Systems

55 pages, 29751 KB

Open AccessArticle

Multi-Objective Combinatorial Optimization for Dynamic Inspection Scheduling and Skill-Based Team Formation in Distributed Solar Energy Infrastructure

by Mazin Alahmadi

Systems 2025, 13(9), 822; https://doi.org/10.3390/systems13090822 (registering DOI) - 19 Sep 2025

Abstract

Maintaining operational efficiency in distributed solar energy systems requires intelligent coordination of inspection tasks and workforce resources to handle diverse fault conditions. This study presents a bi-level multi-objective optimization framework that addresses two tightly coupled problems: dynamic job scheduling and skill-based team formation. [...] Read more.

Maintaining operational efficiency in distributed solar energy systems requires intelligent coordination of inspection tasks and workforce resources to handle diverse fault conditions. This study presents a bi-level multi-objective optimization framework that addresses two tightly coupled problems: dynamic job scheduling and skill-based team formation. The job scheduling component assigns geographically dispersed inspection tasks to mobile teams while minimizing multiple conflicting objectives, including travel distance, tardiness, and workload imbalance. Concurrently, the team formation component ensures that each team satisfies fault-specific skill requirements by optimizing team cohesion and compactness. To solve the bi-objective team formation problem, we propose HMOO-AOS, a hybrid algorithm integrating six metaheuristic operators under an NSGA-II framework with an Upper Confidence Bound-based Adaptive Operator Selection. Experiments on datasets of up to seven instances demonstrate statistically significant improvements (

p < 0.05

) in solution quality, skill coverage, and computational efficiency compared to NSGA-II, NSGA-III, and MOEA/D variants, with computational complexity

O (G \cdot N \cdot (M + log N))

(time complexity),

O (N \cdot L)

(space complexity). A cloud-integrated system architecture is also proposed to contextualize the framework within real-world solar inspection operations, supporting real-time data integration, dynamic rescheduling, and mobile workforce coordination. These contributions provide scalable, practical tools for solar operators, maintenance planners, and energy system managers, establishing a robust and adaptive approach to intelligent inspection planning in renewable energy operations. Full article

(This article belongs to the Special Issue Advances in Operations and Production Management Systems)

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19 pages, 13414 KB

Open AccessArticle

Research on the Causal Chain of Vertical Collusion in Bidding for Government Investment Projects

by Dai Yao, Yun Chen and Chongsen Ma

Systems 2025, 13(9), 821; https://doi.org/10.3390/systems13090821 - 18 Sep 2025

Abstract

Effective control of collusive behavior in the government bidding process is a prerequisite for promoting the high-quality development of social economy, consolidating the results of the anti-corruption struggle and the smooth operation of the project. Based on risk theory and Bayesian networks, this [...] Read more.

Effective control of collusive behavior in the government bidding process is a prerequisite for promoting the high-quality development of social economy, consolidating the results of the anti-corruption struggle and the smooth operation of the project. Based on risk theory and Bayesian networks, this paper uses GeNIE 4.0 software to construct a Bayesian network structure model to analyze the causal chain of vertical collusion in government project tendering processes. The study found three key causal chain paths: ① external supervision subject to collusion gains, external environment, competitive pressure, and lack of compliance awareness of the formation of “external supervision subject → response subject → vertical collusion” regulatory failure of vertical collusion path; ② rights subject to collusion gains, the external environment, and the lack of publicity of policies and regulations. External supervision is influenced by collusion gains, the external environment, competitive pressure, and compliance awareness of the formation of the “rights subject → external supervision subject → response subject → vertical collusion” internal and external collusion path; the rights of the subject, affected by the collusion gains, the external environment, and the lack of publicity of policies and regulations, form a collusion path of uncontrolled rights. It is also found that, at the subject level, the subject of rights and the subject of external supervision are in a key position in the control process; at the factor level, the control of collusion proceeds, the publicity of policies and regulations, and the external environment can significantly enhance the control effect of vertical collusion and provide a precise focus for the collusion chain to break the chain. Full article

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

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33 pages, 1093 KB

Open AccessArticle

Research on the Impact of Digital and Green Transformation on Corporate Sustainability Performance from a Synergistic Perspective

by Yudan Zhu and Chunqing Li

Systems 2025, 13(9), 820; https://doi.org/10.3390/systems13090820 - 18 Sep 2025

Abstract

The digital and green transformation (DGT) has emerged as an essential strategy for companies to enhance competitiveness and achieve sustainable development. Current research has primarily concentrated on the effects of either digital or green transformation individually on corporate sustainability performance (CSP), while largely [...] Read more.

The digital and green transformation (DGT) has emerged as an essential strategy for companies to enhance competitiveness and achieve sustainable development. Current research has primarily concentrated on the effects of either digital or green transformation individually on corporate sustainability performance (CSP), while largely neglecting their synergistic impacts. This study emphasizes that DGT influences CSP mainly through two mechanisms: resource synergy, which alleviates financing constraints and optimizes resource allocation, and innovation synergy, which broadens enterprise knowledge scope and enhances innovation quality. Using data from Chinese publicly listed firms from 2015 to 2023, we adopt a two-way fixed-effects model to analyze the impact of DGT on CSP, the underlying mechanisms, and the moderating role of environmental regulations. The findings reveal the following: First, DGT exerts a significant positive influence on CSP, demonstrating a “multiplier effect” compared to the individual impacts of digital or green transformation alone. Second, environmental regulations positively moderate the relationship between DGT and CSP. Finally, DGT has a more pronounced positive impact on CSP in heavily polluting enterprises, under strong market competition environments, and with high intellectual property protection. This study not only enriches the research on DGT at the enterprise level but also provides empirical evidence from emerging economies for policymakers to formulate relevant strategies. Full article

(This article belongs to the Special Issue Systems Analysis of Enterprise Sustainability: Second Edition)

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17 pages, 2139 KB

Open AccessArticle

Decoding Digital Labor: A Topic Modeling Analysis of Platform Work Experiences

by Oya Ütük Bayılmış and Serdar Orhan

Systems 2025, 13(9), 819; https://doi.org/10.3390/systems13090819 - 18 Sep 2025

Abstract

The growing prevalence of digital labor platforms has fundamentally transformed business models by creating interconnected value systems that redefine how work is organized, delivered, and monetized in today’s digital economy. This study examines platform-based business model innovation through the lens of value co-creation [...] Read more.

The growing prevalence of digital labor platforms has fundamentally transformed business models by creating interconnected value systems that redefine how work is organized, delivered, and monetized in today’s digital economy. This study examines platform-based business model innovation through the lens of value co-creation processes, analyzing user-generated content from digital work platforms including Reddit, FlexJobs, Toptal, and Deel. Using Latent Dirichlet Allocation (LDA) topic modeling on 342 semantically filtered reviews from platform workers, we identified six key themes characterizing stakeholder experiences: User Experience and Platform Evaluation (23.77%), Financial Concerns and Time Management (18.49%), Platform Satisfaction and Recommendation System (16.60%), Paid Services and Investment Strategies (15.09%), Job Search Processes and Remote Work Alternatives (13.96%), and Overall Platform Performance and Account Management (12.08%). These findings reveal how digital platforms create value through complex interactions between technology infrastructure, governance mechanisms, and stakeholder experiences within interconnected ecosystems. The dominance of user experience concerns over purely economic considerations challenges traditional labor economics frameworks and highlights the critical role of platform design in worker satisfaction. Our analysis demonstrates that successful plsatform business models depend on balancing technological capabilities with human-centered value propositions, requiring innovative approaches to ecosystem orchestration, stakeholder engagement, and value distribution. The study contributes to understanding how digital business models can leverage interconnected value systems to drive sustainable innovation, offering strategic insights for platform design, ecosystem governance, and business model optimization in the digital era. Full article

(This article belongs to the Special Issue Business Model Innovation in the Digital Era)

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26 pages, 1737 KB

Open AccessArticle

Towards Enhanced Cyberbullying Detection: A Unified Framework with Transfer and Federated Learning

by Chandni Kumari and Maninder Kaur

Systems 2025, 13(9), 818; https://doi.org/10.3390/systems13090818 - 18 Sep 2025

Abstract

The internet’s evolution as a global communication nexus has enabled unprecedented connectivity, allowing users to share information, media, and personal updates across social platforms. However, these platforms also amplify risks such as cyberbullying, cyberstalking, and other forms of online abuse. Cyberbullying, in particular, [...] Read more.

The internet’s evolution as a global communication nexus has enabled unprecedented connectivity, allowing users to share information, media, and personal updates across social platforms. However, these platforms also amplify risks such as cyberbullying, cyberstalking, and other forms of online abuse. Cyberbullying, in particular, causes significant psychological harm, disproportionately affecting young users and females. This work leverages recent advances in Natural Language Processing (NLP) to design a robust and privacy-preserving framework for detecting abusive language on social media. The proposed approach integrates ensemble federated learning (EFL) and transfer learning (TL), combined with differential privacy (DP), to safeguard user data by enabling decentralized training without direct exposure of raw content. To enhance transparency, Explainable AI (XAI) methods, such as Local Interpretable Model-agnostic Explanations (LIME), are employed to clarify model decisions and build stakeholder trust. Experiments on a balanced benchmark dataset demonstrate strong performance, achieving 98.19% baseline accuracy and 96.37% with FL and DP respectively. While these results confirm the promise of the framework, we acknowledge that performance may differ under naturally imbalanced, noisy, and large-scale real-world settings. Overall, this study introduces a comprehensive framework that balances accuracy, privacy, and interpretability, offering a step toward safer and more accountable social networks. Full article

(This article belongs to the Special Issue Socio-Technical Cyber Security for Socio-Technical Systems: Human Factors and Other Perspectives)

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24 pages, 2090 KB

Open AccessArticle

Research on the Co-Evolution Mechanism of Electricity Market Entities Enabled by Shared Energy Storage: A Tripartite Game Perspective Incorporating Dynamic Incentives/Penalties and Stochastic Disturbances

by Chang Su, Zhen Xu, Xinping Wang and Boying Li

Systems 2025, 13(9), 817; https://doi.org/10.3390/systems13090817 - 18 Sep 2025

Abstract

The integration of renewable energy into the grid has led to problems such as low utilization rate of energy storage resources (“underutilization after construction”) and insufficient system stability. This paper studied the co-evolution mechanism of power market entities empowered by shared energy storage. [...] Read more.

The integration of renewable energy into the grid has led to problems such as low utilization rate of energy storage resources (“underutilization after construction”) and insufficient system stability. This paper studied the co-evolution mechanism of power market entities empowered by shared energy storage. Based on the interaction among power generation enterprises, power grid operators, and government regulatory agencies, this paper constructed a three-party evolutionary game model. The model introduced a dynamic reward and punishment mechanism as well as a random interference mechanism, which makes it more in line with the actual situation. The stability conditions of the game players were analyzed by using stochastic differential equations, and the influences of key parameters and incentive mechanisms on the stability of the game players were investigated through numerical simulation. The main research results showed the following: (1) The benefits of shared energy storage and opportunistic gains had a significant impact on the strategic choices of power generation companies and grid operators. (2) The regulatory efficiency had significantly promoted the long-term stable maintenance of the system. (3) Dynamic incentives were superior to static incentives in promoting cooperation, while the deterrent effect of static penalties is stronger than that of dynamic penalties. (4) The increase in the intensity of random disturbances led to strategy oscillation. This study suggested that the government implement gradient-based dynamic incentives, maintain strict static penalties to curb opportunism, and enhance regulatory robustness against uncertainty. This research provided theoretical and practical inspirations for optimizing energy storage incentive policies and promoting multi-subject coordination in the power market. Full article

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22 pages, 1346 KB

Open AccessArticle

Towards Digital Transformation in the Construction Industry: A Selection Framework of Building Information Modeling Lifecycle Service Providers (BLSPs)

by Guangchong Chen, Qianqin Feng, Chengcheng Jiang, Shengxi Zhang and Qiming Li

Systems 2025, 13(9), 816; https://doi.org/10.3390/systems13090816 - 18 Sep 2025

Abstract

Purpose: The construction industry is now experiencing a thorough transformation through digital technologies, especially with building information modeling (BIM). Despite significant BIM advantages, most construction projects suffer from low BIM performance due to the fragmented BIM use mode. To facilitate lifecycle-integrated BIM implementation, [...] Read more.

Purpose: The construction industry is now experiencing a thorough transformation through digital technologies, especially with building information modeling (BIM). Despite significant BIM advantages, most construction projects suffer from low BIM performance due to the fragmented BIM use mode. To facilitate lifecycle-integrated BIM implementation, this study demonstrates that introducing BIM lifecycle service providers (BLSPs) is feasible and offers significant improvements in terms of BIM benefits. Hence, this study proposes a customized framework to select BLSPs. Approach: This study utilized both qualitative and quantitative methods. It first adopted semi-structured interviews as part of the qualitative method to deduce the initial criteria for BLSPs’ selection. 30 interviews were conducted iteratively with managers proficient and experienced in selecting BLSPs, through which 25 initial criteria were identified. Then, as the basis of the applied quantitative method, a questionnaire survey was used to evaluate these criteria by determining the critical ones, identifying the latent factor groupings, and assigning criteria weights. Subsequently, an assessment framework was established. Finally, the study was in favor of eight construction projects, highlighting the practicality and validity of the framework. Findings: The results depicted that project BIM service capability is a primary factor for BLSPs’ selection. Within this factor, several specialized criteria need to be considered, such as “boundary spanning competence of the BIM manager” and “BIM service plans with lifecycle cognition.” Meanwhile, “past innovative BIM service practices” and “BIM research and development (R&D)” that originate in corporate innovation capacity were emphasized when selecting BLSPs. Furthermore, for holistic assessment and recognizing the peculiarities of digital BIM service, the study found that criteria like “Privacy and security” and “Backup system” are required, which demonstrate BIM service reliability. Originality/value: This study expands on the conventional partner selection frameworks in the construction sector and thus defines and validates a tailored one for BLSPs’ selection. Moreover, drawing such a reference solution from the framework, the study enables the selection of appropriate BLSPs for clients. Full article

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36 pages, 1933 KB

Open AccessArticle

Unraveling the Spatial Effects of Fintech on Urban Energy Efficiency in China

by Di Wang, Tianqi Wang and Rong Zhao

Systems 2025, 13(9), 815; https://doi.org/10.3390/systems13090815 - 17 Sep 2025

Abstract

Improving urban energy efficiency is essential for addressing energy shortages and environmental pollution, thereby facilitating a win–win outcome for both the economy and the environment. As an emerging financial force, fintech is essential for facilitating energy saving, reducing emissions, and advancing modernization. Using [...] Read more.

Improving urban energy efficiency is essential for addressing energy shortages and environmental pollution, thereby facilitating a win–win outcome for both the economy and the environment. As an emerging financial force, fintech is essential for facilitating energy saving, reducing emissions, and advancing modernization. Using panel data of 278 cities in China from 2011 to 2022 to construct a spatial Durbin model for investigating how fintech affects energy efficiency, the following results were found: (1) Energy efficiency shows positive spatial dependence features, and the enhancement of energy efficiency in this location positively influences the energy efficiency of spatially connected regions. (2) Fintech improves local energy efficiency and has notable positive geographical spillover effects on surrounding regions’ energy efficiency. (3) Three mediating pathways are identified: upgrading industrial structure, promoting green innovation, and driving green finance evolution. (4) The regulatory mechanism suggests that environmental regulations can help strengthen fintech’s geographical spillover benefits for the energy efficiency of neighboring areas. The impact of fintech on energy efficiency exhibits heterogeneity due to differences in urban resources and digital infrastructure. These insights offer important theoretical contributions and practical significance for policy-makers in advancing fintech development and urban energy efficiency. Full article

(This article belongs to the Special Issue Technological Innovation Systems and Energy Transitions)

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16 pages, 725 KB

Open AccessArticle

A Study on the Factors Influencing Residents’ Intention of Continuous Residence in Innovation Cities: The Case of South Korea

by Kyung-Young Lee

Systems 2025, 13(9), 814; https://doi.org/10.3390/systems13090814 - 17 Sep 2025

Abstract

This study examined the relationship between residential environment satisfaction, neighbor relations, and the intention of continuous residence. Previous research has not comprehensively analyzed the combined effects of these factors. Accordingly, this study investigated the influence of residential environment satisfaction on the intention of [...] Read more.

This study examined the relationship between residential environment satisfaction, neighbor relations, and the intention of continuous residence. Previous research has not comprehensively analyzed the combined effects of these factors. Accordingly, this study investigated the influence of residential environment satisfaction on the intention of continuous residence and analyzed the mediating role of neighbor relations. Residential environments were categorized into commercial facilities, medical facilities, childcare/educational facilities, and cultural facilities. Respondents aged 20 years and above were selected from Innovation Cities where public institution relocation had been completed. Data were collected from 1606 participants through an online survey. Hypotheses were tested using mediation analysis. The results showed that residential environment satisfaction positively influenced the intention of continuous residence, with satisfaction with medical facilities having the strongest effect. In addition, neighbor relations had both direct and indirect positive effects on the intention of continuous residence, underscoring their importance in encouraging residents to remain. In many developing countries where the private market is less developed, state-owned enterprises play a crucial role in the national economy, and development is often concentrated around their locations. In the long term, relocating public institutions could serve as a strategy to address regional disparities. The findings of this study thus offer important policy implications. Full article

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32 pages, 834 KB

Open AccessArticle

A Systematic Lean-Driven Framework for Warehouse Optimization

by Bruno J. B. Julião, Marco S. Reis and Belmiro P. M. Duarte

Systems 2025, 13(9), 813; https://doi.org/10.3390/systems13090813 - 17 Sep 2025

Abstract

Optimizing warehouse operations is a strategic priority for ensuring the timely and efficient flow of materials in industrial environments. In contexts with limited digital infrastructure, organizations often face persistent challenges such as inefficient picking, poor material traceability, and suboptimal space utilization, ultimately leading [...] Read more.

Optimizing warehouse operations is a strategic priority for ensuring the timely and efficient flow of materials in industrial environments. In contexts with limited digital infrastructure, organizations often face persistent challenges such as inefficient picking, poor material traceability, and suboptimal space utilization, ultimately leading to productivity losses and operational delays. This paper introduces a systematic, lean-driven framework for warehouse optimization, structured around a sequential methodology involving Define, Improve, and Control. The approach begins with a comprehensive diagnostic phase to evaluate the current state and identify performance gaps. It then guides the development and implementation of targeted interventions aimed at eliminating waste, standardizing operations, and aligning resources with value-added activities. Finally, the framework supports long-term sustainability through continuous monitoring, process standardization, and performance control. The methodology is validated through its application in a parts warehouse within the glass transformation industry, highlighting its adaptability, practical relevance, and capacity to generate meaningful improvements, even in low-digitalization environments. The framework offers a scalable solution for organizations seeking to enhance warehouse performance through structured lean practices. Full article

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24 pages, 1893 KB

Open AccessArticle

The Impact of the “Inclusion of Rehabilitation Services in Basic Medical Insurance” Policy on the Utilization of Rehabilitation Services and Household Healthcare Expenditure Among Older Adults with Disabilities: Evidence from China

by Yiran Wang, Lu Tan, Xiaodong Zhang, Xiaoqian Yan, Le Wang, Chenyu Yan, Yichunzi Zhang, Tianran Wang, Sijiu Wang and Wannian Liang

Systems 2025, 13(9), 812; https://doi.org/10.3390/systems13090812 - 16 Sep 2025

Abstract

Background: The intersection of aging and disability is an important social issue. The rehabilitation system of older adults with disabilities is a complex social system including various social units. This study aims to investigate the impact of the “inclusion of rehabilitation services in [...] Read more.

Background: The intersection of aging and disability is an important social issue. The rehabilitation system of older adults with disabilities is a complex social system including various social units. This study aims to investigate the impact of the “inclusion of rehabilitation services in basic medical insurance” (IRSMI) policy on the utilization of rehabilitation services and annual household healthcare expenditure among older adults with disabilities. Methods: Using the data of China Disabled Persons’ Condition Monitoring Survey (2009–2012), this study employed the difference-in-differences method to analyze the impact of IRSMI on rehabilitation services utilization and household healthcare expenditure, and further examined the differential effects of the policy on service utilization across subpopulations with different demographic characteristics, including gender, age, and disability severity. The Heckman two-stage model corrects for sample selection bias caused by the share of households with zero health expenditures. Event-study specification was applied to assess the validity of the parallel trends assumption in the DID framework. Baron & Kenny’s three-step method was used to explore the potential mediating mechanism. Results: (1) IRSMI significantly increased the likelihood of utilizing rehabilitation services among older adults with disabilities (OR = 1.349), but this kind of promotive effect mainly focus on males (OR = 1.530), middle-aged and older disabled individuals (OR = 1.423), and those with mild disabilities (OR = 1.444). (2) The implementation of IRSMI contributed to an approximately 20.3% increase in annual healthcare expenditures for households with older adults with disabilities (

β

= 0.185). (3) IRSMI significantly promoted the increase in household healthcare expenditures for high-income older adults with disabilities (

β

= 0.181), but had limited impact on low- and middle-income groups. (4) Rehabilitation services utilization played a mediating role in the relationship between IRSMI and household healthcare expenditure, with about 19.0% of the increase in annual household healthcare expenditures attributable to the enhanced utilization of rehabilitation services. Conclusions: In the complex social system of rehabilitation for older adults with disabilities, the IRSMI policy significantly increases the likelihood of rehabilitation services utilization and substantially raises annual household healthcare expenditures. However, the heterogeneous effects across gender, age, disability severity, and income levels reflect structural inequities embedded in the rehabilitation system, underscoring the need for adaptive and equity-oriented interventions. Full article

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

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27 pages, 1117 KB

Open AccessArticle

Enabling Intelligent Data Modeling with AI for Business Intelligence and Data Warehousing: A Data Vault Case Study

by Andreea Vines, Ana-Ramona Bologa and Andreea-Izabela Bostan

Systems 2025, 13(9), 811; https://doi.org/10.3390/systems13090811 - 16 Sep 2025

Abstract

This study explores the innovative application of Artificial Intelligence (AI) in transforming data engineering practices, with a specific focus on optimizing data modeling and data warehouse automation for Business Intelligence (BI) systems. The proposed framework automates the creation of Data Vault models directly [...] Read more.

This study explores the innovative application of Artificial Intelligence (AI) in transforming data engineering practices, with a specific focus on optimizing data modeling and data warehouse automation for Business Intelligence (BI) systems. The proposed framework automates the creation of Data Vault models directly from raw source tables by leveraging the advanced capabilities of Large Language Models (LLMs). The approach involves multiple iterations and uses a set of LLMs from various providers to improve accuracy and adaptability. These models identify relevant entities, relationships, and historical attributes by analyzing the metadata, schema structures, and contextual relationships embedded within the source data. To ensure the generated models are valid and reliable, the study introduces a rigorous validation methodology that combines syntactic, structural, and semantic evaluations into a single comprehensive validity coefficient. This metric provides a quantifiable measure of model quality, facilitating both automated evaluation and human understanding. Through iterative refinement and multi-model experimentation, the system significantly reduces manual modeling efforts, enhances consistency, and accelerates the data warehouse development lifecycle. This exploration serves as a foundational step toward understanding the broader implications of AI-driven automation in advancing the state of modern Big Data warehousing and analytics. Full article

(This article belongs to the Special Issue Business Intelligence and Data Analytics in Enterprise Systems)

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27 pages, 3114 KB

Open AccessArticle

Analysis of Information-Sharing Mechanisms in Online Closed-Loop Supply Chain Systems

by Dandan Gao, Nengmin Wang and Bin Jiang

Systems 2025, 13(9), 810; https://doi.org/10.3390/systems13090810 - 16 Sep 2025

Abstract

This research analyzes optimal information-sharing (IS) mechanisms in online closed-loop supply chain (CLSC) systems. In contrast to offline supply chains, online retailers hold a significant informational edge over their upstream counterparts due to their access to both demand and return information. Given that [...] Read more.

This research analyzes optimal information-sharing (IS) mechanisms in online closed-loop supply chain (CLSC) systems. In contrast to offline supply chains, online retailers hold a significant informational edge over their upstream counterparts due to their access to both demand and return information. Given that information asymmetry severely diminishes the efficiency of online CLSCs, it is imperative to optimize IS mechanisms to enhance operational performance. We emphasize the impact of product return and replacement information in e-businesses on inventory costs and bullwhip effects. The present study systematically characterizes four distinct IS mechanisms to assess their efficacy in mitigating information variability and inventory costs. The results underscore the vital importance of return information for supply chain management practices. A distributor who fails to account for return dynamics in their e-business may experience a detrimental operational performance. Particularly, online supply chains exhibit distinctive anomalies: sharing demand information may unexpectedly amplify bullwhip effects if the return period surpasses an online retailer’s lead time. This study offers valuable perspectives to assist managers in identifying the most effective IS strategies based on particular supply chain contexts, thereby facilitating robust supply chain partnerships. Full article

(This article belongs to the Section Supply Chain Management)

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31 pages, 9933 KB

Open AccessArticle

Assessment of Flood Disaster Resilience in an Urban Historic District Based on G-IC Model

by Bo Huang, Tsuyoshi Kinouchi and Gang Zhao

Systems 2025, 13(9), 809; https://doi.org/10.3390/systems13090809 - 15 Sep 2025

Abstract

Urban historic districts play a vital role in shaping the cultural identity and heritage of cities. However, many of these areas face challenges such as aging buildings and deteriorating infrastructure. At the same time, the increasing frequency of extreme rainfall has led to [...] Read more.

Urban historic districts play a vital role in shaping the cultural identity and heritage of cities. However, many of these areas face challenges such as aging buildings and deteriorating infrastructure. At the same time, the increasing frequency of extreme rainfall has led to a rise in flood events, placing these vulnerable districts at greater risk. Therefore, it is essential to carry out a comprehensive and objective assessment of their resilience to flood disasters. This study establishes a G-IC model for evaluating the resilience of urban historic districts to flood disasters based on the game combination empowerment-improved cloud model method. The proposed method has been demonstrated in the Soviet-style building complex of the Daye Steel Plant in Huangshi and reveals that the driving force layer exhibits weak resilience; the pressure and state layers show general resilience; the impact and response layers demonstrate weak resilience; and the overall resilience of the district is categorized as weak. The consistency of the results was verified by calculating the cloud similarity, which shows that the constructed new model has certain rationality and feasibility, and the evaluation results are relatively accurate. The findings offer valuable insights for policy-making and support for decision-makers in local government departments. Full article

(This article belongs to the Special Issue Smart Urban Planning and Governance: Rethinking Cities to Tackle Natural and Climate Risks)

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17 pages, 1474 KB

Open AccessArticle

Quantitative Analysis of Satisfaction with Chinese Local Government Digital Public Service Policies Using XGBoost Algorithm

by Qin Hu, Bin Yang and Shengli Dai

Systems 2025, 13(9), 808; https://doi.org/10.3390/systems13090808 - 15 Sep 2025

Abstract

With the development of digital technology, although local governments have been using digital means to improve the quality of public services, traditional statistical methods have limitations in processing complex, high-dimensional data and revealing factors influencing policies. This paper used the XGBoost algorithm to [...] Read more.

With the development of digital technology, although local governments have been using digital means to improve the quality of public services, traditional statistical methods have limitations in processing complex, high-dimensional data and revealing factors influencing policies. This paper used the XGBoost algorithm to construct a satisfaction prediction model, leveraging its advantages in handling nonlinear relationships and feature interactions to assist government decision-making through prediction and feature analysis. This study is based on questionnaire surveys and public data, and the optimal configuration of the model was determined through preprocessing and parameter tuning. Experiments showed that the proposed model outperforms other models in terms of prediction accuracy, robustness, efficiency, and cross-scenario applicability. Through empirical analysis, this study shows that the XGBoost model has significant advantages in predicting local government digital public service policy satisfaction. Its mean square error (MSE) is only 0.056, which is 37.1% lower than the traditional linear regression model. This means that XGBoost can more accurately capture the complex nonlinear relationships that influence public satisfaction. Full article

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27 pages, 4750 KB

Open AccessArticle

Dynamics and Drivers of Ecosystem Service Values in the Qionglai–Daxiangling Region of China’s Giant Panda National Park (1990–2020)

by Yang Chen, Ruizhi Zhang, Laleh Dehghanifarsani and Majid Amani-Beni

Systems 2025, 13(9), 807; https://doi.org/10.3390/systems13090807 - 15 Sep 2025

Abstract

Understanding the spatiotemporal dynamics and driving forces of ecosystem service values (ESVs) is essential for managing complex socioecological systems, particularly in biodiversity-rich mountainous protected areas. This study investigates the evolution and interactions of ESVs in the Qionglai–Daxiangling region (QDR) of China’s Giant Panda [...] Read more.

Understanding the spatiotemporal dynamics and driving forces of ecosystem service values (ESVs) is essential for managing complex socioecological systems, particularly in biodiversity-rich mountainous protected areas. This study investigates the evolution and interactions of ESVs in the Qionglai–Daxiangling region (QDR) of China’s Giant Panda National Park (GPNP) from 1990 to 2020. Based on a revised equivalent factor method, we quantified ESV changes and analyzed trade-offs and synergies among provisioning, regulating, supporting, and cultural services. A Random Forest (RF) model integrated with SHapley Additive exPlanations (SHAP) was employed to assess the relative importance and interpretability of climatic, topographic, and socioeconomic drivers. The results show that elevation, wind speed, and sunshine duration are the most influential variables affecting ESVs. Notably, synergistic relationships among ecosystem services have increased over the past three decades, reflecting the impacts of national ecological restoration initiatives such as the Returning Farmland to Forest Program (RFFP). The SHAP-based analysis further revealed the complex, nonlinear contributions of both environmental and anthropogenic factors. This study provides an interpretable modeling framework for diagnosing ESV dynamics in protected mountainous landscapes. The findings offer practical insights for adaptive management and evidence-based policymaking in national parks under changing environmental and socioeconomic conditions. To better capture the anthropogenic influences on ecosystem functionality in mountainous regions, future studies should incorporate fine-scale land use data and broaden the socioeconomic indicator set to include variables such as ecological compensation and conservation enforcement levels. Full article

(This article belongs to the Special Issue Applying Systems Thinking to Enhance Ecosystem Services)

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78 pages, 7172 KB

Open AccessArticle

From Fragmented Criteria to a Structured Decision Support Mode: Designing a DEX-Based DSS for Assessing Organizational Readiness for Co-Creation

by Rok Hržica

Systems 2025, 13(9), 806; https://doi.org/10.3390/systems13090806 - 15 Sep 2025

Abstract

Co-creation emphasizes the active involvement of stakeholders in the design and delivery of public services. Despite its potential benefits, many public organizations struggle to implement co-creation because they are unclear about their readiness. To address this gap, this study develops a decision support [...] Read more.

Co-creation emphasizes the active involvement of stakeholders in the design and delivery of public services. Despite its potential benefits, many public organizations struggle to implement co-creation because they are unclear about their readiness. To address this gap, this study develops a decision support system (DSS) to assess an organization’s readiness for co-creation in public administration. This study applies a design science research methodology to develop a structured assessment model. Through an in-depth content analysis of academic papers, 81 criteria were identified that represent drivers and barriers to co-creation. These criteria were hierarchically organized into categories, subcategories and aggregated attributes to create a decision model using the Decision EXpert (DEX) multi-criteria decision method. The resulting DSS allows decision makers to assess readiness based on binary inputs (“No”/“Yes”) at the basic level, which are then aggregated by utility functions to obtain the final readiness score. By providing a transparent, evidence-based and replicable approach, this model contributes to both theory and practice: it consolidates the fragmented readiness factors into a structured framework and supports agile governance by guiding strategic planning and the allocation of organizational resources to co-creation initiatives. This model was validated against synthetic test cases to demonstrate its applicability and potential value for public organizations seeking to better understand and improve their readiness and resilience for effective co-creation. Full article

(This article belongs to the Special Issue Agile Approaches to Organizational Governance: Towards a Resilient and Sustainable System)

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18 pages, 4605 KB

Open AccessArticle

Building a Strategic System for Resilience in a Risky World

by Lisa L. Greenwood, Dawn Hess and Jennifer Schneider

Systems 2025, 13(9), 805; https://doi.org/10.3390/systems13090805 - 15 Sep 2025

Abstract

The world and its operations are becoming increasingly risky and brittle, with organizations and communities facing escalating threats from both internal and external sources. Risk management and business systems exist to help navigate both acute shocks and chronic stressors, but the decisive factor [...] Read more.

The world and its operations are becoming increasingly risky and brittle, with organizations and communities facing escalating threats from both internal and external sources. Risk management and business systems exist to help navigate both acute shocks and chronic stressors, but the decisive factor is how entities plan and respond. This article explores the strategic application of systematic resilience planning across risk types and presents an integrated application for implementation grounded in risk management and business continuity systems standards. The article also explores how these standards can support the identification and treatment of organizational risks and vulnerabilities to provide a clear path to resilience. No risk environment is static. Applied as a dynamic framework that is responsive to evolving risk contexts, a systematic approach offers a powerful path forward in an era of compounding disruption. Full article

(This article belongs to the Special Issue Sustainability, Complexity and Resilience: Insights from Complex Systems Approaches)

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21 pages, 877 KB

Open AccessArticle

Exploring Different Patterns of Perceived Barriers to Sustainable Project Management

by José Magano, Cláudia Sousa Silva, Lea Percht and Gilbert Silvius

Systems 2025, 13(9), 804; https://doi.org/10.3390/systems13090804 - 15 Sep 2025

Abstract

This study explores the subjective perceptions of project managers regarding barriers to implementing sustainable project management (SPM). Using Q-methodology and grounded in the theory of planned behavior (TPB), 28 project managers across diverse industries sorted and ranked statements about sustainability-related constraints. The analysis [...] Read more.

This study explores the subjective perceptions of project managers regarding barriers to implementing sustainable project management (SPM). Using Q-methodology and grounded in the theory of planned behavior (TPB), 28 project managers across diverse industries sorted and ranked statements about sustainability-related constraints. The analysis revealed three distinct belief patterns: “motivated yet confined”, characterized by structural and organizational limitations; “motivated yet lacking competency”, reflecting personal skill gaps and limited training; and “motivated yet unsupported”, highlighting weak normative support from peers and leadership. Despite differing barriers, all participants expressed positive attitudes toward sustainability, underscoring a common intention–behavior gap shaped by varying perceptions of behavioral control and normative reinforcement. The findings suggest that generic interventions are insufficient; instead, belief-sensitive strategies are needed to enable SPM adoption. Implications include reforming performance measurement systems, integrating sustainability into professional training, and cultivating supportive organizational cultures. The study contributes to both behavioral theory and project management practice by reframing sustainability barriers as belief-dependent phenomena and offers a foundation for more tailored, psychologically grounded interventions. These insights are relevant for educators, policymakers, and organizational leaders seeking to enhance sustainability outcomes through empowered and context-aware project management practices. Full article

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

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