Systems

18 pages, 1357 KiB

Open AccessArticle

When Environmental, Social, and Governance (ESG) Meets Shareholder Value: Unpacking the Long-Term Effects with a Multi-Period Difference-in-Differences (DID) Approach

by Yong Zhou and Wei Bu

Systems 2025, 13(5), 315; https://doi.org/10.3390/systems13050315 - 25 Apr 2025

Abstract

As environmental, social, and governance (ESG) concerns increasingly shape corporate behavior, understanding their financial implications remains critical. This study investigates the impact of ESG performance on shareholder value, focusing on the mediating role of dividend policy. A multi-period difference-in-differences (DID) approach is applied [...] Read more.

As environmental, social, and governance (ESG) concerns increasingly shape corporate behavior, understanding their financial implications remains critical. This study investigates the impact of ESG performance on shareholder value, focusing on the mediating role of dividend policy. A multi-period difference-in-differences (DID) approach is applied to panel data from Chinese A-share listed firms between 2011 and 2022 to address endogeneity and establish causal inference. The empirical findings indicate that strong ESG performance significantly enhances shareholder value and that dividend policy is a credible transmission mechanism by signaling financial stability and governance quality. Heterogeneity analysis reveals that the magnitude of the ESG effect is further shaped by firm size, profitability, and ownership concentration, with larger, more profitable, and less concentrated firms benefiting more. Industry-level analysis reveals stronger ESG effects in capital- and technology-intensive sectors, with comparatively minor effects in labor-intensive industries. These results extend the literature by clarifying how ESG translates into financial value and by identifying contextual conditions that amplify or attenuate its impact. The findings also offer practical insights for aligning ESG strategies with financial policies and tailoring sustainability regulation to organizational and industry-specific dynamics. Full article

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

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24 pages, 1285 KiB

Open AccessArticle

Characterizing Efficacy of Alternative Media for Requirements Expression

by Jason Kolligs and Lawrence Dale Thomas

Systems 2025, 13(5), 314; https://doi.org/10.3390/systems13050314 - 25 Apr 2025

Abstract

Requirements are most commonly expressed in natural language, but alternative media can be employed. Previous research has established the viability of model diagrams and engineering drawings for requirements expression. To move beyond viability, three (3) factors—Cognition, Quality, and Accountability—were developed to assess the [...] Read more.

Requirements are most commonly expressed in natural language, but alternative media can be employed. Previous research has established the viability of model diagrams and engineering drawings for requirements expression. To move beyond viability, three (3) factors—Cognition, Quality, and Accountability—were developed to assess the potential impact of using alternate media requirement expressions in systems engineering. The alternate media candidates were evaluated against the factors and their subfactors, which determined that the inclusion of alternate media may be expected to positively impact requirements expression in all three areas. For Cognition, improved communication is predicted as alternate media are situationally preferable based on their inherent context offerings and systematically shorter comprehension times for spatial information, which potentially reduces the cognitive burden on the reader. For Quality, alternate media are predicted to improve the appropriateness of requirement expressions within a specification. For Accountability, improvement is predicted within a project as alternate media can mitigate ambiguity, improve feasibility, and enhance verification and validation efforts. The contribution of this research is the establishment of a conceptual basis for creating multi-media requirement documentation that amplifies the desired characteristics of requirement expressions to better communicate stakeholder information. Full article

(This article belongs to the Section Systems Engineering)

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34 pages, 1125 KiB

Open AccessArticle

Emission Reduction Decisions in the Agricultural Supply Chain Considering Dual Fairness Concerns

by Huanhuan Wang, Qilan Zhao, Hanxing Cui, Junjie Guo and Qiuxia Zhang

Systems 2025, 13(5), 313; https://doi.org/10.3390/systems13050313 - 24 Apr 2025

Abstract

The challenges in reducing emissions within agricultural supply chains mainly arise from the short-term self-interested behaviors of various stakeholders. To study the impact of the agricultural producer’s dual fairness concerns toward the manufacturer and retailer on profit distribution and emission reduction decisions, this [...] Read more.

The challenges in reducing emissions within agricultural supply chains mainly arise from the short-term self-interested behaviors of various stakeholders. To study the impact of the agricultural producer’s dual fairness concerns toward the manufacturer and retailer on profit distribution and emission reduction decisions, this paper develops a centralized model and two decentralized models (with and without dual fairness concerns) for a three-level agricultural supply chain. The paper derives the optimal emission reduction decisions, participant profits, and overall supply chain profits under different decision-making scenarios. The main findings are as follows: First, the centralized model results in higher supply chain profit, emission reduction, and market demand compared to decentralized models, where these factors remain unchanged regardless of fairness concerns. Second, in decentralized decision-making, fairness concerns raise the agricultural producer’s profit while reducing those of the manufacturer and retailer. The manufacturer always earns the highest profit, followed by the retailer. Finally, the agricultural producer’s fairness concerns do not affect emission reduction or overall profit, but they change profit distribution, with increasing concern toward one participant decreasing their profit and increasing the other’s. These findings fill the theoretical gap in existing research and provide valuable theoretical insights for governments and stakeholders in making decisions. Full article

(This article belongs to the Special Issue Systems Approaches in Sustainable Logistics and Supply Chain Management)

29 pages, 1949 KiB

Open AccessArticle

A MapReduce-Based Decision-Making Approach for Multiple Criteria Sorting

by Xiaoxin Mao, Zhanhe Du and Lanlan Zheng

Systems 2025, 13(5), 312; https://doi.org/10.3390/systems13050312 - 24 Apr 2025

Abstract

In the context of big data and artificial intelligence, analyzing and extracting actionable insights from extensive datasets to enhance decision-making processes presents both intriguing opportunities and formidable challenges. Existing multiple criteria sorting (MCS) methodologies often struggle with the magnitude of these datasets, particularly [...] Read more.

In the context of big data and artificial intelligence, analyzing and extracting actionable insights from extensive datasets to enhance decision-making processes presents both intriguing opportunities and formidable challenges. Existing multiple criteria sorting (MCS) methodologies often struggle with the magnitude of these datasets, particularly in terms of time and memory requirements. Furthermore, traditional approaches typically rely on direct preference information, which can be cognitively demanding for decision-makers and may not scale effectively with increasing data complexity. This study introduces a scalable MCS approach grounded in the MapReduce framework, designed to handle extensive sets of alternatives and preference information in a parallel processing paradigm. The proposed approach utilizes an additive piecewise-linear value function as the underlying preference model, with model parameters inferred from assignment examples on a subset of reference alternatives through the application of preference disaggregation principles. To enable the parallel execution of the sorting procedure, a convex optimization model is formulated to estimate the parameters of the preference model. Subsequently, a parallel algorithm is devised to solve this optimization model, leveraging the MapReduce framework to process the set of reference alternatives and associated preference information concurrently, thereby accelerating computational efficiency. Additionally, the performance of the proposed approach is evaluated using a real-world dataset and a series of synthetic datasets comprising up to 400,000 alternatives. The findings demonstrate that this approach effectively addresses the MCS problem in the context of large sets of alternatives and extensive preference information. Full article

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

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13 pages, 317 KiB

Open AccessArticle

Synchronization and Patterns in Human Dynamics

by Franco Orsucci and Wolfgang Tschacher

Systems 2025, 13(5), 311; https://doi.org/10.3390/systems13050311 - 24 Apr 2025

Abstract

We examine couplings, synchronization, pattern formation, and transformation in human dynamics. We consider intraindividual and interpersonal relations as coevolution dynamics of heterogeneous mixed couplings, synchronizations, and desynchronizations. They form the dynamic patterns of the embodied Self and organize intersubjective dynamics. We critically review [...] Read more.

We examine couplings, synchronization, pattern formation, and transformation in human dynamics. We consider intraindividual and interpersonal relations as coevolution dynamics of heterogeneous mixed couplings, synchronizations, and desynchronizations. They form the dynamic patterns of the embodied Self and organize intersubjective dynamics. We critically review various models with differing levels of complexity and degrees of freedom. The Fokker–Planck equation clarifies the balance between determinism and stochasticity. The HKB and Kuramoto models describe complex synchronization and pattern formation dynamics. Chimera states are ubiquitous in the mixed networks of human dynamics. Coupling, synchronization, and patterns form and transform, with gaps in between. We propose a formal model for these complex, mixed, and heterogeneous dynamics. Multidimensional theoretical models can represent the specific nature of human interactions and the dynamic structure of the embodied Self. The embodied Self emerges during a developmental process and retains its dynamical nature by continuously adapting to the ever-changing landscape of affordances of daily life. Full article

(This article belongs to the Special Issue Theoretical Issues on Systems Science)

20 pages, 4571 KiB

Open AccessArticle

Crowd Evacuation Dynamics Under Shooting Attacks in Multi-Story Buildings

by Dianhan Chen, Peng Lu, Yaping Niu and Pengfei Lv

Systems 2025, 13(5), 310; https://doi.org/10.3390/systems13050310 - 23 Apr 2025

Abstract

Mass shootings result in significant casualties. Due to the complexity of buildings, capturing crowd dynamics during mass shooting incidents is particularly challenging. Therefore, it is necessary to study crowd dynamics and the key mechanisms of mass shooting incidents and explore optimal building design [...] Read more.

Mass shootings result in significant casualties. Due to the complexity of buildings, capturing crowd dynamics during mass shooting incidents is particularly challenging. Therefore, it is necessary to study crowd dynamics and the key mechanisms of mass shooting incidents and explore optimal building design solutions to mitigate the damage caused by terrorist attacks and enhance urban safety. In this study, we focused on the Bataclan Shooting (13 November 2015) as the target case. We used an agent-based model (ABM) to model both the attacking force (shooting) and counterforce (anti-terrorism response). According to the real situation, the dynamic behavior of three types of agents (civilians, police, and shooters) during the shooting accident was modeled to explore the key mechanism of individual behavior. Taking civilian casualties, police deaths, and shooter deaths as the real target values, we obtained combinations for optimal solutions fitting the target values. Under the optimal solutions, we verified the effectiveness and robustness of the model. We also used artificial neural networks (ANNs) to detect the predictive stability of the ABM model’s parameters. In addition, we studied the counterfactual situation to explore the impact of police anti-terrorism strategies and building exits on public safety evacuation. The results show that for the real cases, the optimal anti-terrorism size was four police and the optimal response time was 40 ticks. For double-layer buildings, it was necessary to set exits on each floor, and the uniform distribution of exits was conducive to evacuation under emergencies. These findings can improve police patrol routes and the location of police stations and promote the creation of public safety structures, enhancing the urban emergency response capacity and the level of public safety governance. Full article

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

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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)

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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 - 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)

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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)

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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)

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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)

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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)

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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)

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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)

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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)

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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

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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)

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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)

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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)

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