Highlights in Business, Economics and Management
Highlights in Business, Economics and Management is an open access, peer-reviewed publication series published by Darcy & Roy Press. It aims to publish conference proceedings dealing with all areas of business, economics and management, etc.
Research on the Impact of Common Institutional Ownership on Stock Price Crash Risk
Preventing and mitigating stock price crash risk has been a persistent focus in academic research. Targeting the ownership structure characteristic of common institutional ownership, this study empirically examines its impact on stock price crash risk using a sample of A-share listed companies from 20011 to 2023.The findings reveal that firms with common institutional ownership can effectively mitigate stock price crash risk, thereby supporting the "collaborative governance hypothesis. "The aforementioned conclusions remain valid after robustness checks using alternative models. Mechanism tests reveal that information transparency and corporate governance level play partial mediating roles in the relationship between common institutional ownership and stock price crash risk.
Common institutional ownership, Stock price crash risk, Institutional investors, Internal governance.
Copyright (c) 2025 Highlights in Business, Economics and Management https://creativecommons.org/licenses/by-nc/4.0
Research on the Impact of Digital Technology Innovation on Enterprise Value
The report of the 20th National Congress of the Communist Party of China pointed out: "Accelerate the development of the digital economy and promote the deep integration of the real economy and the digital economy." Digital technology is the technical support for the digital economy. With the acceleration of the digitalization process of the entire society, more and more enterprises have begun to adopt emerging technologies such as artificial intelligence, big data, cloud computing, and blockchain. These technologies play an important role in improving the operational efficiency of enterprises, optimizing resource allocation, and enhancing customer experience. The continuous innovation of digital technology also has a significant impact on the market value of enterprises in the digital era. Therefore, this paper studies the relationship between digital technology innovation and enterprise market value of China's listed companies from 2013 to 2020, and draws the following conclusions: Digital technology innovation can significantly enhance the market value of enterprises, but the above improvement effect only holds true for small and medium-sized enterprises, private enterprises, highly competitive industries, and low-tech traditional industries. The research in this paper expands the scope of research on the effects of the digital economy at the micro level, providing useful references for the Chinese government to optimize digital economy policies and for enterprises to formulate digital innovation strategies.
Digital technology innovation, digital economy, market value, digital transformation.
Co-Created Authenticity: Generation Z Themed Hotels' Narrative Experience Strategy
As Generation Z gradually becomes the main consumer group of theme hotels, the paradox of marketing prioritization breaks out. Generation Z, as the group pursuing "search for truth" the core value, puts a higher demand on "authenticity" than ever before. But the essential feature of theme hotels is exactly "staged" and "the false." The core question addressed herein is how to use experiential marketing by theme hotels to construct the brand story that can attain the perception called "authenticity" by Generation Z. This study reveals that the "authenticity" pursued by Generation Z no longer lies in the traditional objective fact, but in the subjective personal concern, emotional resonance, and peer verification (User-Generated Content [UGC]). To address this paradox, the purpose of this study is to build a model of "Co-Created Narrative Experiential Marketing" (CC-NEM). The model conceptually synthesizes the Experience Economy, Strategic Experiential Modules (SEMs), Narrative Servicescape, Service-Dominant Logic (S-D Logic), and Narrative Transportation Theory (NTT). The core premise of this research is that hotel brands need to undergo a role transformation from "Storyteller" to "Story-Facilitator". Through an experiential framework that allows the customer to participate, modify, and co-write the story, and by using UGC as the basic verification channel for authenticity, "co-creation" can be the key mechanism to dissolve the paradox which enables themed hotels to establish genuine emotional connection and brand loyalty in the mind of Generation Z.
Generation Z, Themed Hotels, Authenticity Paradox, Co-Created Narrative, Experiential Marketing.
Comparison of DCF Valuation and DDM Valuation of Stock Price of Boyd Gaming Corporation
The valuation of a company is done through different approaches and models by analysts. The common models utilized by the analysts are the dividend discount model (DDM) and discounted cash flow model (DCF). Some analysts rely on the dividends to analyze the stocks and some analysts rely on the free cash flows to analyze different stocks. The following report determines the accuracy of the two models. The models have been analyzed using the Boyd Gaming Corporation, a publicly listed stock on the New York Stock Exchange. The stock exchange is one of the biggest and most developed markets. Therefore, the market is efficient and states that the market price reflects the true share price or intrinsic share price as per the efficient market hypothesis. The DMM model stated that the stock is underpriced and the DCF model stated that the stock price is overpriced. The results of the study concluded that the discounted cash flow model is more accurate in determining the market price of the share in comparison to the dividend discount model.
The Impact of Corporate ESG Performance on Stock Liquidity: Evidence from Chinese A-Share Listed Companies
This paper examines the impact of corporate ESG performance on stock liquidity using a sample of Chinese A-share listed companies from 2015 to 2022. The results show that good corporate ESG performance significantly enhances stock liquidity. The conclusion remains robust after a series of robustness tests. This study provides empirical evidence for the positive effect of ESG performance on stock liquidity and offers insights for improving ESG-related policies in China.
Corporate ESG performance, Stock liquidity, Listed companies.
The impact of Technical Barriers to Trade on China’s environmental goods exports to CPTPP
In the context of rising global environmental awareness and increasingly stringent non-tariff trade measures, Technical Barriers to Trade (TBT) have become a crucial factor shaping international trade flows, particularly for products with high technological and environmental content. As China seeks accession to the Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP), understanding the relationship between TBT imposed by CPTPP members and China’s environmental goods exports has significant policy relevance. This study examines the extent to which TBT implemented by CPTPP countries influence China’s exports of environmental goods from 2010 to 2024, drawing on the APEC Environmental Goods List as the basis for product classification. The findings consistently demonstrate that TBT exert a statistically significant and positive impact on China’s environmental goods exports to CPTPP member states. They have meaningful implications for China’s CPTPP accession efforts, suggesting that aligning domestic standards with high-level international norms may transform TBT compliance into a competitive advantage in global green trade.
export trade, Technical Barriers to Trade, environmental goods, CPTPP, China.
The Theoretical Correlation Between Bank Credit Expansion and Financial Vulnerability
The theoretical link between bank credit expansion and financial vulnerability is explored in this paper. The study shows that during economic booms, banks often over-expand credit scale, which, while promoting economic growth in the short term, also accumulates systemic financial risks. The article first reviews key theoretical frameworks such as Minsky's financial instability hypothesis and the financial accelerator theory and analyzes the micro drivers and macro environmental factors of bank credit expansion, and then constructs theoretical models to reveal the intrinsic linkage mechanism between bank credit expansion and asset price fluctuations, rising leverage ratios, maturity mismatch, and liquidity risk. The study also shows that bank credit expansion alters the balance sheet structure of economic entities, increases the interconnectivity and complexity of the financial system, and thereby raises financial vulnerability. Finally, the article discusses counter-cyclical adjustment mechanisms within the macroprudential policy framework and the role of regulatory tools such as capital adequacy ratios and liquidity coverage ratios in curbing excessive credit expansion, and puts forward policy recommendations such as improving the financial regulatory system, optimizing the credit structure, and strengthening the risk early warning mechanism in the hope of finding a balance between promoting economic growth and maintaining financial stability.
Bank credit expansion; Financial vulnerability; Systemic risk; Financial cycles; Macroprudential policy.
Market Risk of Gold Futures and Gold Spot under Geopolitical Risk
With the heightening financial globalization, the market risk has increased strongly especially at times of geopolitical uncertainty. Gold that has traditionally been considered a safe-haven asset is highly volatile when there is an escalation of geopolitical tensions. Nonetheless, the variability that occurs to the spot and futures markets has not been fully investigated. The paper determines the factor of Geopolitical Risk (GPR) on conditional volatility of gold futures and spot returns by the GARCH-X(1,1) model that incorporates the Student-t innovations. A standardized GPR index is introduced as an exogenous variable in the equation of variance using monthly data between the year 1980 and 2023. We find that, lagged GPR has a positive effect on futures volatility, but that effect is somewhat significant, indicating that futures markets that are more vulnerable to geopolitical shocks are speculative and leveraged derivatives markets. By comparison, the spot market volatility does not exhibit any important effect of GPR, meaning that it is self-enhanced by past shocks. Ljung-Box diagnostics indicate some residual autocorrelation in the futures model, indicating that there is some possibility to refine the model by using alternative GARCH specification, or adding more terms to the mean equation. GARKH-X(t) model is highly suitable in terms of volatility dynamics in the futures, whereas spot volatility is more stable. The study has significant implications on risk management, portfolio hedging policies, and regulatory controls on derivatives markets in times of geopolitical crises.
GARCH-X; Geopolitical Risk; Gold futures; Spot market; Volatility; Value-at-Risk; Conditional heteroskedasticity.
A Review of Research on the Relationship between Macroeconomic Variables and Stock Market Returns
This paper provides a comprehensive review of research on the relationship between macroeconomic variables and stock market returns. Theoretical foundations such as the Capital Asset Pricing Model (CAPM), Arbitrage Pricing Theory (APT), and Discounted Cash Flow (DCF) models explain how macroeconomic factors influence asset pricing through risk premiums, factor exposures, and corporate cash flows. Foreign studies, which began earlier, have developed mature analytical frameworks ranging from linear regressions to dynamic and nonlinear models such as VAR/SVAR, GARCH, and copula functions. Their findings generally confirm stable and significant linkages between macroeconomic indicators and stock returns in mature markets. In contrast, domestic research emphasizes market inefficiency, policy intervention, and investor behavior, employing methods such as cointegration analysis, event studies, and semi-parametric models. Results often reveal weak or stage-specific correlations, reflecting incomplete transmission mechanisms. Overall, macroeconomic variables—including GDP, inflation, money supply, interest rates, and exchange rates—affect stock markets through multiple channels, but the strength and stability of these effects depend on institutional and structural contexts. Future research should incorporate high-frequency data, strengthen expectation and behavioral modeling, refine industry-level analysis, and expand cross-market comparisons to better capture the complex dynamics between macroeconomics and financial markets.
Macroeconomic variables, Stock market returns, Asset pricing models, VAR/SVAR, GARCH, Policy uncertainty.
Comparative Analysis of ARIMA and Random Forest Models for Forecasting COVID-19 Cases in China
The COVID-19 pandemic has had a profound global impact on public health systems and global economic situation, making accurate forecasting of infection cases crucial for formulating effective intervention strategies. This study systematically compares the performance of the ARIMA time series model and the Random Forest machine learning model in predicting daily COVID-19 cases in China from 2020 to 2022. The data was partitioned into training and testing sets for model development and evaluation. Results indicate that the Random Forest model significantly outperforms the ARIMA model across all evaluated metrics, including residual mean, standard deviation, and key error indicators, demonstrating a superior ability to capture the timing and amplitude of infection peaks and troughs. Therefore, the value of this study lies in providing clear empirical evidence for model selection in epidemic prediction, indicating that in the face of complex epidemic data, machine learning models may be more reliable than traditional time series methods.
COVID-19 forecasting, ARIMA model, random forest model, time series, machine learning.
The Shaping Mechanism of Institutional Quality Differences on the Long-Term Economic Growth Path and Its Theoretical Explanation
This paper explores how the long-term economic growth paths of countries are shaped by differences in institutional quality and the underlying theoretical mechanisms, and constructs a comprehensive analytical framework for the impact of institutional quality on economic growth after reviewing relevant literature in institutional economics, new growth theory, and comparative institutional analysis. The research shows that many aspects such as property rights protection, transaction costs, technological innovation incentives, factor accumulation and allocation efficiency are the ways in which institutional quality affects the economic growth path, among which high-quality institutions can reduce uncertainty, provide reasonable incentive structures to promote the effective operation of markets, support innovation activities to achieve sustainable growth, On the contrary, low-quality institutions may lead to rent-seeking, misallocation of resources and thus fall into a growth trap. Further analysis reveals that institutional evolution is path-dependent and that both historical initial conditions and cultural factors act on the direction of institutional change, resulting in a diverse growth trajectory. This study presents a theory of institutional co-evolution from the perspectives of new institutional economics, endogenous growth theory, and comparative political economy, which explains the dynamic interaction between institutional bundles and economic performance, as well as the situation where differences in institutional quality affect innovation, human capital accumulation, and resource allocation efficiency, resulting in sustained development differences among countries. This theoretical framework opens up a new perspective for understanding long-term economic growth disparities and offers policy implications for institutional reform in developing countries.
Institutional quality; Long-term economic growth; Path dependence; Technological innovation; Institutional complementarity.
A Cross-country Study on the Effects of Cultural Tightness on Donation Request Compliance
The world is becoming increasingly dependent on charities to solve inequality and poverty. Charitable giving is a social phenomenon heavily dependent on cultural factors. One such underexplored factor is cultural tightness/looseness (CTL), or the degree to which individuals within a society adhere to the social norm. Prior literature indicated that there may be greater extrinsic motivations for individuals in tighter cultures to comply with donation requests based on very limited data. To verify this hypothesis, we used data from [1] and the 2021 World Giving Index Report across 54 different nations. We then developed a model for the relationship between CTL and the donation request compliance rate in a cross-country study. The model was then adjusted with other factors such as GDP per capita, ethnic tensions, and internal conflicts to improve the accuracy. We find evidence that as the culture is looser, individuals are less willing to comply with donation requests, validating the initial hypothesis and expanding on the external validity of past literature. We reveal a critical link between culture and donor behavior, and we also provide a strong foundation for future research regarding cultural effects on donor behavior at the individual level.
Charitable giving, CTL, Cross-country data.
A study on the consumption experience and evaluation of customers at the Hangzhou cuisine restaurant “Jiuwei”
This study aims to explore the customer experience and evaluation of the Hangzhou cuisine restaurant “Jiuwei” in order to help the restaurant improve its service quality, meet customer needs and enhance its competitive advantage. With the popularity of social media and online review platforms, the impact of customer reviews on the restaurant industry is becoming increasingly significant. This study used methods such as questionnaire surveys, targeted interviews and social media comment analysis to collect and analyze customers’ evaluations of the “Jiuwei” restaurant in terms of food quality, dining efficiency, environmental comfort, restaurant image and service. there is a significant positive correlation between satisfaction, attention and complaint levels in various dimensions of a restaurant and customer loyalty. Specifically, improving restaurant satisfaction in all dimensions can help reduce customer complaints and promote customer loyalty. there are significant differences in restaurant experience among consumers of different ages, genders and educational levels. Younger consumers, female consumers and consumers with a master's degree or above have relatively higher evaluations of restaurants. Based on the research results, this paper puts forward targeted marketing suggestions, including improving restaurant satisfaction in various dimensions, developing differentiated marketing strategies, strengthening customer relationship management and loyalty building, and using social media and online platforms for promotion. These suggestions are designed to help Jiuwei Restaurant better understand customer needs, optimize service processes, and enhance its brand image, thereby standing out in the fiercely competitive catering market.
Hangzhou cuisine restaurants; customer consumption experience; customer evaluation; satisfaction; marketing strategy.
K-pop Fans as Participants in South Korea’s New Public Diplomacy
This paper is situated within the context of South Korea’s strategic deployment of its cultural industries as instruments of soft power and the concurrent global rise of digitally networked participatory fan cultures. It investigates how K-pop fans move beyond passive audiences to actively engage in South Korea’s new public diplomacy, shaping South Korea’s soft power and international image as non-state actors. The research employs a qualitative case study methodology to delve into two different yet complementary fan participation cases—BTS Love Myself Campaign and Kpop4Planet—to illustrate the breadth of fan participation in public diplomacy, from official humanitarian advocacy to grassroots environmental activism. The analysis reveals that through a combination of affect, digital media, and resource-mobilization, K-pop fans participate in South Korea’s new public diplomacy and translate their cultural affinity into tangible diplomatic outcomes, enhancing South Korea’s soft power influence and international image by projecting values of social responsibility and global citizenship. The paper concludes by suggesting the potential tensions within fandoms and the potential conflict between interests of fandom and state or corporate.
K-pop, fans, new public diplomacy, participatory culture, soft power.
The Impact of Exchange Rate Fluctuations on China’s Industrial Stock Prices: An Empirical Analysis
This paper investigates the impact of RMB exchange rate fluctuations on China’s industrial stock prices using daily data from January 1, 2016, to December 31, 2022. A vector autoregression (VAR) model is constructed based on the RMB/USD exchange rate and the Shanghai Industrial Index. The empirical results indicate a long-term cointegration relationship between the exchange rate and industrial stock prices. A depreciation of the RMB tends to drive up industrial stock prices in the short term. The findings support the existence of a positive transmission mechanism from the foreign exchange market to the stock market, particularly within the industrial sector. Policy implications are discussed in the context of exchange rate reform and capital market development.
exchange rate, industrial stocks, VAR model, cointegration, stock price.
The Design and Pricing of a Bull Shark Fin Structured Deposit Linked to the CSI 500 ESG Value Index
In recent years, the concept of sustainable development has gained increasing recognition among the public. Investors are no longer solely focused on investment returns but are also paying closer attention to corporate performance in environmental, social, and governance (ESG) aspects. The ESG investment philosophy emphasizes incorporating environmental, social, and corporate governance factors into investment decisions, aiming for long-term sustainable returns. With the advancement of global sustainable development goals and the growing awareness of investor responsibility, the scale of ESG investments has expanded rapidly, gradually becoming a mainstream investment strategy. Against this backdrop, the ESG investment philosophy has risen swiftly, and related financial products have flourished. As an investment product that balances risk and return, structured deposits have gained significant popularity among investors in recent years. Structured deposits, as innovative financial products, combine traditional deposits with financial derivatives. They not only offer returns higher than those of traditional deposits but also effectively manage risks through embedded options, meeting investors' dual needs for yield and security in a low-interest-rate environment. Among these, structured deposits linked to ESG-themed indices, such as the CSI 500 ESG Value Index, provide investors with a new choice that balances social responsibility and wealth appreciation.
Structured Deposit, CSI 500 ESG Value, Shark Fin.
The impact of corporate targeted poverty alleviation on corporate value
Based on data from A-share listed companies from 2016 to 2020, this paper employs a nonlinear regression model, U-test, and Propensity Score Matching (PSM) method to investigate the impact of corporate participation in targeted poverty alleviation on corporate value. The research reveals a significant positive U-shaped relationship between the intensity of corporate targeted poverty alleviation and corporate value. Specifically, there is an inflection point in corporate value as the intensity of targeted poverty alleviation increases. On the left side of the inflection point, corporate participation in targeted poverty alleviation reduces corporate value; on the right side, it enhances corporate value. Further research indicates that the positive U-shaped relationship between participation in targeted poverty alleviation and corporate value is more pronounced among state-owned enterprises and enterprises located in the eastern region. This paper provides a decision-making basis for enterprises to continue participating in poverty alleviation and offers new empirical evidence for consolidating and expanding the achievements of poverty eradication.
Targeted poverty alleviation, corporate value, property rights nature, regional differences.
Research on the impact of green innovation on stock returns of listed companies
This study examines all listed companies over the past decade, using green patent grants as a proxy for corporate green innovation and annual stock returns with reinvested cash dividends as a measure of stock performance. The empirical analysis demonstrates that green innovation initiatives are recognized by market participants and generate higher stock returns. The positive correlation between green innovation and corporate stock performance indicates that such practices can achieve a win-win outcome in both economic and social benefits.
Green innovation, Stock income, Listed company.
Research on the Relationship Between CPI and the Shanghai Composite Index
Previous literature has primarily used the price-to-earnings ratio method to analyze stock indices. Given the current phenomenon of the inverted relationship between CPI and PPI in China, empirical research on the impact of CPI on stock indices has attracted scholarly attention. Therefore, this paper employs a VAR model, selecting monthly data on CPI and the Shanghai Composite Index (SZZS) from December 2009 to March 2024 for empirical research. Using the VAR model, it is discovered that the first lag of CPI has a positive relationship with the SZZS, while the second lag exhibits a negative relationship. However, this study does not establish a Vector Error Correction Model to verify the long-term impact of CPI on the SZZS.
CPI, Shanghai Composite Index, VAR Mode.
Applications of Artificial Intelligence in the Financial Sector: Current Challenges and Future Directions
As the global financial business becomes more digital, artificial intelligence (AI) has become the main force behind change in the whole industry. This paper’s research object is the application of AI within the financial sector, focusing specifically on the primary challenges this integration presents. This paper systematically and comprehensively examines the application of AI in finance, concentrating on three principal challenges: the absence of transparency and interpretability in model decision-making, excessive dependence on historical data and intrinsic biases, and ethical dilemmas and regulatory delays arising from swift technological progress. This study provides a systematic approach based on building explainable AI (XAI), enhancing data foundations and model robustness, and constructing a comprehensive governance framework through a thorough examination of the underlying causes of these difficulties. It looks at how these solutions will work together and what benefits they will provide, as well as what the future holds for combining AI with new technologies like blockchain and quantum computing. This study seeks to establish a theoretical framework for financial institutions, regulators, and researchers, thereby fostering the healthy, dependable, and sustainable advancement of artificial intelligence in the financial sector.
Artificial intelligence; financial technology; risk management; financial regulation.
The Penetration of Trust and the Reconstruction of Assets: A Deconstruction and Comparative Analysis of Block Chain-Based Accounts Receivable Financing Platform Models
This paper aims to carry out a systematic study on the application of blockchain technology in the field of Accounts Receivable Financing (ARF). The report first peels apart the main pain points of the traditional ARF model (factoring) from the aspect of information asymmetry, transmission of credit and confirmation of rights. Then the report does a thorough analysis on how blockchain technology (especially the characteristics of unchangeable nature, smart contracts, and asset digitization) theoretically solves these pain points, emphasizing the elaboration on the realization path of "penetration of credit". The core of this report is the in-depth study and comparison of four important cases of significance, namely, the "Dual-Chain Connect" of Ant Group, "Yi Enterprise Chain" (YQLink) of Ping An OneConnect, WeBank (based on FISCO BCOS), and "Jing Bao Bei" of JD Technology. Through the comparison of these cases in terms of their business models, technical architecture and risk control mechanism, this report summarizes three mainstream realization mode: "central enterprise-led", "fintech platform-led", and "(digital) bank-led", and reveals their basic difference regarding "source of credit". Finally, the study talks about the common problems confronting the field, such as data silo, interoperability and regulatory uncertainty, and gives its optimistic outlook regarding its future trends of integration into Artificial Intelligence (AI), Internet of Things (IoT), and evolution towards Decentralized Finance (DeFi).
Blockchain, Supply Chain Finance, Accounts Receivable Financing, Credit Penetration.
Resolving the Opioid Crisis in the United States: A Time-series Analysis on the Efficacy of Major Federal Policies
The opioid crisis has emerged as one of the most pressing public health emergencies in the United States, with overdose deaths increasing more than tenfold since 1999. This study investigates the impact of major federal policies on opioid-related harms, with a focus on respiratory depression, the leading cause of opioid overdose mortality. Using data from the FDA Adverse Event Reporting System (FAERS) between 2015 and 2025, the analysis combines opioid distribution and adverse event data into a monthly time series, incorporating key policy interventions as structural breaks. The study evaluates both short-term policy effects and long-term trends through forecasting models like SARIMAX, Prophet, and LSTM. Results indicate that opioid distribution strongly predicts adverse outcomes, with a one to two-month lag, reinforcing the link between prescription practices and patient adverse effects. Policies like the 2016 CDC Opioid Prescribing Guidelines and the 2018 SUPPORT Act produced measurable reductions in adverse event growth, while others had limited statistical significance. The findings emphasize that resolving an epidemic requires a comprehensive strategy that implements both supply control through proper regulations and market control through patient-centered education and harm reduction initiatives.
Opioid crisis; Opioid policy; Respiratory depression; Time-series analysis.
Analysis of California's Accommodation GDP Based on the ARIMA Model
This study focuses on forecasting the future trajectory of California's annual accommodation GDP using an ARIMA model. This study utilizes annual accommodation GDP data for California from 1997 to 2023, comprising 27 observations, sourced from the Federal Reserve Economic Database (FRED) maintained by the Federal Reserve Bank of St. Louis. The ARIMA(1,1,0) with drift model is established and reasonable predictions are made about future changes in California's annual accommodation GDP. In building the model, this study employed a variety of tests, such as the stationarity test of the data, the white noise test of the data, the significance test of parameter estimates, the significance test of the model, etc., to construct the most appropriate model. The model chosen in this study is ARIMA(1,1,0) with drift, and the prediction shows that California's annual accommodation GDP will still show a significant upward trend in the future. Based on the research results, this study proposes that people need to prepare more funds to deal with the rising cost of accommodation in California or look for a partner to share the cost of accommodation.
Time Series Forecasting; ARIMA Model; ADF test; Model Caliber; California's Annual Accommodation GDP.
As the market for fashionable toys is rapidly expanding, several companies are emerging, especially POP MART as a dominant leader. This paper examines the business model, market position and competitive status, and financial condition of POP MART through the SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis. The internal and external considerations leading to the present status of the company will be analyzed through consideration of the internal strengths (business model based upon highly interesting IP, multiple channels of distribution, etc.) internal weaknesses (intense competitive environment, rising cost of IP, etc.). The external opportunities (going abroad and spreading cultural influence) and threats (aesthetic fatigue of IP, regulatory scrutiny, etc.) faced by the company will be analyzed. A comparative financial analysis determining POP MART's financial condition vis a vis a competitive company will be presented, and an evaluation of POP MART's competitive status will be made. It will be suggested that POP MART has a promising growth path ahead, but also has challenges to overcome. The conclusions of this paper will be to forecast the future of the company dependent upon how the company negotiates its challenges so as to achieve its potential for success as the expanding global competitive environment continues to evolve.
Beyond Prohibition: Understanding and Reducing AI Reliance in University Learning
The strong abilities of artificial intelligence have encouraged people to apply it in different areas, especially in education. However, the widespread use of AI makes people start to question whether it can destroy academic integrity, and they want to limit its use on campus. This essay demonstrates the reasons behind this widespread phenomenon and how people can reduce the increasing popularity in the use of AI in universities by analyzing the data from AI Assistant Usage in Student Life by Ayesha Saleem through classification and comparison in sections like outcome distribution, AI assistance level, and whether used again. It turns out that students mainly use AI as a tool to complete assignments, revise essays, and search for information, and these are mainly caused by the imbalance between students’ abilities and assignment difficulty, lack of essay suggestions, and incomplete required information. Hence, universities can better reduce the use rate of AI by altering the assignment level, arranging more sessions for essay revision, and providing more necessary information for study.
Artificial Intelligence; education; students benefit.
Artificial Intelligence in Scientific Research: Opportunities, Limits, and the Engineering Realization of the Data-Driven Paradigm
This paper presents a publication-oriented blueprint for using artificial intelligence in scientific research, written strictly in the format requested and developed as sustained paragraphs rather than bullet points. The central claim is that AI augments, rather than replaces, the scientific method when its use follows a sequence that prioritizes domain structure, leverages learning for acceleration, quantifies and calibrates uncertainty, and secures results through reproducibility and auditability. It articulate four research questions: where AI most productively intervenes within mathematics, physics, chemistry, and cross-disciplinary settings; how order-of-magnitude gains can be realized without violating conservation laws, symmetries, or boundary and initial conditions; how unified evaluation practices, calibration, out-of-distribution (OOD) testing, negative controls, independent verification, distinguish operational value from deceptively high scores; and how to operationalize the entire process as a closed loop connecting data, models, decisions, and new evidence. The analysis section develops, for each discipline, a coherent account of problem formulations, representative methods such as neural operators and physics-informed neural networks, evaluation practices that emphasize physical validity alongside error, characteristic failure modes and mitigations, and the rationale for combining learning with structures. The solutions section translates these ideas into engineering practice, describing structure encoding at architectural and objective levels, probabilistic reporting and calibration, robust OOD testing, closed-loop optimization with laboratory or simulation interfaces, and the governance elements that make findings portable, auditable, and energy-aware. The conclusion integrates these strands into design principles for research programs, courses, and deployments. Throughout, the prose is organized into continuous paragraphs under numbered headings, in line with academic style, while in-text citations follow the bracketed numbering convention.
AI for Science; physics-aware machine learning; neural operator; physics-informed neural networks.
Research on the Collaborative Mechanism of Public Administration and Marketing under the Government Purchase of Services Model
Government purchase services (GPS) model is a significant change in government governance, and the state shifts its role of service "provider" to "purchaser" and "regulator". In the past, this transition was usually examined through the perspective of public administration (PA), which focuses on procurement, contract management, and efficiency and accountability. But this is often missing the fact that marketing is very important. This paper contends that the efficacy and public value of GPS hinges much on an intricate, although presently undeveloped, collaboration between public administration and marketing. We believe that PA and marketing are not separate processes, but rather should become an integral part throughout the entire life span of GPS. In this research, a theoretical model of synergy is conceptualized based on 4 nodes of collaboration identified. These include: (1) Incorporating market research in policies and services; (2) Aligning PA’s performance metrics with marketing’s focus on service quality and citizen satisfaction; (3) Governing public value co-creation via integrated brand management; and (4) Shifting stakeholder management into a comprehensive relationship marketing strategy. The points of collaboration looked at in this paper indicate that a model is possible wherein the focus on control and accountability of PA is enhanced by the focus on the responsiveness and relationships of marketing. This type of mechanism is being made important for making services work better, earning people’s trust, and doing real good for the public as the world of running things gets more complicated.
Government Purchase of Services (GPS), Public Administration, Public Sector Marketing, Collaborative Mechanism, Public Value, Service Efficiency.
Between Crisis and Militarism: Japan’s Interwar Struggle for Economic Stability and Democratic Survival
This study examines Japan's socioeconomic and political dynamics during the interwar period (1918–1939), revealing the interplay of global economic dislocation and internal institutional fragility. Despite post-WWI industrial growth, Japan faced domestic overproduction, inflation, and rising inequality, exacerbated by the Great Depression and the 1927 Shōwa Financial Crisis. Rural areas suffered from plummeting commodity prices and debt, while urban unemployment and labor unrest soared, eroding trust in democratic governance. Politically, democratic experimentation coexisted with entrenched patronage systems, enabling military influence and corruption. Policy responses evolved from fiscal austerity and gold standard adherence to expansionary measures and structural reform proposals, including land redistribution, financial regulation, and industrial diversification. However, implementation faced elite resistance and geopolitical constraints, leading to militarist escalation. Comparative analysis with Sweden’s social democratic model highlights alternative pathways to stability. The study concludes that Japan’s failure to enact inclusive reforms propelled it toward total war, underscoring the critical linkage between economic equity, political legitimacy, and social cohesion in avoiding fascist-militarist trajectories.
Japan, Economic crisis, Interwar period.
The Impact of ESG Ratings on Corporate Debt Financing Costs: A Cross-Regional Comparison of the European Union, the United States, and China
This study aims to explore how the environmental, social and governance (ESG) performance of enterprises affects their debt financing costs, and to conduct a cross-regional comparative analysis of the European Union (EU), the United States (US), and China from the perspectives of policies, markets, and mechanisms. Research has found a significant negative correlation between ESG performance and the cost of corporate debt financing. Specifically, the European Union, with its strict and precise rule-oriented regulation and mature ESG market system, has the strongest inhibitory effect of ESG on debt costs; the United States, due to the differentiation of federal and state-level regulation, highly politicized market, and rating differences, has a slightly weaker impact of ESG; China's ESG market is still in its early stage of development, characterized by policy-driven approaches. The impact of ESG on debt costs mainly manifests in the availability of financing and interest rate discounts, and its overall intensity is weaker than the former two. This study can provide reference for the improvement of China's ESG market and corporate debt financing decisions.
ESG; Cost of Debt Financing; Cross-Regional Comparison.
Longevity Hedging for Dutch Pensions: q‑Forward Fair Value vs. Cost‑of‑Capital Pricing under the CBD Model — Expanded with APA Citations
This paper studies longevity hedging for Dutch pensions using strips of q‑forwards that linearly transfer mortality risk to capital markets. We link demographic forecasting to market‑consistent hedging and compare fair q‑forward rates with Solvency‑II Cost‑of‑Capital (CoC) loaded rates to provide a consistent pricing yardstick Mortality for ages 65–74 is bucketized and projected for 2011–2040 using models from the Lee–Carter/CBD family to obtain expected death probabilities by year. Discounting uses the EIOPA EUR no‑VA curve smoothed to enforce monotonicity in discount factors to avoid spurious humps from interpolation noise. A static strip of q‑forwards is calibrated to match first‑order sensitivities of the liability present value with respect to expected q to deliver linear risk neutralization. Monte‑Carlo experiments apply multiplicative shocks to expected death probabilities to quantify hedge effectiveness under several volatility scales that emulate modelling uncertainty. Using the monotone discount curve, the base PV equals 19.956423 and the unhedged standard deviations of ΔPV for σ=5/10/15% are 0.0557/0.1122/0.1673 while the hedged standard deviations shrink to 0.00012/0.00051/0.00113, implying HE of 99.9995%/99.9979%/99.9955% consistent with first‑order theory. We discuss economic materiality via 95% ranges, robustness to σ, the importance of discount‑curve monotonicity, sparse‑strip implementability, and a mapping from Solvency‑II CoC risk margins to q‑forward premia for price benchmarking.
Longevity Hedging; Q‑Forwards; Mortality Risk; Solvency II.