Frontiers in Economics and Management (FEM) is a monthly online, international, peer-reviewed journal. All articles published are rigorously and fast reviewed meeting the Journal Quality standards. FEM is dedicated to publish empirical, academic, theoretical and review research articles that contribute to the practice in economics, management, and related topics. All articles published are rigorously and fast reviewed meeting the Journal Quality standards.
Research on the Influencing Factors and Problems of Financial Asset Allocation of Family Care
In recent years, China's population aging has become increasingly severe due to the continuous decline in birth rates and the extension of average human life expectancy. Consequently, some residents have begun to pay attention to and systematically allocate personal and family pension financial assets. However, given the profound degree of population aging, the relatively low financial literacy of residents, and the limited financial inclusiveness of pension services in China, there remain certain challenges in how families manage their pension financial assets.This paper selects the 2019 data from the China Household Financial Survey (CHFS) and constructs the residents 'financial literacy index and the financial inclusiveness index of elderly care services using factor analysis. It employs the Probit model and Tobit model to study the impact of population aging, financial literacy, and the financial inclusiveness of elderly care services on the allocation of household financial assets for elderly care. The study reveals: (1) China has a deepening degree of population aging, with residents' overall financial literacy level being relatively low and the financial inclusiveness of elderly care services being insufficient; (2) Improving the national financial literacy level and enhancing the financial inclusiveness of elderly care services are conducive to increasing the proportion of elderly care finance in household total assets.
Aging; Financial Literacy; Pension Finance; Asset Allocation.
Copyright (c) 2026 Frontiers in Economics and Management https://creativecommons.org/licenses/by-nc/4.0
Empirical Test of the Impact of R&D Expenditures on the Price-to-Earnings Ratios of Photovoltaic Enterprises
Amidst China's "dual carbon" goals and accelerating global technological evolution, photovoltaic (PV) enterprises are intensifying their research and development (R&D) investments to secure advantages in technological pathways and cost competitiveness. However, the capital market has historically shown divergence in its valuation of R&D expenditures: R&D can be perceived as an investment to build technological moats or interpreted as "hollow storytelling" that inflates valuations. The Price-to-Earnings Ratio (PER) is a crucial metric for stock valuation. Therefore, this paper utilizes A-share listed PV companies as samples to construct a panel fixed-effects model to examine the impact of R&D expenditure ratio on PER, and further investigates lagged effects and heterogeneity. The results indicate a significant positive correlation between R&D expenditure ratio and PER, and the R&D expenditure ratio from the previous period also shows significant positive influence, suggesting a certain delay in the recognition of R&D value. The positive impact of R&D on PER is stronger within the high R&D group, while it is not significant in the low R&D group. The conclusion for state-owned enterprise samples is unstable due to limited sample size. This paper discusses the aforementioned findings from the perspectives of industry cycles and information environments, and provides implications for corporate R&D resource allocation and investor valuation recognition.
Photovoltaic Enterprises; R&D Investment; PER; Fixed Effects; Heterogeneity.
Study on the Influencing Factors of Consumers' Purchase Behavior of New Energy Vehicles
Against the backdrop of the global implementation of carbon neutrality goals and the in-depth practice of China's green development philosophy, the new energy vehicle industry has become a core engine driving the high-quality development of China's economy. Although a series of industrial policies have propelled its market size to achieve leapfrog growth, consumers' purchase behavior remains the pivotal core variable that determines whether the industry can realize sustainable, healthy, and high-quality development. This paper systematically reviews relevant domestic and international research findings and analyzes the influencing mechanism of new energy vehicle purchase behavior in China from four dimensions: consumers' individual characteristics, core product attributes, policy support system, and social perception environment. The study reveals that: sound charging infrastructure and stable policy support are the core prerequisites for the growth of new energy vehicle consumption; the 25–35 age group has shown significantly higher attention to intelligent connected and high-level intelligent driving functions than to price factors; social media word-of-mouth and user community operation can effectively stimulate potential consumer demand; range anxiety and battery safety concerns remain the key pain points restricting the comprehensive popularization of the industry. This research can provide a reference basis for automobile enterprises to optimize market strategies and government departments to improve industrial policies.
New Energy Vehicles; Purchase Behavior; Influencing Factors.
The Impact of Local Government Overtime on Urban Economic Growth: Evidence from 313 Cities in China
Existing research on overtime work has primarily focused on the corporate level, with insufficient attention paid to overtime phenomena at the government level-and even less to their impact on urban economic growth. Therefore, this study aims to explore the influence of local government overtime(LGO) on urban economic growth(UEG) and its micro-level mechanism of action. Employing a two-way fixed effects model, we analyze panel data of 313 cities in China from 2012 to 2025. Empirical results indicate that LGO exerts a significant inverted U-shaped relationship with UEG. Mechanism analysis reveals that LGO affects UEG mainly by altering government innovation capacity. Moderating effect analysis demonstrates that government digital transformation plays a moderating role in the relationship between LGO and UEG.
Local Government; Overtime Intensity; Urban Economic Growth;
The Short Selling System Improve the Quality of Corporate Disclosure?
With the rollout of margin trading and short-selling regulations in China's capital market around 2010, this paper applies a two-step DID framework to analyze how short-selling activities affect the quality of firms' information disclosure. The study finds that the liberalization of short-selling mechanisms leads to a significant delay in the disclosure of annual reports, particularly among non-state-owned enterprises and those with poor internal controls. Further analysis indicates that while short-selling mechanisms affect the timeliness of annual report disclosure, they simultaneously enhance the reliability of accounting information. The results suggest that the relaxation of short-selling regulations implies higher requirements for the reliability of accounting information, thereby increasing corporate prudence in information disclosure and leading to a strategic delay in the release of annual reports.
Short-selling Regulations; Timeliness of Annual Report Disclosure; Ownership Structure; Internal Control.
A Discussion on Cross-Border E-Commerce Marketing Strategies for Small and Medium-Sized Enterprises in the Era of Big Data
The global e-commerce competitive environment is experiencing significant shifts as a result of how big data technologies allow a business to analyze an individual consumer’s actions more thoroughly than ever before. Cross-border e-commerce companies are beginning to make their marketing decisions based on data rather than just intuition. Large companies with the inherent capability of gathering large amounts of data from the marketplace have taken leading positions in this shift while SMEs are facing increasing competitition as a result of limited resources. Businesses are changing how they interpret their consumers’ demands in addition to changing the ways in which they communicate marketing messages to their consumers; as a result, Small and Medium-Sized Enterprises (SMEs) have to reassess their strategic marketing strategies. Therefore, creating a marketing strategy that is aligned with the limited resources of SMEs in this big data environment is both an urgent practical imperative and an important area for future research.
Big Data; Small and Medium-Sized Enterprises; Cross-Border E-Commerce; Marketing Strategies; Targeted Marketing.
Research on the Challenges and Countermeasures of Implementing Intelligent Expense Control in Enterprise Financial Shared Service Centers
Against the backdrop of the digital economy and the digital transformation of enterprises, intelligent expense control systems have become a key tool for enhancing the operational efficiency and value creation capabilities of Financial Shared Service Centers (FSSCS). However, practice has shown that enterprises generally encounter the predicament of "easy to go online but difficult to achieve results" during the implementation process. The white paper "A New Era of Financial Management:" jointly released by Deloitte and HSI in 2025 The "Outstanding Path of Intelligent Expense Control for World-Class Enterprises" points out that although more than half of the enterprises have adopted intelligent expense control systems, only a few have successfully implemented AI scenarios and achieved regular application. The majority of enterprises still face multiple practical obstacles such as system integration, data governance, organizational adaptation, compliance risk control, and talent support. The problem of the system being "in form but not in spirit" is prominent. Based on the Technology-Organization-Environment (TOE) framework and the Business Process Reengineering (BPR) theory, and by introducing the "L1-L5 non-reimbursement classification standard" and the "Four-step Breakthrough Method for AI Implementation" proposed in the above-mentioned white paper, this study has constructed a comprehensive analysis framework and response system of "technology integration - organization activation - environment adaptation". Based on case studies, it is found that the key factors affecting the effective implementation of intelligent expense control include system integration obstacles in the technical dimension, resistance to institutional processes and the scarcity of financial talents in the organizational dimension, as well as dynamic changes and the lack of relevant standards in the environmental dimension. This study proposes effective countermeasures from aspects such as hierarchical and phased technical construction, business process reengineering, organizational change, and regulatory external environment, providing support for enterprises to build an efficient intelligent expense control system and promoting the high-quality and long-term development of financial sharing and intelligent expense control.
Intelligent Expense Control; Financial Management; TOE Theory; BPR Theory.
Research on the Evaluation of Corporate Environmental Information Disclosure Quality: A Case Study of Changyuan Electric Power
With the continuous advancement of the carbon peaking and carbon neutrality goals and ecological civilization development, environmental information disclosure has become a key indicator for evaluating corporate sustainable development capabilityThis study selects Hubei Energy Group Changyuan Electric Power Co., Ltd. as the case company.Drawing on relevant domestic and international laws and regulations on environmental information disclosure and considering the characteristics of China's industry practices, the study adopts the content analysis method to construct an environmental information disclosure evaluation index system.The system is based on 17 core indicators covering environmental assets, environmental liabilities, environmental income, and other related aspects. By examining the company's Social Responsibility Reports and ESG Reports from 2021 to 2024, this study calculates the Environmental Disclosure Index (EDI) and analyzes both the EDI and each evaluation indicator. The analysis reveals several weaknesses in the company's current environmental information disclosure practices and examines the factors contributing to these issues. On this basis, corresponding recommendations are developed to improve the quality and effectiveness of environmental information disclosure. The findings may also offer useful insights for other coal-fired power enterprises seeking to strengthen their environmental information disclosure and support their sustainable development efforts.
Environmental Information; Quality Evaluation; Information Disclosure.
The Evolutionary Study of China’s Technology Transfer Policy Structure
As global competition in science and technology has intensified, the commercialization of scientific and technological achievements has become an important way to promote innovation-driven and high-quality economic development. Using a corpus of 409 policy documents issued by China's central and local governments from 1991 to 2024, this study examines how policies on the commercialization of scientific and technological achievements changed over time through a mixed analytical framework. The Latent Dirichlet Allocation (LDA) topic model is used to analyze policy development from internal and external perspectives. The internal analysis focuses on the thematic structure and content of policy documents, whereas the external analysis looks at their temporal evolution, spatial distribution, and institutional sources. Together, these two dimensions trace the development path and policy logic of China's system in this area. The study further examines the structural features and changes in technology transfer policy instruments, identifies the main weaknesses in the current policy framework, and proposes targeted suggestions for improvement. In this way, the findings clarify how China's technology transfer policies have evolved and provide evidence for strengthening the policy system and improving the efficiency of commercializing scientific and technological achievements.
Technology Transfer; LDA Model; Policy Text Analysis; Evolution Trend.
The Logic of Consumer Forgiveness in Luxury Brand Crises: Dual Perspective of Emotional Attachment and Moral Decoupling
In today's consumer market, luxury brands always find themselves in crises. Yet, interestingly, they frequently manage to gain consumer forgiveness. This phenomenon has drawn more and more attention in market research. However, a closer look at past studies shows a clear gap. Prior research has mostly focused on two separate mechanisms. One is the buffering effect of emotional attachment, which protects brands from negative information. The other is moral decoupling, a cognitive strategy that separates brand performance from ethical judgment. For the most part, these mechanisms always studied in isolation. As a result, the underlying logic that links luxury brand crises to consumer forgiveness is still not well understood.Our study adopts a dual-perspective framework. We combine the emotional attachment and moral decoupling. By using both questionnaire surveys and real case studies, we aim to explore how these two ways together shape consumer forgiveness in the luxury market. It not only knows our understanding of consumer psychology but also provides useful guidance for brand crisis management.
Luxury Brands; Emotional Attachment; Moral Decoupling; Consumer Forgiveness; Brand Crisis.
A Game-Theoretic Study on the Evolution of Carbon Emission Reduction Strategies among Chemical Companies under a Carbon Trading Mechanism
With the national carbon market set to expand coverage to the chemical industry, chemical enterprises face strategic divergence and interaction between two options: achieving emissions reductions through proprietary technologies, or purchasing carbon allowances to meet compliance obligations. This paper incorporates key parameters including carbon price, the severity of government penalties, differences in emission reduction costs, and low-carbon subsidies to construct an evolutionary game model of the interaction between local governments and chemical enterprises under the carbon trading mechanism. Based on this model, this paper employs numerical simulation methods to systematically analyze the evolutionary paths and steady-state conditions of group strategies under different parameter combinations. The results indicate that the system exhibits four evolutionary equilibrium states, and periodic fluctuations are the most common transitional state in carbon emission reduction governance. This phenomenon essentially stems from a "regulation–relaxation" cycle caused by asymmetric incentive structures between the government and enterprises. The ideal equilibrium can be achieved through two pathways: market-driven and policy-guided. Among these, the policy-guided equilibrium combines endogenous dynamics with regulatory safeguards, and delivers greater stability and sustainability. Finally, based on the research findings, this paper proposes targeted recommendations from the perspectives of both the government and chemical enterprises.
Carbon Trading; Evolutionary Game; Chemical Enterprises.
Mechanisms, Heterogeneity and Practical Paths of Intelligent Manufacturing Driving Enterprise Innovation Capability Improvement
The new round of global scientific and technological revolution and industrial transformation is advancing continuously. Intelligent manufacturing has become the core driving force for China's manufacturing industry to complete transformation and upgrading and achieve high-quality development. This paper systematically sorts out several internal paths through which intelligent manufacturing helps manufacturing enterprises cultivate innovation capabilities, analyzing from the dimensions of digital technology application, internal organizational adjustment, simultaneous advancement of diversified innovations, and overall industrial chain transformation. Meanwhile, it distinguishes the differentiated effects under different operating entities, industry tracks, enterprise scales and matching degrees of development plans. The paper sorts out the common practical problems existing in the process of intelligent transformation of domestic manufacturing enterprises at this stage, including the disconnection between software and hardware construction, insufficient supply of digital skilled talents, insufficient linkage of various entities in the industrial chain, and the need to improve the accuracy of supporting support policies. Finally, it puts forward feasible development ideas from the government level and the enterprise itself respectively, providing theoretical reference for various manufacturing enterprises to cultivate innovation strength relying on intelligent transformation.
Intelligent Manufacturing; Enterprise Innovation Capability; Digital Capability; Organizational Change; Supply Chain Collaboration.
Hadoop-based Financial News Text-Driven Market Volatility Prediction: TF-IDF, Machine Learning, and SHAP Interpretability Analysis
The variation of financial market is largely influenced by the emergence of new information like macroeconomic policies, corporate notifications and international political events. With the growing amount of financial textual data, it has become an important issue to predict market trends from news materials. In our research, we have collected an empirical data set including 1,985 news articles concerning market volatility. A binary target label has been established based on whether the daily volatility exceeds a 1% level, resulting in a positive class ratio approximately 0.27. We carry out the Hadoop framework (HDFS and distributed processing) in the first stage of text processing to preprocess and organize the raw data. For feature extraction, a TF-IDF model (with 1-2 grams and 5,000 maximum features) is used to obtain the text vector representation. Then, we train and test two kinds of algorithms: a calibrated probability linear Support Vector Machine (SVM) and an XGBoost classifier. We conduct validation tests based on a TimeSeriesSplit method. The performance measures consist of the area under the Receiver Operating Characteristic curve (ROC-AUC), Precision-Recall curve (PR-AUC) and the optimal F1 score. Additionally, we integrate other features such as VADER sentiment indices, token entropy and special shock words to do an ablation study. The SHAP parameters give explanations for the results both globally and locally. The experimental results indicate that there are strong predictive hints in the news texts and the interpretive step is beneficial to confirm the model logic.
Financial Volatility Prediction; News Text; Hadoop; TF-IDF; SVM; XGBoost; Ablation Study; SHAP.
Research on Pathways to Enhancing the Effectiveness of Internal Control in Universities from the Perspective of Financial and Accounting Supervision
Amid the national efforts to establish a robust financial and accounting supervision system and deepen comprehensive reforms in education, internal control serves as a pivotal mechanism for universities to standardize economic activities, mitigate financial risks, and enhance governance capabilities. Its effectiveness directly impacts institutional operations and long-term development. Currently, Chinese universities face challenges in implementing internal controls, including inadequate supervisory environments, incomplete regulatory frameworks, insufficient risk management capacities, poor coordination among oversight bodies, and underdeveloped digital infrastructure-all of which hinder optimal control efficacy. This study examines the intrinsic relationship between financial accounting supervision and university internal control systems, considering institutions' characteristics as non-profit organizations with diversified funding sources and complex operational structures. It systematically identifies practical issues in current internal control practices and proposes actionable solutions-including optimizing supervisory environments, refining regulatory frameworks, strengthening risk assessment, enhancing collaborative oversight, advancing digital transformation, and cultivating specialized talent teams-to improve control effectiveness. These recommendations aim to provide theoretical foundations and practical guidance for universities in establishing robust internal control systems, complying with accounting supervision requirements, and achieving modernized governance capabilities.
Financial and Accounting Supervision; Higher Education Institutions; Internal Control; Risk Prevention and Control; Information Technology Development.
The Impact of Data Assetization on Corporate ESG Performance: Research Progress and Literature Review
Under the dual strategy of Digital China and new quality productivity, the connection between data assetization and corporate ESG performance provides a key micro-level link for their development at the enterprise level. This article reviews the related research on both, clarifies the progress made, and offers direction for future studies. Existing literature shows that research on data assetization is relatively new, mainly focusing on measurement methods and microeconomic effects; ESG-related research is more abundant, and the cross-study of the two mostly uses empirical analysis to test mechanisms and moderating effects. Current research mainly faces issues like relatively fixed mediating mechanisms, inconsistent measurement standards, and insufficient heterogeneity analysis, which can serve as references for future research.
Data Assetization; ESG Performance; Literature Review.
Study on the Relationship between Short Selling Regulations and Corporate Equity Financing Costs
As capital market regulation has been progressively refined,and as short-selling mechanisms have continued to widen in scope,the question of whether short-selling rules affect corporate equity financing costs-and through which channels they do so-has moved to the foreground of scholarly inquiry. Focusing on A-share listed firms on the Shanghai and Shenzhen stock exchanges over the 2015–2024 period,the study draws on the quasi-natural experiment generated by the phased liberalisation of margin trading regulation and,with a multi-period difference-in-differences framework,conducts a structublue test of the effects of short-selling regulation on corporate equity financing costs as well as the mechanisms through which those effects operate.The empirical results point in a consistent direction: short-selling regulation blueuces corporate equity financing costs. That inference,importantly,remains intact across a series of robustness checks,including alternative proxy-variable specifications,propensity score matching,and placebo tests. Turning to the transmission channels-this is where the pattern becomes more analytically interesting-the mechanism tests suggest an intermediary pathway whereby short-selling regulation raises firms’ cash dividend payout ratios while also strengthening market value assessments,with investor risk premiums correspondingly compressed and financing costs,in turn,pushed downward.
Short-selling Regime; Equity Financing Costs; Margin Trading.
Economic Policy Uncertainty and Volatility Forecasting in China’s Stock Market
This paper develops the GARCH-MIDAS-RV-EPU model, which integrates high-frequency realized volatility, low-frequency macro indicators and the exogenous Chinese Economic Policy Uncertainty (EPU) index to predict China’s stock market volatility. Using 5-minute high-frequency data of the Shanghai Composite Index (SSEC) and the Shenzhen Component Index (SZSEC), we find that the proposed model outperforms alternative specifications in return fitting and volatility description. With robust loss functions as evaluation criteria, we compare the out-of-sample volatility forecasting performance of all models. The empirical results show that incorporating high-frequency, low-frequency and EPU information significantly boosts volatility predictability, and our model exhibits the strongest forecasting power among all competing specifications.
Volatility Forecasting; Realized Volatility; Economic Policy Uncertainty; Mixed-Frequency Data Sampling.
A Rough Set-Cloud Model Approach for Digital Twin-Enabled Natural Heritage Protection Evaluation: A Case Study of Huanglong Scenic Area, China
While digital twin technology has emerged as a promising tool for natural heritage conservation, few studies have put forward systematic evaluation frameworks specifically designed for assessing the operational effectiveness of such platforms. Building on existing research, this paper introduces a hybrid evaluation methodology that combines rough set theory with cloud modeling techniques to measure the performance of digital twin platforms in heritage protection contexts. To address the complexity of multi-dimensional evaluation systems with intricate interrelationships among indicators, we employ rough set theory grounded in conditional information entropy to filter out redundant metrics and compute objective weight values. The cloud model component translates qualitative assessments provided by domain experts into quantitative evaluation clouds through forward and backward cloud generation algorithms, while a thickness-based iterative scoring process helps converge divergent expert opinions toward consensus. By weighting each indicator cloud according to its importance, a comprehensive evaluation cloud can be synthesized. We test the proposed method using data from Huanglong Scenic Area, a UNESCO World Natural Heritage site in southwestern China where an integrated digital twin platform-incorporating multi-source data fusion capabilities and real-time monitoring systems for conservation management-has been deployed and running for several years. Our findings indicate that this approach not only successfully pinpoints key performance indicators but also overcomes the difficulties associated with converting qualitative judgments into quantitative measures, while offering intuitive three-dimensional visualizations of evaluation results. The evaluation framework presented in this study provides a practical, replicable model for assessing digital technology implementations in protected area management settings.
Digital Twin; Rough Set; Cloud Model; Natural Heritage; Huanglong Scenic Area; Smart Conservation.
How Short-Video Marketing Shapes Generation Z Consumer Decision-Making: Evidence from the UK Fast-Fashion Market
While many studies have described the effects of short-video platforms in the context of fast-fashion communication with younger generations, the relationship between exposure, evaluation and purchase behaviour has rarely been described through a psychological mechanism. With the case of fast fashion in the UK, this study aims to explore the influence of short video marketing from exposure to purchase and reflection of Generation Z consumers. The analysis is based on semi-structured interviews with 15 consumers in the UK belonging to Generation Z, using an integrated model based on the stimulus-organism-response (SOR) model, uses and gratifications theory (UGT) and social identity theory. The results demonstrate that external stimuli with the highest saliency are influencer-led IP marketing, scarcity cues and algorithmic network diffusion. These stimuli are not just about making it more visible, it's also about making it more valuable, more of an emotion and more of a sense of belonging-a sense of community-which leads to buying intent, quick conversion, and-at least at times-impulsive buying. The study also tells of the existence of a defensive consumption loop. Given poor buying experiences, participants are more apt to check reviews, compare creators and even seek out negative information before purchasing again. The article provides a qualitative understanding of the functioning of short-video marketing in the context of fast fashion and provides actionable insights for brands interested in cultivating long-term trust with Generation Z, not just short-term conversions.
Fast Fashion; Short Video Marketing; Consumer Decision-making; Generation Z; Social Identity and SOR Model.
Forecasting Chinese Stock Market Volatility Using the Range and Climate Policy Uncertainty
Within the conditional autoregressive range (CARR) framework, this paper introduces climate policy uncertainty (CPU) as a low-frequency macroeconomic variable and develops a CARR-MIDAS-CPU model for modeling and forecasting Chinese stock market volatility. Using data on the SSE 50 Index, the empirical results show that CPU has a significant effect on long-run stock market volatility. In terms of in-sample fitting performance, range-based CARR models consistently outperform their return-based GARCH counterparts, corroborating the informational value of intraday extreme price data in volatility modeling. We further conduct an out-of-sample forecasting comparison between the CARR-MIDAS-CPU model and a set of competing benchmark specifications, adopting two robust loss functions as the core evaluation criteria. Forecasting results demonstrate that the integration of climate policy uncertainty (CPU) delivers incremental predictive power for Chinese stock market volatility, and the CARR-MIDAS-CPU model achieves the highest predictive accuracy among all specifications under examination. Overall, the proposed model effectively exploits range-based volatility information and climate policy uncertainty to enhance forecasting performance, and offers a practical econometric tool to support risk management for both policymakers and market investors.
Volatility Forecasting; Range; Climate Policy Uncertainty; Mixed-Frequency Sampling.
Analysis of the Financial Capabilities of Muyuan Foods Co., Ltd.
The consumer demand and stable supply of China's major agricultural products show obvious cyclical characteristics, and are very susceptible to fluctuations in pig prices, feed costs, disease risks and policy regulation. As a representative enterprise of China's pig industry, Muyuan Food Co., Ltd. reflects the operating characteristics of large breeding enterprises under the fluctuations of the industry cycle to a certain extent. Taking Muyuan Food as the research object, this article selects the relevant financial data from 2015 to 2024, analyzes the enterprise from the four dimensions of solvency, profitability, operating capacity and growth potential, and discusses its financial performance and existing problems in combination with the development background of the pig industry. The research results show that Muyuan Food has significant advantages in large-scale breeding, industrial chain layout and cost control; the overall operating efficiency is high, and the overall operating income shows a growth trend; however, there are also a number of problems - the short-term solvency is relatively weak, and the current ratio and the fast-moving ratio are low for a long time; profitability The ability is significantly affected by the pig price cycle, and the return on equity and gross margin fluctuate greatly; in terms of growth potential, it is manifested in the coexistence of income expansion and profit fluctuations. Based on these research results, this paper puts forward suggestions such as optimizing the debt term structure, strengthening cost control, improving asset utilization efficiency and controlling the expansion speed, aiming to help Muyuan Food improve financial stability and anti-cyclical ability to achieve more sustainable development.
Muyuan Foods; Financial Statement Analysis; Solvency; Profitability; Hog Farming Industry.
A Simple Study on the Impact of Strategic Differences between Luckin and Starbucks China on Sales Revenue
Our study conducts a comparative analysis of the strategic disparities between Luckin Coffee and Starbucks in the Chinese market, along with the tangible impacts of these strategies on sales performance. We also delve into the effectiveness and sustainability of both companies' business models within the rapidly expanding coffee industry. For instance, Luckin Coffee's innovative online marketing campaigns, such as its viral referral programs and personalized discount offers, have played a crucial role in driving customer acquisition and retention. On the other hand, Starbucks' localization efforts, like introducing tea-based beverages and collaborating with local brands, have helped it resonate with Chinese consumers and maintain its brand appeal. Luckin Coffee exemplifies an internet-driven approach, characterized by rapid market entry, aggressive expansion, and a focus on market capture through rapid store openings, online marketing, and substantial subsidies. The results were indeed remarkable: in 2021, its revenue reached 7.965 billion yuan, a 97.5% year-on-year increase, with the number of stores surging to 6,024, making it China's largest coffee chain brand. By 2024, revenue further grew to 34.475 billion yuan, and net profit margin improved to 8.5%. However, the question remains whether this model can sustain itself. The 2020 financial fraud scandal, weak brand culture, and supply chain pressures have introduced uncertainties for its future development. In our view, while Luckin Coffee has achieved impressive growth in recent years, it needs to address these challenges to ensure long-term sustainability. For example, it should invest in building a stronger brand culture and improving its supply chain management to reduce costs and enhance efficiency. Starbucks, on the other hand, follows a different path, emphasizing quality and offline experiences while targeting the mid-to-high-end market. However, this strategy has also faced challenges in recent years, with same-store sales dropping by 23% in the second quarter of 2022 as market share was gradually eroded by competitors. To counter this, Starbucks has intensified its focus on delivery services and digital offerings while leveraging localization efforts to maintain brand appeal. We believe that Starbucks' strategic adjustments are necessary to adapt to the changing market dynamics, but it should also continue to emphasize its core strengths in quality and customer experience. In summary, Luckin Coffee relies on affordability and speed to dominate the market, boasting strong momentum but lacking stability; Starbucks, by contrast, thrives on brand and experiential appeal, offering greater resilience but slower responsiveness. Both models have distinct strengths and weaknesses, with the key challenge being whether they can adapt to changing consumer preferences. To achieve long-term market success, relying on a single strategy is insufficient-finding the right balance between growth and stability, along with continuous adjustments and innovation, is essential.
Strategic Differences; Sales Revenue; Operational Model; Marketing Strategy.
Multi-Stakeholder Collaborative Governance Mechanism in Rural Industrial Revitalization
Against the backdrop of the in-depth advancement of the rural revitalization strategy, prominent dilemmas including scattered governance entities, fragmented resource allocation and insufficient cross-stakeholder linkage efficiency have become core bottlenecks restricting industrial revitalization. Integrating collaborative governance theory and stakeholder theory, this paper adopts qualitative research and takes Village S with targeted assistance from central state-owned enterprises (CSOEs) as the research case to systematically analyze the dynamic evolution and operational logic of multi-stakeholder collaborative governance in rural industrial revitalization. The study finds that taking embedded empowerment by CSOEs as a critical pivot, Village S has gone through four developmental stages, gradually formed a multi-stakeholder collaborative governance pattern and built a multi-level collaborative governance network, thus realizing the transformation from single-village governance to regional collaborative governance. This paper refines the embedded multi-stakeholder collaborative governance mechanism driven by CSOEs, and provides a practical paradigm and theoretical reference for villages with medium resource endowments to tackle governance obstacles in industrial revitalization.
Collaborative Governance; Industrial Revitalization; Central SOE Embedding; Multi-stakeholder Linkage; Village S Case.
The Impact Mechanism and Spatial Effects of Land Transfer on the New Productive Forces in Agriculture
To clarify the intrinsic relationship between land transfer and new agricultural productive forces and explore its impact mechanisms, this study utilizes panel data from 30 provinces (autonomous regions and municipalities) in China from 2005 to 2023, employing threshold effects and dynamic SDM models to investigate their interplay. The findings reveal: (1) A significant positive correlation exists between land transfer and new agricultural productive forces. (2) Land transfer primarily promotes the development of new agricultural productive forces by enhancing land resource allocation efficiency. (3) Green technology innovation significantly moderates the relationship between land transfer and new agricultural productive forces. (4) The impact of land transfer on new agricultural productive forces exhibits nonlinear characteristics. (5) The effects of land transfer on new agricultural productive forces demonstrate regional heterogeneity. (6) Compared to long-term spatial effects, land transfer's short-term spatial spillover effects are more pronounced.
Land Transfer; New Agricultural Productive Forces; Efficiency of Land Resource Allocation; Green Technology Innovation; Spatial Durbin (SDM) Model.
Influence of Effort-Reward Imbalance of Primary Medical Staff on Performance Management Reform: A Cross-Sectional Study
Objective: To explore the impact of the Effort-Reward Imbalance of medical staff in primary medical institutions on the performance management reform, and to analyze the influencing factors of the performance management reform in primary medical institutions. Methods: Using the Effort-Reward Imbalance scale and the performance management questionnaire of primary medical institutions compiled by the research group, 1084 medical staff from 30 primary medical institutions in Anhui Province, China were investigated, using descriptive statistical analysis and logistic regression methods. Results: The Effort-Reward Imbalance of medical staff in primary medical institutions was 0.93 ± 0.38, of which 38.19% were in the state of high effort-low reward, 61.81% were in the state of low effort-high reward, and 88.1% supported the performance management reform. Logistic regression results showed that gender, working life, authorized strength and effort-reward ratio were the influencing factors of the performance management reform of primary medical institutions (P < 0.05). Conclusion: The performance management reform of primary medical institutions should consider the gender of medical staff, working life, authorized strength and the status of effort-reward.
Primary Medical Staff; Effort-Reward Imbalance; Performance Management.
The Implementation of China’s Fair Competition Review System: A SWOT Analysis of Shanxi Province in China
The Fair Competition Review System constitutes a key measure for deepening the reform of the market economic system and constructing a unified national market. As a typical resource-based region, Shanxi Province has long been confronted with multiple challenges, including a single industrial structure and administrative intervention. During the critical period of energy transition, the province is in urgent need of relying on the Fair Competition Review System to dismantle policy barriers and boost the endogenous driving force of the market. This study systematically reviews the progress achieved since the implementation of Shanxi Province’s Fair Competition Review System in January 2017. By integrating characteristic local review cases and policy cleanup data, it summarizes the effectiveness and innovative practices in the comprehensive coverage of the system and the enforcement of reviews. On this basis, employing the SWOT analysis method, the study conducts an in-depth analysis of the internal strengths and weaknesses, as well as external opportunities and threats, inherent in Shanxi’s implementation of the system. Targeted optimization strategies are proposed in four dimensions: deepening precise policy alignment by leveraging top-level design and digital economy dividends; addressing the fragmentation in review enforcement through capacity building and regional coordination; curbing regional policy games via rigid institutional constraints; and mitigating external economic fluctuations through industrial risk early warning and third-party evaluation. The research findings could provide theoretical references and practical pathways for Shanxi Province and other similar resource-based regions nationwide to curb administrative monopolies, optimize the business environment, and advance the construction of a unified national market against the backdrop of the Carbon Peak and Carbon Neutrality goals.
Fair Competition Review System; Resource-based Regions; Business Environment; SWOT Analysis.
Research on the Impact of Green Trust on Consumers' Willingness to Purchase Low-Carbon Products
In the context of global low-carbon development, the gap between consumers' willingness to purchase low-carbon products and their actual behavior has become a key bottleneck restricting the development of the low-carbon market. Combining planned behavior theory and trust theory, this paper constructs a theoretical model with green trust as the core anfactorial variable to explore the direct impact of green trust on purchase intention, as well as the indirect effects of attitudes, subjective norms, and perceived behavior control. Taking consumers in Liaoning Province as the research subjects, 229 valid questionnaires were collected and empirical analysis was conducted using various statistical methods. The results show that the level of green trust among consumers needs to be improved, and there are problems such as insufficient construction of green trust among enterprises, imperfect government guarantee system, and lack of credibility of third-party certification. Based on this, this paper proposes countermeasures from the perspectives of enterprises, governments, and third-party institutions to enhance consumers' purchasing intentions, serve the "dual carbon" goals, and at the same time enrich the application of relevant theories to provide empirical evidence for enterprise marketing and policy-making.
Green Trust; Low-carbon Products; Purchase Intention; Theory of Planned Behavior; Mediating Effect.
Schedule Risk Evaluation and Control Countermeasures for Supporting Infrastructure Projects of Large-Scale Equipment based on ISM-BN
To address the issues of vague schedule risk identification, insufficient quantitative research, and poorly targeted control measures in supporting infrastructure projects for large-scale equipment, this paper takes the perspective of the owner (the construction unit) as the starting point. Through expert interviews, a set of risk factors for such projects is identified and established. Using Interpretive Structural Modeling (ISM), the hierarchical relationships and propagation paths of schedule risks are revealed. A Bayesian Network (BN) model is then constructed for quantitative analysis to identify key risk nodes and causal chains, and to determine and classify schedule risk levels. Based on a comprehensive evaluation, targeted risk control measures are proposed, providing a reference for the owner's schedule management.
Large-scale Equipment Supporting Infrastructure Projects; Owner's Perspective; Schedule Risk Control; ISM-BN.
Study on the Mechanism of Mobile Phone Brand Preference Switching based on the Push-Pull-Mooring Framework
Against the background that the smartphone market is shifting from incremental expansion to stock based competition, consumers' brand preference switching has become an important issue affecting user retention, market share, and brand competitiveness of mobile phone enterprises. Drawing on the Push Pull Mooring framework, this paper analyzes the influencing factors and mechanism of mobile phone brand preference switching in the context of digital and intelligent consumption. The study argues that brand satisfaction and brand quality constitute the push factors that drive consumers away from their original brands; brand promotion, brand competitiveness, country of origin, price performance ratio, and brand awareness constitute the pull factors that attract consumers to alternative brands; and brand uniqueness constitutes an important mooring factor affecting whether consumers actually switch brands. The findings provide references for mobile phone enterprises to optimize brand positioning, enhance user loyalty, and carry out refined user operations.
Brand Preference Switching; Push Pull Mooring Framework; Consumer Behavior; Mobile Phone Brand.
Research on the Impact of Carbon Trading Policy on Corporate ESG Performance
Selecting Chinese listed enterprises from 2010 to 2024 as the research sample, this study constructs a multi-period difference-in-differences (DID) model to investigate the impact of carbon trading policy on corporate ESG performance. The findings reveal that carbon trading policy significantly enhances the overall ESG performance of enterprises, a conclusion that remains robust after a series of tests, including parallel trend and placebo tests. Heterogeneity analysis demonstrates that the driving effect of the policy varies significantly across different types of enterprises, primarily manifesting in large-scale enterprises, high-carbon industries, and enterprises located in regions with stringent environmental regulations. Mechanism tests indicate that green technology innovation, digital transformation, and political-business connection serve as key moderating variables between carbon trading policy and corporate ESG performance, significantly moderating the policy's effects on ESG outcomes. The research findings of this paper contribute to advancing the government's refinement of the carbon trading market system and promoting high-quality corporate transformation.
Carbon Trading Policy; ESG Performance; Corporate Transformation.