Social Science and Management (SSM) is an international peer-reviewed, open access journal.
AN INTEGRATED PROCESS-MINING AND EXPLAINABLE MACHINE-LEARNING FRAMEWORK FOR BOTTLENECK AND INTERNAL-CONTROL RISK DETECTION IN THE MULTI-ENTITY FINANCIAL CLOSE
The financial close of a multi-entity group is a recurring, deadline-driven process in which operational congestion and internal-control weaknesses interact, yet the two are normally analysed by separate functions with separate tools. This paper proposes CLOSE-XPM, a framework integrating process mining and explainable machine learning to attribute close-cycle delay to individual record-to-report activities, to flag close instances carrying elevated internal-control risk, and to rank remediation actions against both objectives at once. Two contributions are introduced: a cause-aware Bottleneck Contribution Index (BCI-C) that decomposes every pre-activity delay into resource contention, calendar unavailability and residual, then propagates a contention-truncation counterfactual along a per-case critical path, yielding an estimate in calendar days saved; and a screening procedure that estimates the risk effect of capacity and control actions from the event log alone. Because no public financial-close log exists, we build MEFC-Sim, a resource-aware generator (30 entities, 24 periods, 14,187 events) in which weaknesses are injected as behaviour and the outcome depends on variables the log cannot reveal; paired counterfactual re-runs provide an oracle. BCI-C reaches 0.907 rank correlation with the oracle against 0.544 for the best observable baseline, and predicts the attainable reduction within 0.076 days. Risk detection reaches 0.828 AUC across unseen entities with a 2.86-fold lift in the top-20% inspected sample. Delay and control risk are strongly coupled (rho = 0.708): relieving the three dominant bottlenecks shortens the close by 1.70 days and cuts the deficiency rate by 22.7%. A ground-truth fidelity analysis shows that SHAP is faithful to the model but only moderately faithful to the data-generating process. Validation on a real public log of 1,434 cases confirms transferability and identifies a boundary condition: coupling requires waiting time to be contention-driven.
Copyright (c) 2024 YaNan Jiao; YiWen Liang https://creativecommons.org/licenses/by/4.0
EXPLAINABLE SUPPLIER RISK PREDICTION FOR CRITICAL TELECOMMUNICATIONS INFRASTRUCTURE PROCUREMENT: AN EMPIRICAL XGBOOST–SHAP FRAMEWORK
Telecommunications networks are critical national infrastructure, yet their equipment supply base is highly concentrated, so a single supplier failure can propagate into a national service outage. Machine-learning supplier-risk models are increasingly proposed for procurement screening, but they are almost always evaluated on discrimination alone: nobody asks whether the resulting explanations are directionally sensible, whether they survive a model refit, or whether the model actually reduces procurement cost. We present CTI-SRP, a two-tier explainable framework that decomposes supplier risk into financial-viability risk and operational delivery risk, couples a monotonicity-constrained XGBoost learner to exact TreeSHAP attribution, and adds an audit layer with three new explanation-quality metrics — Explanation Coherence Rate (ECR), Local Coherence Rate (LCR) and Monotonicity Violation Rate (MVR) — plus an Explanation Stability Index (ESI) and a cost-sensitive decision layer. Experiments use two real datasets (6,819 listed firms with 95 financial ratios; 180,519 order lines) and a transparently specified synthetic telecom cohort in which the true drivers, signs and interactions are known by construction. Encoding 46 accounting-theory sign priors as monotone constraints raises ECR from 0.870 to 0.978 and drives MVR from 0.345 to exactly zero at no cost in AUC (0.9547→0.9573). TreeSHAP nearly doubles top-5 driver stability over gain importance (Jaccard 0.446 vs 0.247). A leakage audit shows that the near-perfect delivery-risk accuracy reported in prior work collapses from AUC 0.992 to 0.733 once post-shipment features are removed. On the synthetic cohort the pipeline recovers all 16 true drivers with zero false drivers, all three true interactions in the top three, and a 0.953 correlation between true coefficient magnitude and mean |SHAP|. A criticality-weighted composite index captures 62.7% of realised loss within a 10% audit budget, versus 48.2% for probability ranking alone.
Copyright (c) 2024 MengLin Bian; Ying Wang; YiZhen Lin https://creativecommons.org/licenses/by/4.0
THE FOOD SECURITY CONSEQUENCE OF MANDATED EMPLOYMENT ELIGIBILITY VERIFICATION
This study investigated the impact of E-Verify mandates, which make it more difficult for certain undocumented workers to find a new job in the United States, on the food security status of both U.S citizens and non-citizens. Using a Difference in Difference approach and data from CPS’s food security supplements, this study found that even though E-Verify mandates had no significant effects on family income, but they had unintended consequences on households’ food security. E-Verify mandates reduced the food security of both U.S citizens and non-citizens residing in the U.S. The effect was consistent over different sub-types of food security measures.
Copyright (c) 2026 Xia Si https://creativecommons.org/licenses/by/4.0
LLM DEVELOPERS’ PLATFORM‑SIDE INFRINGEMENT RISKS & LEGAL STRATEGIES: EU‑US‑CHINA COMPARISON
The commercial deployment of large language models (LLMs) for automated content generation has exposed developers to unprecedented platform-side infringement liabilities under copyright, data privacy, and tort law. Unlike traditional internet intermediaries that passively host user-uploaded content, LLM developers actively generate outputs through algorithmic inference, rendering existing safe harbor frameworks substantially inadequate. This paper conducts a tri-jurisdictional comparative analysis of platform-side infringement risks for LLM developers in the European Union (EU), United States (US), and China. Through doctrinal legal analysis of the EU AI Act (Regulation 2024/1689), EU Digital Services Act (DSA), US Section 230 jurisprudence and pending federal legislation, and China's Interim Measures for Generative AI (2023), this paper identifies three distinct risk categories: output-side copyright infringement, training data-derived privacy violations, and tort liability for defamatory hallucinations. The EU imposes proactive due diligence obligations on high-risk general-purpose AI systems. The US maintains a fragmented approach, with growing judicial and scholarly consensus that Section 230 immunity does not extend to AI-generated content, though final rulings remain pending. China adopts a strict administrative oversight model requiring algorithm filing and direct developer responsibility. The paper proposes a hybrid legal avoidance matrix integrating technical measures, organizational measures, and contractual measures. The paper concludes that LLM developers should develop jurisdictionally adaptive compliance architectures in the absence of globally harmonized AI regulations.
Copyright (c) 2026 MingLu Ma https://creativecommons.org/licenses/by/4.0
ABSOLUTE DEVOTION AND THE LIFE-AFFIRMING SACRIFICE IN WILLIAM FAULKNER'S A ROSE FOR EMILY AND D. H. LAWRENCE'S THE HORSE DEALER'S DAUGHTER
This essay examines the nature of absolute love and sacrifice in William Faulkner’s A Rose for Emily and D. H. Lawrence’s The Horse Dealer’s Daughter. Through close textual analysis, it argues that both Emily Grierson and Mabel Pervin embody a form of devotion so total that it dismantles self-preservation and social conventions, rendering them paradoxically most alive. While Emily turns inward, preserving the beloved in an eternal present through ritualized care, Mabel moves forward through self-dissolution toward an unknown future shaped by reciprocal sacrifice. Despite their different temporal orientations, both protagonists reject the limits imposed by time and mortality. The essay concludes that love’s deepest significance lies not in its moral justification or outcome, but in the total surrender it demands—an act that becomes the most life-affirming expression available to individuals.
Copyright (c) 2026 Ya Ma https://creativecommons.org/licenses/by/4.0
POPULATION AGEING, INDUSTRIAL RESTRUCTURING, AND THE SILVER ECONOMY: A THEORETICAL AND REGIONAL ANALYSIS OF SHAOXING, CHINA
Population ageing and persistent low fertility are reshaping the development logic of Chinese city-regions, yet their regional implications remain insufficiently explored. This paper examines Shaoxing, a manufacturing-oriented city in Zhejiang Province, to analyze how demographic transition affects regional development through labour supply, dependency burdens, spatial differentiation, and industrial restructuring. The evidence shows that Shaoxing has entered a new stage marked by slowing population growth, negative natural increase, deep ageing, and growing internal divergence. In 2024, the share of the population aged 60 and above reached 31.6%, while population maintenance increasingly depended on migration rather than natural reproduction. To interpret these changes, the paper develops a stylized two-sector model composed of a traditional manufacturing sector and a silver-economy sector. The analysis shows that ageing has a dual effect: it weakens labour-intensive growth by reducing effective labour supply and increasing welfare burdens, while also creating new demand for healthcare, elderly care, rehabilitation, and age-friendly products. The paper argues that ageing in Shaoxing is best understood as a process of regional restructuring rather than merely demographic decline.
Copyright (c) 2026 ChunXiao Cui https://creativecommons.org/licenses/by/4.0
THE SOCIAL ENCODING MECHANISM OF WELL-BEING: A CATEGORICAL TRANSITION FROM PSYCHOLOGICAL INDICATORS TO CULTURAL DISCIPLINARY REGIMES
This study investigates the social encoding mechanisms of happiness, analyzing the paradigm shift from psychological metrics to cultural norms. Through historical tracing, it reveals how the concept of "happiness" has evolved—from ancient philosophical ethical ideals to modern psychological quantification, and ultimately to technical standardized measurements in global governance. The measurement mech, This paper critically examines the measurement systems of happiness, revealing how they not only reduce the diversity of individual emotions but also reinforce mechanisms of inequality and exclusion within social structures. The study further explores the institutionalization pathways of "happiness," introducing the concept of "happiness justice." It advocates for reconstructing the social significance of happiness through critical and pluralistic perspectives, while calling for breaking free from the limitations of existing measurement frameworks to drive reflective reconstruction of both the concept and measurement systems of happiness.
Copyright (c) 2026 ZhenYu Zhao; AiLi Xie; Ran Liu https://creativecommons.org/licenses/by/4.0
THE IMPACT OF ARTIFICIAL INTELLIGENCE ON ENTERPRISE INCOME DISTRIBUTION
As the most representative general technology at present, artificial intelligence is profoundly reshaping the organizational form, operating model and operating mechanism of enterprises, and bringing unprecedented impact to the income distribution structure within enterprises. Therefore, based on the panel data of China's Shanghai and Shenzhen A-share non-financial listed companies from 2010 to 2022, this paper explores whether the development of AI will trigger new changes in the interest pattern between corporate profits and labor compensation. Based on basic theories such as capital-labor substitution principle and factor reward theory, this paper explores how AI can promote enterprises to adopt different income distribution modes by improving marginal output of capital and substituting low-skilled labor from the perspective of technology bias. At the same time, the key factor of financing constraint is considered to hinder the enterprise's choice of technology level, which leads to the change of its corresponding distribution effect. Finally, the group regression is carried out from the two perspectives of the ownership structure and the industry to find the different responses of different types of enterprises to the income distribution changes brought by this new technology. This study attempts to outline the basic picture of the evolution of enterprise income distribution mechanism in the era of artificial intelligence, and also provides certain theoretical support and practical evidence for coordinating the relationship between technological innovation process and social distribution justice.
Copyright (c) 2026 Jiang Zhan; Jianheng Ye; GuoFeng Liang; FanRong Feng https://creativecommons.org/licenses/by/4.0
EFFECTS OF ENGLISH BRAND NARRATIVE ON EMOTIONAL RESONANCE AND PURCHASING BEHAVIOR: A MEDIATING-EFFECT STUDY
Against the backdrop of global brand communication and cross-border consumption, English brand narrative has become an important means for multinational brands and Chinese overseas brands to carry out cross-cultural marketing and build brand identity. Based on the brand narrative theory, emotional marketing theory and consumer behavior theory, this paper divides English brand narrative into four dimensions: story integrity, value delivery, linguistic appeal and cultural adaptability, and constructs a theoretical model of "English brand narrative - emotional resonance - consumers' purchasing behavior". Valid sample data were collected through questionnaire surveys, and empirical research was conducted by using reliability and validity analysis, correlation analysis, regression analysis and Bootstrap mediating effect test. The results show that all four dimensions of English brand narrative have a significant positive impact on consumers' emotional resonance; emotional resonance has a significant positive impact on purchasing behavior; and emotional resonance plays a partial mediating role between English brand narrative and purchasing behavior. The conclusions of this paper enrich the empirical research results in the fields of brand narrative and cross-cultural marketing, and provide practical references for enterprises to optimize their English brand narrative strategies, deepen emotional connections with consumers and improve the transformation of consumption behavior.
Copyright (c) 2026 YanHui He; MingLiang Huang https://creativecommons.org/licenses/by/4.0
THE TRAINING MODE OF APPLIED TALENTS IN THE MAJOR OF BIG DATA MANAGEMENT AND APPLICATION UNDER THE GUIDANCE OF CURRICULUM IDEOLOGICAL AND POLITICAL EDUCATION
Against the backdrop of the in-depth integration of emerging engineering education and curriculum ideological and political education, the major of Big Data Management and Application, a typical interdisciplinary emerging engineering major, needs to break through the limitation of "emphasizing technology over values" in cultivating applied talents. Taking the Introduction to Big Data course as the core starting point, based on the implemented ideological and political construction practice and the systematic content of the teaching syllabus of this course, this paper constructs a four-in-one talent training mode of in-depth integration of "Curriculum Ideological and Political Education + Professional Education" covering "goals-content-practice-evaluation". By exploring ideological and political elements suitable for the professional characteristics, designing case-driven and project-oriented teaching practice paths, and establishing a multi-dimensional quantitative evaluation system, the organic unity of knowledge imparting, ability training and value shaping is realized. This research provides a replicable and promotable practical plan for the cultivation of big data-related professional talents in private application-oriented undergraduate universities.
Curriculum ideological and political education
Copyright (c) 2026 HongYan Li; HongLei Bao; YuShan Gao https://creativecommons.org/licenses/by/4.0
FROM DIGITALIZATION TO SERVITIZATION: UNRAVELING MECHANISMS AND PATHWAYS IN MANUFACTURING FIRM TRANSFORMATION
Manufacturing enterprises are the cornerstone of China’s national economy, and servitization has emerged as a vital pathway for their transformation, upgrading, and high-quality development. In the context of building a manufacturing powerhouse, leveraging digital technologies to enable servitization transformation has become a key strategic focus. This study adopts a bibliometric approach and utilizes CiteSpace to conduct a visual analysis of both domestic and international literature on digitally enabled servitization transformation in manufacturing enterprises. The objective is to clarify the research scope, trace the evolutionary trajectory, and identify regional distributions within the field. Digital empowerment is identified as a current research hotspot. Through keyword co-occurrence and cluster analyses, the study investigates three core research questions: What is digital servitization? Why does digital empowerment matter for servitization transformation? How does it facilitate upgrading? The findings reveal three primary research themes—theoretical foundations, effectiveness, and pathways of digitally enabled servitization—offering a structured overview of the field’s development and contributing to a deeper understanding of its underlying mechanisms. These insights provide valuable guidance for future research and strategic decision-making in manufacturing servitization.
Servitization transformation of manufacturing enterprises
Copyright (c) 2026 RuoYu Chang https://creativecommons.org/licenses/by/4.0
THE SUSTAINABILITY OF DIGITAL MARKETING BASED ON AFRICAN-AMERICAN CONSUMERS-TAKING TIKTOK AMERICAN DISTRICT WIGS AS AN EXAMPLE
Under the background of the deep integration of the global digital economy and cross-border e-commerce, the wig market in the U.S. shows unique growth momentum and market complexity with high reliance on digital marketing. As a typical representative of China's wig industry going overseas, the company has relied on TikTok and other platforms to build a digital marketing ecosystem, achieving an average annual revenue growth of 30% in the U.S. market. Based on a three-dimensional model of economy, environment, and society, this paper analyzes wigs in TikTok's live-broadcast marketing, UGC content segmentation, and green brand narratives. It addresses the challenges of cultural adaptation and traffic involvement faced by African-American consumers. The study finds that accurate, data-driven, localized product development, multi-platform, synergistic omni-channel operations, and social responsibility integration are the core path to digital marketing sustainability. The findings provide theoretical guidance for the digital transformation of cross-border e-commerce companies in culturally sensitive markets and validate the practical value of the "Technology Enablement - Value Symbiosis - Ecological Construction" model.
Copyright (c) 2026 Zhen Zhang; ZhuoXian Hong; JiaHuan Zhang; GuoHui Zhou https://creativecommons.org/licenses/by/4.0
ZHAOQING CITY’S “DUAL-TRANSFORMATION SYNERGY” DEVELOPMENT MECHANISM
Amid the accelerated restructuring of the Guangdong-Hong Kong-Macao Greater Bay Area supply chain network, the competitive advantages of node cities are gradually shifting from factor costs to capability embedding and functional stratification. This study constructs an analytical framework—“supply chain network restructuring—dual transformation synergy—structural leap”—based on system coupling theory. Using entropy weight analysis and the coupling coordination index model, it measures the levels of digitalization and green development and their synergy status across 21 cities in Guangdong Province. Focusing on Zhaoqing City, it identifies its structural potential and the constraints on transformation. Findings reveal a pronounced gradient in Guangdong's dual-transition coordination, with coupling coordination degree ranging from 0.725 to 0.191 on average, forming a pyramid-shaped structure characterized by “core polarization—secondary core transition—peripheral reception.” Shenzhen and Guangzhou form a highly synergistic core zone, while Dongguan and Foshan are in the phase of functional enhancement. Most cities remain in the structural adjustment phase. Zhaoqing exhibits a coupling coordination index of only 0.146, with its digitalization index significantly lower than its greening index, resulting in a structurally asymmetric state of “relative green leadership—marked digital lag.” Its relative gap coefficient is 0.723, indicating a pronounced gradient fault line relative to core cities. From a supply chain embedding perspective, Zhaoqing's insufficient coordination stems from inadequate depth of digital capability embedding and limited spillover absorption capacity. This study provides quantitative evidence to identify the structural positions and transformation pathways of peripheral cities during regional network restructuring.
Copyright (c) 2026 ZiLing Wang; YongXin Peng; LianHua Liu https://creativecommons.org/licenses/by/4.0
GRAPH NEURAL NETWORKS FOR REAL-TIME MALWARE DETECTION IN ENTERPRISE ENVIRONMENTS
The escalating sophistication of malware threats poses unprecedented challenges to enterprise cybersecurity infrastructure. Traditional signature-based detection methods struggle to identify polymorphic and zero-day malware variants that continuously evolve to evade detection mechanisms. This research presents a comprehensive investigation into the application of Graph Neural Networks (GNNs) for real-time malware detection in enterprise environments. By leveraging the structural properties of malware represented as control flow graphs and function call graphs, GNN-based approaches can capture complex behavioral patterns that distinguish malicious software from benign applications. This study examines the theoretical foundations of graph-based malware representation, evaluates state-of-the-art GNN architectures including Graph Convolutional Networks and Graph Attention Networks, and proposes an integrated framework optimized for real-time detection in enterprise settings. Experimental evaluation demonstrates that the proposed approach achieves detection accuracy exceeding 96 percent while maintaining computational efficiency suitable for deployment in production environments. The findings indicate that GNN-based detection systems offer significant advantages over traditional machine learning methods, particularly in identifying previously unseen malware families through structural pattern recognition. This research contributes to the advancement of proactive cybersecurity measures by demonstrating the viability of graph-based deep learning for scalable, real-time threat detection in complex enterprise networks.
Copyright (c) 2025 XinYu Li; Daniel Roberts; Oliver Bennett https://creativecommons.org/licenses/by/4.0
COUNTERFACTUAL REASONING IN SUPPLY CHAIN DISRUPTION PREDICTION: A CAUSAL GRAPH NEURAL NETWORK APPROACH WITH MULTIMODAL EXTERNAL SIGNALS
Supply chain disruptions have emerged as critical challenges in global operations, with economic impacts exceeding trillions of dollars annually. Traditional prediction methods often fail to capture complex causal relationships and counterfactual scenarios essential for proactive risk management. This paper proposes a novel Causal Graph Neural Network (C-GNN) framework that integrates counterfactual reasoning with multimodal external signals for supply chain disruption prediction. The framework leverages directed acyclic graphs to represent causal dependencies among supply chain entities while incorporating diverse data sources including financial indicators, geopolitical events, and environmental factors. Experimental results demonstrate that our approach achieves superior prediction accuracy compared to conventional methods, with the ability to generate actionable counterfactual explanations for potential disruptions. The proposed framework offers supply chain managers interpretable insights for scenario planning and proactive intervention strategies, contributing to enhanced supply chain resilience in increasingly volatile global markets.
Copyright (c) 2025 YuChen Li https://creativecommons.org/licenses/by/4.0
THE PATH OF PSYCHOLOGICAL CAPITAL’S INFLUENCE ON THE SUBJECTIVE SENSE OF SHARED PROSPERITY AMONG RESIDENTS IN HENAN PROVINCE
Shared prosperity, a core goal of Chinese modernization, has expanded from economic indicators to broader social and psychological dimensions. In this context, residents' subjective sense of gain, as a psychological perception of development achievements and fairness, has become essential. This study explores how psychological capital in Henan Province—hope, resilience, optimism, and self-efficacy—affects residents' sense of shared prosperity. Based on social support theory, we hypothesize that social support mediates this relationship. A large-scale survey of 655 residents (588 valid) was analyzed using descriptive statistics, correlation, and regression models. Results show a significant positive link between psychological capital and shared prosperity, both directly and through enhanced social support. These findings enrich the psychological theory of shared prosperity and offer policy insights on promoting residents' well-being and sense of gain through psychological interventions and community building.
Copyright (c) 2025 XiaoBo Yu https://creativecommons.org/licenses/by/4.0
THE IMPLEMENTATION PATHS AND EFFECTIVENESS ANALYSIS OF GREEN LOGISTICS: A CASE STUDY
Against the backdrop of increasingly severe global environmental issues and the deepening advancement of the "Dual Carbon" goals, green logistics, as a crucial pathway to achieving sustainable development, has become an inevitable trend for the transformation of the logistics industry. Green logistics not only emphasizes reducing resource consumption and environmental pollution in logistics activities but also pursues the synergistic development of economic, social, and environmental benefits. In recent years, the Chinese government has intensively issued numerous green logistics policies, promoting the industry's green transformation across all segments, including packaging, transportation, warehousing, and informatization. Concurrently, a growing number of enterprises are actively exploring implementation pathways for green logistics. Through technological innovation, management optimization, and business model innovation, they aim to fulfill environmental responsibilities while enhancing operational efficiency. However, enterprises across different industries and of varying scales still face challenges in path selection, cost control, and technology application during their green logistics practices. Based on theories of sustainable development, stakeholder engagement, and green development, and by integrating literature review and typical case studies, this paper systematically explores the implementation pathways of green logistics and its associated environmental, economic, and social benefits. The findings are intended to provide theoretical reference and practical insights for the green transformation of China's logistics industry.
Copyright (c) 2025 HuiYing Wang; JiaYi Shi; JingYun Shi; ZhongYi Tao https://creativecommons.org/licenses/by/4.0
THE SOCIO-ECONOMIC AND PUBLIC HEALTH IMPACTS OF THE NATIONAL CENTRALIZED DRUG PROCUREMENT POLICY
Purpose: Under the background of the regular implementation of the National Centralized Drug Procurement (NCDP) policy, this study aimed to assess the impacts of the NCDP policy on drug utilization and overall healthcare services in county-level medical institutions, as well as to probe into the influencing factors of changes in drug utilization. Method: A pre-post study was applied using inpatient data from a county-level medical institution in Nanjing. The drug utilization behavior of medical institutions regarding 88 commonly used policy-related drugs (by generic name, including bid-winning and bid-non-winning brands) was analyzed, and the substitution of bid-winning brands for brand-name drugs after policy intervention was evaluated. Results: After policy intervention, 43.18% of policy-related drugs realized the substitution of bid-winning brands for bid-non-winning brands (6.82% of complete substitution, 36.36% of partial substitution). Meanwhile, 40.90% of policy-related drugs failed to realize brand substitution. Multiple factors affected brand substitution, including: (1) Policy effect: Brand substitution was more pronounced after the intervention of the first and third rounds of NCDP. (2) Drug market competition: The greater the price reduction of bid-non-winning brands, and the more drugs available for the same indication, the more likely that medical institutions would continue using the same brands as they did before policy intervention. (3) Previous drug utilization of medical institutions: Brand substitution was more evident in drugs with a large number of prescriptions and weak preference for brand-name drugs. Conclusion: The NCDP policy promoted the substitution of bid-winning brands for bid-non-winning brands, thereby positively impacting the quality and accessibility of overall healthcare services. However, further implementation of the NCDP policy is needed in county-level medical institutions. Efforts in policy implementation, drug market competition, and the drug utilization patterns of medical institutions will affect the success of the NCDP policy and its overall impact on the healthcare system.
National Centralized Drug Procurement (NCDP)
Copyright (c) 2025 YiFan Ge https://creativecommons.org/licenses/by/4.0
PREDICTION OF LOGISTICS DEMAND IN GUANGZHOU BASED ON GREY MARKOV MODEL
This paper selects the logistics data of Guangzhou from 2015 to 2019, using grey theory model and grey Markov model to forecast the logistics development data of Guangzhou from 2015 to 2019. Based on the actual data and forecast data of Guangzhou logistics from 2015 to 2019, the grey Markov model with high forecasting accuracy is selected to calculate the logistics demand of Guangzhou from 2020 to 2024, the empirical results show that there are two characteristics of logistics demand growth in Guangzhou in the future: First, the total demand of logistics industry in Guangzhou shows a continuous growth trend; Second, the structure of logistics demand in Guangzhou has changed slightly. According to the results of empirical research, this paper puts forward two countermeasures: First of all, under the background of new infrastructure, Guangzhou needs to strengthen the construction of logistics infrastructure, focusing on the development and improvement of infrastructure construction such as Internet of Things and logistics big data. Secondly, in view of the changes in the logistics demand structure in Guangzhou, we should continue to optimize the structure of the logistics industry, drain the highway logistics with higher carbon emissions, and pay attention to the development of clean, efficient and low-energy logistics methods to help achieve the goals of peak carbon dioxide emissions and carbon neutrality.
Copyright (c) 2025 YongXin Peng; SiMei Pan; YuJing Huang; LianHua Liu; WenChao Pan https://creativecommons.org/licenses/by/4.0
A DEA-MALMQUIST ANALYSIS OF MILITARY-CIVILIAN COLLABORATIVE INNOVATION EFFICIENCY
Taking listed companies involved in civil-military integration (CMI) in Sichuan Province as the research sample, this paper constructs a multi-dimensional evaluation system comprising resource input, technological output, economic output, and strategic output. Notably, government subsidies are incorporated as an output indicator measuring the "strategic value" of enterprises. On this basis, the DEA-BCC model and Malmquist index model are employed to conduct static measurement and dynamic evolution analysis of the collaborative innovation efficiency of these enterprises from 2022 to 2024. The study finds that: the low scale efficiency of innovation in Sichuan's CMI enterprises is the main factor restricting the improvement of overall effectiveness, and there is significant efficiency differentiation within the industry, Total Factor Productivity (TFP) shows a slight overall upward trend but fluctuates significantly due to the external environment, presenting a non-equilibrium characteristic of being significantly driven by technological progress while lagging in management efficiency catch-up. The conclusions of this paper provide a reference for optimizing the allocation of regional civil-military integration resources.
Copyright (c) 2025 Miao Li; LiJing Xie; Xue Yang https://creativecommons.org/licenses/by/4.0
THE PHASE-BASED DEVELOPMENT OF TRANSLATION COMPETENCE AND ITS PEDAGOGICAL IMPLICATIONS
While the PACTE model identifies translation competence components and the Dreyfus model describes general skill acquisition stages, neither adequately explains the cognitive mechanisms underlying stage transitions in translation learning. This paper addresses this gap by proposing an integrated theoretical framework that synthesizes cognitive psychology theories with translation-specific empirical findings. Drawing upon the Dreyfus Model of Skill Acquisition and Anderson’s ACT-R Theory, the study analyzes translation competence development across three stages—novice, intermediate, and advanced—from four dimensions: bilingual operation, strategy use, metacognitive monitoring, and translation output. Crucially, this paper explicates the cognitive mechanisms driving stage transitions: from declarative-to-procedural knowledge conversion that enables automatization to working memory load reduction that facilitates strategic allocation to improved metacognitive calibration accuracy. Based on empirical evidence from process-oriented translation studies (n = 35 novices, 28 intermediates, 24 professionals), this analysis reveals that novice translators exhibit 47% higher pause frequencies (M = 8.2 vs. 5.6 per 100 words) and 2.3 times longer dictionary consultation durations than professionals. The paper proposes a stage-adaptive pedagogical framework featuring differentiated scaffolding-withdrawal strategies aligned with cognitive developmental trajectories. This framework advances beyond existing models by providing mechanism-based pedagogical prescriptions rather than purely descriptive stage characteristics.
Copyright (c) 2026 QiLin Li https://creativecommons.org/licenses/by/4.0
MEASUREMENT AND ANALYSIS OF DIGITAL AGRICULTURE DEVELOPMENT: A CASE STUDY OF ANHUI PROVINCE
The application of digital technology is increasingly extensive, which has injected new vitality into China's traditional agriculture. Measurement agricultural digitization is of great significance for promoting agricultural development. In this paper, the index system of agricultural digital development in Anhui Province is constructed, the level of agricultural digital development in Anhui Province is calculated based on the entropy method, and the tire index is used to analyze the regional differences. The results show that the agricultural digital development level in Anhui Province increases year by year, and in Anhui Province, the low investment of agricultural capital assets is the biggest problem of agricultural digital development.
Copyright (c) 2026 XinYi Tao; YiMin Wu; MengJuan Xia; Jie Li https://creativecommons.org/licenses/by/4.0
FROM SIDE HUSTLES TO VENTURE CREATION: AN INDIVIDUAL-BASED MULTI-VALUE CONFIGURATION THEORY OF ENTREPRENEURSHIP
Contemporary entrepreneurship research remains largely anchored in a firm-centric paradigm that equates entrepreneurial action with venture creation and organizational founding. While this approach has enabled cumulative theory building, it increasingly fails to account for a growing range of entrepreneurial activities that unfold at the individual level, including side hustles, hybrid entrepreneurship, and AI-enabled micro-ventures. This paper develops the Individual-Based Multi-Value Configuration Theory (IMVCT), a novel theoretical framework that reconceptualizes entrepreneurship as a dynamic managerial configuration process centered on individuals rather than firms. IMVCT defines entrepreneurship as the continuous allocation and reallocation of time, capabilities, risk exposure, and identity commitment across scalable value-creating activities under uncertainty. Building on this definition, the paper proposes a four-state configuration model that explains entrepreneurial persistence, transition, and escalation without presuming linear progression toward organizational formation. By theorizing digital platforms and artificial intelligence as structural forces that shift experimentation, coordination, and scaling costs, IMVCT extends configuration theory to the individual level and offers a more precise account of entrepreneurial heterogeneity in technology-mediated contexts. The theory contributes to entrepreneurship and management research by reframing firm formation as a contingent outcome rather than a definitional boundary, thereby expanding the conceptual domain of entrepreneurial action.
Copyright (c) 2026 YuChen Chih https://creativecommons.org/licenses/by/4.0
DYNAMIC CREDIT PRICING MODEL FOR BUYER-PAID-INTEREST SUPPLY CHAIN FINANCING IN EMERGING PLATFORM ECONOMIES
The emergence of digital platforms in emerging market economies has fundamentally transformed supply chain finance, creating novel opportunities for working capital optimization while introducing distinct credit risk challenges. This paper develops a comprehensive dynamic credit pricing model for supply chain financing arrangements where the buyer assumes financial responsibility and interest payments, termed buyer-paid-interest financing. We integrate game-theoretic equilibrium analysis with credit risk assessment frameworks to characterize optimal pricing mechanisms across heterogeneous supplier credit profiles. Through a two-period modeling framework, we demonstrate that optimal interest rates exhibit non-linear relationships with both probability of default and loss given default parameters. Our analysis reveals that platform-based economies realize superior welfare outcomes compared to traditional bank-intermediated arrangements when credit assessment technologies efficiently capture supplier transaction data. We further establish conditions under which buyer-paid-interest structures dominate alternative financing mechanisms from both platform and supplier perspectives. Numerical analysis demonstrates that optimal pricing policies balance operational coordination benefits against credit risk compensation requirements. The model offers actionable insights for platform operators, financial institutions, and policymakers designing sustainable supply chain financing ecosystems in emerging markets.
Copyright (c) 2025 Yang Wu https://creativecommons.org/licenses/by/4.0
CONNECTING DIMINISHING FERTILITY RATES TO PHILOSOPHY, AND ITS REAL-LIFE IMPLICATIONS
Decreasing fertility rates have been a growing concern in today’s society; factors are complex, including scarce resources and economic hardships. This essay evaluates the present generation’s moral obligation to others’ lives and argues that while existing individuals are entitled to protection under the social contract, future generations lack the reciprocal moral claims necessary for similar obligations. By analyzing the philosophical perspectives of Rousseau and others, the paper differentiates between the rights of living beings and the conceptual nature of future lives. It concludes that decisions regarding procreation are deeply influenced by practical considerations of scarcity, autonomy, and the socio-economic concerns, necessitating a reevaluation of ethical responsibilities. Ultimately, analysis underscores the importance of balancing support for existing lives while acknowledging the complexities surrounding future generations in an increasingly resource-constrained world.
Copyright (c) 2026 RuoNan Liu https://creativecommons.org/licenses/by/4.0
RESEARCH REPORT ON CENTRALIZED PROCUREMENT OF HEALTHCARE EQUIPMENT AND INDUSTRY TRENDS
The Centralized Procurement System of Medical Consumables results in a drastic price reduction of numerous high-value medical consumables and has long-term effects on public hospitals that cannot be overlooked. This study employs both descriptive statistics and qualitative analysis methods to investigate some practical issues arising from the CPSMC from an economic perspective. The conclusions of this study are as follows: 1) Since 2010, China’s per capita health expenditure, per capita healthcare expenditure, and basic medical insurance fund expenditure have been growing rapidly. Seeking a more sustainable approach to medical consumables procurement is a prevailing trend. 2) The proportion of medical materials income within the medical income of public hospitals is increasing year by year. The promotion of zero markup for consumables and the Centralized Procurement System (CPS) may negatively impact the profitability of certain public hospitals. 3) Chinese doctors in public hospitals have faced long-term underpayment. Due to the combined effects of the COVID-19 epidemic and the CPS, the salaries of some doctors are also experiencing a significant decline in the short term. 4) Doctors are unable to receive reasonable income compensation for their long-term heavy medical workloads, which may lead to negative consequences such as decreased work enthusiasm and changes in medical types and processes. The conclusions of this paper will assist decision-making departments and relevant groups in deepening their comprehensive understanding and assessment of the impacts of the CPS, improving the corresponding compensation mechanisms and regulatory systems, and promoting a sustainable and healthy development of the CPS.
Copyright (c) 2025 YuZe Chen https://creativecommons.org/licenses/by/4.0
THE CONSTRUCTION PATH OF UNIVERSITY INNOVATION AND ENTREPRENEURSHIP PLATFORMS FROM THE PERSPECTIVE OF CHINA-ASEAN COOPERATION
In the context of the deepening of China-ASEAN cooperation and the acceleration of regional economic integration, the university innovation and entrepreneurship platform plays a pivotal role in promoting the integration of the educational, innovation, and industrial chains. This platform is of strategic importance in the cultivation of internationally oriented and versatile talents, the promotion of the transformation of scientific and technological achievements, and the empowerment of the synergistic development of the region. This paper is predicated on a comprehensive review of extant literature and a meticulous qualitative analysis. It systematically discusses the construction path of a university innovation and entrepreneurship platform in the context of China-ASEAN cooperation. The novelty of this paper is that it proposes a three-dimensional platform construction framework of education, economy, and culture from the theory of regional cooperation, which provides theoretical and practical references for the synergistic development of higher education and economic quality in China-ASEAN. Subsequent research endeavors may entail the amalgamation of empirical data and regional heterogeneity analysis, thereby facilitating a more profound exploration of the long-term governance mechanism of the platform.
Innovation and entrepreneurship platform
Copyright (c) 2025 Bin Li; ZiRou Wen; TingTing Pan; YiLu Huang https://creativecommons.org/licenses/by/4.0
THE ISSUES OF ACCOUNTING RECOGNITION AND MEASUREMENT OF PUBLIC DATA ASSETS
Public data constitute a critical component of China’s data factor supply system, embodying substantial political, economic, and social value. However, existing accounting standards are insufficient to accommodate their unique characteristics. This study begins by clarifying the conceptual connotation of public data and defining public data assets within the accounting framework. From the perspective of administrative and public institutions, it explores the conditions for accounting recognition and the categorization of ownership of public data assets. Furthermore, it examines the accounting treatments involved in subsequent measurement processes, including initial recognition and amortization, subsequent expenditures, impairment, and disposal. The findings enrich the accounting framework for emerging asset types within governmental accounting theory and provide practical guidance for administrative and public institutions to enhance the management efficiency of public data assets and to promote the market-oriented circulation of data factors.
Copyright (c) 2025 ZhenNan Li; MeiTing Shu https://creativecommons.org/licenses/by/4.0
TEAM SIZE AS A MODERATING FACTOR IN REMOTE PROJECT MANAGEMENT: EVIDENCE FROM SAUDI ARABIA
This study investigates the moderating effect of team size on remote project management outcomes in Saudi Arabian organizations, addressing a critical gap in understanding optimal virtual team configurations in emerging markets. Through quantitative analysis of data collected from 289 project professionals across multiple sectors in Saudi Arabia, the research examines how varying team sizes influence project completion rates, resource utilization, and coordination efficiency in remote work environments. Using structural equation modeling and hierarchical regression analysis, the findings reveal that medium-sized teams (8-12 members) demonstrate optimal performance metrics in remote settings. In comparison, larger teams (>15 members) show diminishing returns in coordination efficiency and project completion rates. The study also identifies critical thresholds where increasing team size begins to negatively impact virtual collaboration effectiveness. Results indicate that team size explains 34% of the variance in project completion rates when controlling for project complexity and industry type. These findings contribute to project management theory by establishing team size as a significant moderating variable in remote project success, particularly within the Saudi Arabian context. The research provides practical implications for project managers in optimizing team configurations for remote work, offering evidence-based recommendations for team sizing based on project scope and complexity. This study advances our understanding of virtual team dynamics in emerging markets and provides a foundation for future research on team size optimization in remote project management.
Copyright (c) 2025 Nofal Abdulhadi https://creativecommons.org/licenses/by/4.0
EXECUTIVE COMPENSATION, INNOVATION INVESTMENT, AND CORPORATE PERFORMANCE
This study examines non-financial listed companies in China's A-share market from 2016 to 2020 to empirically analyze the effects of executive compensation on corporate performance, the influence of innovation investment on corporate performance, and the moderating role of executive compensation in the relationship between innovation investment and corporate performance. The empirical findings indicate that executive compensation positively impacts corporate performance; there exists a significant positive correlation between innovation investment and corporate performance; and executive compensation partially moderates the relationship between innovation investment and corporate performance.
Copyright (c) 2025 YiFan Wang; YongHui Li https://creativecommons.org/licenses/by/4.0