Systems

19 pages, 4619 KiB

Open AccessArticle

Uncertainty and Entrepreneurship: Acknowledging Non-Optimization and Remedying Mismodeling

by Richard J. Arend

Systems 2025, 13(3), 214; https://doi.org/10.3390/systems13030214 - 20 Mar 2025

Viewed by 238

There has been recent proliferation of entrepreneurship theorizing involving the true uncertainty of a system—most often labeled as Knightian. This has been noted in both individual papers and in the main partial theories that attempt to explain entrepreneurial activity more holistically. We [...] Read more.

There has been recent proliferation of entrepreneurship theorizing involving the true uncertainty of a system—most often labeled as Knightian. This has been noted in both individual papers and in the main partial theories that attempt to explain entrepreneurial activity more holistically. We detect a danger in this work involving such true uncertainty—defined by the condition that decisions plagued by it are non-optimizable by every interested party. It is that all the recent theorizing misinterprets that uncertainty in one of two ways: with a logical contradiction (i.e., that the non-optimizable is actually optimizable); or with a misrepresentation (i.e., that an uncertainty consisting of a knowable unknown that can be made known through known means by the time the decision must be made is true). Our concern is that such misinterpretations create unnecessary costs to academics and practitioners who are struggling to define the system they are managing. We explain this concern and its costs, detail the underlying premises, illustrate it with several examples, and then offer various specific directions to improve the theorizing over such uncertainty in entrepreneurship. Full article

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

23 pages, 5889 KiB

Open AccessArticle

Assessing the Influence of Equipment Reliability over the Activity Inside Maritime Container Terminals Through Discrete-Event Simulation

by Eugen Rosca, Florin Rusca, Valentin Carlan, Ovidiu Stefanov, Oana Dinu and Aura Rusca

Systems 2025, 13(3), 213; https://doi.org/10.3390/systems13030213 - 20 Mar 2025

Viewed by 226

Abstract

(1) Background: The reliability of port equipment is of significant interest to industry stakeholders due to the economic and logistical factors governing the operation of maritime container terminals. Failures of key equipment like quay cranes can halt operations or cause economically significant delays. [...] Read more.

(1) Background: The reliability of port equipment is of significant interest to industry stakeholders due to the economic and logistical factors governing the operation of maritime container terminals. Failures of key equipment like quay cranes can halt operations or cause economically significant delays. (2) Methods: The impact assessment of these disruptive events is conducted through terminal activity modeling and discrete-event simulation of internal processes. The system’s steady-state or transient condition, induced by disruptive events, is statistically assessed within a set of scenarios proposed by the authors. (3) Results: The Heidelberg–Welch and Geweke tests enabled the evaluation of steady-state and transient conditions within the modeled system, which was affected by the reduced reliability of container-handling equipment. (4) Conclusions: The research findings confirmed the usefulness of modeling and simulation in assessing the impact of equipment reliability on maritime container terminal operations. If the magnitude of the disruptive event exceeds the terminal’s absorption capacity, the system may become blocked or remain in a transient state without the ability to recover. This underscores the necessity of analyzing the reliability of critical handling equipment and implementing corrective maintenance actions when required. Full article

(This article belongs to the Special Issue Modelling and Simulation of Transportation Systems)

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17 pages, 479 KiB

Open AccessArticle

Digital Capabilities, Integration into Global Innovation Networks, and Enterprise Innovation Performance

by Shanwu Tian, Xiaozhen Lai, Lijun Dong and Xiurui Xu

Systems 2025, 13(3), 212; https://doi.org/10.3390/systems13030212 - 19 Mar 2025

Viewed by 456

Abstract

Against the backdrop of accelerated global digital transformation and the shift toward open innovation models, this study examines how enterprises leverage digital capabilities to integrate into global innovation networks (GINs) and enhance innovation performance, while exploring the moderating role of organizational flexibility. Drawing [...] Read more.

Against the backdrop of accelerated global digital transformation and the shift toward open innovation models, this study examines how enterprises leverage digital capabilities to integrate into global innovation networks (GINs) and enhance innovation performance, while exploring the moderating role of organizational flexibility. Drawing on dynamic capability and social network theories, a multidimensional framework of digital capabilities (perception, operation, and coordination) and organizational flexibility (cultural, resource, and capability) is proposed. The empirical analysis of 343 Chinese multinational corporations using SPSS 27 and AMOS 24 reveals three key findings: (1) all dimensions of digital capabilities significantly improve innovation performance; (2) GIN integration partially mediates this relationship by facilitating resource acquisition and collaboration; and (3) capability flexibility positively moderates the GIN–performance link, while cultural and resource flexibility show no significant effects. This study advances digital capability research by emphasizing dynamic processes over static technology adoption and provides practical insights for balancing technological investments with organizational adaptability. Full article

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

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29 pages, 6318 KiB

Open AccessArticle

Economic and Environmental Sustainability Performance Improvements in the Outdoor Wood Furniture Industry Through a Lean-Infused FMEA-Supported Fuzzy QFD Approach

by Melike Nur Ince, Emrecan Arpaci, Cagatay Tasdemir and Rado Gazo

Systems 2025, 13(3), 211; https://doi.org/10.3390/systems13030211 - 19 Mar 2025

Viewed by 442

Abstract

Fiercer competition across all industries has made identifying and eliminating lean wastes to enhance sustainability performance an effective route that many companies take. This study focuses on the production process of wood park/garden benches at a company that manufactures outdoor wood furniture. The [...] Read more.

Fiercer competition across all industries has made identifying and eliminating lean wastes to enhance sustainability performance an effective route that many companies take. This study focuses on the production process of wood park/garden benches at a company that manufactures outdoor wood furniture. The goal was to identify lean wastes within a sustainability framework across seven operations and integrate multi-criteria decision making (MCDM) methodologies for waste elimination. Eleven lean KPIs addressing economic and environmental sustainability were used to develop and prioritize 13 lean failure modes (LFMs) with Risk Priority Numbers (RPNs) above 100, leading to lean project proposals for each LFM. Eighteen lean tools were ranked using the Fuzzy Quality Function Deployment (Fuzzy QFD) method. A total of eight improvement propositions, namely, Kaizen and continuous improvement, upgrade machinery for energy efficiency, Just-In-Time (JIT), optimize production processes with lean methodologies, implement cost reduction strategies, Total Productive Maintenance (TPM), Investing in Automation, and Andon were implemented. Significant improvements were observed post-implementation: total lead time was reduced by approximately 38.46%, value-added time by 22.05%, and non-value-added time by 47.64%. The required number of workers decreased by 14.29%, and the total inventory decreased by approximately 57.31%. The results contribute to sustainability goals by reducing energy consumption and waste while increasing economic efficiency. It also provides a robust framework for decision making in fuzzy environments, guiding practitioners and academics in lean management and sustainability. Full article

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

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16 pages, 1626 KiB

Open AccessArticle

Portfolio Procurement Strategies with Forward and Option Contracts Combined with Spot Market

by Nurul Anastasya Talaba and Pyung-Hoi Koo

Systems 2025, 13(3), 210; https://doi.org/10.3390/systems13030210 - 18 Mar 2025

Viewed by 328

Abstract

Increasing supply chain uncertainty due to market volatility has heightened the need for more flexible procurement strategies. While procurement through long-term forward contracts provides supply stability and cost predictability, it limits adaptability. Option contracts offer procurement flexibility, but require additional upfront premiums. Meanwhile, [...] Read more.

Increasing supply chain uncertainty due to market volatility has heightened the need for more flexible procurement strategies. While procurement through long-term forward contracts provides supply stability and cost predictability, it limits adaptability. Option contracts offer procurement flexibility, but require additional upfront premiums. Meanwhile, the spot market enables real-time purchasing without prior commitments, enhancing flexibility but exposing buyers to price volatility. Despite the growing adoption of portfolio procurement—combining forward contracts, option contracts, and spot market purchases—the existing research primarily examines these channels in isolation or in limited combinations, lacking an integrated perspective. This study addresses this gap by developing a comprehensive procurement model that simultaneously optimizes procurement decisions across all three channels under uncertain demand and fluctuating spot prices. Unlike prior studies, which often analyze one or two procurement channels separately, our model presents a novel, holistic framework that balances cost efficiency, risk mitigation, and adaptability. Our findings demonstrate that incorporating the spot market significantly enhances procurement flexibility and profitability, particularly in environments with high demand uncertainty and price volatility. Additionally, sensitivity analysis reveals how fluctuations in spot prices and demand uncertainty influence optimal procurement decisions. By introducing a new, practical approach to portfolio procurement, this study provides managerial insights that help businesses navigate complex and uncertain supply chain environments more effectively. However, this study assumes unlimited spot market capacity and reliable suppliers, highlighting a limitation that future research should address. Full article

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

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29 pages, 3122 KiB

Open AccessArticle

Complexity to Resilience: Machine Learning Models for Enhancing Supply Chains and Resilience in the Middle Eastern Trade Corridor Nations

by Wajid Nawaz and Zhaolei Li

Systems 2025, 13(3), 209; https://doi.org/10.3390/systems13030209 - 18 Mar 2025

Viewed by 473

Abstract

The durable nature of supply chains in the Middle Eastern region is critical, given the region’s strategic role in global trade corridors, yet geopolitical conflicts, territorial disputes, and governance challenges persistently disrupt key routes like the Suez Canal, amplifying vulnerabilities. This study addresses [...] Read more.

The durable nature of supply chains in the Middle Eastern region is critical, given the region’s strategic role in global trade corridors, yet geopolitical conflicts, territorial disputes, and governance challenges persistently disrupt key routes like the Suez Canal, amplifying vulnerabilities. This study addresses the urgent need to predict and mitigate supply chain risks by evaluating machine learning (ML) models for forecasting economic complexity as a proxy for resilience across 18 Middle Eastern countries. Using a multidimensional secondary dataset, we compare gated recurrent unit (GRU), support vector regression (SVR), gradient boosting, and other ensemble models, assessing performance via MSE, MAE, RMSE, and R². The results demonstrate the GRU model’s superior accuracy (R² = 0.9813; MSE = 0.0011), with SHAP, sensitivity, and sensitivity analysis confirming its robustness in identifying resilience determinants. Analyses reveal infrastructure quality and natural resource rents as pivotal factors influencing the economic complexity index (ECI), while disruptions like trade embargoes or infrastructure failures significantly degrade resilience. Our findings underscore the importance of diversifying infrastructure investments and stabilizing governance frameworks to buffer against shocks. This research advances the application of deep learning in supply chain resilience analytics, offering actionable insights for policymakers and logistics planners to fortify regional trade corridors and mitigate global ripple effects. Full article

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

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23 pages, 4723 KiB

Open AccessArticle

AI-Driven Decision Support Systems in Agile Software Project Management: Enhancing Risk Mitigation and Resource Allocation

by Sultan Saaed Almalki

Systems 2025, 13(3), 208; https://doi.org/10.3390/systems13030208 - 18 Mar 2025

Viewed by 1805

Abstract

Agile software project management (ASPM) serves modern industries to conduct iterative development of complicated code bases. The decision-making process in Agile environments regularly depends on individual opinions, creating ineffective results for risk management and resource distribution. Artificial intelligence (AI) is a promising approach [...] Read more.

Agile software project management (ASPM) serves modern industries to conduct iterative development of complicated code bases. The decision-making process in Agile environments regularly depends on individual opinions, creating ineffective results for risk management and resource distribution. Artificial intelligence (AI) is a promising approach for handling these challenges by delivering data-based choices to project management. This research introduces an AI-based decision support system for improving risk reduction and resource distribution in ASPM. The system merges optimization frameworks and predictive analytics to enhance operational decision efficiency. The machine learning solution anchors data evaluation using AI models that simultaneously predict risks and strengthen decision power for resource scheduling. This analysis relied on project records and recent operational data to perform model validation and training procedures. Tests determined how the framework performed against contemporary Agile project management systems by measuring the completion speed of sprints, resource management practices, and risk prediction accuracy. The framework demonstrated better performance by predicting risks and simultaneously maximizing resources utilized during projects. The proposed framework outperformed traditional Agile applications, achieving 94% accuracy in risk identification and enhancing workload management by 25%, leading to an 18% improvement in sprint completion rates and overall project efficiency. These findings confirm that AI-driven decision support systems (DSSs) are crucial in enhancing Agile project management by enabling proactive risk mitigation and optimized resource allocation. By integrating AI-powered decision-making, the framework empowers organizations to improve project outcomes, streamline resource management, and facilitate the adoption of AI-driven methodologies within Agile systems. Full article

(This article belongs to the Special Issue Decision Making in Software Project Management)

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37 pages, 3200 KiB

Open AccessArticle

Enabling Open Architecture in Military Systems: A Systemic and Holistic Analysis

by Raquel L. V. Radoman, Michael Henshaw, Melanie King and Tim Rabbets

Systems 2025, 13(3), 207; https://doi.org/10.3390/systems13030207 - 17 Mar 2025

Viewed by 659

Abstract

Military systems, with their extended lifecycles, face challenges such as managing obsolescence, adapting to evolving operational needs, and ensuring interoperability in System of Systems contexts. Open Architectures (OAs) have been pursued to address these issues by adopting widely recognized interface standards instead of [...] Read more.

Military systems, with their extended lifecycles, face challenges such as managing obsolescence, adapting to evolving operational needs, and ensuring interoperability in System of Systems contexts. Open Architectures (OAs) have been pursued to address these issues by adopting widely recognized interface standards instead of proprietary solutions, enabling more flexible and cost-effective system modifications. However, establishing effective OA environments—encompassing technical, commercial, and organisational dimensions—remains complex, with much of the existing knowledge restricted to the practices of a few governments. This paper presents a comprehensive analysis of OA in military systems, employing systems thinking tools to examine this multifaceted concept. It integrates perspectives from government and industry, addressing the ‘what’, ‘why’, and ‘how’ of OA, and introduces a framework for identifying enabling actions. Key findings highlight that OA success depends on defining ‘open for whom’, ‘to what level of detail’, and ‘in which parts of the system’. Moreover, achieving an effective OA environment requires strategic investment, the active engagement of a Community of Practice, and maturity in the technical and legal domains. This study provides decision-makers at early stages of adoption with the necessary strategic understanding to support the customisation of OA transformation plans to suit unique contexts. Full article

(This article belongs to the Special Issue System of Systems Engineering)

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18 pages, 3613 KiB

Open AccessArticle

Application of the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) in a Two-Echelon Cold Supply Chain

by Aslı Acerce and Berrin Denizhan

Systems 2025, 13(3), 206; https://doi.org/10.3390/systems13030206 - 17 Mar 2025

Viewed by 663

Abstract

A two-stage cold supply chain manages the transportation, storage, and distribution of temperature-sensitive products like frozen food, fresh/green products, and pharmaceuticals, which makes it costly. It consists of three key elements: a supplier, a warehouse, and multiple customers. Procurement planning can be conducted [...] Read more.

A two-stage cold supply chain manages the transportation, storage, and distribution of temperature-sensitive products like frozen food, fresh/green products, and pharmaceuticals, which makes it costly. It consists of three key elements: a supplier, a warehouse, and multiple customers. Procurement planning can be conducted for various products, and this study assumes the transport of a fresh/green product with gradually decreasing quality due to its perishable nature. In a two-stage cold supply chain, multiple objective functions can be defined, including cost minimization, product quality optimization, and transportation/storage condition optimization. We developed a mathematical model to optimize these objectives, incorporating two specific functions, cost minimization and product age reduction, to ensure efficient supply chain performance. Traditional solution methods often struggle with multi-objective mathematical models due to their complexity. Therefore, the Non-Dominated Sorting Genetic Algorithm II (NSGA-II), a Genetic Algorithm-based approach, was applied to solve the model efficiently. NSGA-II optimized planning for a 7-day period under specific demand conditions, ensuring better resource allocation. The results showed that NSGA-II was better than traditional methods at making decisions and routing efficiently in the two-stage cold supply chain. This led to much better outcomes, with lower costs, less waste, and better product quality throughout the process. Full article

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

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40 pages, 4470 KiB

Open AccessArticle

Tripartite Evolutionary Game Analysis on the Employment of University Graduates from the Perspective of the Talent Supply Chain Based on Prospect Theory

by Lingwei Fan, Chuan Zhang, Kaiyu Lian and Jingjing Chen

Systems 2025, 13(3), 205; https://doi.org/10.3390/systems13030205 - 16 Mar 2025

Viewed by 417

Abstract

From the perspective of the talent supply chain, this paper employs evolutionary game theory to study the decision-making behaviors of university graduates’ employment-related participants, establishes a tripartite evolutionary game model of enterprises, graduates, and universities based on prospect theory, and analyzes the main [...] Read more.

From the perspective of the talent supply chain, this paper employs evolutionary game theory to study the decision-making behaviors of university graduates’ employment-related participants, establishes a tripartite evolutionary game model of enterprises, graduates, and universities based on prospect theory, and analyzes the main factors affecting the system game strategy by combining numerical simulation. The evolutionary game theory is a theory that integrates game theory with the analysis of dynamic evolutionary processes, studying the strategy selection and dynamic equilibrium of bounded rational participants in complex environments. The findings are as follows: (1) The decision-makers influence and promote each other, and universities play a very important role in promoting the employment of graduates. (2) In the case of random initial probability, when the additional profit of each decision-maker is greater than their cost, enterprises, graduates, and universities can realize the ideal model of “recruitment, participation in recruitment, active employment assistance”. The higher the initial probability, the faster the system reaches a steady state. (3) Enhancing the risk perception of enterprises, graduates, and universities has a dual effect on the employment ecosystem. (4) The behavioral strategies of enterprises, graduates, and universities are affected by many factors, such as the initial probability, loss aversion degree, profit and loss sensitivity degree, talent loss risk, cost, and unemployment risk. Full article

(This article belongs to the Section Supply Chain Management)

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29 pages, 2984 KiB

Open AccessArticle

Advancing Deliberative Discourse Measurement: The Intersection with Computational Abstract Argumentation in Discourse Quality Evaluations

by Sanjay Kumar, Jane Suiter and Luca Longo

Systems 2025, 13(3), 204; https://doi.org/10.3390/systems13030204 - 16 Mar 2025

Viewed by 474

Abstract

This research investigates the potential of computational argumentation, specifically the application of the Abstract Argumentation Framework (AAF), to enhance the evaluation of deliberative quality in public discourse. It focuses on integrating AAF and its related semantics with the Discourse Quality Index (DQI), which [...] Read more.

This research investigates the potential of computational argumentation, specifically the application of the Abstract Argumentation Framework (AAF), to enhance the evaluation of deliberative quality in public discourse. It focuses on integrating AAF and its related semantics with the Discourse Quality Index (DQI), which is a reputable indicator of deliberative quality. The motivation is to overcome the DQI’s constraints using the AAF’s formal and logical features by addressing dependency on hand coding and attention to specific speech acts. This is done by exploring how the AAF can identify conflicts among arguments and assess the acceptability of different viewpoints, potentially leading to a more automated and objective evaluation of deliberative quality. A pilot study is conducted on the topic of abortion to illustrate the proposed methodology. The findings of this research demonstrate that AAF methods can improve discourse analysis by automatically identifying strong arguments through conflict resolution strategies. They also emphasise the potential of the proposed procedure to mitigate the dependence on manual coding and improve deliberation processes. Full article

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19 pages, 1526 KiB

Open AccessArticle

Strategic Inventory Management with Private Brands: Navigating the Challenges of Supply Uncertainty

by Junjie Guo, Huanhuan Wang, Guang Song, Hanxing Cui and Qilan Zhao

Systems 2025, 13(3), 203; https://doi.org/10.3390/systems13030203 - 15 Mar 2025

Viewed by 632

Abstract

In the context of globalized and complex supply chains, supply uncertainty occurs frequently. To reduce dependence on suppliers, retailers often consider holding strategic inventory and introducing private brands. To explore the relationship between private brands and strategic inventory strategies, and to determine the [...] Read more.

In the context of globalized and complex supply chains, supply uncertainty occurs frequently. To reduce dependence on suppliers, retailers often consider holding strategic inventory and introducing private brands. To explore the relationship between private brands and strategic inventory strategies, and to determine the optimal strategic decisions, this paper constructs a two-stage supply chain model. Using game theory methods, we calculate the equilibrium outcomes of the supply chain under two scenarios: one with only national brands and the other with the introduction of private brands. The main findings are as follows. First, we identify the optimal decisions for both suppliers and retailers in each scenario. The influencing factors include perceived quality, inventory costs, and supply stability. Second, we find that there are constraints for retailers to activate strategic inventory, but these constraints are less restrictive when private brands are introduced. Finally, introducing private brands benefits retailers in implementing strategic inventory, although the extent of this impact depends on the conditions under which the strategic stockpile is implemented. These findings fill the gap in the existing literature on the impact of private brand introductions on strategic inventory under supply uncertainty and highlight valuable implications for business decision-makers. Full article

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

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22 pages, 525 KiB

Open AccessArticle

Growth Mechanism in Transformation and Upgrading of Logistics Industry

by Fangzhou Li, Xiaojia Yang, Ruili Zhu, Tao Li and Jingyi Liu

Systems 2025, 13(3), 202; https://doi.org/10.3390/systems13030202 - 15 Mar 2025

Viewed by 426

Abstract

Despite the crucial contribution of the logistics industry to economic development, existing research has yet to comprehensively explore how the integration of basic and emerging business models fuels growth during the transformation and upgrading process. To address this research gap, this study utilizes [...] Read more.

Despite the crucial contribution of the logistics industry to economic development, existing research has yet to comprehensively explore how the integration of basic and emerging business models fuels growth during the transformation and upgrading process. To address this research gap, this study utilizes provincial panel data from 30 regions covering the period from 2008 to 2022. By employing an intermediary effect model and a moderation effect model, we aim to uncover the underlying mechanisms driving growth. The findings reveal that the logistics industry can be categorized into traditional and emerging logistics elements, with the integration of traditional elements forming the fundamental business model. This foundational model serves as the primary driver of the logistics industry’s growth, exerting both direct and indirect influences on its expansion. Moreover, the level of economic development positively moderates these direct and indirect effects. These insights underscore the importance of enhancing infrastructure development, fostering business innovation, and promoting region-specific differentiated growth strategies. Full article

(This article belongs to the Special Issue Modeling and Simulation Innovations for Advanced Logistics Systems Management)

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37 pages, 6089 KiB

Open AccessArticle

Quantifying Social Justice in Energy Transition: A Policy-Driven Assessment Framework for China

by Siqing Shan, Yinong Li, Yangzi Yang, Haoyuan Zhang and Junze Li

Systems 2025, 13(3), 201; https://doi.org/10.3390/systems13030201 - 14 Mar 2025

Viewed by 485

Abstract

Addressing climate change and promoting social justice are crucial sustainable development goals. However, the quantitative assessment of how energy transition policies impact social justice remains a significant challenge. To address this gap, we develop a novel Energy Transition Social Justice Framework (ETSJF) that [...] Read more.

Addressing climate change and promoting social justice are crucial sustainable development goals. However, the quantitative assessment of how energy transition policies impact social justice remains a significant challenge. To address this gap, we develop a novel Energy Transition Social Justice Framework (ETSJF) that integrates four dimensions (energy supply, energy demand, procedural justice, and distributive justice) and three perspectives (individual, group-organizational, and society). The ETSJF index is constructed to measure the progress of social justice in China’s energy transition from 2010 to 2021. The index exhibits a robust growth trend, increasing from 269 in 2010 to 965 in 2021, with an average annual growth rate of 12.9%. The years 2014 and 2020–2021 mark turning points, coinciding with the implementation of transformative policy initiatives and China’s carbon neutrality pledge. Employing multi-source data analysis, we evaluate the impact of energy transition policies on social justice using the Energy Transition Policy Impact Intensity (ETPII). Our analysis reveals that energy transition policies significantly positively impact overall social justice (ETPII: 1.133), with variations across dimensions. Energy supply shows the most potent effects (ETPII: 1.203), while procedural justice exhibits the weakest impact (ETPII: 0.804). These findings offer policy implications for achieving a just and inclusive energy transition. The proposed ETSJF and ETPII enable the systematic monitoring of social justice progress and offer methodological tools for policymakers to optimize energy transition policies through data-driven decision-making. Full article

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

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27 pages, 3662 KiB

Open AccessReview

Circular Economy in Small and Medium-Sized Enterprises—Current Trends, Practical Challenges and Future Research Agenda

by Ayon Chakraborty, Debashree De and Prasanta Kumar Dey

Systems 2025, 13(3), 200; https://doi.org/10.3390/systems13030200 - 14 Mar 2025

Viewed by 1122

Abstract

The Circular Economy (CE) has evolved as a philosophy to transform industrial supply chains to become greener to combat climate change issues. Countries’ target of achieving Net Zero will never be fulfilled unless, along with larger organizations, small and medium-sized enterprises (SMEs) are [...] Read more.

The Circular Economy (CE) has evolved as a philosophy to transform industrial supply chains to become greener to combat climate change issues. Countries’ target of achieving Net Zero will never be fulfilled unless, along with larger organizations, small and medium-sized enterprises (SMEs) are decarbonized, as more than 90% of the world’s businesses are SMEs. Although, recently, there have been many studies on SMEs’ sustainability practices and performance covering drivers, bottlenecks, and opportunities, the holistic approach for embedding circular economy and sustainability covering design, planning, implementation, and operations is missing. This research bridges this knowledge gap by revealing trends and theories of circular economy adoption in SMEs. Additionally, this research derives the drivers/enablers, issues, and challenges and determines strategies, resources, and competencies for CE adoption in SMEs. This study concludes with a consolidated framework comprising factors and methods for CE implementation in SMEs. This entire piece of research has been undertaken using the secondary data analysis method through the content analysis of 188 published articles in highly ranked peer-reviewed journals. Full article

(This article belongs to the Section Supply Chain Management)

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21 pages, 473 KiB

Open AccessArticle

The Effect of the Use of Digital Technology on the Impact of Labor Outflow on Rural Collective Action: A Social–Ecological Systems Perspective

by Yiqing Su, Qiang Li and Lihua Li

Systems 2025, 13(3), 199; https://doi.org/10.3390/systems13030199 - 13 Mar 2025

Viewed by 616

Abstract

The rapid development of urbanization has led to a continuous migration of rural labor to cities, while also facilitating the widespread adoption of digital technologies in both urban and rural areas. The existing literature predominantly focuses on the negative impact of labor outflow [...] Read more.

The rapid development of urbanization has led to a continuous migration of rural labor to cities, while also facilitating the widespread adoption of digital technologies in both urban and rural areas. The existing literature predominantly focuses on the negative impact of labor outflow on rural collective action, with insufficient research addressing how to mitigate these adverse effects. By using the social–ecological systems framework, and based on survey data from 131 villages across 14 cities in Guangxi, China, this study finds that digital technologies can alleviate the negative impact of labor outflow on irrigation collective action. The relationship between labor outflow, irrigation collective action, and the use of digital technologies is particularly evident in villages located in non-plain regions, those with distinctive cultural resources, high collective economic income, and restructured planning, and where technological advancements have been promoted. The findings of this study highlight a beneficial relationship between the phenomena of labor outflow and the diffusion of digital technologies, both of which are consequences of urbanization. This suggests that issues arising from urbanization can also be addressed and resolved through urbanization itself. The conclusions offer a new perspective for understanding the interactions between variables in social–ecological systems and provide a reference for developing countries to find suitable paths for combating rural decline and achieving sustainable rural development amidst rapid urbanization. Full article

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

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22 pages, 2696 KiB

Open AccessArticle

How to Enhance Enterprises’ Radical Innovation Performance Through Multiple Pathways—A Machine Learning Analysis of SRDI Enterprises in China

by Liping Zhang, Hanhui Qiu, Jinyi Chen, Hailin Li and Xiaoji Wan

Systems 2025, 13(3), 198; https://doi.org/10.3390/systems13030198 - 12 Mar 2025

Viewed by 525

Abstract

Specialized, Refined, Differentiated, and Innovative (SRDI) enterprises are crucial to China’s economic development. It is important to examine how various factors’ combinations impact the radical innovation performance of SRDI enterprises in order to promote high-quality regional economic development. Based on the Technology–Organization–Environment (TOE) [...] Read more.

Specialized, Refined, Differentiated, and Innovative (SRDI) enterprises are crucial to China’s economic development. It is important to examine how various factors’ combinations impact the radical innovation performance of SRDI enterprises in order to promote high-quality regional economic development. Based on the Technology–Organization–Environment (TOE) framework, this study selected SRDI enterprises as research samples, used a hierarchical clustering algorithm to divide the enterprises into groups according to the characteristics of SRDI enterprises, and employed a classification and regression tree (CART) algorithm to reveal the complex nonlinear relationships between the combinations of multiple key influencing factors and radical innovation performance from multi-source big data. The findings indicate that (1) there are significant variations in the factors affecting the radical innovation performance of different types of SRDI enterprises; (2) the radical innovation performance of SRDI enterprises stems from the synergistic interaction among various factors; and (3) the impact of R&D investment on radical innovation is not simply linear. This study effectively captures the complex nonlinear relationships between combinations of multiple influencing factors and radical innovation performance. It is of great practical significance for revealing SRDI enterprises’ radical innovation performance improvement pathways and enhancing their innovation capability. Full article

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

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23 pages, 3564 KiB

Open AccessArticle

Serious Game Design for Teaching University Students to Address Complexity Issues in the Healthcare Logistics System: Lessons from an Emergency Department Case Study

by Yan Sun and Chen Zhang

Systems 2025, 13(3), 197; https://doi.org/10.3390/systems13030197 - 12 Mar 2025

Viewed by 642

Abstract

As pioneers in this field, our role in shaping the future of serious games in healthcare logistics is crucial. Digital media design significantly influences the quality of gaming simulation studies in healthcare. The leading challenge scholars face is introducing innovative and valuable features [...] Read more.

As pioneers in this field, our role in shaping the future of serious games in healthcare logistics is crucial. Digital media design significantly influences the quality of gaming simulation studies in healthcare. The leading challenge scholars face is introducing innovative and valuable features to university students. The data–simulation–gaming pyramid could serve as a blueprint for outlining how interactive simulations could be conducted. A participatory design process is important in serious game development. More recently, the literature has illustrated the contribution of extended reality. However, researchers have not explored this research framework in detail. This paper traces the participatory design process of serious games using an emergency logistics case study in Stockholm, Sweden. It underscores the importance of choosing the correct narratives and game mechanics to support the implementation of serious games using extended reality for the demonstration of non-technical skills. The research findings are threefold. (1) The participatory design process helps to place focus on the implementing philosophy that values health equality in networked hospitals. (2) Further analysis reveals that gamification could turn everyday tasks in the emergency department, which represents a stressful workplace in a hospital, into a spectrum of learning experiences for in-demand skills, including situational awareness, leadership, communication, and ethical thinking. (3) A closer inspection of the reality-changing methods shows new requirements to shorten patient queues before and after the (implementation of the) strengthened waiting time guarantee proposal in 2024. There is abundant room for principals in healthcare institutions to implement reality-changing methods to foster collaboration at the departmental, cross-departmental, and cross-institutional levels. Full article

(This article belongs to the Special Issue Innovative Systems Approaches to Healthcare Systems)

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19 pages, 3787 KiB

Open AccessArticle

Blockchain Effects and Investment Strategies in the Maritime Supply Chain Under Perishable Goods Loss

by Liying Li and Jianqin Zhou

Systems 2025, 13(3), 196; https://doi.org/10.3390/systems13030196 - 11 Mar 2025

Viewed by 593

Abstract

As the global market for shipping perishable goods expands, the substantial loss and high claim costs associated with these goods have drawn increasing attention. Blockchain technology (BCT) can improve customs clearance efficiency and reduce perishable goods loss. However, the high investment costs present [...] Read more.

As the global market for shipping perishable goods expands, the substantial loss and high claim costs associated with these goods have drawn increasing attention. Blockchain technology (BCT) can improve customs clearance efficiency and reduce perishable goods loss. However, the high investment costs present a clear trade-off between enhancing clearance efficiency to mitigate loss and claims costs and the financial burden of BCT adoption. Additionally, determining which stakeholder should invest in BCT has become a critical strategic issue. To address this, we develop three Stackelberg game models to investigate the optimal BCT investment strategies for different entities—the port and the shipping company—in the maritime supply chain. Building on previous models in the existing literature, we incorporate the perishable goods loss rate and claim costs to offer new insights into how the perishable goods loss rate influences BCT investment outcomes. The results reveal that when the shipping company invests in BCT, if its BCT investment cost coefficient is within a certain range, a higher perishable goods loss rate can generate higher profits for both the port and the shipping company. Furthermore, our findings indicate that BCT investment enhances consumer surplus and social welfare in the maritime supply chain when considering perishable goods loss. Full article

(This article belongs to the Section Supply Chain Management)

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18 pages, 1389 KiB

Open AccessArticle

Integrating Cultural and Emotional Intelligence to Examine Newcomers’ Performance and Error Reduction: A Moderation–Mediation Analysis

by Tesfaye Agafari Bafa, Mingyu Zhang and Chong Chen

Systems 2025, 13(3), 195; https://doi.org/10.3390/systems13030195 - 11 Mar 2025

Viewed by 558

Abstract

Built on the Conservation of Resources (COR), Multiple Intelligence (MI), and Social Exchange (SET) theories, this study investigates how cultural intelligence, emotional intelligence, and perceived organizational support influence newcomers’ task performance and error reduction. The research also explores the mediating effects of emotional [...] Read more.

Built on the Conservation of Resources (COR), Multiple Intelligence (MI), and Social Exchange (SET) theories, this study investigates how cultural intelligence, emotional intelligence, and perceived organizational support influence newcomers’ task performance and error reduction. The research also explores the mediating effects of emotional exhaustion and the moderating effects of cognitive diversity. Data were collected from 476 participants in organizations employing newcomers, using census, stratified, and simple random sampling techniques. Structural Equation Modeling (SEM) was employed to test the research hypotheses. The results reveal that higher levels of cultural and emotional intelligence are negatively associated with emotional exhaustion, while an increase in perceived organizational support reduces emotional exhaustion. Emotional exhaustion was found to be linked to higher error rates and lower task performance. The mediation analyses showed that emotional exhaustion mediated the relationship between cultural intelligence, emotional intelligence, and perceived organizational support and both task performance and error reduction. Furthermore, cognitive diversity moderated the relationships between cultural intelligence and emotional exhaustion, as well as between emotional intelligence and emotional exhaustion. These findings underscore the critical roles of cultural and emotional intelligence, along with organizational support, in mitigating emotional exhaustion, reducing errors, and enhancing task performance, while emphasizing the importance of cognitive diversity in shaping organizational outcomes. Full article

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

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21 pages, 4413 KiB

Open AccessArticle

Estimation of CO₂ Emissions in Transportation Systems Using Artificial Neural Networks, Machine Learning, and Deep Learning: A Comprehensive Approach

by Seval Ene Yalçın

Systems 2025, 13(3), 194; https://doi.org/10.3390/systems13030194 - 11 Mar 2025

Viewed by 631

Abstract

This study focuses on estimating transportation system-related emissions in CO₂ eq., considering several socioeconomic and energy- and transportation-related input variables. The proposed approach incorporates artificial neural networks, machine learning, and deep learning algorithms. The case of Turkey was considered as an example. [...] Read more.

This study focuses on estimating transportation system-related emissions in CO₂ eq., considering several socioeconomic and energy- and transportation-related input variables. The proposed approach incorporates artificial neural networks, machine learning, and deep learning algorithms. The case of Turkey was considered as an example. Model performance was evaluated using a dataset of Turkey, and future projections were made based on scenario analysis compatible with Turkey’s climate change mitigation strategies. This study also adopted a transportation type-based analysis, exploring the role of Turkey’s road, air, marine, and rail transportation systems. The findings of this study indicate that the aforementioned models can be effectively implemented to predict transport emissions, concluding that they have valuable and practical applications in this field. Full article

(This article belongs to the Special Issue Modeling, Planning and Management of Sustainable Transport Systems)

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20 pages, 1694 KiB

Open AccessArticle

Dynamic Optimal Control Strategy of CCUS Technology Innovation in Coal Power Stations Under Environmental Protection Tax

by Chang Su, Xinxin Zha, Jiayi Ma, Boying Li and Xinping Wang

Systems 2025, 13(3), 193; https://doi.org/10.3390/systems13030193 - 10 Mar 2025

Cited by 6 | Viewed by 503

Abstract

Carbon capture, utilization, and storage (CCUS) technology is an essential technology for achieving low-carbon transformation and upgrading of the coal power industry. This study applies optimal control theory to analyze the dynamic optimization of CCUS technological innovation investment in coal power stations under [...] Read more.

Carbon capture, utilization, and storage (CCUS) technology is an essential technology for achieving low-carbon transformation and upgrading of the coal power industry. This study applies optimal control theory to analyze the dynamic optimization of CCUS technological innovation investment in coal power stations under environmental protection tax. A dynamic control model is constructed to analyze the investment decisions of firms at system steady-state equilibrium, and numerical simulations are performed. The study shows that under both profit maximization and social welfare maximization conditions, a distinct saddle-point steady-state; the environmental protection tax affects technological innovation investment in coal power stations, which in turn affects electricity prices; the learning rate of knowledge accumulation also impacts technological innovation investment: under the social welfare maximization condition, the investment levels in technological innovation, technology, and knowledge accumulation are higher than those under profit maximization. Full article

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

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23 pages, 693 KiB

Open AccessArticle

Does Financialization Alleviate the Funding Dilemma of Green Innovation in Heavily Polluting Firms?: Evidence from China’s A-Share Listed Companies

by Zifeng Zhong, Shaoxiong Wu, Jieying Hu, Liting Fang and Kunming Li

Systems 2025, 13(3), 192; https://doi.org/10.3390/systems13030192 - 10 Mar 2025

Viewed by 511

Abstract

Green innovation in heavily polluting firms is crucial for sustainable development, yet financial constraints remain a major barrier. This study employs a Spatial Durbin Model to analyze how financialization influences green innovation in China’s A-share listed firms. The results indicate that financialization intensifies [...] Read more.

Green innovation in heavily polluting firms is crucial for sustainable development, yet financial constraints remain a major barrier. This study employs a Spatial Durbin Model to analyze how financialization influences green innovation in China’s A-share listed firms. The results indicate that financialization intensifies financing constraints, leading to a suppression of green innovation. This effect is primarily driven by the “crowding-out effect”, which outweighs the “reservoir effect” that financialization may provide. Additionally, industry-wide peer effects further spread the negative impact, while agency conflicts and managerial incentives exacerbate the problem. Regional disparities are also observed, with stronger negative effects in eastern and central regions and among firms with high managerial compensation. To address these issues, the study recommends strengthening policy guidance, expanding green finance mechanisms, promoting industry collaboration, and improving corporate governance. These findings enhance our understanding of the dual impact of financialization on green innovation and provide actionable policy recommendations for achieving sustainable development in high-pollution industries. Full article

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

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38 pages, 17360 KiB

Open AccessArticle

Systems Developmental Dependency Analysis for Scheduling Decision Support: The Lunar Gateway Case Study

by Cesare Guariniello and Daniel DeLaurentis

Systems 2025, 13(3), 191; https://doi.org/10.3390/systems13030191 - 9 Mar 2025

Viewed by 587

Abstract

Project Managers face many difficulties when scheduling the development and production of multiple, largely independent systems required for a new capability, especially when there are multiple stakeholders, uncertainties in the expected development time, and developmental dependencies among the systems. The Systems Developmental Dependency [...] Read more.

Project Managers face many difficulties when scheduling the development and production of multiple, largely independent systems required for a new capability, especially when there are multiple stakeholders, uncertainties in the expected development time, and developmental dependencies among the systems. The Systems Developmental Dependency Analysis methodology provides a systemic approach to address these challenges by offering decision support for such a ‘System-of-Systems’. The method, based on a parametric piece-wise linear model of dependencies between elements in the developmental domain, propagates the interactions between systems to estimate delays in the development of individual systems and to evaluate the impact of such delays on the expected schedule of completion for the establishment of the whole desired capability. The schedule can be automatically re-generated based on new system information, changed dependencies, and/or modified risk levels. As demonstrated in this paper using a complex space mission case, the method enhances decision-support by identifying criticalities, computing possible delay absorption strategies, and comparing different development strategies in terms of robustness to delays. Full article

(This article belongs to the Special Issue System of Systems Engineering)

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26 pages, 746 KiB

Open AccessArticle

How Does Artificial Intelligence Shape Supply Chain Resilience? The Moderating Role of the CEOs’ Sports Experience

by Yuxuan Xu, Hua Yu, Ran Qiu and Liying Yu

Systems 2025, 13(3), 190; https://doi.org/10.3390/systems13030190 - 9 Mar 2025

Viewed by 1286

Abstract

In the volatility, uncertainty, complexity, and ambiguity (VUCA) environment, the application of artificial intelligence (AI) technologies is a key engine for shaping supply chain resilience (SCR). This study employs the entropy method to develop an evaluation index system for SCR, incorporating two key [...] Read more.

In the volatility, uncertainty, complexity, and ambiguity (VUCA) environment, the application of artificial intelligence (AI) technologies is a key engine for shaping supply chain resilience (SCR). This study employs the entropy method to develop an evaluation index system for SCR, incorporating two key dimensions: resistance and recovery capacity. Using a sample of Chinese-listed enterprises from 2009 to 2022, this study reveals that AI significantly enhances SCR, and CEOs’ sports experience can positively moderate the association between AI and SCR. Mechanism examination shows that AI promotes SCR through operational efficiency optimization, information, and knowledge spillover in the supply chain. Heterogeneity analysis reveals that the positive impact of AI is more significant in firms with a high-skilled labor force, firms with high heterogeneity of the executive team’s human capital, high-tech industries, and regions with strong digital infrastructure. Moreover, the AI application has a diffusion effect on the upstream and downstream enterprises of the supply chain, improving AI adoption levels. Our research not only augments the existing literature on the economic ramifications of AI adoption and the strategic value derived from CEOs’ extramural experience but also offers both theoretical frameworks and empirical insights for executive recruitment and fortifying SCR. Full article

(This article belongs to the Special Issue Multi-criteria Decision Making in Supply Chain Management)

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19 pages, 1020 KiB

Open AccessArticle

Exploring Consumers’ Technology Acceptance Behavior Regarding Indoor Smart Farm Restaurant Systems: Focusing on the Value-Based Adoption Model and Value–Attitude–Behavior Hierarchy

by Kyuhyeon Joo and Jinsoo Hwang

Systems 2025, 13(3), 189; https://doi.org/10.3390/systems13030189 - 8 Mar 2025

Viewed by 685

Abstract

This study examines consumers’ technology acceptance behavior regarding indoor smart farm restaurant systems focusing on the value-based adoption model and value–attitude–behavior hierarchy. More specifically, the study explores the effects of the benefits (i.e., perceived naturalness, psychological benefits, healthy well-being, and enjoyment) and sacrifices [...] Read more.

This study examines consumers’ technology acceptance behavior regarding indoor smart farm restaurant systems focusing on the value-based adoption model and value–attitude–behavior hierarchy. More specifically, the study explores the effects of the benefits (i.e., perceived naturalness, psychological benefits, healthy well-being, and enjoyment) and sacrifices (i.e., perceived fee, perceived risk, and food technophobia) on perceived value. This study also probes the influence of perceived value on attitude and intentions to use and the relationship between attitude and intentions to use. The data were collected from 360 respondents in South Korea. The data analysis results indicate that all the benefit factors positively affect perceived value, whereas only food technophobia negatively affects perceived value among the sacrifice factors. Lastly, perceived value aids in the formation of attitude, while perceived value and attitude have a positive influence on intentions to use. Full article

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

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32 pages, 5893 KiB

Open AccessArticle

Pricing Analysis of Risk-Averse Supply Chains with Supply Disruption Considering Reference Price Effect

by Gui-Hua Lin, Ruimin Dai, Yu-Wei Li and Qi Zhang

Systems 2025, 13(3), 188; https://doi.org/10.3390/systems13030188 - 7 Mar 2025

Viewed by 649

Abstract

This paper examines the impact of the reference price effect on pricing decisions in a risk-averse supply chain with a dual-sourcing procurement strategy, particularly during single-sourcing supply disruption. To analyze supply chain pricing decisions under non-disrupted and disrupted scenarios, we innovatively use semivariance [...] Read more.

This paper examines the impact of the reference price effect on pricing decisions in a risk-averse supply chain with a dual-sourcing procurement strategy, particularly during single-sourcing supply disruption. To analyze supply chain pricing decisions under non-disrupted and disrupted scenarios, we innovatively use semivariance as a risk measure to effectively avoid the limitations of the traditional variance approach and integrate it into Stackelberg game models. Based on these models, we analyze the impact of the reference price effect, risk aversion, and single-sourcing supply disruption on supply chain members’ pricing decisions. The main findings include the following: the single-sourcing supply disruption degree may increase the price of non-disrupted products and then increase the non-disrupted supplier’s utility; the strength of the reference price effect positively influences retailer utility but negatively impacts product pricing for supply chain members; the pricing decisions and utility of supply chain members are influenced by their risk aversion, and supply chain members with higher risk aversion adopt more conservative pricing strategies and consequently obtain lower utility; and equilibrium decisions generally demonstrate a degree of robustness. These insights may help supply chain managers respond rationally to supply disruptions and properly develop pricing strategies by taking into account the reference price effect. Full article

(This article belongs to the Section Supply Chain Management)

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31 pages, 13000 KiB

Open AccessArticle

Research on the Nonlinear and Interactive Effects of Multidimensional Influencing Factors on Urban Innovation Cooperation: A Method Based on an Explainable Machine Learning Model

by Rui Wang, Xingping Wang, Zhonghu Zhang, Siqi Zhang and Kailun Li

Systems 2025, 13(3), 187; https://doi.org/10.3390/systems13030187 - 7 Mar 2025

Viewed by 898

Abstract

Within globalization, the significance of urban innovation cooperation has become increasingly evident. However, urban innovation cooperation faces challenges due to various factors—social, economic, and spatial—making it difficult for traditional methods to uncover the intricate nonlinear relationships among them. Consequently, this research concentrates on [...] Read more.

Within globalization, the significance of urban innovation cooperation has become increasingly evident. However, urban innovation cooperation faces challenges due to various factors—social, economic, and spatial—making it difficult for traditional methods to uncover the intricate nonlinear relationships among them. Consequently, this research concentrates on cities within the Yangtze River Delta region, employing an explainable machine learning model that integrates eXtreme Gradient Boosting (XGBoost), SHapley Additive exPlanations (SHAP), and Partial Dependence Plots (PDPs) to investigate the nonlinear and interactive effects of multidimensional factors impacting urban innovation cooperation. The findings indicate that XGBoost outperforms LR, SVR, RF, and GBDT in terms of accuracy and effectiveness. Key results are summarized as follows: (1) Urban innovation cooperation exhibits different phased characteristics. (2) There exist nonlinear and interactive effects between urban innovation cooperation and multidimensional factors, among them, the Scientific and Technological dimension contributes the most (30.59%) and has the most significant positive promoting effect in the later stage after surpassing a certain threshold. In the Social and Economic dimension (23.61%), the number of Internet Users (IU) contributes the most individually. The Physical Space dimension (20.46%) generally exhibits mutation points during the early stages of urban development, with overall relationships predominantly characterized by nonlinear positive trends. (3) Through the application of PDP, it is further determined that IU has a positive synergistic effect with per capita Foreign Direct Investment (FDI), public library collections per capita (LC), and city night light data (NPP), while exhibiting a negative antagonistic effect with Average Annual Wage of Staff (AAS) and number of Enterprises above Designated Size in Industry (EDS). (4) For cities at different developmental stages, tailored development proposals should be formulated based on single-factor contribution and multifactor interaction effects. These insights enhance our understanding of urban innovation cooperation and elucidate the nonlinear and interactive effects of multidimensional influencing factors. Full article

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

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25 pages, 1712 KiB

Open AccessArticle

Improving the Information Systems of a Warehouse as a Critical Component of Logistics: The Case of Lithuanian Logistics Companies

by Kristina Vaičiūtė and Aušra Katinienė

Systems 2025, 13(3), 186; https://doi.org/10.3390/systems13030186 - 7 Mar 2025

Viewed by 605

Abstract

Rapid changes in the modern world and technological advances and processes are increasingly contributing to greater attention being given to emerging problems associated with obtaining big data, as well as modifying decision-making processes in diverse spheres. Special attention in logistics companies should be [...] Read more.

Rapid changes in the modern world and technological advances and processes are increasingly contributing to greater attention being given to emerging problems associated with obtaining big data, as well as modifying decision-making processes in diverse spheres. Special attention in logistics companies should be given to the warehouse as a critical component of logistics, in particular to such processes as big data processing and automation, as well as the improvement, development, and support of information systems. Enhancing logistics information systems provides companies with a competitive advantage, reduces the emergence of human error, accelerates processes, and ensures the collection and sharing of information and big data are used in a sustainable manner. The automation of warehouse processes results in better-established operational safety and overall service quality. The present paper reviews the importance of improving warehouse automation and logistics information systems. Its advantages are highlighted, and the results of the conducted research are provided to expose the problem areas of warehouse automation and encourage improvements in information systems in Lithuanian logistics companies wherein there is a need to transfer a large amount of information and increase service quality. Full article

(This article belongs to the Special Issue Intelligent Logistics Systems Applications: Enhancing Efficiency and Adaptability)

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21 pages, 794 KiB

Open AccessArticle

Intelligent Transformation: The Invisible Shield Against Corporate Credit Risk

by Yang Li, Liangrong Song, Yashan Peng and Jianjia He

Systems 2025, 13(3), 185; https://doi.org/10.3390/systems13030185 - 7 Mar 2025

Viewed by 496

Abstract

In the context of a progressively intricate and uncertain global economic landscape, the credit risk businesses encounter is intensifying. This study seeks to analyze whether intelligent transformation, a significant trend in current organization development, might serve as a novel method for mitigating credit [...] Read more.

In the context of a progressively intricate and uncertain global economic landscape, the credit risk businesses encounter is intensifying. This study seeks to analyze whether intelligent transformation, a significant trend in current organization development, might serve as a novel method for mitigating credit risk. We employ panel data from 1533 listed enterprises in China’s manufacturing sector to investigate how intelligent transformation influences credit risk empirically. This research indicates that intelligent transformation can mitigate business credit risk. The production, management, and financing effects are the primary mechanisms via which intelligent transformation mitigates credit risk. Heterogeneity analysis indicated that the credit risk reduction effect of the intelligent transformation of traditional manufacturing firms surpassed that of intelligent manufacturing enterprises. In contrast to high-growth firms, low-growth enterprises exhibited more robust credit risk mitigation benefits from intelligent transformation. Subsequent analysis indicated that enhancing supply chain finance can facilitate intelligent transformation and, hence, more effectively mitigate credit risk. Full article

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

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