ISSN 2960-1312(Online) Editor: Ji Chen (Denver University), Alexei (Columbia University), Aytek Erdil (University of Cambridge), Cosimo Arnesano (University of Southern California), Freya Baetens (Cambridge University), Osman (Carnegie Mellon University) Finance & Economics serves as a dynamic platform for scholars, practitioners, and students to exchange their latest research and insights in the fields of finance and economics. The journal stands out for its comprehensive coverage, spanning traditional topics such as investment, banking, and financial markets, as well as emerging areas like behavioral finance, fintech, and sustainable finance. This broad scope ensures that readers stay informed about the most relevant and cutting-edge developments in the discipline. Additionally, Finance & Economics places a strong emphasis on the practical applications of research, fostering studies that offer real-world implications for policy formulation and business decision-making. This commitment to bridging theory and practice makes it an essential resource for professionals in finance and economics.
Research on the influence of venture capital on enterprise innovation
In recent years, against the backdrop of increasingly fierce market competition and continuous technological development, venture capital has had a very important role in influences enterprise innovation. Firstly, this study defines the concept and characteristics of venture capital; Secondly, it explains the function of venture capital in enterprise financing, enterprise merger and acquisition, and enterprise innovation. Then, it analyzes the influence of venture capital on enterprise innovation as well as illustrates it with examples. The results show that venture capital has a significant positive impact on enterprise innovation and promotes high-quality economic development. This study aims to discuss the influence of venture capital on enterprise innovation through case analysis and provide a reference for enterprises and investors.
Starbucks Investment Analysis, WACC and Portfolio Optimization
This essay presents an integrated financial analysis through three distinct lenses: corporate finance, portfolio theory, and behavioral economics. First, a case study of Starbucks Corporation estimates its Weighted Average Cost of Capital (WACC) at 8.58% and demonstrates, through the evaluation of a recent acquisition, how strategic investments can create shareholder value by exceeding this hurdle rate. Second, employing quantitative portfolio analysis, we construct a minimum-variance portfolio for three hypothetical assets and recommend an optimal allocation for a risk-averse investor, highlighting the benefits of diversification. Finally, the paper critically examines the limitations of standard asset-pricing models by analyzing proposed U.S. legislation on capital gains exemptions for primary residences. We argue that real-world frictions—such as discrete policy changes, psychological biases like nominal loss aversion, and the consumption-hedging dual role of housing—create market dynamics that classical theories cannot fully explain. Collectively, this synthesis underscores the necessity of complementing quantitative models with insights from behavioral and institutional economics to achieve a more nuanced understanding of financial decision-making in practice.
Evaluate Amazon’s HWM department using the five factors Framework
This study evaluates Amazon’s Human Resource Management (HRM) strategies using a five-factor analytical framework. It examines how external environmental factors, workforce demographics and skills, organizational culture, strategic alignment, and technological integration influence HR practices. The analysis highlights Amazon’s proactive initiatives, including diversity programs such as Amazon Future Engineer and Women in Amazon Engineering, as well as employee development offerings like Amazon Career Choice. These efforts align with the company’s customer-centric mission and support innovation and global expansion. However, the report also identifies critical challenges, such as workplace safety concerns, high-pressure environments, and the mixed impacts of automation. Recommendations emphasize enhancing transparency, expanding wellness programs, and strengthening social responsibility initiatives to improve employee well-being and organizational sustainability. Overall, Amazon’s HRM effectively supports strategic objectives but requires continued refinement to address employee satisfaction and operational ethics.
Impact of COVID-19 Containment Measures on Labor Force Participation
The COVID-19 pandemic led governments to implement containment measures that reshaped labor market conditions worldwide. In this paper, I examine how the severity of these containment policies affected labor force participation, which captures both employment and job-search activity and therefore reflects broader labor market engagement than unemployment alone. Using 152 country-quarter observations from 2020, drawn from the Oxford COVID-19 Government Response Tracker and the World Bank, this study applies a simplified difference-in-differences model with macroeconomic controls and finds that higher containment stringency is associated with lower labor force participation, with an estimated coefficient of around −0.10 (p < 0.01). Inflation is negatively associated with labor force participation, while GDP growth shows a small positive relationship, and these estimates remain stable after adding the additional covariates. Taken together, the results indicate that stricter containment policies contributed to labor market withdrawal during 2020, underscoring the importance of using participation-based measures when assessing the broader economic effects of pandemic response policies.
The Empirical Test of the Fama–French Three-Factor Model in the Chinese Stock Market
This paper examines the applicability of the Fama–French (1993) three-factor model in China’s A-share market. Using monthly data from September 1999 to June 2022, we estimate time-series regressions of excess returns on six representative Chinese A-share stocks on the market factor, the size factor, and the value factor. The evidence shows that the market factor is highly significant for all six stocks, the size factor is significantly positive for four of them, while the value factor is not statistically significant in any case. All estimated intercepts (alphas) are large and negative. These results suggest that the Fama–French three-factor structure captures important market and size-related components of risk in the Chinese stock market but does not fully reconcile realised returns with model-implied expected returns.
Theoretical Framework and Empirical Analysis of Modern Household Asset Allocation
Based on modern portfolio theory, this paper constructs an asset allocation analysis framework applicable to the Chinese market. Using quantitative analysis methods, it compares the risk-return characteristics of different asset classes and introduces the Sharpe ratio for risk-adjusted performance evaluation. The research results indicate that in the current market environment, a diversified investment portfolio can effectively balance risk and return, providing investors with superior risk-adjusted returns. This study offers a systematic asset allocation decision-making method for individual investors.
The Impact of Digital Transformation and Corporate Cost Efficiency: Evidence from China’s A-Share Listed Firms
This study aims to investigate the impact of digital transformation on corporate cost efficiency and its underlying mechanisms. In relate to panel data from Chinese A-share listed companies for the period 2007-2022, we construct a Digital Transformation (DT) indicator using a keyword-based method and measure cost efficiency using metrics such as the input-output efficiency of main business costs. Furthermore, this study introduces variables including financing constraints, industry technological intensity, and property rights nature to examine the pathways through which digital transformation affects cost efficiency. A review of the literature reveals that existing research predominantly focuses on the impact of digital transformation on investment efficiency, innovation performance, or cost stickiness (e.g., Wu et al., 2021; Liu et al., 2025; Chen & Xu, 2023), with less attention paid to the perspective of cost efficiency, particularly lacking research on the cost channel within the Chinese context. Grounded in agency theory and technological innovation theory, we propose four hypotheses: Digital transformation significantly enhances corporate cost efficiency (H1); Financing constraints weaken the promoting effect of digital transformation on cost efficiency (H2); The effect of digital transformation is stronger in high-technologyintensive industries (H3); Property rights nature moderates the effect of digital transformation (H4). Empirical results indicate that digital transformation has a significant positive impact on cost efficiency, but this effect is attenuated in contexts of high financing constraints or non-technologyintensive industries. The research conclusions enrich the theoretical perspective on the relationship between digital transformation and corporate performance and provide insights for enterprises implementing digital strategies and for governments formulating relevant policies.
Framing the Bicultural Consumer: How Language and Group Identity Shift Loss Aversion in Marketing
Companies find it difficult to synchronize their messages with the oscillating sense of identity of the bicultural consumer that experiences a rapid change in identity, depending on situations. The paper has suggested a Cultural Nudging Framework that is shaped by two main ideas: loss aversion (the fear of losing something valuable) and bicultural frame switching (the inclination to alternate the views between the cultural identities). Studies show that subtle cues, such as the language used in an advertisement, can activate either a Collectivist (grouporiented) or Individualist (self-oriented) mindset. Once triggered, this shift alters what the consumer perceives as the real loss, which could be financial, social, or familial. The framework that’s been proposed in this paper offers marketers a practical way to align their message with a bicultural consumer shopping interests. This alignment becomes critical in that it turns a segment that is usually missed into a very responsive segment. Through the conscious use of linguistic cues, marketers will be able to circumvent the vagueness of a dual identity and simply exploit the currently hegemonic value system of the consumer. The focus of this paper consists of a main introduction to the world of applied cultural psychology as a prescriptive marketing voice, which introduces a blueprint of what more accurate and more effective crosscultural communication entails. More importantly, the framework does not discuss the simple language ONtranslation, but rather a more effective and detailed process of identity triggering. This advanced method makes sure that the perceived emotional significance of the possible loss, which could be an individual material downgrade or a national disgrace, is overdramatized and will cause the persuasiveness of the message to increase many times over.
The Green-Inclusive Paradox in the Digital Economy: Technological Progress, Sustainable Development, and Social Stratification
While driving socioeconomic development, the digital economy is also having a profound impact on social inequality. Research shows that digital technology exacerbates social stratification through mechanisms such as skill-biased progress, platform monopolies, and the digital divide. This is manifested in several ways: skill premiums, technological displacement, and digital rent differentiation in income distribution; polarization trends, algorithmic control, and flexible employment inequality in the labor market structure; and disparities in digital access, capabilities, and resources in educational opportunities, which reinforce the intergenerational transmission of inequality. Empirical analyses indicate that while the digital economy may temporarily narrow income gaps through inclusive effects in the short term, its skill-biased nature and digital divide effects are likely to further exacerbate social stratification in the long run. Therefore, we should embed “inclusive digital development” at the core of sustainable transformation, ensuring the digital economy serves as an accelerator for the SDGs rather than a new engine of division.
Digital Disruption in Asset Pricing: Reexamining CAPM Assumptions in Platform Economies and Algorithmic Trading Era
We examine the theoretical impact of digital technologies on the CAPM and trace the pathways through which these technologies reshape asset pricing mechanisms. Findings reveal that the rapid development of platform economies and algorithmic trading is challenging the three core assumptions of CAPM: market efficiency, investor rationality, and mean-variance preferences. Digital technologies have reconfigured asset pricing mechanisms by altering market microstructure, reshaping risk-return relationships, and introducing novel pricing logic channels. Empirical results indicate that digital transformation exerts a significant positive impact on firm value but a negative effect on short-term asset returns, revealing the limitations of traditional CAPM in explaining asset pricing in the digital era. This study offers a new theoretical perspective for understanding asset pricing patterns in the digital finance era, providing important implications for investment practice and financial regulation.
Strategic Analysis and Synergy Research of BYD’s Greenfield Investments in Southeast Asia
This paper focuses on BYD’s greenfield investment strategy in Southeast Asia. Using the OLI (Operational Licensing Inequality) theory of international production, it deeply analyzes the underlying logic behind the company’s investment decisions and explores the driving and synergistic role played by the tourism industry in this process. The results indicate that BYD ultimately chose the greenfield investment model, leveraging its advantages in ownership, location, and internalization. Southeast Asia’s developed tourism industry, in terms of consumer education, improved infrastructure, and an optimized policy environment, provided key support for BYD’s local market expansion. Together, these two factors fostered a virtuous cycle of “industrial investment - green transformation - tourism upgrading.” Furthermore, this paper identifies BYD’s current internal and external challenges and potential risks, and proposes corresponding practical recommendations and future research directions. The paper hopes to provide theoretical support and practical guidance for Chinese new energy vehicle companies in expanding into overseas markets.
Analysis of Bilibili’s Profit Model and Financial Risks
This article primarily examines the financial status and operational model of Bilibili in 2024, and provides a detailed analysis of the strengths and weaknesses of its profit model. The study finds that although Bilibili has achieved revenue growth through diversified income sources, it still faces issues such as profit pressure and slowing user growth. This article delves into risks from aspects such as advertising dependence, user churn, and fluctuations in the gaming business, and proposes countermeasures such as optimizing the content ecosystem, expanding into international markets, enhancing the monetization efficiency of creators, and improving the cost structure. The aim is to provide references and directions for improvement for Bilibili’s future business strategies.
Research on the Path of Monetizing the Commercial Value of Sports Stars
As one of the hotspots of attention in today’s society, sports stars have been the subject of multiple studies by scholars on their commercial value. However, there is a lack of explanation and organization regarding the process of how the commercial value of sports stars is converted into final income. Therefore, this article will investigate the pathways for the monetization of sports stars’ commercial value. The research method of this paper is to review and analyze the literature. The study finds that, firstly, “commercial endorsement” and “commercial activities” are suitable for sports stars to monetize their commercial value in the short term. Secondly, “IP operation” can help sports stars achieve flexible operation and maintain initiative in the process of monetizing their commercial value, while yielding higher and more sustainable final returns. Furthermore, “IP operation” is the more important pathway. Based on the research results, the author suggests that sports stars should choose the appropriate pathway for monetizing their commercial value according to their own needs; in addition, sports stars should pay attention to the operation of their personal IP.
Fan Participation and the Mechanism of Commercial Revenue in Professional Football Clubs: A Case Study of Beijing Guoan Football Club
Professional football clubs in China’s commercially driven league use fan engagement as their source of revenue, since broadcasting rights are still limited. This paper investigates how Beijing Guoan FC transforms fan participation into commercial gains in a systematic “Engagementto- Earnings” process. Based on the three-level model of fan engagement (pleasurable, symbolic, and central) and the peculiar Chinese digital ecosystem, the research finds that symbolic identity and digital participation are the main drivers. Symbolic attachment to the club as a civic symbol reinforces brand attachment and makes comarketing and merchandise sales more profitable. Digital engagement using WeChat, Weibo, and livestreaming allows the expansion of the revenue funnel outside the stadium, through direct e-commerce and membership drives. Beijing’s infrastructure and market scale lead to compounding of these benefits. This case study provides an obvious mechanism for how clubs in markets where there is little broadcast income can use identity and digital platforms to translate cultural influence into sustainable commercial value.
From “Flash Crashes” to “GameStop”: Paradigm Shift in Algorithm-Driven Market Crises
This paper examines the paradigm shift in financial market crises during the era of algorithms and social media, using the 2010 “Flash Crash” and the 2021 “GameStop” incident as comparative case studies. The research reveals that the driving mechanisms of market crises have evolved from the old paradigm dominated by technical failures in institutional algorithms to a new paradigm fueled by retail algorithmic trading and emotional resonance amplified by social media. This paradigm shift is driven by three structural forces: technological democratization, the information dissemination revolution, and cultural paradigm shifts. It manifests in fundamental transformations: crisis agents shifting from institutions to retail investors; core drivers transitioning from mathematical logic to social psychology; communication channels evolving from specialized networks to public squares; and crisis forms changing from systemic shocks to targeted explosions. This paradigm shift poses profound challenges to financial stability: it leads to the “diffusion” of risk sources, the ‘malfunction’ of classical theories, and the “defocusing” of traditional regulation. To address these challenges, this paper constructs a multi-dimensional agile governance framework based on three pillars: technology empowerment, platform accountability, and mechanism reconstruction. This framework aims to tackle new market risks and provides theoretical insights and practical pathways for regulating financial markets in the digital age.
The Evolution of Pricing Power: A Paradigm Shift in Virtual Asset Valuation Driven by Algorithms and AI?
This study constructs a theoretical framework for algorithm-driven pricing, revealing how algorithms fundamentally reshape pricing logic across three dimensions: market structure, equilibrium mechanisms, and value discovery. Automated market makers algorithmize pricing mechanisms through mathematical functions, arbitrage algorithms become micro-level mechanisms for market equilibrium, and AI prediction models pioneer a new data-driven paradigm for value discovery. Simultaneously, algorithmic pricing has triggered deepseated contradictions, including the restructuring of systemic risk, shifts in power dynamics, and regulatory efficacy dilemmas. The homogenization of algorithmic consensus, positive feedback loops, and oracle dependency constitute novel sources of vulnerability. Meanwhile, the democratic paradox of code governance and the implicit concentration of algorithmic power pose fundamental challenges to traditional financial governance frameworks. Consequently, establishing a new governance framework tailored to algorithmic finance is urgently needed. This research breaks through the explanatory boundaries of traditional financial theory, offering a fresh analytical perspective for studying price formation mechanisms in the digital finance era.
The Impact of E-commerce on the Financial Performance of Small Enterprises: Evidence from Official Trade Data
This research conducts a quantitative evaluation of how the adoption of e-commerce influences the financial performance of Small and Medium-sized Enterprises (SMEs), We utilize a comprehensive panel dataset sourced from U.S. official trade statistics spanning from 2018 to 2024, One crucial challenge we confront is selection bias, that is, more prosperous firms might be more likely to embrace e-commerce. To handle this issue, we integrate Propensity Score Matching (PSM) with a Differencein- Differences (DID) framework, This methodological approach aims to identify the causal impact of e-commerce adoption, The research findings are notable. Compared to a meticulously selected control group, the adoption of e-commerce is associated with approximately a 15.2% rise in revenue growth and simultaneously a 5.8% decrease in operational costs, This twofold effect leads to a substantial enhancement in overall profitability, Our results offer solid, data-based evidence for the transformative significance of digital platforms. They also highlight the importance of formulating policies that can expedite the digitalization process of SMEs.
Small and Medium-sized Enterprises (SMEs)
Family Strategy with Professional Execution: Improving Daily Reliability in Family-Owned Service Small and Mediumsized Enterprises
Decision-making power shared between owners and frontline employees influences daily reliability in family-owned service Small and Medium-sized Enterprises(SMEs). This paper proposes a model termed “Family Strategy with Professional Execution” and undertakes a comparative analysis against over-centralized family control. On-time task completion (finishing routine tasks within a target window) is used as a practical, observable indicator. Three hypotheses are articulated regarding delegation, service intensity, and role clarity. The approach integrates a literature review with a documented before–after case of Din Tai Fung to illustrate how standard operating procedures (SOPs) and bounded frontline authority can reduce waiting, stabilize customer journeys, and improve completion. Contexts of highest effectiveness are clarified—particularly service segments with relatively homogeneous demand and brand sensitivity to service quality. A measurement framework and actionable implications are outlined for future empirical tests.
The Challenges of Aligning Green Finance with SMEs under the Dual Carbon Goals and the Resolving Role of Supply Chain Finance
In the context of global initiatives to address climate change and advance the agenda of sustainable development, the “carbon neutrality” objective is exerting a profound impact on socio-economic transitions. Small and medium-sized enterprises (SMEs), as a vital component of the national economy, play a pivotal role in the realization of the “dual carbon” goals. This paper examines the integration of green finance and supply chain finance as a mechanism for enhancing SME ESG performance and drive sustainable development by alleviating financing constraints and optimizing resource allocation. It analyzes the current development status and inherent challenges within the green finance system, outlines the structural barriers that SMEs face in green transformation, and constructs a theoretical framework for how supply chain finance impacts SME ESG performance. The study concludes that by leveraging the credit strength of core enterprises, mitigating information asymmetry, and enhancing supply chain coordination efficiency, supply chain finance can effectively channel green capital to SMEs and systematically elevate their ESG standards across environmental, social, and governance dimensions.
The Influence of Merchant’s Marketing Strategies on Consumers’ Decision
In today’s consumer market, advertisements have become increasingly pervasive, serving as a crucial bridge between merchants and consumers. However, many of these advertisements are designed not merely to inform but to persuade—often in ways that may mislead individuals into making purchases they might otherwise avoid. Consumer purchasing decisions are highly susceptible to external influences, with advertising being one of the most powerful. Among the psychological mechanisms leveraged by marketers, the framing effect stands out due to its close connection with loss aversion—a cognitive bias in which potential losses exert a stronger emotional impact than equivalent gains. The findings reviewed in this study suggest that the framing effect can significantly distort consumer judgment, reinforcing the asymmetry between risk aversion and risk seeking. The conclusion emphasizes that while framing is an effective marketing strategy, consumers must adopt critical awareness and decision-making strategies—such as evaluating numerical information independently of its wording—to mitigate undue influence and make more rational purchasing decisions.
Overview and application of Endowment Effect, Anchoring and Hindsight Bias
This paper systematically examines three core cognitive biases in behavioral economics: the endowment effect, anchoring effect, and hindsight bias, delving into their respective applications and impacts across diverse economic scenarios. Research indicates that the endowment effect causes individuals to assign higher value to possessions they already own, exerting a significant influence on investors’ stock-holding behaviors and the formulation of environmental policies. The anchoring effect reveals the significant influence of initial information on judgments, manifesting prominently in areas such as real estate pricing, art auctions, and project management—even affecting the estimation behaviors of professional practitioners. Hindsight bias manifests as an overestimation of the predictability of outcomes after they become known, subsequently influencing entrepreneurs’ reflections on failure, judgments of audit responsibility, and investors’ ability to learn from market dynamics. This paper employs a literature review methodology to systematically synthesize existing empirical research. It not only provides a theoretical foundation for understanding irrational factors in economic decision-making but also offers robust empirical support for policymakers, facilitating the development of more effective market mechanisms and behavioral intervention strategies.
Research on the Application of Security- Weighted Aggregation in Federated Learning for Financial Risk Control
Federated learning is a privacy-preserving distributed machine learning approach that enables collaborative training by keeping data local and sharing only model parameters. This effectively addresses the challenges of “data silos” and privacy regulations in the field of financial risk control. This paper systematically elaborates on the concepts, development history, architecture, and core mechanisms of federated learning, with a focus on analyzing the principles and implementation of security- weighted aggregation technology, including its reliance on key technologies such as homomorphic encryption, differential privacy, and secure multi-party computation. Besides, this study examines how this technology applies to fintech, outlines common practices, and highlights challenges in technical performance, cross-platform collaboration, and compliance, with possible solutions. The results show that federated learning, using secure aggregation, enables the financial industry to share data and conduct joint risk modeling while staying compliant.
The Impact of Housing Price Fluctuations on Family Fertility Decisions in Modern China: A Review of Theoretical Mechanisms and Empirical Evidence
This study examines the intricate relationship between housing price fluctuation and household fertility decisions in present-day China, with a focus on the Guangdong- Hong Kong-Macao Greater Bay Area. The article creates a theory called the “dual-effect” that is based on the existing literature and that is made up of two components: a wealth effect and a crowding out effect, in light of that the area has a historically low total fertility rate at the same time as their housing market has unpredictable swings. The literature contains significant gaps, especially with respect to the non-attention to price volatility, and the regional institutional variety. We will use a hybrid research design, consisting of surveys, interviews, and policy research. The research aims to reveal particular mechanisms through which housing market characteristics affect fertility decisions. The research results will provide a comprehensive theoretical framework. There will be evidence-based, unified policy implications on housing stability and population sustainability in a high cost urban agglomeration.
Artificial Intelligence Reshaping the Business Model of the Streaming Media Industry: A Case Study Based on Netflix
Against the backdrop of the vigorous development of the digital economy and the rise of the Artificial Intelligence (AI) industry, streaming media platforms have developed rapidly. The text aims to analyze how the recommendation algorithms of AI contribute to reducing transaction costs with users, alleviating information asymmetry, achieving long-tail effects, and the future development direction of enterprises. This paper is based on the Netflix streaming media platform, which generates personalized homepage recommendations with the help of AI by analyzing users’ viewing time, rating, pause, fast forward and other data. This not only reduces the decision-making cost of users in massive content, but also improves the retention rate and subscription tendency of platform users, and also provides big data reference for the subsequent film and television production of enterprises-the client realizes the transformation from traditional on-demand to customized recommendation, and the enterprise integrates the user behavior information of the whole platform with AI to clarify the production direction. This paper adopts case study method, takes Netflix as the core analysis object, and combines its financial performance report, industry journals and literature to explore the fundamental reshaping of the business model of streaming media industry by AI from the aspects of production, distribution and profit model under the digital economy.
Analysis of the Wage-CPI Relationship Under the California Wage Privacy Act Based on DID Model
In 2018, California initiated the implementation of the California Wage Privacy Act, which aims to promote gender and racial equality in employment issues. This paper explores the impact of the implementation of this law on the relationship between wages and the Consumer Price Index (CPI). The research employs a Difference-in- Differences (DID) model, utilizing annual data from 2015 to 2024 sourced from the U.S. Bureau of Labor Statistics and the Federal Reserve Bank of St. Louis. The data from Los Angeles, serving as the treatment group, is used for comparison with the data from four control cities-Boston, Chicago, New Jersey, and St. Louis. Empirical results indicate that although visual analysis shows that the policy has mitigated the wage-CPI relationship in Los Angeles, the key coefficients in the DID model are not statistically significant. This suggests that the impact of the policy on the overall CPI through channels such as increasing wage transparency and reducing the anchoring effect may be limited. Further research reveals that the influence of wage transparency legislation may be more pronounced within specific industries rather than at the overall economic level. This provides an important reference for evaluating the macroeconomic impact of labor regulations and suggests that the policy effects may be more evident at the industry level rather than the overall economic level. Therefore, this paper recommends that policymakers consider formulating industry-specific regulations and establishing a dynamic monitoring system to better evaluate and guide policy effectiveness.
The Impact of Environmental Performance on the Debt Cost
This study aims to explore whether enterprises with stronger environmental performance can benefit from lower debt financing costs, and it pay particular attention to the possible differences between high-pollution industries and low-pollution industries. The study utilized a panel dataset of 255 US-listed companies from 2010 to 2023, combining Compustat financial data with MSCI ESG environmental performance scores. Debt costs are calculated from dividing interest expenses by total debt. The model also uses enterprise size, leverage ratio and profitability as control variables. Mitigate unobserved heterogeneity by estimating panel regression that includes fixed effects of enterprises and years. The results of the baseline model indicate that there is a significant negative correlation between environmental performance and debt costs, suggesting that creditors tend to offer more favorable financing to enterprises with stronger environmental practices. The interaction model did not find significant differences in high-pollution industries, while sub-sample regression showed that this relationship was stronger and more stable among enterprises in low-pollution industries. These findings suggest that the financial benefits brought by environmental responsibility are obvious, but their intensity may depend on the industry context. This study contributes to the literature in the ESG and corporate finance fields by providing strong evidence that environmental performance can reduce debt costs, highlighting its strategic importance to managers and policymakers.
When Green Mission Meets ESG Ratings: An Event Study of Tesla’s Market Reaction
As global inves tment preferences shi f t toward environmental and sustainability factors, ESG ratings are becoming an increasingly important factor in investment decisions. Many existing studies have confirmed the correlation between ESG ratings and corporate financial performance, but in-depth discussion on the “paradox” of companies such as Tesla, which make outstanding contributions in core environmental protection areas but perform poorly in overall ESG ratings, is limited. This paper takes the event of Tesla being removed from the S&P 500 ESG Index on May 18, 2022, as the research object, and adopts the event study method to analyze the stock price changes in the event window period ([-5, +5] trading days) and the later period (30 trading days after the event). Results indicate that there is no significant abnormal return before the event date, suggesting that the information was not leaked in advance, while after the event, the largest negative abnormal return occurs on the second trading day after the event, reflecting the rapid market reaction to ESG information and the negative impact of the event on firm valuation. This study supports the view that ESG information is value-relevant and provides an empirical basis for incorporating ESG factors into investment decisions.
Family Business Governance Evolution during Intergenerational Succession
Intergenerational succession stands as one of the most complex and defining junctures in the life cycle of family enterprises. It is during this phase that the firm’s governance structure, management philosophy, and cultural underpinnings undergo rigorous testing and strategic transformation. As control shifts from the founder to the successor generation, family firms must evolve from relationship-oriented, centralized models of governance toward more institutionalized, professional systems capable of balancing family values with business efficiency. By drawing on socioemotional wealth (SEW) theory, institutional theory, and agency theory, this study develops a multi-dimensional analytical framework to examine the evolutionary trajectory of governance during intergenerational succession. It focuses on the interaction between emotional attachment and rational management, exploring how family cohesion, successor capability, and external pressures collectively delineate governance outcomes. Using China’s Midea Group as the primary case and Fotile Group as a comparative reference, this paper identifies three dominant governance pathways of family firms during intergenerational succession—progressive hybridization, transformative professionalization, and conservative family reinforcement. These findings underscore that sustainable intergenerational transition necessitates the harmonization of socioemotional wealth with institutional adaptation.
The Correlation Between Business Management Methods and Enterprise Economic Benefits
In the fierce market competition, enterprises take improving economic benefits as their core goal. There is a close correlation between business management methods and economic benefits, and scientifically appropriate management methods are crucial to the development of enterprises at different stages. This paper aims to study the practical application of business management methods in enterprises, explore the feasibility of these methods, and analyze the gaps in daily research. By integrating literature and theories related to business management methods and conducting comparative case analysis, this paper systematically sorts out the implementation paths of typical business management methods, proposes the research theme of the correlation between business management methods and enterprise economic benefits, and empirically analyzes the specific impact of business management methods on enterprises. The experimental results show that scientifically appropriate business management methods can increase enterprise economic benefits by an average of 15% to 20%. The research conclusions reveal the positive driving mechanism of business management methods on enterprise economic benefits, providing a theoretical basis and practical reference for enterprises to enhance their core competitiveness by optimizing management models.
The Long-Term Impact of Push Notification Timing and Frequency on Customer Loyalty: A Causal Analysis of ROI and User Behavior
This study investigates the causal effects of promotional push notifications on short-term ROI, long-term retention, and user heterogeneity. Results show that while promotions drive short-term revenue growth (H1), these effects are mediated by repeat purchases (H2) and fail to sustain longterm loyalty (H3). Theoretically, this work bridges the gap between short-term promotional gains and lasting customer outcomes, while practically emphasizing precision targeting to maximize ROI and preserve loyalty. Despite limitations in proxy user identification, dataset generalizability, and potential confounding, the study highlights future directions such as real user data, randomized testing, multichannel strategies, and adaptive algorithms to balance immediate profit with enduring engagement.