Systems

23 pages, 1421 KiB

Open AccessArticle

C2C E-Commerce Platform Trust from the Seller’s Perspective Based on Institutional Trust Theory and Cultural Dimension Theory

by Yulu Sun, Zhenhua Wang, Hongxiao Lyu and Qixing Qu

Systems 2025, 13(5), 309; https://doi.org/10.3390/systems13050309 - 23 Apr 2025

Abstract

With the development of electronic retailing in C2C e-commerce platforms, the issue of trust loss from sellers has worsened. It is urgent for platform operators to learn how to retain quality sellers and improve their trust. Based on institutional trust theory, we combine [...] Read more.

With the development of electronic retailing in C2C e-commerce platforms, the issue of trust loss from sellers has worsened. It is urgent for platform operators to learn how to retain quality sellers and improve their trust. Based on institutional trust theory, we combine formal institutions (structural assurance) and informal institutions (cultural factors), intending to examine the direct effects of masculinity, uncertainty avoidance, and long-term orientation on platform trust, the moderating effects of website quality, institutional guarantee and security systems, and the relationships among cultural factors. A total of 2970 valid responses were collected and analyzed from individual sellers on Taobao, which is one of the most representative C2C e-commerce platforms in China. The results reveal that uncertainty avoidance is negatively associated with platform trust, while masculinity and long-term orientation are positively associated with platform trust. Significant associations are also found among cultural factors. Website quality and institutional guarantee weaken the negative correlation between uncertainty avoidance and platform trust, while the security system strengthens it. Details of theoretical and managerial implications are discussed. Full article

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

► Show Figures

Figure 1

14 pages, 1149 KiB

Open AccessArticle

Risk Identification and Prevention of Supply Chain Operation in Small and Medium-Sized Livestock Farms

by Man Xu, Xinglong Yang and Zhiru Sun

Systems 2025, 13(5), 308; https://doi.org/10.3390/systems13050308 (registering DOI) - 23 Apr 2025

Abstract

In recent years, there has been rapid development in Chinese small and medium-sized livestock farms, accompanied by an increase in operational risks within the supply chain. To ensure the stability and sustainability of supply chain operations in small and medium-sized livestock farms, it [...] Read more.

In recent years, there has been rapid development in Chinese small and medium-sized livestock farms, accompanied by an increase in operational risks within the supply chain. To ensure the stability and sustainability of supply chain operations in small and medium-sized livestock farms, it is essential to thoroughly analyze their potential hazards and formulate effective prevention strategies. This paper employs the relevant supply chain theories, combined with previous research and expert interviews, to conduct an empirical analysis of supply chain operation risks in small and medium-sized livestock farms, with a specific focus on pig farms, beef cattle farms, laying hen farms, and broiler farms. The research indicates that the supply chain operation risks faced by small and medium-sized livestock farms primarily stem from external environmental factors and production-related challenges. Furthermore, external environmental risks predominantly arise from market fluctuations and compliance with environmental regulations, while production risk mainly pertains to disease safety. Based on the research findings, this paper proposes specific measures for risk prevention, including the strengthening of external environmental security, driving production innovation capacity, strengthening market forecasting capacity, constantly enhancing environmental awareness, and strengthening epidemic prevention efforts. Full article

(This article belongs to the Section Supply Chain Management)

► Show Figures

Figure 1

19 pages, 507 KiB

Open AccessArticle

Unravelling the Motivational Dynamics of Established Entrepreneurs: A Systems Perspective

by Karin Širec, Nataša Šarlija and Katja Crnogaj

Systems 2025, 13(5), 307; https://doi.org/10.3390/systems13050307 - 23 Apr 2025

Abstract

The question of what motivates entrepreneurs to maintain and grow their ventures beyond the startup phase remains an underexplored aspect of entrepreneurship research. Using data from the Global Entrepreneurship Monitor, GEM (2023), this study examines four key entrepreneurial motivations among 103 established Croatian [...] Read more.

The question of what motivates entrepreneurs to maintain and grow their ventures beyond the startup phase remains an underexplored aspect of entrepreneurship research. Using data from the Global Entrepreneurship Monitor, GEM (2023), this study examines four key entrepreneurial motivations among 103 established Croatian entrepreneurs who are making a difference in the world, building great wealth or a very high income, continuing a family tradition, and earning a living. Employing a multivariate multiple regression approach, we analyze how sociodemographic factors, opportunity perception, fear of failure, media influences, and sustainability-oriented mindsets (e.g., UN SDG awareness) influence these diverse motivations. Findings reveal distinct motivational patterns: socially responsible mindsets and awareness of the SDGs primarily drive the aspiration to “make a difference”, while age, perceived opportunities, and fear of failure reinforce the pursuit of wealth. Media narratives uniquely influence the intent to “continue a family tradition”, while necessity-driven motives—linked to fear of failure and lower growth ambitions—predominate among those aiming simply to “earn a living”. By applying a systems thinking approach, this research illustrates how interdependent factors create distinct motivational clusters, and it highlights the importance of tailored policies and support programs for established entrepreneurs seeking sustainable growth. It contributes to the interdisciplinary discourse on entrepreneurship, offering insights for policymakers, educators, and advisors working to foster resilient and innovative entrepreneurial ecosystems. Full article

(This article belongs to the Special Issue Harnessing Systems Thinking in Entrepreneurship: Interdisciplinary Perspectives and Emerging Trends)

► Show Figures

Figure 1

22 pages, 2641 KiB

Open AccessArticle

Digital Oasis: How Green Infrastructure Is Reshaping China’s Energy Resilience Landscape

by Xue Lei, Jian Xu, You Chen, Chang Liu and Kunjian Zhao

Systems 2025, 13(5), 306; https://doi.org/10.3390/systems13050306 - 22 Apr 2025

Abstract

In the context of global energy transition and climate change, energy system resilience has become critical for countries worldwide. While green digital infrastructure—emerging from the integration of digitalization and low-carbon development—shows theoretical potential to strengthen energy resilience, empirical evidence remains limited. This study [...] Read more.

In the context of global energy transition and climate change, energy system resilience has become critical for countries worldwide. While green digital infrastructure—emerging from the integration of digitalization and low-carbon development—shows theoretical potential to strengthen energy resilience, empirical evidence remains limited. This study utilizes China’s 2015 Green Data Center Pilot Policy as a quasi-natural experiment to examine this relationship through comprehensive panel data from 30 Chinese provinces spanning 2011–2021. We developed an integrated energy resilience evaluation framework across four dimensions: economic resilience, engineering resilience, resource resilience, and ecological resilience, applying the CRITIC method to determine objective indicator weights. Our difference-in-differences analysis demonstrates that green digital infrastructure significantly enhances regional energy resilience, with pilot regions experiencing a 2.83% improvement compared to non-pilot areas. This impact shows regional heterogeneity, with stronger effects in economically developed areas with better digital foundations. We identify two primary mechanisms through which green digital infrastructure influences energy resilience: industrial structure optimization (particularly through service industry growth) and enhanced innovation capacity. These findings provide robust empirical support for green digital infrastructure’s role in strengthening energy system stability and adaptability, offering valuable policy insights for promoting both digitalization and low-carbon transition under global climate governance. Full article

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

► Show Figures

Figure 1

18 pages, 1541 KiB

Open AccessArticle

The Development of a Methodology for Assessing Data Value Through the Identification of Key Determinants

by Daye Lee and Byungun Yoon

Systems 2025, 13(4), 305; https://doi.org/10.3390/systems13040305 - 21 Apr 2025

Abstract

This study introduces a methodology for assessing data value by identifying the key determinants that influence it. As data represents critical assets in modern business, companies must evaluate and use them strategically to maintain competitiveness. However, the intangible and complex nature of data [...] Read more.

This study introduces a methodology for assessing data value by identifying the key determinants that influence it. As data represents critical assets in modern business, companies must evaluate and use them strategically to maintain competitiveness. However, the intangible and complex nature of data makes objective valuation difficult. The proposed methodology categorizes data value determinants into two groups: essential value factors (completeness, accuracy, uniqueness, and consistency) and value-of-use factors (risk, timeliness, restrictive use, accessibility, and utility). This study analyzes the impact of each factor on the data value using quantitative methods. A regression analysis reveals the influence, interactions, and relative importance of these determinants. A real-world case study on the “Papers with Code” platform—widely used in machine learning research—demonstrates the methodology in practice. The results indicate that essential value factors, such as Percentage Correct and Task, have the strongest positive effect on data value, which underscores the importance of accuracy and relevance to specific applications. In contrast, factors such as Similar Datasets and Benchmarks reduce the data value, which highlights the need for uniqueness and differentiation in determining the value of a company’s data assets. This study provides practical guidelines for companies on the key factors to focus on when evaluating and managing data value. This study offers practical guidance on prioritizing value-related factors and enables more effective investment and utilization strategies. By addressing current limitations in data valuation and presenting a new approach, this study enhances data-driven decision-making and strengthens its associated competitive advantage. Full article

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

► Show Figures

Figure 1

30 pages, 2851 KiB

Open AccessArticle

Modernizing Small and Medium-Sized Enterprises: A Lean Audit Model for Digital Integration

by María Jesús Ávila-Gutiérrez, Antonio Córdoba-Roldán, Pablo Morato-Huerta and Juan Ramón Lama-Ruiz

Systems 2025, 13(4), 304; https://doi.org/10.3390/systems13040304 - 21 Apr 2025

Abstract

This study proposes an audit model to modernize artisanal manufacturing companies and facilitate their transition to Industry 4.0. Based on Lean Manufacturing, Lean Thinking, and Lean Management principles, the model enhances operational efficiency and competitiveness while considering the resource constraints of Small and [...] Read more.

This study proposes an audit model to modernize artisanal manufacturing companies and facilitate their transition to Industry 4.0. Based on Lean Manufacturing, Lean Thinking, and Lean Management principles, the model enhances operational efficiency and competitiveness while considering the resource constraints of Small and Medium-Sized Enterprises (SMEs). It provides a structured approach to identifying key improvement areas and guiding digital transformation. The research follows a four-phase methodology: (1) a company assessment questionnaire to diagnose the current state, (2) a method matrix to analyze improvement strategies, (3) a dimension map to structure key transformation areas, and (4) prioritization of improvement dimensions to define a tailored action plan. A case study in an SME validated its applicability. Findings show that the model helps identify critical improvement factors and implement targeted Lean interventions, enhancing Industry 4.0 readiness. It enables a progressive adoption of digital enablers while optimizing traditional manufacturing processes. The originality of this study lies in its integrated auditing framework, structured around four dimensions and twelve key factors. It introduces a 48-question assessment tool, methods matrices, and prioritization mechanisms. Additionally, it defines four strategic development stages—Readiness, Start-up, In-transition, and Advanced—providing a roadmap for continuous improvement in SMEs. Full article

(This article belongs to the Special Issue Digital Innovation and Business Model Transformation in Small- and Medium-Sized Enterprises)

► Show Figures

Figure 1

30 pages, 7693 KiB

Open AccessArticle

Analyzing New Operation Strategy of Demand-Responsive Transports Using Discrete-Event Simulation Framework

by Seung-Wan Cho, Yeong-Hyun Lim, Seong-Hyeon Ju and Kyung-Min Seo

Systems 2025, 13(4), 303; https://doi.org/10.3390/systems13040303 - 21 Apr 2025

Abstract

Demand-responsive transport (DRT) provides flexible ride-sharing by dynamically adjusting routes based on real-time user demand, making it suitable for complex urban mobility needs. This study proposes a modular simulation framework based on the DEVS (Discrete Event System Specification) formalism and introduces an “express [...] Read more.

Demand-responsive transport (DRT) provides flexible ride-sharing by dynamically adjusting routes based on real-time user demand, making it suitable for complex urban mobility needs. This study proposes a modular simulation framework based on the DEVS (Discrete Event System Specification) formalism and introduces an “express service” strategy that enables direct trips without intermediate stops. The framework supports scenario-based analysis using key performance indicators (KPIs) and allows for flexible testing of operational strategies. Two experiments were conducted: the first validated the simulation model under varying demand and fleet conditions; and the second assessed the impact of the express service. Results showed that express passengers experienced significantly shorter waiting and riding times, while standard passenger service remained stable. The strategy also improved operational efficiency under constrained resources. This study contributes to a configurable simulation platform for evaluating differentiated DRT services and provides practical insights for adaptive service planning, especially in urban settings where tiered mobility solutions are increasingly needed. Full article

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

► Show Figures

Figure 1

19 pages, 601 KiB

Open AccessArticle

Understanding Teachers’ Adoption of AI Technologies: An Empirical Study from Chinese Middle Schools

by Jin Zhao, Siyi Li and Jianjun Zhang

Systems 2025, 13(4), 302; https://doi.org/10.3390/systems13040302 - 21 Apr 2025

Abstract

The advancements in artificial intelligence (AI) technologies and the implementation of government policies are accelerating educational reform in China. In this context, understanding the critical factors influencing middle school teachers’ adoption of AI technologies for classroom instruction is essential for fostering the deep [...] Read more.

The advancements in artificial intelligence (AI) technologies and the implementation of government policies are accelerating educational reform in China. In this context, understanding the critical factors influencing middle school teachers’ adoption of AI technologies for classroom instruction is essential for fostering the deep integration of these technologies into teaching and improving teaching efficiency in middle schools. Grounded in the structural equation model (SEM) approach, this research integrates the Innovation Diffusion Theory, the Technology Acceptance Model (TAM), and the Unified Theory of Acceptance and Use of Technology (UTAUT), and proposes a structural model comprising 10 latent variables. A measurement model is then developed for each latent variable, forming the basis of a survey questionnaire. Through empirical research using the questionnaires of 202 middle school teachers, a validated structural equation model with strong model fitting is established. The findings indicate that the most influential factors positively affecting teachers’ willingness to use AI technologies, in descending order, are Interpersonal Relationships, Innovativeness, Mass Media, Compatibility, Perceived Usefulness, and Perceived Ease of Use. Similarly, factors positively influencing teachers’ actual usage behavior, ranked by impact, include teachers’ willingness, Facilitating Conditions, Career Aspiration, and Perceived Usefulness. Results involving the impact of teachers’ Interpersonal Relationships can update the theoretical understanding of the factors driving the integration of AI into teaching, and be used to put forward specific directions such as social network embedding for actionable practice recommendations. Full article

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

► Show Figures

Figure 1

42 pages, 4070 KiB

Open AccessArticle

The Coordinated Relationship Between the Tourism Economy System and the Tourism Governance System: Empirical Evidence from China

by Ning Wang and Gangmin Weng

Systems 2025, 13(4), 301; https://doi.org/10.3390/systems13040301 - 19 Apr 2025

Abstract

The development of tourism governance (TG) is influenced by the tourism economy (TE), and the development of TE is guaranteed by tourism governance. This study investigates the development levels of the tourism economy and tourism governance, as well as their interactive coordination in [...] Read more.

The development of tourism governance (TG) is influenced by the tourism economy (TE), and the development of TE is guaranteed by tourism governance. This study investigates the development levels of the tourism economy and tourism governance, as well as their interactive coordination in 31 Chinese provinces (including municipalities and autonomous regions) from 2012 to 2021. First, the vertical and horizontal differentiation method was employed to measure tourism economy and tourism governance development levels. Second, the Panel Vector Autoregression (PVAR) model was adopted to examine the Granger causality and the interactive effects between the tourism economy and tourism governance. Third, the coupled coordination model, kernel density estimation, and Markov chain model were combined to explore the degree of coordinated development and the spatio-temporal evolutionary trend of TE-TG. The findings reveal the following: (1) The development level of the tourism economy exhibits a fluctuating upward trend, with its spatial distribution pattern demonstrating a distinct coastal-to-inland decreasing gradient. Meanwhile, tourism governance shows a steady improvement trajectory marked by significant regional disparities. (2) A long-term equilibrium relationship has been established between the tourism economy and tourism governance, with bidirectional Granger causality observed between the two systems. (3) The coupled coordination between the tourism economy and tourism governance has progressively increased. However, the development level of tourism governance still lags behind that of the tourism economy. The eastern and central regions demonstrate significantly higher TE-TG coordination levels compared to the western and northeastern regions. Full article

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

► Show Figures

Figure 1

20 pages, 661 KiB

Open AccessArticle

Digital Entrepreneurial Orientation, Technology Absorptive Capacity, and Digital Innovation on Business Performance

by Sung Hee Jang and Chang Won Lee

Systems 2025, 13(4), 300; https://doi.org/10.3390/systems13040300 - 19 Apr 2025

Abstract

The purpose of this study was to investigate the factors affecting digital entrepreneurial orientation, technology absorptive capacity, and digital innovation in business performance. To achieve the purpose of research, digital entrepreneurial orientation, technology absorptive capacity, digital innovation, and business performance (financial and technological [...] Read more.

The purpose of this study was to investigate the factors affecting digital entrepreneurial orientation, technology absorptive capacity, and digital innovation in business performance. To achieve the purpose of research, digital entrepreneurial orientation, technology absorptive capacity, digital innovation, and business performance (financial and technological performance) were chosen as research variables to explore the relationship effects and medicating effects. Industry type variable was selected to examine moderating effect. Industry type, employees’ numbers, and sales volumes were used as control variables to identify compounding effects of variables. A survey questionnaire was developed, and the proposed model was analyzed to target 122 small and medium venture enterprises (SMEs) in Republic of Korea. Smart PLS 4.0 and SPSS 27.0 were utilized to derive the study results as follows. First, digital entrepreneurial orientation and technology absorptive capacity have a positive influence on digital innovation. Second, digital entrepreneurial orientation has a positive impact on technology absorptive capacity. Finally, digital innovation has a positive effect on financial and technological business performance. The results of this study provide strategic implications for digital innovation and business performance for firms pursuing digital transformation. Therefore, firm managers should prioritize digital entrepreneurial orientation and technology absorptive capacity to improve business performance. Full article

► Show Figures

Figure 1

27 pages, 6390 KiB

Open AccessArticle

Resilience Analysis of Seaport–Dry-Port Network in Container Transport: Multi-Stage Load Redistribution Dynamics Following Cascade Failure

by Zhigang Lu and Wenhao Qiu

Systems 2025, 13(4), 299; https://doi.org/10.3390/systems13040299 - 19 Apr 2025

Abstract

Container shipping networks are vulnerable to cascading failures due to seaport disruptions, underscoring the need for resilient multimodal transport systems. This study proposes a cascading failure model for the seaport–dry-port network in container transport, incorporating a multi-stage load redistribution strategy (CM-SDNCT-MLRS) to enhance [...] Read more.

Container shipping networks are vulnerable to cascading failures due to seaport disruptions, underscoring the need for resilient multimodal transport systems. This study proposes a cascading failure model for the seaport–dry-port network in container transport, incorporating a multi-stage load redistribution strategy (CM-SDNCT-MLRS) to enhance network resilience. Extending the Motter–Lai framework, the model introduces multiple port state transitions and accounts for uncertainties in load redistribution, tailoring it to the cascading failure dynamics of SDNCT. Using empirical data from China’s coastal port system, the proposed MLRS dynamically reallocates loads through dry-port buffering, neighboring seaport sharing, and port skipping. This strategy effectively contains cascading failures, mitigates network efficiency losses, and protects major seaports while reducing mutual disruptions. Resilience analysis demonstrates that the network exhibits scale-free properties, with its resilience being highly sensitive to random port failures and critical port vulnerabilities. The experimental results highlight the pivotal role of dry ports, where operational numbers influence resilience more significantly than capacity. In addition, the study identifies the optimal port-skipping probability that mitigates cascading disruptions. These findings provide valuable insights for port management and logistics planning, contributing to the development of more resilient container transport networks. Full article

(This article belongs to the Topic Digital Technologies in Supply Chain Risk Management)

► Show Figures

Figure 1

27 pages, 1300 KiB

Open AccessArticle

Organizational Work System as the Predictor of Creative Performance: A New Approach to the Learning Method System of Comprehensive Systems and Expansion of Research Field

by Zhiliang Lyu, Chengao Zhang and Xiu Jin

Systems 2025, 13(4), 298; https://doi.org/10.3390/systems13040298 - 18 Apr 2025

Abstract

Previous researchers have questioned and attempted to verify whether the association between organizational work system and individual and organizational performance indicates causality. A work system is a comprehensive concept; it may be of various types, and gaps exist between the type of organizational [...] Read more.

Previous researchers have questioned and attempted to verify whether the association between organizational work system and individual and organizational performance indicates causality. A work system is a comprehensive concept; it may be of various types, and gaps exist between the type of organizational work system and performance. To fill these gaps, we investigated the causal relationship between how a high-performance work system improves creative performance via work involvement through social exchange theory, expectancy theory, and the ability–motivation and opportunity framework. Therefore, we established an amalgamated research framework that uses the moderated mediation model of learning method system of comprehensive systems to facilitate creative performance. To verify the above, this study conducted an empirical study targeting 315 organizational members working in Chinese small and medium-sized enterprises (SMEs). For empirical analysis, we utilized SPSS Macro Process, AMOS, and SmartPLS 4 Program. We found that high-performance work systems significantly improve work involvement and creative performance. Additionally, work involvement acts as a mediator between high-performance work systems and creative performance. However, the moderating effect of the learning method system of comprehensive systems was not significant. Overall, this research was conducted in consideration of the fact that there is a considerable lack of empirical research verifying the relationship between high-performance work systems and creative performance that promotes survival and competitiveness for SMEs. In addition, the learning method system of comprehensive system has not been studied actively and it was utilized with the expectation that it would be a variable that would receive new attention through this study. Finally, this research is expected to contribute to the research fields of SMEs and organizational work systems. Full article

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

► Show Figures

Figure 1

36 pages, 1370 KiB

Open AccessArticle

Local Digital Economic Growth, Enterprise Digital Transformation, and Digital Dividends: Evidence from China

by Yunqi Yang and Grace T. R. Lin

Systems 2025, 13(4), 297; https://doi.org/10.3390/systems13040297 - 18 Apr 2025

Abstract

Achieving digital transformation in enterprises is vital for advancing the digital economy. Using the World Bank’s China Enterprise Survey data, this study investigates how local digital economic growth impacts enterprise transformation. Findings suggest that higher local digital growth significantly boosts enterprise transformation, thereby [...] Read more.

Achieving digital transformation in enterprises is vital for advancing the digital economy. Using the World Bank’s China Enterprise Survey data, this study investigates how local digital economic growth impacts enterprise transformation. Findings suggest that higher local digital growth significantly boosts enterprise transformation, thereby improving short-term operations and long-term innovation. Remarkably, threshold regression reveals a stronger impact on larger enterprises and those with higher human capital. Additional analyses demonstrate that effective access to digital dividends enhances enterprises’ production, R&D, and management. These results offer guidance for local governments, supporting digital shifts and helping enterprises tailor transformation strategies. Full article

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

► Show Figures

Figure 1

37 pages, 18181 KiB

Open AccessArticle

Smart Cities in the Global Context: Geographical Analyses of Regional Differentiations

by Kabeer Saleh Tijjani, Yasemin Sarıkaya Levent and Tolga Levent

Systems 2025, 13(4), 296; https://doi.org/10.3390/systems13040296 - 17 Apr 2025

Abstract

The increasing urbanisation and technological advancements have driven the global adoption of smart city initiatives, yet regional differences persist due to economic, social, and technological disparities. Despite the numerous studies on smart cities, there remains a research gap in comprehensive global analyses exploring [...] Read more.

The increasing urbanisation and technological advancements have driven the global adoption of smart city initiatives, yet regional differences persist due to economic, social, and technological disparities. Despite the numerous studies on smart cities, there remains a research gap in comprehensive global analyses exploring regional differentiations in smart city development. This study aims to examine how smart cities differentiate, especially through associations between regions and smart city dimensions. This study utilises data from the IMD Smart City Index 2023 and applies a multi-step methodology based on the United Nations’ geographic regions, employing geographical and statistical analyses. The findings reveal distinct regional differentiations, highlighting a clear Global North–South divide and notable subregional differentiations, including the North–South divide in the Americas and the East–West divide in Asia. The correlation analysis demonstrates significant relationships between smart city dimensions, with smart mobility and smart living exhibiting the highest association. The correspondence analysis further identifies four major regional concentration groups, notably the Global North, with equi-distant associations with all dimensions, and Asia, which is closely linked to smart governance. The findings confirm that smart city development is not uniform and is shaped by regional socio-economic and technological conditions and emphasises the need for context-dependent regional policies. Full article

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

► Show Figures

Figure 1

22 pages, 879 KiB

Open AccessArticle

Breaking Down the Barriers to Innovation Quality: The Impact of Digital Transformation

by Mengmeng Meng, Siyao Fan, Jiasu Lei and Yinbo Feng

Systems 2025, 13(4), 295; https://doi.org/10.3390/systems13040295 - 17 Apr 2025

Abstract

While the influence of digital technologies on firms’ innovation performance has been examined in the digital transformation literature, the mechanism by which digital transformation affects innovation quality has remained largely unexplored. By analyzing a longitudinal sample of 17,216 China’s A-share listed companies from [...] Read more.

While the influence of digital technologies on firms’ innovation performance has been examined in the digital transformation literature, the mechanism by which digital transformation affects innovation quality has remained largely unexplored. By analyzing a longitudinal sample of 17,216 China’s A-share listed companies from 2009 to 2021 (excluding real estate and financial firms), we employed a fixed-effects regression model to investigate the impact of digital transformation on strategic risk-taking behavior. The findings indicate that digital transformation significantly enhances innovation quality. Market competition enhances the positive effect of digital transformation on innovation quality. Further analysis reveals that digital transformation has a positive impact on dynamic capability, which in turn mediates the relationship between digital transformation and innovation quality. Furthermore, digital transformation breaks down the barriers to innovation quality by reducing financing costs and financing constraints. These findings have implications for firms’ digital strategy in emerging economies. Full article

► Show Figures

Figure 1

42 pages, 2328 KiB

Open AccessArticle

A Blockchain-Driven Cyber-Systemic Approach to Hybrid Reality

by Massimiliano Pirani, Alessandro Cucchiarelli, Tariq Naeem and Luca Spalazzi

Systems 2025, 13(4), 294; https://doi.org/10.3390/systems13040294 - 17 Apr 2025

Abstract

Hybrid Reality (HyR) is the place where human beings and artificial entities interact. HyR modelling relies simultaneously on the cognitive power of humans and artificial entities. In addition, HyR is an evolving paradigm where natural and artificial intelligence can intervene in processes that [...] Read more.

Hybrid Reality (HyR) is the place where human beings and artificial entities interact. HyR modelling relies simultaneously on the cognitive power of humans and artificial entities. In addition, HyR is an evolving paradigm where natural and artificial intelligence can intervene in processes that demand proper control. This work aims to lay the foundation for a systematic approach to understanding and modeling present and future human–machine symbiosis under a systems engineering perspective. It introduces a novel cyber-systemic methodology for managing the engineering of purposeful regulation for HyR phenomena by integrating the Blockchain technology framework and principled methods of cybernetics. This formalized interdisciplinary methodology integrates system dynamics, agent-based computation, artificial intelligence, and Blockchain-powered security and safety layers. The Blockchain framework, seen under a new cyber-systemic perspective, provides new opportunities and tools for the organization and control of HyR. A Cybersystemic Security Kit is here defined as a major component of the methodology, representing a candidate to offer viable breakthroughs in the field with respect to the best practices of Industry 5.0 when a systemically augmented perspective is adopted. Ongoing research and experimentation in the real field of sustainable supply chains is used as a motivating use case to support the proposed position. The industrial target is the primary one in its multi-dimensional and multi-faceted sustainability impacts, but this study will also reveal other potential societal areas of intervention. Full article

(This article belongs to the Special Issue CyberSystemic Transformations for Social Good)

► Show Figures

Figure 1

27 pages, 3166 KiB

Open AccessArticle

Can Government Incentive and Penalty Mechanisms Effectively Mitigate Tacit Collusion in Platform Algorithmic Operations?

by Yanan Wang and Yaodong Zhou

Systems 2025, 13(4), 293; https://doi.org/10.3390/systems13040293 - 16 Apr 2025

Abstract

Algorithmic collusion essentially constitutes a form of monopolistic agreement that utilizes algorithms as tools for signaling collusion, making it particularly challenging for both consumers and antitrust enforcement agencies to detect. Algorithmic collusion can be primarily categorized into two distinct types: explicit collusion and [...] Read more.

Algorithmic collusion essentially constitutes a form of monopolistic agreement that utilizes algorithms as tools for signaling collusion, making it particularly challenging for both consumers and antitrust enforcement agencies to detect. Algorithmic collusion can be primarily categorized into two distinct types: explicit collusion and tacit collusion. This paper specifically investigates the phenomenon of platform-driven tacit algorithmic collusion within the platform economy. Employing an evolutionary game theory approach, we conduct a comprehensive simulation analysis of the economic system involving four key stakeholders: government regulators, platform operators, in-platform merchants, and consumers. This paper primarily investigates the conditions that may reduce the likelihood of platforms engaging in algorithmic tacit collusion, examines how government incentive–penalty mechanisms influence such collusive behaviors, and provides an in-depth analysis of the critical roles played by both in-platform merchants and consumers in detecting and exposing these practices. Full article

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

► Show Figures

Figure 1

28 pages, 3658 KiB

Open AccessArticle

Extended Application of Double Machine Learning in Corporate Financial Resilience Research: Based on Data Factor Marketization

by Fangzhou Song, Yang Huang and Chengkun Liu

Systems 2025, 13(4), 292; https://doi.org/10.3390/systems13040292 - 16 Apr 2025

Abstract

Corporate financial resilience and its integration with institutional reforms play a crucial role in promoting organizational sustainability in the digital economy. Previous research has predominantly focused on internal determinants of corporate financial resilience. However, it has paid limited attention to the role of [...] Read more.

Corporate financial resilience and its integration with institutional reforms play a crucial role in promoting organizational sustainability in the digital economy. Previous research has predominantly focused on internal determinants of corporate financial resilience. However, it has paid limited attention to the role of external institutional factors. This gap is particularly evident in the context of data factor marketization (DFM). We addressed this gap by investigating the impact of DFM on corporate financial resilience, drawing on resource dependence theory (RDT) to highlight the importance of the external policy environment and inter-organizational resource exchange. We employed a double machine learning (DML) framework to assess corporate financial resilience using comprehensive panel data from Chinese listed firms. This approach overcomes the limitations of traditional econometric methods by allowing nonlinear interactions and high-dimensional controls. The results show that DFM significantly enhances corporate financial resilience, with its impact varying across different institutional contexts. Additionally, firm characteristics moderate this relationship. Specifically, ownership structure strengthens or weakens the positive effect of DFM, while industry competition and geographical location have varying effects on resilience outcomes. We offered novel theoretical insights and practical guidance for policymakers seeking to leverage institutional reforms to enhance financial resilience within an increasingly volatile and uncertain business landscape. Full article

(This article belongs to the Special Issue Sustainable Business Models and Digital Transformation)

► Show Figures

Figure 1

28 pages, 584 KiB

Open AccessArticle

Pathway to Smart Aviation: Identifying and Prioritizing Key Factors for Smart Aviation Development Using the Fuzzy Best–Worst Method

by Fei Gao and Weikai He

Systems 2025, 13(4), 291; https://doi.org/10.3390/systems13040291 - 15 Apr 2025

Abstract

Smart aviation has received significant attention from various stakeholders in China as its advancement holds crucial implications for the aviation industry, and there is a growing need for aviation authorities to assess the extent of its development. The evaluation of smart aviation development [...] Read more.

Smart aviation has received significant attention from various stakeholders in China as its advancement holds crucial implications for the aviation industry, and there is a growing need for aviation authorities to assess the extent of its development. The evaluation of smart aviation development processes rely on various factors that reflect the smart aviation development level, and these factors could help pave the way for the successful development of smart aviation. However, few studies have focused on the identification and prioritization of the key factors for smart aviation development, especially considering the uncertain nature of the problem. To this end, this study employs the grounded theory and the fuzzy best–worst method (BWM) to identify and prioritize the factors for smart aviation development. Through the utilization of grounded theory, 37 factors are determined to be critical for smart aviation development. Then, the fuzzy BWM is employed to evaluate and prioritize the identified factors considering their importance. The findings of this study reveal that the 4D track development level, proportion of R&D investment, and data resources sharing degree are the most influential factors for smart aviation development. By integrating grounded theory, fuzzy sets, and BWM, this study identifies and prioritizes the significant factors for smart aviation for the first time. In general, the outcomes of this study hold the potential to guide practitioners in focusing on the pivotal factors that contribute to smart aviation development. Full article

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

► Show Figures

Figure 1

Journal Description

Systems

Latest Articles

Journal Menu

Journal Browser

Highly Accessed Articles

Latest Books

E-Mail Alert

News

Topics

Conferences

Special Issues

Topical Collections

Further Information

Guidelines

MDPI Initiatives

Follow MDPI