Systems

21 pages, 575 KiB

Open AccessArticle

Complexity Mechanisms for Interaction to Foster Digital Innovation Processes: A Multiple Case Study

by Yomn Elmistikawy and Jennie Gelter

Systems 2025, 13(6), 460; https://doi.org/10.3390/systems13060460 - 10 Jun 2025

A digital innovation (DI) process with multiple stakeholder involvement is complex. While a reductionist approach might be occasionally favourable, embracing the complexity is more beneficial. In terms of researchers, it is social scientists’ central task to study complex phenomena in society. For practitioners, [...] Read more.

A digital innovation (DI) process with multiple stakeholder involvement is complex. While a reductionist approach might be occasionally favourable, embracing the complexity is more beneficial. In terms of researchers, it is social scientists’ central task to study complex phenomena in society. For practitioners, complexity causes innovation due to heterogeneous actors and dynamic interactions (i.e., non-linearity). Thus, this paper aimed to unveil the complexity mechanisms in DI processes’ structures and how interactions through these mechanisms foster DI. Two case studies of DI processes were conducted, where data was collected through interviews with project participants and through observing project meetings. The complexity mechanisms in DI processes’ structures include open systems, nested systems, distributed control, and dependence on key stakeholders (i.e., hubs). This research offers a theoretical contribution to understanding DI process complexity by identifying how these mechanisms can foster and hinder innovation. The complex interplay of these mechanisms could also bring change in how the DI process works and its boundary definition. Research about the complexity of DI has focused on DI ecosystems. This paper shifts the focus to the complexity of DI processes that produce DIs and cause their ecosystems to come into existence and evolve, and even cause the ecosystem’s extinction. Full article

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

13 pages, 500 KiB

Open AccessArticle

Probabilistic Linguistic Grey Target Group Decision-Making Method Considering Decision Makers’ Expected Information

by Peng Li and Chen Zhu

Systems 2025, 13(6), 459; https://doi.org/10.3390/systems13060459 - 10 Jun 2025

Abstract

Grey target decision making is a useful tool to solve multiple-criteria decision-making problems. Decision makers’ expected information can reflect their preferences and play an important role in decision process. In this paper, a new grey target group decision-making method considering decision makers’ expected [...] Read more.

Grey target decision making is a useful tool to solve multiple-criteria decision-making problems. Decision makers’ expected information can reflect their preferences and play an important role in decision process. In this paper, a new grey target group decision-making method considering decision makers’ expected information is proposed. First, based on the decision makers’ expected information, a novel method to obtain synthetical criteria weights combining subjective weights and objective weights is presented. Furthermore, a new way to determine decision makers’ weights is put forward. Moreover, on the basis of the decision matrix, criteria weights, and decision makers’ weights, a ranking method for all alternatives is proposed. Finally, a case for maintaining a precise instrument in a nursing home is used to illustrate the effectiveness of our proposed method. Full article

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

► Show Figures

Figure 1

28 pages, 2893 KiB

Open AccessArticle

Manufacturer Strategies for Blockchain Adoption and Sales Mode Selection with a Dual-Purpose Platform

by Lirong Wu, Congying Duan and Qingkai Ji

Systems 2025, 13(6), 458; https://doi.org/10.3390/systems13060458 - 10 Jun 2025

Abstract

This study examines how a low-carbon manufacturer strategically adopts blockchain technology and selects sales modes with a dual-purpose e-commerce platform that focuses on both profit and consumer surplus. We develop six game-theoretic models by combining three sales modes (agency, reselling, and dual modes) [...] Read more.

This study examines how a low-carbon manufacturer strategically adopts blockchain technology and selects sales modes with a dual-purpose e-commerce platform that focuses on both profit and consumer surplus. We develop six game-theoretic models by combining three sales modes (agency, reselling, and dual modes) with two blockchain scenarios (adoption vs. non-adoption). Using backward induction, we derive equilibrium strategies for supply chain members and analyze the impacts of key parameters. Building on these analyses, we further investigate the joint decision-making of blockchain adoption and sales mode selection, exploring how the platform’s consumer surplus concern influences manufacturer decisions, and evaluating the economic value created by blockchain under alternative sales modes, ultimately leading to three key findings: (1) The agency mode is generally preferred in most cases, especially when the platform has a moderate level of concern for consumer surplus. Blockchain adoption is only recommended when its unit operational cost is below certain thresholds, and it can significantly impact the choice between agency and dual modes based on the platform’s consumer surplus concern. (2) Platform’s degree of consumer surplus concern exerts a negligible effect on manufacturer’s sales mode selection without blockchain, but it becomes crucial and can trigger a shift to the dual mode when blockchain is adopted. (3) Blockchain generates the greatest economic value for the manufacturer under the dual mode, regardless of cost thresholds. For platforms, the optimal strategy depends on blockchain’s unit operational cost, with the reselling mode being optimal for low cost and the agency mode preferred for higher cost. Full article

(This article belongs to the Special Issue Blockchain Technology in Supply Chain Management and Logistics)

► Show Figures

Figure 1

26 pages, 2689 KiB

Open AccessArticle

A Study on Predicting Key Times in the Takeout System’s Order Fulfillment Process

by Dongyi Hu, Wei Deng, Zilong Jiang and Yong Shi

Systems 2025, 13(6), 457; https://doi.org/10.3390/systems13060457 - 10 Jun 2025

Abstract

With the rapid development of the Internet, businesses in the traditional catering industry are increasingly shifting toward the Online-to-Offline mode, as on-demand food delivery platforms continue to grow rapidly. Within these takeout systems, riders have a role throughout the order fulfillment process. Their [...] Read more.

With the rapid development of the Internet, businesses in the traditional catering industry are increasingly shifting toward the Online-to-Offline mode, as on-demand food delivery platforms continue to grow rapidly. Within these takeout systems, riders have a role throughout the order fulfillment process. Their behaviors involve multiple key time points, and accurately predicting these critical moments in advance is essential for enhancing both user retention and operational efficiency on such platforms. This paper first proposes a time chain simulation method, which simulates the order fulfillment in segments with an incremental process by combining dynamic and static information in the data. Subsequently, a GRU-Transformer architecture is presented, which is based on the Transformer incorporating the advantages of the Gated Recurrent Unit, thus working in concert with the time chain simulation and enabling efficient parallel prediction before order creation. Extensive experiments conducted on a real-world takeout food order dataset demonstrate that the Mean Squared Error of the prediction results of GRU-Transformer with time chain simulation is reduced by about 9.78% compared to the Transformer. Finally, according to the temporal inconsistency analysis, it can be seen that GRU-Transformer with time chain simulation still has a stable performance during peak periods, which is valuable for the intelligent takeout system. Full article

► Show Figures

Figure 1

37 pages, 1357 KiB

Open AccessArticle

Antecedents of Sustainable Usage Behaviors Through Mobile Payment Technology for Digital Financial Inclusion in Ghana

by Gladys Wauk, Junwu Chai, Gideon Adjorlolo, Edem Koffi Amouzou, Belinda Bonney and Benedict N-yanyi

Systems 2025, 13(6), 456; https://doi.org/10.3390/systems13060456 - 10 Jun 2025

Abstract

Mobile payment technology (MPT) has emerged as a tool with the potential to advance financial inclusion and sustainable development. However, the existing literature inadequately explains how sustainability factors influence user behavior toward MPT adoption and how this behavior translates into financial inclusion especially [...] Read more.

Mobile payment technology (MPT) has emerged as a tool with the potential to advance financial inclusion and sustainable development. However, the existing literature inadequately explains how sustainability factors influence user behavior toward MPT adoption and how this behavior translates into financial inclusion especially under the influence of mobile transaction tax policies in African countries. This study addresses this gap by examining the antecedents of sustainable usage behaviors of MPT and their implications for digital financial inclusion in Ghana. Specifically, it integrates the triple bottom line (TBL) dimensions (economic, social, and environmental impact) with constructs from the theory of planned behavior (TPB) (attitude, perceived behavioral control, and subjective norms) into a unified sustainability-TPB framework. This study further investigates the moderating role of a mobile transaction tax policy (MTTP) on the relationship between sustainable usage behaviors and financial inclusion. The PLS-SEM method was utilized to analyze the theoretical model using the cross-sectional data of 320 respondents. The findings of this study supported that all TBL dimensions and TPB constructs influence behavioral intention and adoption through the usage of mobile payment technology and consequently financial inclusion. Notably, the mobile transaction tax policy negatively impacts the adoption of sustainable behaviors and financial inclusion. This study contributes to the current theoretical discourse on sustainable consumer behaviors and positions it on the broader sustainable development framework through financial inclusion by providing a shred of empirical evidence in the Ghanaian mobile payment industry perspective. The practical and policy implications are also suggested. Full article

► Show Figures

Figure 1

22 pages, 629 KiB

Open AccessArticle

Privacy Ethics Alignment in AI: A Stakeholder-Centric Framework for Ethical AI

by Ankur Barthwal, Molly Campbell and Ajay Kumar Shrestha

Systems 2025, 13(6), 455; https://doi.org/10.3390/systems13060455 - 9 Jun 2025

Abstract

The increasing integration of artificial intelligence (AI) in digital ecosystems has reshaped privacy dynamics, particularly for young digital citizens navigating data-driven environments. This study explores evolving privacy concerns across three key stakeholder groups—young digital citizens, parents/educators, and AI professionals—and assesses differences in data [...] Read more.

The increasing integration of artificial intelligence (AI) in digital ecosystems has reshaped privacy dynamics, particularly for young digital citizens navigating data-driven environments. This study explores evolving privacy concerns across three key stakeholder groups—young digital citizens, parents/educators, and AI professionals—and assesses differences in data ownership, trust, transparency, parental mediation, education, and risk–benefit perceptions. Employing a grounded theory methodology, this research synthesizes insights from key participants through structured surveys, qualitative interviews, and focus groups to identify distinct privacy expectations. Young digital citizens emphasized autonomy and digital agency, while parents and educators prioritized oversight and AI literacy. AI professionals focused on balancing ethical design with system performance. The analysis revealed significant gaps in transparency and digital literacy, underscoring the need for inclusive, stakeholder-driven privacy frameworks. Drawing on comparative thematic analysis, this study introduces the Privacy–Ethics Alignment in AI (PEA-AI) model, which conceptualizes privacy decision-making as a dynamic negotiation among stakeholders. By aligning empirical findings with governance implications, this research provides a scalable foundation for adaptive, youth-centered AI privacy governance. Full article

(This article belongs to the Special Issue The Application of a Large Language Model (LLM) in Education Reform and Innovation)

27 pages, 2830 KiB

Open AccessArticle

Evolutionary Game of Medical Knowledge Sharing Among Chinese Hospitals Under Government Regulation

by Liqin Zhang, Na Lv and Nan Chen

Systems 2025, 13(6), 454; https://doi.org/10.3390/systems13060454 - 9 Jun 2025

Abstract

This study investigates the evolutionary game dynamics of medical knowledge sharing (KS) among Chinese hospitals under government regulation, focusing on the strategic interactions between general hospitals, community health service centers, and governmental bodies. Leveraging evolutionary game theory, we construct a tripartite evolutionary game [...] Read more.

This study investigates the evolutionary game dynamics of medical knowledge sharing (KS) among Chinese hospitals under government regulation, focusing on the strategic interactions between general hospitals, community health service centers, and governmental bodies. Leveraging evolutionary game theory, we construct a tripartite evolutionary game model incorporating replicator dynamics to characterize the strategic evolution of the involved parties. Our analysis examines the regulatory decisions of the government and the strategic choices of Chinese hospitals, considering critical factors such as KS costs, synergistic benefits, government incentives and penalties, and patient evaluations. The model is analyzed using replicator dynamic equations to derive evolutionary stable strategies (ESSs), complemented by numerical simulations for sensitivity analysis. Key findings reveal that the system’s equilibrium depends on the balance between KS benefits and costs, with government regulation and patient evaluations significantly influencing Chinese hospital behaviors. The results highlight that increasing government incentives and penalties, alongside enhancing patient feedback mechanisms, can effectively promote KS. However, excessive incentives may reduce willingness to regulate, suggesting the need for balanced policy design. This research provides novel theoretical insights and practical recommendations by (1) pioneering the application of a tripartite evolutionary game framework to model KS dynamics in China’s hierarchical healthcare system under government oversight, (2) explicitly integrating the dual influences of government regulation and patient evaluations on hospital strategies, and (3) revealing the non-linear effects of policy instruments. These contributions are crucial for optimizing Chinese medical resource allocation and fostering sustainable collaborative healthcare ecosystems. Full article

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

► Show Figures

Figure 1

15 pages, 594 KiB

Open AccessArticle

A Hybrid Genetic Algorithm and Proximal Policy Optimization System for Efficient Multi-Agent Task Allocation

by Zimo Zhu, Chuanqiang Yu and Junti Wang

Systems 2025, 13(6), 453; https://doi.org/10.3390/systems13060453 - 9 Jun 2025

Abstract

Efficient task allocation remains a fundamental challenge in multi-agent systems, particularly under resource constraints and large-scale deployments. Classical methods, including market-based mechanisms, centralized optimization techniques, and game-theoretic strategies, have been widely applied to address the multi-agent task allocation problem. While effective in small-to-medium-sized [...] Read more.

Efficient task allocation remains a fundamental challenge in multi-agent systems, particularly under resource constraints and large-scale deployments. Classical methods, including market-based mechanisms, centralized optimization techniques, and game-theoretic strategies, have been widely applied to address the multi-agent task allocation problem. While effective in small-to-medium-sized settings, these approaches often encounter limitations in terms of scalability, adaptability to dynamic environments, and computational efficiency as the problem size increases. To address these limitations, this study introduces a proximal policy optimization system augmented with a genetic algorithm (GAPPO) that integrates evolutionary search with deep reinforcement learning. GAPPO enables agents to develop energy-efficient task allocation strategies by perceiving environmental states and optimizing their actions through iterative policy updates. The genetic component promotes broader policy exploration beyond local optima, while the proximal policy optimization ensures update stability and sample efficiency. To evaluate the proposed GAPPO algorithm, extensive simulations are conducted across four scenarios, with the largest involving 50 tasks and 500 agents. The results demonstrate that GAPPO achieves superior performance compared to baseline methods, particularly in reducing task completion time. These findings highlight the algorithm’s robustness and efficiency in handling large-scale and computationally intensive coordination tasks. Full article

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

► Show Figures

Figure 1

21 pages, 1240 KiB

Open AccessPerspective

Shifting the Burden: Corporate Indigenous Relations and How They Can Go Wrong

by Daniel D. P. McCarthy, Christine A. Daly, Alexandra Davies Post, Gillian Donald, Jean L’Hommecourt, Bori Arrobo and Gregory Hill

Systems 2025, 13(6), 452; https://doi.org/10.3390/systems13060452 - 9 Jun 2025

Abstract

This paper utilizes the Shifting the Burden Archetype (Senge/Stroh) to document a systemic pattern that is unfortunately, often unconscious to the parties involved and inadvertently leads to the undermining of corporate or government/Indigenous relationships, despite best intentions. Based on over a decade of [...] Read more.

This paper utilizes the Shifting the Burden Archetype (Senge/Stroh) to document a systemic pattern that is unfortunately, often unconscious to the parties involved and inadvertently leads to the undermining of corporate or government/Indigenous relationships, despite best intentions. Based on over a decade of experience in these contentious contexts, the author(s), document a set of interacting feedback loops that illustrate an unfortunate set of patterns of behaviour, based on starkly different worldviews, in which the choice to engage in more superficial attempts at relationship building actually undermines the ability of the parties to engage in the more difficult but fundamental solution of trust-based relationships. Recommendations for interventions in these typical or archetypal relationships will be made based on an understanding of the dynamics of the system and process design. Full article

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

► Show Figures

Figure 1

31 pages, 5948 KiB

Open AccessArticle

Intelligent Digital Twin for Predicting Technology Discourse Patterns: Agent-Based Modeling of User Interactions and Sentiment Dynamics in DeepSeek Discourse Case

by Kaihang Zhang, Changqi Dong, Yifeng Guo, Guang Yu and Jianing Mi

Systems 2025, 13(6), 451; https://doi.org/10.3390/systems13060451 (registering DOI) - 8 Jun 2025

Abstract

Understanding user interaction patterns during technology-triggered public discourse provides critical insights into how emerging technologies gain social meaning. This study develops an intelligent digital twin framework for modeling discourse dynamics around DeepSeek, an indigenous large language model that generated approximately 250,000 social media [...] Read more.

Understanding user interaction patterns during technology-triggered public discourse provides critical insights into how emerging technologies gain social meaning. This study develops an intelligent digital twin framework for modeling discourse dynamics around DeepSeek, an indigenous large language model that generated approximately 250,000 social media interactions during a 13-day period. By integrating LLM-enhanced semantic analysis with agent-based modeling, we create a comprehensive virtual representation that captures both content characteristics and behavioral dynamics. Our analysis identifies six distinct thematic domains that structure public engagement: Technological Competition, Technological Breakthrough, User Feedback, Financial Market, Social Influence, and Information Security. The agent-based simulation reveals distinctive participation and sentiment patterns across different user segments, with general users expressing stronger positive sentiments than domain experts and institutional accounts. Network analysis demonstrates the evolution from random-like initial connection patterns to scale-free structures with pronounced influence hubs. The simulation results illuminate how individual behaviors aggregate to produce complex discourse patterns, offering insights into the micro-mechanisms underlying technology reception. This research advances digital twin methodologies beyond physical systems into social phenomena, providing a framework for anticipating public responses to technological innovations and informing more effective communication strategies. Full article

(This article belongs to the Special Issue Advancements in Practical Applications of Agents, Multi-Agent Systems and Digital Twins)

► Show Figures

Figure 1

29 pages, 2684 KiB

Open AccessArticle

Comparisons Between Quantitative FMECA Methods: A Case Study on Power Transformer Risk Assessments

by Andrés A. Zúñiga, João F. P. Fernandes and Paulo J. C. Branco

Systems 2025, 13(6), 450; https://doi.org/10.3390/systems13060450 - 7 Jun 2025

Viewed by 166

Abstract

The efficacy of new FMECA methods can be assessed through qualitative comparisons of the failure mode rankings. This approach is suitable for a few failure modes but can become impractical or lead to misleading results for more extensive problems. This fact motivated us [...] Read more.

The efficacy of new FMECA methods can be assessed through qualitative comparisons of the failure mode rankings. This approach is suitable for a few failure modes but can become impractical or lead to misleading results for more extensive problems. This fact motivated us to introduce an alternative approach for comparing different FMECA methods based on agreement coefficients, enabling a statistical comparison between rankings generated by independent raters. Despite its relevance, the application of agreement coefficients is limited in the FMECA context. Our proposed approach utilizes Cohen’s kappa coefficient to evaluate the agreement between six FMECA configurations based on a type-2 fuzzy inference system and a reference FMECA ranking. We conducted an FMECA on power transformers to test our approach, identifying fourteen potential failure modes. Results show that, based on the agreement coefficient, our proposed approach proves effective for a statistical comparison of different FMECA methods rather than a qualitative comparison between rankings. Full article

(This article belongs to the Special Issue Advances in Reliability Engineering for Complex Systems)

► Show Figures

Figure 1

18 pages, 5804 KiB

Open AccessArticle

The Coordination Between Urban Population Growth and Economic Development in African Countries

by Hang Ren, Zhenke Zhang and Shengnan Jiang

Systems 2025, 13(6), 449; https://doi.org/10.3390/systems13060449 - 6 Jun 2025

Viewed by 145

Abstract

Urbanization in African countries entails substantial growth in the urban population and economic development. The interdependent progress of the population and economy significantly impacts the sustainable development of these nations. By constructing an evaluation framework, this paper assesses the urban population growth and [...] Read more.

Urbanization in African countries entails substantial growth in the urban population and economic development. The interdependent progress of the population and economy significantly impacts the sustainable development of these nations. By constructing an evaluation framework, this paper assesses the urban population growth and economic development systems in African countries. Building upon the coupling coordination model, it quantitatively investigates the relationship between the two and utilizes a geographical detector model to analyze the driving factors of the coordination of evolution. The findings reveal a continuous improvement in the quality of urban population growth and economic development between 2001 and 2020. Nevertheless, their overall quality remains relatively low, exhibiting considerable variation across different countries. Many African countries struggle with a low level of development coordination, with economic progress often trailing behind the pace of urban population growth. The average coupling coordination degree increased from 0.464 to 0.526 over 20 years, with 48.08% of countries still in uncoordinated development by 2020. Factors such as industrialization, foreign trade dependence, government spending, international aid, and political stability are all influential factors affecting the degree of coordination. The absence of industrialization in conjunction with urbanization poses a major impediment to effectively harnessing urban population growth for economic development. Ultimately, this study provides a targeted framework for integrating urban population growth and economic development to address low coupling coordination. Full article

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

► Show Figures

Figure 1

26 pages, 2538 KiB

Open AccessArticle

Multi-Skilled Project Scheduling for High-End Equipment Development Considering Newcomer Cultivation and Duration Uncertainty

by Yaohui Liu, Ronggui Ding, Shanshan Liu and Lei Wang

Systems 2025, 13(6), 448; https://doi.org/10.3390/systems13060448 - 6 Jun 2025

Viewed by 129

Abstract

Traditional off-the-job training is becoming ineffective in high-end equipment research and development (R&D) projects due to the contradiction between rapid technological progress and the slow growth of newcomers, calling for “on-the-job mentoring” to enable synchronized advancement of project execution and newcomer cultivation. For [...] Read more.

Traditional off-the-job training is becoming ineffective in high-end equipment research and development (R&D) projects due to the contradiction between rapid technological progress and the slow growth of newcomers, calling for “on-the-job mentoring” to enable synchronized advancement of project execution and newcomer cultivation. For this, we propose the multi-skilled project scheduling problem with newcomer cultivation under uncertain durations (MSPSP-NCU) and abstract it as a stochastic programming model. The model aims to minimize expected makespan and maximize newcomers’ skill efficiency by optimizing workforce assignment that enables experienced workers to mentor newcomers while simultaneously optimizing task scheduling. Solving the model is blocked by the inherently NP-hard nature of the project scheduling problem and the stochasticity of the durations. Therefore, we put forward an adaptive simulation–optimization approach featuring two-fold: a simulation module capable of dynamically adjusting sample sizes based on convergence feedback and evaluating solutions with improved efficiency and stable accuracy; a tailored non-dominated sorting genetic algorithm II (NSGA-II) with adaptive evolutionary operators that enhance search effectiveness and ensure the identification of a well-distributed Pareto front. By using data from an aerospace component R&D project, the proposed approach is validated for its performance in identifying Pareto-optimal solutions. Several personalized rules are designed by integrating workforce development strategies into the selection process, providing actionable guidelines for cultivating newcomers in technology-intensive projects. Full article

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

► Show Figures

Figure 1

16 pages, 2289 KiB

Open AccessArticle

Multi-Source Heterogeneous Data-Driven Digital Delivery System for Oil and Gas Surface Engineering

by Wei Zhang, Zhixiang Dai, Taiwu Xia, Gangping Chen, Yihua Zhang, Jun Zhou and Cui Liu

Systems 2025, 13(6), 447; https://doi.org/10.3390/systems13060447 - 6 Jun 2025

Viewed by 194

Abstract

To address the challenges of data fragmentation, inconsistent standards, and weak interactivity in oil and gas field surface engineering, this study proposes an intelligent delivery system integrated with three-dimensional dynamic modeling. Utilizing a layered collaborative framework, the system combines optimization algorithms and anomaly [...] Read more.

To address the challenges of data fragmentation, inconsistent standards, and weak interactivity in oil and gas field surface engineering, this study proposes an intelligent delivery system integrated with three-dimensional dynamic modeling. Utilizing a layered collaborative framework, the system combines optimization algorithms and anomaly detection methods during data processing to enhance the relevance and reliability of high-dimensional data. The model construction adopts a structured data architecture and dynamic governance strategies, supporting multi-project secure collaboration and full lifecycle data management. At the application level, it integrates three-dimensional visualization and semantic parsing capabilities to achieve interactive display and intelligent analysis of cross-modal data. Validated through practical engineering cases, the platform enables real-time linkage of equipment parameters, documentation, and three-dimensional models, significantly improving data integration efficiency and decision-making capabilities. This advancement drives the transformation of oil and gas field engineering toward intelligent and knowledge-driven practices. Full article

► Show Figures

Figure 1

21 pages, 3863 KiB

Open AccessArticle

Hierarchical Control Based on Ramp Metering and Variable Speed Limit for Port Motorway

by Weiqi Yue, Hang Yang, Meng Li, Yibing Wang, Yusheng Zhou and Pengjun Zheng

Systems 2025, 13(6), 446; https://doi.org/10.3390/systems13060446 - 6 Jun 2025

Viewed by 113

Abstract

Congestion on port motorways often leads to reduced capacity and traffic efficiency, while the growing prevalence of connected vehicles (CVs) offers new opportunities for improving traffic control. This paper proposes a hierarchical control method integrating ramp metering (RM) and variable speed limits (VSLs) [...] Read more.

Congestion on port motorways often leads to reduced capacity and traffic efficiency, while the growing prevalence of connected vehicles (CVs) offers new opportunities for improving traffic control. This paper proposes a hierarchical control method integrating ramp metering (RM) and variable speed limits (VSLs) explicitly designed for port motorway environments dominated by CVs. The method uses real-time CV data to reduce congestion through a hierarchical control framework in which the upper-level optimization determines system-wide parameters, and the lower-level execution translates them into local control commands. A microscopic simulation using SUMO in the Guoju area of the Chuanshan Port Motorway demonstrated that the proposed method increases traffic capacity by approximately 16% compared to the no-control scenario and improves traffic efficiency by 4.8% and 4.5% compared to PI-ALINEA and MTFC-FB, respectively. Further experiments in varying CV penetration rates (MPRs) from 60% to 100% revealed that while lower MPRs result in higher traffic fluctuations, the method remains effective and robust, particularly when MPRs exceed 80%. This highlights its ability to mitigate congestion and enhance the utilization of the existing infrastructure. Full article

► Show Figures

Figure 1

26 pages, 629 KiB

Open AccessArticle

Fostering Productive Open Source Systems: Understanding the Impact of Collaborator Sentiment

by Joonhaeng Lee and Keuntae Cho

Systems 2025, 13(6), 445; https://doi.org/10.3390/systems13060445 - 6 Jun 2025

Viewed by 119

Abstract

Open Source Software (OSS) development is a complex socio-technical system in which collaborator attitudes influence the outcomes. This study empirically analyzes the impact of participant sentiment (positive, neutral, negative) on productivity, defined by Pull Requests (PR), Lines of Code (LoC), and interactions (as [...] Read more.

Open Source Software (OSS) development is a complex socio-technical system in which collaborator attitudes influence the outcomes. This study empirically analyzes the impact of participant sentiment (positive, neutral, negative) on productivity, defined by Pull Requests (PR), Lines of Code (LoC), and interactions (as indicated by comment volume). Data on PRs, LoC, and comments, were collected from 20 top GitHub repositories. SentiStrength-SE was used to classify participant sentiment based on average comment sentiment. Appropriate nonparametric statistical and correlation analyses were performed. The results showed that contributors with positive sentiments have the highest productivity and interaction. Negative-sentiment contributors also significantly outperform the neutral group in both areas. The neutral group consistently ranks the lowest. The general patterns are as follows: positive > negative > neutral. The strongest positive correlations between productivity and interaction are observed in the positive-sentiment group. These findings empirically demonstrate that the sentiment levels of collaborators are significantly associated with OSS productivity and engagement, offering insights into socio-technical dynamics. Fostering a positive environment is a key strategy for enhancing OSS performance and sustainability. Full article

► Show Figures

Figure 1

23 pages, 1330 KiB

Open AccessArticle

Risk Management Practices in the Purchasing System of an Automotive Company

by Anabela Tereso, Cláudia Santos and João Faria

Systems 2025, 13(6), 444; https://doi.org/10.3390/systems13060444 - 6 Jun 2025

Viewed by 107

Abstract

This paper presents the results of a case study conducted in the purchasing department of Bosch Car Multimedia Portugal, aiming to analyze and improve risk management practices within its project environment. Projects in this department are characterized by high complexity and uncertainty, making [...] Read more.

This paper presents the results of a case study conducted in the purchasing department of Bosch Car Multimedia Portugal, aiming to analyze and improve risk management practices within its project environment. Projects in this department are characterized by high complexity and uncertainty, making effective risk management essential. The study adopts a multi-method qualitative approach, integrating document analysis, direct observation, semi-structured interviews, and questionnaires. A comprehensive literature review established the theoretical foundation and guided the identification of best practices in project risk management. The field research revealed significant gaps in the structuring, standardization, and cultural integration of risk management processes. A comparative analysis between theoretical models and current practices led to the development of a tailored risk management framework, including a practical good-practices manual and a workshop format designed to promote internal engagement and capacity-building. This work contributes both theoretically—by validating literature-based models in an industrial setting—and practically, by offering replicable tools for similar departments in the automotive sector. The findings highlight the necessity of fostering a proactive risk culture to ensure the sustained implementation and effectiveness of the proposed measures. Full article

(This article belongs to the Special Issue Risk Management in Project Management—How Two Major Dimensions (Relational and Processual) Influence Risk Management in Project Management)

► Show Figures

Figure 1

28 pages, 371 KiB

Open AccessArticle

Political Connection Heterogeneity and Green Technological Innovation: Evidence from Chinese Listed Companies

by Siqi Meng, Xiaoyu Wu and Shuyang Wang

Systems 2025, 13(6), 443; https://doi.org/10.3390/systems13060443 - 6 Jun 2025

Viewed by 219

Abstract

With the continuous development of today’s economy and the growing interest in green technological innovation, this study investigates the impact of executive political connection heterogeneity (EPCH) on corporate green technological innovation (CGTI) in Chinese listed companies. Specifically, it distinguishes between ascribed and achieved [...] Read more.

With the continuous development of today’s economy and the growing interest in green technological innovation, this study investigates the impact of executive political connection heterogeneity (EPCH) on corporate green technological innovation (CGTI) in Chinese listed companies. Specifically, it distinguishes between ascribed and achieved political connections, examining their influence on incremental and radical CGTI. This study employs a quantitative research design, utilizing a sample of Chinese A-share listed companies from 2007 to 2022. Data are sourced from the China Securities Market & Accounting Research (CSMAR) database and the China National Research Data Service (CNRDS) database. The study analysis applies fixed-effect regression models to test the relationships between political connection heterogeneity and innovation outcomes. The findings reveal that ascribed political connections promote incremental innovation, while achieved political connections drive radical innovation. Moreover, strong GEO weakens the effect of ascribed political ties on incremental CGTI while enhancing the effect of achieved political ties on radical CGTI. These results contribute to the understanding of how political ties influence corporate innovation strategies and provide insights into the role of dynamic capabilities in green technological advancements. Full article

(This article belongs to the Special Issue Sustainable Strategies and Organizational Transitions for Green Economy)

18 pages, 627 KiB

Open AccessArticle

Attributes Influencing Visitors’ Experiences in Conservation Centers with Different Social Identities: A Topic Modeling Approach

by Zhongkai Li, Ping Chen and Jian Ming Luo

Systems 2025, 13(6), 442; https://doi.org/10.3390/systems13060442 - 6 Jun 2025

Viewed by 370

Abstract

The importance of charismatic flagship species (CFSs) in efforts to raise public awareness of conservation has been widely recognized. However, the effect of differences in social identities on shaping visitors’ experiences remains underexplored, although these differences can inform the development of inclusive and [...] Read more.

The importance of charismatic flagship species (CFSs) in efforts to raise public awareness of conservation has been widely recognized. However, the effect of differences in social identities on shaping visitors’ experiences remains underexplored, although these differences can inform the development of inclusive and culturally sensitive conservation strategies to increase visitors’ satisfaction in conservation centers. This study explores how cultural social identities influence visitors’ conservation experiences, particularly how the out-group homogeneity effect shapes individuals’ perceptions of CFSs. This effect can help to explain why visitors from different cultural backgrounds often perceive CFSs in a homogenized manner. Based on data collected from 6804 online reviews of a giant panda conservation center, this study employs anchored CorEx topic modeling and regression analysis. This research develops a novel framework for understanding how CFSs contribute to visitors’ experiences in conservation centers. It reveals that social identities affect interactions not only among people, but also between people and culturally significant animals. These findings offer practical implications for conservation center management. Full article

(This article belongs to the Special Issue Systems Modeling and Analysis of Consumer Behavior and Business Management)

► Show Figures

Figure 1

22 pages, 941 KiB

Open AccessArticle

Systematically Formulating Investments for Carbon Offset by Multiple-Objective Portfolio Selection: Classifying, Evolving, and Optimizing

by Long Lin and Yue Qi

Systems 2025, 13(6), 441; https://doi.org/10.3390/systems13060441 - 6 Jun 2025

Viewed by 106

Abstract

Our society is facing serious challenges from global warming and environmental degradation. Scientists have identified carbon dioxide as one of the causes. Our society is embracing carbon offset as a way to field the challenges. The purpose of carbon offset is trying to [...] Read more.

Our society is facing serious challenges from global warming and environmental degradation. Scientists have identified carbon dioxide as one of the causes. Our society is embracing carbon offset as a way to field the challenges. The purpose of carbon offset is trying to cancel out the large amounts of carbon dioxide by investing in projects that reduce or remove emissions elsewhere. Examples of carbon offset projects are planting trees, renewable energy projects, and capturing methane from landfills or farms. Not all carbon offset projects are equally effective. In stock markets, investors eagerly pursue carbon offset. Namely, investors favor carbon offset in addition to risk and return when investing. Therefore, investors supervise risk, return, and carbon offset. Investors’ pursuits raise the question of how to model carbon offset for investments. The traditional answer is to adopt carbon offset screening and engineer portfolios by stocks with good carbon offset ratings. However, Nobel Laureate Markowitz emphasizes portfolio selection rather than stock selection. Moreover, carbon offset is composed of multiple components, ranging from business, social, economic, and environmental aspects. This multifaceted nature requires more advanced models than carbon offset screening and portfolio selection. Within this context, we systematically formulate multiple-objective portfolio selection models that include carbon offset. Firstly, we extend portfolio selection and treat carbon offset as a whole. Secondly, we separate carbon offsets into different components and build models to monitor each component. Thirdly, we innovate a model to monitor each component’s expectation and mitigate each component’s risk. Lastly, we optimize the series of models and prove the models’ properties in theorems. Mathematically, this paper makes theoretical contributions to multiple-objective optimization, particularly by proving the consistency of efficient solutions during objective classification and model evolution, describing the structure of properly efficient sets for multiple quadratic objectives, and elucidating the optimization’s sensitivity analyses. Moreover, by coordinating the abstract objective function, our formulation is generalizable. Overall, this paper’s contribution is to model carbon offset investments through multiple-objective portfolio selection. This paper’s methodology is multiple-objective optimization. This paper’s achievements are to provide investors with greater precision and effectiveness than carbon offset screening and portfolio selection through engineering means and to mathematically prove the properties of the model. Full article

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

► Show Figures

Figure 1

16 pages, 984 KiB

Open AccessArticle

Reinforcement Learning Model for Optimizing Bid Price and Service Quality in Crowdshipping

by Daiki Min, Seokgi Lee and Yuncheol Kang

Systems 2025, 13(6), 440; https://doi.org/10.3390/systems13060440 - 5 Jun 2025

Viewed by 225

Abstract

Crowdshipping establishes a short-term connection between shippers and individual carriers, bridging the service requirements in last-mile logistics. From the perspective of a carrier operating multiple vehicles, this study considers the challenge of maximizing profits by optimizing bid strategies for delivery prices and transportation [...] Read more.

Crowdshipping establishes a short-term connection between shippers and individual carriers, bridging the service requirements in last-mile logistics. From the perspective of a carrier operating multiple vehicles, this study considers the challenge of maximizing profits by optimizing bid strategies for delivery prices and transportation conditions in the context of bid-based crowdshipping services. We considered two types of bid strategies: a price bid that adjusts the RFQ freight charge and a multi-attribute bid that scores both price and service quality. We formulated the problem as a Markov decision process (MDP) to represent uncertain and sequential decision-making procedures. Furthermore, given the complexity of the newly proposed problem, which involves multiple vehicles, route optimizations, and multiple attributes of bids, we employed a reinforcement learning (RL) approach that learns an optimal bid strategy. Finally, numerical experiments are conducted to illustrate the superiority of the bid strategy learned by RL and to analyze the behavior of the bid strategy. A numerical analysis shows that the bid strategies learned by RL provide more rewards and lower costs than other benchmark strategies. In addition, a comparison of price-based and multi-attribute strategies reveals that the choice of appropriate strategies is situation-dependent. Full article

(This article belongs to the Special Issue Data-Driven Analysis of Industrial Systems Using AI)

► Show Figures

Figure 1

29 pages, 1626 KiB

Open AccessArticle

Cybersecurity for Analyzing Artificial Intelligence (AI)-Based Assistive Technology and Systems in Digital Health

by Abdullah M. Algarni and Vijey Thayananthan

Systems 2025, 13(6), 439; https://doi.org/10.3390/systems13060439 - 5 Jun 2025

Viewed by 221

Abstract

Assistive technology (AT) is increasingly utilized across various sectors, including digital healthcare and sports education. E-learning plays a vital role in enabling students with special needs, particularly those in remote areas, to access education. However, as the adoption of AI-based AT systems expands, [...] Read more.

Assistive technology (AT) is increasingly utilized across various sectors, including digital healthcare and sports education. E-learning plays a vital role in enabling students with special needs, particularly those in remote areas, to access education. However, as the adoption of AI-based AT systems expands, the associated cybersecurity challenges also grow. This study aims to examine the impact of AI-driven assistive technologies on cybersecurity in digital healthcare applications, with a focus on the potential vulnerabilities these technologies present. Methods: The proposed model focuses on enhancing AI-based AT through the implementation of emerging technologies used for security, risk management strategies, and a robust assessment framework. With these improvements, the AI-based Internet of Things (IoT) plays major roles within the AT. This model addresses the identification and mitigation of cybersecurity risks in AI-based systems, specifically in the context of digital healthcare applications. Results: The findings indicate that the application of the AI-based risk and resilience assessment framework significantly improves the security of AT systems, specifically those supporting e-learning for blind users. The model demonstrated measurable improvements in the robustness of cybersecurity in digital health, particularly in reducing cyber risks for AT users involved in e-learning environments. Conclusions: The proposed model provides a comprehensive approach to securing AI-based AT in digital healthcare applications. By improving the resilience of assistive systems, it minimizes cybersecurity risks for users, specifically blind individuals, and enhances the effectiveness of e-learning in sports education. Full article

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

► Show Figures

Figure 1

18 pages, 361 KiB

Open AccessArticle

Inhibiting Factors Affecting Metaverse Convention Tourism in Macau

by Songhong Chen, Chunhui Cai, Jian Ming Luo and Lam Fai

Systems 2025, 13(6), 438; https://doi.org/10.3390/systems13060438 - 5 Jun 2025

Viewed by 184

Abstract

This study thoroughly investigated the inhibiting factors pertaining to the development of metaverse convention tourism in Macau through a qualitative investigation. This study employed semi-structured interviews and data that were analyzed using NVivo software 14 through a grounded theory approach, involving open, axial, [...] Read more.

This study thoroughly investigated the inhibiting factors pertaining to the development of metaverse convention tourism in Macau through a qualitative investigation. This study employed semi-structured interviews and data that were analyzed using NVivo software 14 through a grounded theory approach, involving open, axial, and selective coding to identify emergent themes. Despite Macau’s established and prosperous tourism industry, it has experienced obstacles when assimilating metaverse technologies into its convention operations. Based on stakeholder theory, this study reviews the inhibitory factors relating to metaverse technology in the development of convention tourism in Macau. The foremost challenges include insufficient infrastructure, a shortage of skilled professionals, limited government support, high costs, and lack of standardized platforms. Notwithstanding, the metaverse offers significant potential to enhance global involvement, interaction, and reachability in convention tourism. Efforts to maximize this potential include upgrading the infrastructure, developing talent, implementing clear government policies, and providing financial support. The current results offer practical recommendations for policymakers, industry experts, and researchers to promote sustainable development of the metaverse in convention tourism, positioning Macau as a leader in this emerging field. Full article

(This article belongs to the Special Issue Toward Innovative Hospitality and Tourism Systems: Exploring Challenges and Opportunities)

► Show Figures

Figure 1

25 pages, 3291 KiB

Open AccessArticle

Research on Private Label Introduction and Sales Mode Decision-Making for E-Commerce Platforms Considering Coupon Promotion Strategies

by Zuoying Lu, Yinyuan Si, Zhihua Han and Chao Ma

Systems 2025, 13(6), 437; https://doi.org/10.3390/systems13060437 - 4 Jun 2025

Viewed by 208

Abstract

With the rapid development of the digital economy and the evolving shopping preferences of consumers, e-commerce platforms have been enhancing their competitiveness by launching private label brands and optimizing their sales channel strategies. This study focuses on an online sales system comprising a [...] Read more.

With the rapid development of the digital economy and the evolving shopping preferences of consumers, e-commerce platforms have been enhancing their competitiveness by launching private label brands and optimizing their sales channel strategies. This study focuses on an online sales system comprising a strong brand and an e-commerce platform. Four game modes were constructed: agency selling only (NN), agency selling combined with reselling (NS), agency selling combined with private labels (IN), and reselling combined with agency selling under the introduction of private labels (IS). Under the coupon promotion strategy, this study focused on the introduction strategy for private labels (PLs) and the selection strategy for platform sales modes. Our research produced the following findings: (1) Regardless of whether the platform introduces its own brand, adopting a reselling mode can significantly enhance the profits of both the brand owner and platform. (2) Irrespective of whether the reselling mode is implemented, the platform’s profits are always increased when introducing its own brand. (3) When the coupon redemption rate is higher, the brand owner achieves greater profitability in the absence of PL introduction. Conversely, when the coupon redemption rate is low, an increase in the commission rate leads to reduced profit margins for the brand owner due to competition from a private label. (4) When the coupon redemption and commission rate are both high, the coupon face value without a PL is larger. Otherwise, when these rates are both low, the coupon face value is higher under the introduction of a PL. This study offers a theoretical foundation and decision-making support for e-commerce platforms to optimize sales mode selection, introduce private-label brands, and develop coupon strategies. Full article

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

► Show Figures

Figure 1

28 pages, 1162 KiB

Open AccessArticle

Multi-Entity Collaboration Mechanism of Key Core Technology Innovation Based on Differential Game

by Xinxin Fan, Dingding Xiao, Peng Hui, Lizhuang Cui and Guilong Zhu

Systems 2025, 13(6), 436; https://doi.org/10.3390/systems13060436 - 4 Jun 2025

Viewed by 145

Abstract

Key core technology innovation has become an important strategic path for countries to maintain industrial security amid intensifying global technological competition. As an important innovation paradigm, R&D collaboration is generally regarded as an effective way to achieve such innovation. However, the key issue [...] Read more.

Key core technology innovation has become an important strategic path for countries to maintain industrial security amid intensifying global technological competition. As an important innovation paradigm, R&D collaboration is generally regarded as an effective way to achieve such innovation. However, the key issue of which collaborative mechanism is most effective at promoting key core technology innovation remains insufficiently explored. Therefore, systematically comparing the effectiveness of different mechanisms of collaborative innovation is of great strategic significance for achieving key core technology innovation and overcoming Western technological blockades. In this study, the R&D level and market share of key core technology were incorporated into an analytical framework and applied to a differential game focused on the innovation behaviors of leading enterprises, supporting enterprises, and academic research institutions under Nash non-collaborative, cost-sharing, and collaborative mechanisms. A simulation analysis was conducted using the MATLAB 2020a software. The results show that the optimal strategies for the key core technology innovation of innovation entities are negatively correlated with the cost coefficient, discount rate, technology, and market recession coefficient. Meanwhile, they are positively correlated with the sensitivity coefficient of technology R&D and market promotion. Furthermore, the R&D levels and market shares of key core technology are highest under the collaborative mechanism. In this scenario, the revenues of the innovation entity and the overall system reach Pareto optimality. Within a threshold range, the cost-sharing mechanism significantly improves innovative efforts, the R&D level, and the market share of key core technology, leading to a Pareto improvement for both the participants’ and overall system’s revenues compared to the non-collaborative mechanism. This study not only contributes to theoretical results of differential games but also provides valuable suggestions for policymakers and innovation entities to foster key core technology innovation from the perspective of collaboration. Full article

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

► Show Figures

Figure 1

35 pages, 5548 KiB

Open AccessArticle

Optimizing and Visualizing Drone Station Sites for Cultural Heritage Protection and Research Using Genetic Algorithms

by Seok Kim and Younghee Noh

Systems 2025, 13(6), 435; https://doi.org/10.3390/systems13060435 - 4 Jun 2025

Viewed by 189

Abstract

(1) Background: Cultural heritage plays a vital role in shaping collective identity and supporting tourism, yet it faces increasing threats from natural and human-induced disasters. As a response, digital technologies—especially drone-based monitoring systems—are being explored for disaster prevention. This study examines whether a [...] Read more.

(1) Background: Cultural heritage plays a vital role in shaping collective identity and supporting tourism, yet it faces increasing threats from natural and human-induced disasters. As a response, digital technologies—especially drone-based monitoring systems—are being explored for disaster prevention. This study examines whether a Genetic Algorithm can effectively optimize the placement of drone stations for the economic protection of cultural heritage. (2) Method: A simulation was conducted in a 2500 km² virtual space divided into 25 km² grid units, each assigned a random land price. Drone stations have an operational radius of 40 km. GA optimization uses a fitness function based on the ratio of cultural artifacts covered to installation cost. To prevent premature convergence, multi-point crossover and roulette wheel selection are employed. Key GA parameters were fine-tuned through repeated simulations. (3) Results: The optimal parameter set—population size of 300, mutation rate of 0.2, mutation strength of ±5 km, and crossover ratio of 0.3—balances exploration and convergence. The results show convergence toward low-cost, high-coverage locations without premature stagnation. Visualization clearly illustrates the optimization process. (4) Conclusions: GA proves effective for economically optimizing drone station placement. Though virtual, this method offers practical implications for real-world cultural heritage protection strategies. Full article

► Show Figures

Figure 1

34 pages, 8588 KiB

Open AccessArticle

Study on the Technological Innovation Supply–Demand Matching Mechanism for Major Railway Projects Based on a Tripartite Evolutionary Game

by Xi Zhao, Yuming Liu and Xianyi Lang

Systems 2025, 13(6), 434; https://doi.org/10.3390/systems13060434 - 3 Jun 2025

Viewed by 229

Abstract

Current technological innovation in mega projects faces the problem of mismatch between supply and demand, where technology demand-side entities struggle to translate engineering problems into precise scientific research language, while technology supply-side entities fail to capture authentic scenario parameters from engineering sites. This [...] Read more.

Current technological innovation in mega projects faces the problem of mismatch between supply and demand, where technology demand-side entities struggle to translate engineering problems into precise scientific research language, while technology supply-side entities fail to capture authentic scenario parameters from engineering sites. This study employs an evolutionary game model to thoroughly investigate behavioral interaction processes among governance entities, demand-side entities, and intermediary collaborative innovation platforms during technological innovation supply–demand matching. By constructing and deriving a tripartite evolutionary game model, this research analyzes the impacts of initial states, the matching effort coefficient, the innovation risk coefficient, and other factors on the evolution of scientific technological innovation supply–demand matching. Additionally, this study simulates the dynamic evolutionary processes of strategic selection. The findings reveal that the initial states of the three parties do not influence behavioral evolution. Furthermore, the subsidy coefficient, additional benefits, and risk coefficient emerge as the most significant parameters affecting tripartite strategy selection. The research outcomes and managerial implications provide crucial reference value for enhancing the alignment between scientific research supply and demand in mega projects, thereby promoting the transformation of scientific and technological achievements in major railway engineering projects. Full article

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

► Show Figures

Figure 1

33 pages, 781 KiB

Open AccessArticle

Open-Source Collaboration and Technological Innovation in the Industrial Software Industry: A Multi-Case Study

by Xiaohong Chen and Yuan Zhou

Systems 2025, 13(6), 433; https://doi.org/10.3390/systems13060433 - 3 Jun 2025

Viewed by 225

Abstract

Open-source collaboration, as both an open and cooperative software development paradigm and a novel production model in the era of the industrial internet, plays a pivotal role in overcoming technological bottlenecks in the industrial software industry. However, previous studies have often treated open-source [...] Read more.

Open-source collaboration, as both an open and cooperative software development paradigm and a novel production model in the era of the industrial internet, plays a pivotal role in overcoming technological bottlenecks in the industrial software industry. However, previous studies have often treated open-source collaboration as a single unified concept and have not explored the specific types of open-source collaboration and their differential effects on technological innovation. To address these gaps, this study aims to answer two core research questions: (1) What are the different types of open-source collaboration models based on their characteristics? (2) How do these collaboration models influence technological innovation in the industrial software industry? Drawing upon four representative collaboration cases in the industrial software domain, this study conducts within-case and cross-case comparative analyses to propose a typological framework based on the dimensions of coreness and complementarity. The analysis identifies four distinct open-source collaboration models: (1) single-core with high complementarity, (2) single-core with low complementarity, (3) multi-core with high complementarity, and (4) multi-core with low complementarity. The formation of these models is shaped by three key factors: strategic intentions, resource endowments, and technological capabilities. Moreover, different collaboration types exert varied impacts on organizational characteristics, innovation strategies, and technological impacts. Theoretically, this study makes an original contribution by opening the “black box” of open-source collaboration and revealing the internal mechanisms through which it shapes innovation dynamics. Practically, the findings offer targeted insights for enterprises, policymakers, and open-source communities in selecting appropriate collaboration models that align with innovation goals, thereby supporting technological upgrading and ecosystem resilience in the industrial software industry. Full article

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

► Show Figures

Figure 1

27 pages, 1500 KiB

Open AccessArticle

CSR Input and Recycling Decisions for Closed-Loop Supply Chain with Asymmetric Demand Information

by Minghui Ni, Wenbo Bo, Xudong Qin and Fengmin Yao

Systems 2025, 13(6), 432; https://doi.org/10.3390/systems13060432 - 3 Jun 2025

Viewed by 138

Abstract

In reality, there is often information asymmetry between upstream and downstream enterprises in a closed-loop supply chain (CLSC) system, which can have a profound impact on the decisions of member enterprises and the operation of the system. Under asymmetric market demand information, this [...] Read more.

In reality, there is often information asymmetry between upstream and downstream enterprises in a closed-loop supply chain (CLSC) system, which can have a profound impact on the decisions of member enterprises and the operation of the system. Under asymmetric market demand information, this study examines CSR input and recycling decision making in CLSC. Four decision-making models were developed for CLSC, and the effects of consumer sensitivity to CSR input and demand information asymmetry on CLSC optimization were studied. The results indicate that higher consumer sensitivity to CSR input enhances both CSR levels and recycling rates, benefiting both manufacturer and retailer by increasing profits. In terms of increasing CSR levels, the manufacturer achieves the best results when independently managing CSR input and recycling. However, for improving recycling rates and market demand, the retailer is more effective when responsible for CSR input, with the manufacturer handling recycling. Additionally, demand information asymmetry reduces the manufacturer’s profit but may not affect the retailer’s profit. The retailer–manufacturer cooperation model proves more beneficial for overall CLSC system performance compared to information symmetry. Full article

► Show Figures

Figure 1

21 pages, 3311 KiB

Open AccessArticle

How Reclamation Policy Shapes China’s Coastal Wetland Ecosystem Services

by Yuefei Zhuo, Tiantian Li, Zhongguo Xu and Guan Li

Systems 2025, 13(6), 431; https://doi.org/10.3390/systems13060431 - 3 Jun 2025

Viewed by 251

Abstract

China’s reclamation regulation policy is an important policy tool used by the government to balance land development and ecological protection in coastal areas, but few studies have focused on the impact of the implementation of this policy on ecosystem services. To fill the [...] Read more.

China’s reclamation regulation policy is an important policy tool used by the government to balance land development and ecological protection in coastal areas, but few studies have focused on the impact of the implementation of this policy on ecosystem services. To fill the gap, this study takes Ningbo City as an example, applies the InVEST model as a scenario analysis and trend indication tool, combines the market value method to quantify the ecosystem services of coastal wetlands, and explores the impact of the reclamation regulation policy on the coastal wetland ecosystem services through the regression discontinuity model. The findings are as follows: (1) from 2005 to 2020, the natural ecological landscape in the coastal zone of Ningbo City continued to shrink, but the overall value of ecosystem services showed a fluctuating upward trend. Among them, cropland and wetlands served as the primary conduits for ecosystem services in this region, highlighting the need to strengthen the protection of these two land types. (2) The implementation of reclamation regulation policy has an impact on ecosystem services. The policy implementation in 2011 appeared to suppress the downward trend of ecological habitat quality and carbon storage, while the policy implementation in 2017 had a positive impact on the enhancement of carbon storage and material production. (3) As for the effect of reclamation regulation policy on the changes in ecosystem services, although the measured positive impact of reclamation regulation policy on ecological habitat quality was less statistically pronounced compared to other services during the study period, it had significant positive effects on carbon storage and material production. On the whole, the reclamation regulation policy proves effective in contributing to the maintenance of coastal wetland ecosystem services. Although the model-based results in this study reveal more indicator trends rather than precise quantitative evidence, it helps mitigate degradation trends and enhance specific services like carbon storage and material production. Through its implementation, the policy aids in pursuing the win–win goal of balancing urban economic development and ecological environment protection. Full article

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

► Show Figures

Figure 1

Journal Menu

Journal Browser

Systems, Volume 13, Issue 6 (June 2025) – 63 articles

Further Information

Guidelines

MDPI Initiatives

Follow MDPI