through a multiple case study methodology, eight manufacturing companies were examined to assess how digital technologies foster the development of digital capabilities. The case studies provide practical insights into the application of these technologies and their impact on organizational resilience and competitiveness, particularly in response to global disruptions such as the COVID-19 pandemic. Our findings reveal that certain technologies are more promising than others for enhancing digital capabilities and that their strategic implementation significantly improves a company’s ability to navigate uncertainty. Embracing digital transformation not only mitigates operational risks but also ensures sustainable competitive advantages in an increasingly volatile and complex environment. This research bridges the gap between theory and practice, offering actionable insights for managers to strategically develop and leverage digital capabilities for long-term success. Full article

(This article belongs to the Special Issue Enablers and Capabilities for the Digital Supply Chain)

► Show Figures

Figure 1

20 pages, 1936 KiB

Open AccessArticle

Product Competitive Analysis Model Based on Consumer Preference Satisfaction Similarity: Case Study of Smartphone UGC

by Yu Wang, Jiacong Wu, Xu Ye and Yue Wu

Systems 2025, 13(1), 38; https://doi.org/10.3390/systems13010038 - 7 Jan 2025

Viewed by 590

Abstract

Accurately identifying key competitors across multiple product lines is essential for enhancing the flexibility and competitiveness of product strategies. This study introduces a novel data-driven model for competitive analysis termed the Product Competition Analysis Model based on Consumer Preference Satisfaction Similarity (PCAM-CPSS). Unlike [...] Read more.

Accurately identifying key competitors across multiple product lines is essential for enhancing the flexibility and competitiveness of product strategies. This study introduces a novel data-driven model for competitive analysis termed the Product Competition Analysis Model based on Consumer Preference Satisfaction Similarity (PCAM-CPSS). Unlike traditional methods that rely on assessments of the competitive environment, the PCAM-CPSS leverages sentiment analysis of user-generated content (UGC) to quantify consumer preference satisfaction. This method constructs a network based on product satisfaction similarity to map competitive relationships and employs a community detection algorithm to identify key competitors. To assess the model’s efficacy, we collected and analyzed user reviews of various smartphone brands to serve as an evaluation dataset. We compared the performance of the PCAM-CPSS against two mainstream competitive analysis methods: attribute similarity-based ratings and co-occurrence statistics. The results, evaluated using the Normalized Discounted Cumulative Gain (NDCG) index, demonstrate that the PCAM-CPSS, particularly with price adjustment, offers significant advantages in identifying competitors more accurately than other evaluated methods. Full article

► Show Figures

Figure 1

Journal Menu

Journal Browser

Systems, Volume 13, Issue 1 (January 2025) – 67 articles

Further Information

Guidelines

MDPI Initiatives

Follow MDPI