Simon Owen Academic Proceedings Series is an international, refereed, double-blind peer-reviewed, open-access journal that compiles the proceedings of academic conferences, workshops, and symposia across various disciplines. The series highlights groundbreaking research, emerging trends, and innovations presented by scholars, researchers, and practitioners in their respective fields. With a focus on high-quality contributions, the series serves as a valuable resource for the academic community, facilitating the dissemination of knowledge, fostering collaboration, and offering insights into the latest developments in science, technology, and academia.
Challenges and Countermeasures in Accounting Informatization for Small and Medium-Sized Enterprises
With the rapid advancement of information technology, accounting informatization has emerged as a crucial strategy for small and medium-sized enterprises (SMEs) to enhance managerial capabilities, optimize resource allocation, and strengthen market competitiveness. Despite its potential, SMEs continue to encounter numerous challenges in implementing and applying accounting informatization, including weak technical infrastructure, limited financial investment, low system integration, data security vulnerabilities, and insufficient professional talent. This study employs a combination of literature review, case analysis, and questionnaire survey to provide a comprehensive assessment of the current state of accounting informatization among SMEs, systematically identifying existing issues and examining their root causes. Based on these insights, the paper proposes a series of innovative countermeasures, such as designing a tiered informatization development strategy, integrating cloud accounting and artificial intelligence technologies, enhancing data security frameworks, streamlining accounting business processes, and establishing cross-departmental information-sharing mechanisms. The findings suggest that through strategic technological investments and optimized application models, SMEs can not only significantly reduce operational costs but also achieve deep integration between business operations and financial management via data-driven approaches, ultimately securing sustainable competitive advantages in the digital economy era.
small and medium-sized enterprises (SMEs)
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Business Model of a Vegan Food Company in Germany
In the context of the global vegan trend, Germany stands out as a significant contributor to the international vegan food market. This study investigates the business models of German vegan companies, aiming to identify the factors that drive their success, the marketing strategies they employ, and the challenges they face. The research begins by clarifying fundamental concepts, including the definition of business models, and outlines analytical tools such as the Business Model Canvas, which encompasses nine dimensions: customer segments, customer relationships, channels, revenue streams, key activities, key resources, key partners, cost structure, and value proposition, as well as the magic triangle, which considers cost, performance, and time. In addition, a SWOT analysis is employed to provide a comprehensive evaluation of strategic positioning. The study then analyzes the contemporary German vegan market, revealing rapid growth in both consumer numbers and the production and sales of vegan products. The Business Model Canvas is applied to conduct external analyses, including an examination of customer segments and partnerships, and internal analyses of cost structures and revenue streams. It also serves as a framework for exploring strategic and operational marketing approaches adopted by vegan companies. Using Rügenwalder Mühle, Germany's leading vegan company by sales, as a case study, the paper applies a SWOT analysis to assess its strengths, such as product innovation and brand recognition; weaknesses, including logistics overload and outdated marketing practices; opportunities, including market expansion and policy support; and threats, such as rising costs and competitive pressure in the retail sector. Based on this analysis, the study proposes targeted recommendations for enhancing company performance. In conclusion, the paper summarizes the key findings, acknowledges the limitations of the research due to incomplete reference data, and provides suggestions for future studies.
Sustainable Supply Chain Finance and Corporate Performance: Moderating Role of Regulatory Policies
Sustainable Supply Chain Finance (SSCF) has emerged as a pivotal mechanism for integrating financial management with sustainability objectives amid increasingly complex global supply networks. As regulatory scrutiny intensifies worldwide, SSCF is transforming traditional financing models by embedding environmental, social, and governance (ESG) criteria into financial decision-making structures. Despite growing corporate adoption, scholarly inquiry has yet to sufficiently examine how regulatory frameworks influence the relationship between SSCF implementation and corporate performance. Addressing this research gap, the present study explores how differences in regulatory environments moderate SSCF's performance outcomes. Employing a comparative case study design, the research investigates Siemens (Germany), Huawei (China), and Unilever (Netherlands), each operating under distinct regulatory conditions. The results indicate that SSCF adoption consistently enhances both operational efficiency and sustainability performance, with the positive effects being more pronounced in rule-based regulatory contexts. The study contributes to the literature by integrating insights from financial innovation theory with institutional and regulatory economics, proposing a moderated mediation framework that elucidates how policy environments amplify or constrain SSCF's advantages. These findings hold practical significance for firms seeking to optimize SSCF strategies and for policymakers aiming to construct regulatory systems that foster sustainable financial practices across global supply chains.
Monetary Policy Communication and Household Inflation Expectation Heterogeneity: A Cross-Country Empirical Study Based on Micro Survey Data
This paper investigates the influence of monetary policy communication on the formation of household inflation expectations, examining how this influence varies across households with different income levels, educational backgrounds, and degrees of attention to economic information. Using multinational microsurvey data covering multiple countries, which include household inflation expectations, knowledge of central banks, information sources, and socioeconomic characteristics, we find that monetary policy communication plays a significant role in shaping household inflation expectations. However, the magnitude and accuracy of this effect differ markedly among various household groups. Households with higher income and education levels, as well as those who actively follow economic news, demonstrate greater sensitivity to central bank communications and exhibit less bias in their inflation expectations. In contrast, households with lower income or education levels often struggle to accurately interpret policy signals due to limited access to relevant information, leading to systematically higher expectations. These findings provide empirical support for central banks to design targeted communication strategies that consider the diverse informational needs and responsiveness of different household groups.
Valuation Gaps and Deal Outcomes in Cross-Border M&A: The Mitigating Role of Investment Banks
Cross-border mergers and acquisitions (M&A) have emerged as a critical avenue for global investment, yet they frequently encounter negotiation breakdowns due to valuation disagreements between acquiring and target firms. While prior research has primarily focused on institutional and cultural determinants of such valuation gaps, the intermediary mechanisms that may alleviate these disparities remain underexplored. This study addresses this gap by investigating how investment banks moderate the impact of valuation gaps on deal outcomes in cross-border M&A. Utilizing a dataset of 1,842 transactions spanning 2010 to 2024 from the Refinitiv Eikon and Zephyr databases, logistic regression analyses reveal that larger valuation gaps significantly decrease the likelihood of deal completion (β = −0.63, p < 0.01), whereas engagement with reputable investment banks mitigates this negative effect (β = 0.41, p < 0.05), particularly in contexts characterized by high institutional distance. Complementary evidence drawn from the ArcelorMittal-Essar Steel, Tencent-Supercell, and Geely-Volvo cases illustrates three distinct mediation mechanisms: reputational certification, information alignment, and structural bridging. These findings underscore the critical coordinating role of financial intermediaries in reducing valuation friction and offer practical implications for the selection of advisory services as well as for enhancing regulatory transparency in international deal-making.
A Comparative Study of Deep Learning Architectures for Multivariate Financial Time Series Forecasting
Accurate forecasting of multivariate financial time series remains a critical challenge due to high volatility, non-stationarity, and complex cross-variable dependencies. Although deep learning models such as LSTM, GRU, TCN, and Transformer have shown notable progress, existing research often evaluates these architectures in isolation, lacks interpretability, and provides limited analysis of robustness across different markets. These limitations impede the deployment of reliable forecasting systems in practical financial settings. This study presents a comprehensive comparative analysis of representative deep learning architectures for financial forecasting and introduces a novel Hybrid Attention-Gated Module (HAGM). HAGM combines convolutional feature extraction, gated fusion, and multi-head self-attention mechanisms to efficiently capture both local and global dependencies. Experiments were conducted on stock indices, foreign exchange, and cryptocurrency datasets, assessing model performance across multiple forecast horizons. The results demonstrate that HAGM consistently outperforms baseline models, achieving lower RMSE and MAPE while exhibiting faster convergence. Ablation studies confirm the complementary contributions of convolution, gating, and attention components, and interpretability analyses identify critical variables such as trading volume and volatility. Robustness evaluations further reveal superior cross-market generalization and resilience under noisy conditions. Overall, this work advances the methodological understanding of deep learning approaches for financial forecasting and provides actionable insights for practitioners aiming to develop accurate, efficient, and interpretable predictive systems.
Integrating Intellectual Capital into Enterprise Valuation: A Framework for the Knowledge Economy
The accelerating transition toward a knowledge-based economy has shifted enterprise value from tangible assets to intellectual capital, encompassing human expertise, organizational processes, and relational networks. Traditional valuation models, including discounted cash flow and multiples, consistently underrepresent these intangible drivers, resulting in a divergence between reported financials and market assessments. To bridge this gap, this study develops a comprehensive framework that integrates intellectual capital considerations with insights from both knowledge-based and resource-based perspectives on the firm. Methodologically, the research combines a systematic review of recent literature, a comparative evaluation of existing intellectual capital models, and a case-based framework illustrated through analyses of Moderna, Alphabet, and Tencent, representing the biotechnology, artificial intelligence, and digital platform sectors, respectively. The findings reveal that human capital serves as a key driver of innovation, structural capital enhances scalability and organizational resilience, and relational capital strengthens trust and market legitimacy, collectively generating valuation outcomes that exceed the explanatory power of conventional models. The study contributes theoretically by unifying strategic management and financial perspectives, and practically by equipping investors, managers, and policymakers with structured tools to identify and measure the true sources of enterprise value. By embedding intellectual capital into valuation processes, this research redefines how competitiveness and growth potential are assessed in the contemporary knowledge economy.
Comparative Financial Analysis of Lowe's and Home Depot for Investment Decisions
With nearly eighty years of presence in the U.S. home-improvement market, Lowe's has enhanced asset efficiency and profitability through the advancement of digital tools, the expansion of professional-contractor services, and the refinement of supply-chain logistics. Compared to Home Depot, Lowe's operates on a smaller scale yet achieves higher gross profit relative to assets, faster earnings-per-share growth, and a notably lower price-to-earnings-growth ratio, reflecting either an undervalued investment opportunity or market skepticism regarding the sustainability of its growth, which contributes to the observed discount in its price-to-earnings multiple. Brand equity remains strong, profit margins are stable, and the product assortment is increasingly concentrated in higher-margin categories such as smart-home devices and seasonal offerings. Challenges include softening consumer demand driven by rising interest rates, intensifying online competition led by e-commerce giants, and ongoing volatility in raw-material costs encompassing lumber, metals, and chemicals. In response, management is deepening engagement with professional customers, accelerating omnichannel investments that integrate physical stores with rapid delivery and buy-online-pick-up-in-store services, and diversifying the supplier base to reduce geographic and logistical concentration. Despite operating in a mature industry, the combination of operational leverage, strategic initiatives, and disciplined capital allocation suggests that Lowe's retains substantial growth potential and sustained competitive resilience in the years ahead.
Utilizing Family Business Chatime Data to Study the Global Differences in Milk Tea Price Elasticity
This study examines the global variations in milk tea price elasticity, with a particular focus on Chatime's performance across diverse international markets. By systematically analyzing cultural, economic, and market structural factors, the research elucidates how these elements shape consumer responsiveness to price changes. In markets characterized by high price elasticity, such as the United States and Malaysia, consumers exhibit heightened sensitivity to price fluctuations, prompting brands to adopt strategies such as bundling, membership programs, and promotional offers to stabilize demand. Conversely, in markets with low price elasticity, including Taiwan and Saudi Arabia, consumer responsiveness is comparatively muted, requiring companies to maintain and enhance market share through brand value cultivation, premium product offerings, and tailored marketing initiatives. Cultural influences emerge as a critical determinant of elasticity, with milk tea functioning as a cultural symbol in certain regions while serving primarily as a social or lifestyle commodity in others. Economic factors, including income distribution, purchasing power, and the intensity of market competition, further contribute to these variations, affecting both consumer behavior and corporate pricing decisions. Chatime's adaptive pricing strategies, which are informed by local elasticity patterns, demonstrate the brand's capacity to navigate complex market dynamics and optimize performance across heterogeneous global environments. The findings provide practical insights for multinational companies seeking to develop market-sensitive pricing strategies, enhance brand positioning, and effectively engage consumers in diverse cultural and economic contexts.
Valuation of Technology Companies: An Investment Banking Perspective on Traditional Models vs. Innovative Approaches
The rapid expansion of technology companies has profoundly transformed the valuation landscape, creating distinct challenges for investment banking practices. Conventional valuation models, such as discounted cash flow and price-to-earnings multiples, often fail to accurately capture the intrinsic value of high-growth technology firms due to their substantial reliance on intangible assets, accelerated innovation cycles, and network effects. This gap highlights the necessity for a more comprehensive framework that integrates both quantitative financial metrics and qualitative technological indicators. This study addresses this need by proposing a hybrid valuation model specifically designed for technology companies, incorporating innovation-related metrics. The methodology combines patent strength analysis, user economics through customer acquisition cost to lifetime value ratios (CAC/LTV), and adjustments for R&D capitalization within a weighted evaluation framework. Empirical validation is conducted via a comparative analysis of 50 technology IPOs between 2018 and 2023, assessing the divergence between traditional valuation outputs and actual market performance. The results indicate that innovation-focused valuation approaches reduce average pricing errors by 23% relative to conventional methods, particularly for platform-based business models and companies with deep-tech R&D pipelines. These findings carry significant implications for investment banking, suggesting that integrating technology-specific due diligence into standard valuation procedures can improve pricing accuracy in both IPOs and M&A transactions. Moreover, the study contributes to broader financial discourse by advocating for the revision of accounting standards to better represent intangible assets in the valuation of technology firms.
Mechanisms of Green Financial Product Innovation in Driving the Low-Carbon Economy: A Systemic Study
The global transition toward a low-carbon economy requires innovative financial instruments to bridge the funding gap for sustainable development. Although green financial products have rapidly proliferated, their systemic mechanisms for facilitating decarbonization remain insufficiently explored. This study examines how innovation in green financial products structurally supports low-carbon transitions through integrated policy, market, and technology interactions. A tripartite mechanism framework is developed, encompassing price discovery, risk allocation, and value circulation, addressing the critical disconnect between financial design and emission-reduction outcomes. Methodologically, the research combines systematic case studies of representative green financial instruments across China, the EU, and the US with a novel mechanism effectiveness assessment matrix, evaluating coverage breadth, market responsiveness, and sustainability impact across twelve flagship products. Findings highlight three key dynamics: policy signals amplify market expectations through certification systems, securitization techniques reduce technology adoption risks, and blockchain-enabled carbon tracing generates positive feedback loops. Products incorporating dynamic ESG pricing demonstrate 23% higher capital efficiency compared with conventional green instruments. This study advances sustainable finance theory by operationalizing the concept of "mechanism stacking," where complementary designs produce nonlinear climate benefits. Practically, it offers regulators evidence-based templates for product standardization and guides financial institutions in designing next-generation climate-aligned instruments. These insights promote the alignment of financial innovation with Paris Agreement targets and emphasize the importance of cross-border mechanism interoperability.
This study examines whether comovement exists in the Chinese stock market by investigating the relationship between individual stock returns and the CSI 300 Index. Using both univariate and bivariate regression analyses, we test the changes in beta coefficients and R-squared values when a stock is added to or removed from the CSI 300 Index. The empirical results indicate that the overall change in these parameters is statistically insignificant. To further explore this phenomenon, we analyze the potential influence of index arbitrageurs on comovement. The findings remain robust even after accounting for the mean reversion of beta. Therefore, the results provide strong evidence that comovement in the Chinese stock market is statistically significant.
A Study on Users' Algorithmic Imagination and Counter-Domestication Behavior from the Perspective of Media Affordances: The Case of the "Momo" Phenomenon
This paper takes the "momo" phenomenon as a case study, examining users' algorithmic imagination and counter-domestication behaviors toward social platform algorithms through the three dimensions of media affordances: production affordance, social affordance, and mobile affordance. By analyzing the dissemination and underlying mechanisms of the "momo" phenomenon, it reveals how users leverage media affordances to resist and protect themselves against algorithmic constraints and potential risks. The study further explores the relationship between algorithmic visibility in platform society and users' algorithmic imagination reflected in this phenomenon, while discussing its implications for the future development of social platforms and user-algorithm interaction practices.
Challenges and Opportunities for Preschool Music Appreciation
In recent years, early childhood education has increasingly emphasized the arts, with music recognized as a vital component of holistic development. This study investigates the challenges and opportunities associated with preschool music appreciation, highlighting its significance in fostering children's cognitive, emotional, social, and linguistic growth. Music education promotes creativity, enhances attention, and cultivates cultural literacy, contributing to long-term academic and personal development. Despite these benefits, several barriers persist, including a shortage of qualified music educators, limited professional training opportunities, financial constraints, and insufficient instructional resources. These obstacles constrain the variety and effectiveness of musical experiences available to young learners. Drawing on interpretivist perspectives and a synthesis of recent literature, this research examines how teacher beliefs, curriculum design, and resource allocation influence outcomes in preschool music education. Opportunities for innovation are evident through play-based learning strategies, integration of music with language and physical development, and the application of evidence-informed practices. By addressing existing limitations, preschool music appreciation can serve as a transformative foundation, supporting lifelong learning, creative expression, and meaningful cultural engagement.
Towards a Strategic Framework for Hospital-Community Integration: Evidence from Digital Health Platforms in the Greater Bay Area
The aging population and the growing prevalence of chronic diseases are creating a global imperative for integrated care models, yet the persistent divide between hospitals and community care continues to impede seamless patient journeys and efficient utilization of healthcare resources. Although digital health platforms are widely recognized as catalysts for integration, existing research predominantly emphasizes technological capabilities, often overlooking the necessity of a strategic framework that harnesses these platforms to orchestrate comprehensive service delivery. This consideration is particularly salient in complex, cross-border regions such as the Guangdong-Hong Kong-Macau Greater Bay Area (GBA), where diverse institutional structures and regulatory environments add layers of operational complexity. This study employs a qualitative case study methodology, combining documentary analysis of GBA healthcare policies with a review of ongoing digital health initiatives to construct a strategic framework for integrated care. The analysis identifies three critical pillars for effective integration: interoperable data standards, aligned incentive structures, and patient-centric service design. Findings demonstrate that digital health platforms transcend their role as mere technological tools; they are central to reconfiguring care workflows, enabling data-driven decision-making, and facilitating collaboration between hospitals and community-based care providers. From an academic perspective, this research advances the service ecosystem framework, offering a novel model for digitally enabled healthcare integration in multi-jurisdictional contexts. Practically, it provides a strategic roadmap for policymakers and healthcare administrators in the GBA to develop resilient, efficient, and patient-focused integrated care systems that can adapt to the complexities of cross-border healthcare delivery.
Guangdong-Hong Kong-Macau Greater Bay Area (GBA)
The Analysis of Luckin Coffee's Financial Fraud Based on GONE Theory
On April 1, 2020, Luckin Coffee, once celebrated as the "Pride of the Nation," faced intense public scrutiny following the exposure of a large-scale financial fraud scandal. The severity and widespread consequences of this incident significantly disrupted the stable development of the market economy. This paper reviews the Luckin Coffee financial fraud case, providing a comprehensive analysis of its accounting manipulation techniques, and applies the GONE theory to explore the underlying motivations behind the misconduct. By examining the case through the four dimensions of the GONE framework, the study identifies targeted preventive measures to mitigate the risk of financial fraud. The findings indicate that while financial fraud may create a temporary illusion of profitability, it inflicts substantial long-term damage on internal corporate management structures. This research aims to assist enterprises in recognizing the serious consequences of financial misconduct and emphasizes the critical role of robust internal governance for corporate sustainability. In doing so, it contributes to the improvement of internal control mechanisms, reinforces regulatory functions, and ultimately enhances the overall quality of enterprise development.
Digital Diplomacy in Motion: How Chinese and Japanese State Media Reframe National Culture on TikTok and YouTube
In the era of algorithmic communication, digital diplomacy increasingly operates through entertainment-oriented platforms such as TikTok and YouTube, where national narratives are shaped through algorithms, aesthetics, and audience engagement. While prior research has focused on textual diplomacy on platforms like Twitter and Facebook, it has insufficiently examined how short-video formats transform cultural representation and state communication. To address this gap, this study introduces the Algorithmic-Cultural Mediation (ACM) framework, which integrates digital diplomacy theory, cultural narrative analysis, and platform algorithm studies. Employing a comparative multimodal discourse analysis of 400 high-engagement videos from CGTN and NHK World spanning 2023 to 2025, the study investigates how China and Japan reconstruct national culture through algorithmically mediated visibility, localized storytelling, and visual design. The findings identify two complementary models of digital diplomacy: CGTN's velocity-oriented strategy, which emphasizes trend adaptation and collective identity, and NHK World's authenticity-oriented strategy, which prioritizes aesthetic minimalism and individual creativity. Both approaches demonstrate that algorithms not only amplify but also reshape diplomatic narratives into participatory, data-driven cultural performances. The study contributes to theoretical understanding by framing digital diplomacy as a process of algorithmic-cultural negotiation and offers practical insights for designing cross-cultural communication strategies within the global platform ecosystem.
Infrastructure Financing Efficiency through Green Bonds: An ESG Performance Perspective on Emerging Markets
The global demand for sustainable infrastructure has intensified in emerging markets as a result of rapid urbanization and industrialization. Financing large-scale infrastructure projects, however, remains a significant challenge, as traditional funding sources often prove insufficient. Green bonds have emerged as a viable instrument to mobilize capital for environmentally sustainable projects. Nevertheless, the impact of green bonds on infrastructure financing efficiency (IFE), particularly in emerging markets characterized by less developed capital markets and inconsistent ESG data, remains inadequately understood. This study addresses this gap by investigating the effects of green bond issuance and ESG performance on IFE across twelve emerging economies from 2015 to 2024. Employing econometric models and mediation analysis, the research demonstrates that ESG performance acts as a mediator in the relationship between green bond issuance and financing efficiency. The analysis reveals that green bonds significantly enhance IFE in China and India, with China experiencing the most pronounced improvements due to its robust regulatory framework, while Brazil's fragmented institutional structure constrains the effectiveness of green bonds. The findings underscore the importance of a strong regulatory environment, consistent ESG disclosures, and institutional coherence in maximizing the benefits of green bonds. This research contributes to the literature by providing empirical evidence and offering practical guidance for policymakers, investors, and development banks seeking to improve infrastructure financing through ESG-aligned financial instruments.
Digital Inclusive Finance and Rural Household Income: An Empirical Study
Based on panel data from 31 provinces, autonomous regions, and municipalities in China between 2011 and 2020, this study employs a fixed-effects model to investigate the impact mechanisms and outcomes of digital inclusive finance on rural household income. The empirical results indicate that, overall, the expansion of digital inclusive finance has significantly contributed to income growth among rural residents. A more detailed examination of sub-dimensions reveals that the breadth of coverage exerts a particularly strong positive influence, while the effects of usage depth and the level of digitalization are relatively less pronounced. This suggests that ensuring widespread access to digital financial services is more critical for enhancing rural income than merely deepening the intensity or sophistication of usage. Further analysis of regional differences demonstrates that the western region of China has experienced more substantial benefits from the development of digital inclusive finance compared to other regions. This finding underscores the importance of considering regional heterogeneity when formulating policies aimed at promoting digital financial inclusion and rural economic development. Moreover, the study highlights a clear "threshold effect" associated with rural digital infrastructure. Specifically, when digital infrastructure reaches a certain level, the marginal promoting effect of digital inclusive finance on rural income growth diminishes. This phenomenon suggests that while initial investments in digital infrastructure can substantially boost the effectiveness of digital financial services, the incremental benefits may taper off once a baseline level of infrastructure maturity is achieved. These findings provide both empirical evidence and a theoretical foundation for improving the rural financial service system, optimizing strategies for digital inclusive finance, and enhancing the income potential of rural households. The results carry particular significance for the implementation of rural revitalization strategies and the advancement of urban-rural integration, offering valuable guidance for policymakers seeking to leverage digital finance as a tool for inclusive economic growth.
Artificial Intelligence for Sustainable Manufacturing: Governance Models and Supply Chain Resilience in China
The rapid advancement of artificial intelligence (AI) presents transformative opportunities for sustainable manufacturing, particularly in China, where industrial decarbonization and supply chain resilience have become critical priorities under the "dual-carbon" policy framework. However, current research lacks a comprehensive examination of how AI-enabled governance models can simultaneously enhance green manufacturing practices and strengthen supply chain resilience in emerging economies. This study addresses this gap by investigating the interplay between AI adoption, institutional governance, and resilience-building mechanisms within China's manufacturing sector. Employing a mixed-methods approach that combines policy text analysis, case studies of smart factories, and qualitative comparative analysis, the research identifies three predominant governance models: government-led regulatory frameworks, market-driven incentive systems, and technology-enabled collaborative platforms. Key findings indicate that AI-powered dynamic monitoring and decision-support systems substantially reinforce supply chain resilience, with empirical evidence showing a 23-41% improvement in order fulfillment rates among AI-integrated green manufacturers. Furthermore, the study proposes a "smart-ecological co-governance" framework that aligns technological innovation with institutional adaptation. This research contributes to the theoretical discourse on sustainable supply chain management by integrating digital governance theory with principles of industrial ecology. Practically, it offers policymakers actionable insights for promoting AI-driven green transitions, emphasizing the importance of adaptive regulatory sandboxes and cross-industry data-sharing platforms. The findings provide significant implications for developing nations seeking to reconcile economic growth with environmental sustainability through intelligent manufacturing systems.
Strategic Adjustment and Performance Evaluation in the Context of Digital Transformation
This study explores the impact of digital transformation on corporate strategic adjustment and performance by employing multi-industry panel data, regression analysis, Data Envelopment Analysis (DEA), and panel modeling. The empirical results demonstrate a significant positive association between digital transformation inputs-such as R&D expenditure, IT investment, and employee training-and financial performance indicators, including return on assets (ROA) and return on equity (ROE). The DEA findings reveal notable efficiency disparities among industries, with information technology enterprises outperforming those in manufacturing and service sectors. This suggests that industry-specific capabilities play a crucial role in shaping the effectiveness of digital transformation initiatives. Furthermore, the panel data analysis confirms that digital investment yields sustained long-term benefits, particularly within innovation-driven industries where cumulative advantages emerge progressively over time. The results emphasize that achieving successful digital transformation extends beyond mere technological adoption; it requires strategic realignment, enhanced organizational agility, and implementation approaches tailored to contextual conditions. Overall, this research offers practical insights for enterprises seeking to strengthen competitiveness and attain sustainable growth within the digital economy. It also provides valuable guidance for policymakers in promoting digital adoption across industries through targeted support measures, workforce skill development, and infrastructure enhancement. By integrating both financial and non-financial performance indicators, this study contributes to advancing theoretical understanding and developing practical frameworks for effectively managing digital transformation in diverse industrial settings.
A Comparative Study of Audience Engagement with Health Science Communication Across Different Platforms: Douyin, Weibo, and WeChat Official Accounts
The rapid expansion of social media platforms has profoundly transformed how sports science knowledge is communicated to the public. Platforms such as Douyin, Weibo, and WeChat Official Accounts have emerged as essential channels for disseminating information on athletic training, injury prevention, sports performance optimization, and nutrition management. Despite this growing trend, there remains a lack of systematic comparative research examining how these platforms influence audience engagement with sports science content. This study seeks to address this gap by analyzing the relative effectiveness of different social media platforms in promoting the communication of sports science, emphasizing measurable indicators of audience participation and interaction. A mixed-methods research design is employed, integrating both quantitative data analysis and qualitative content evaluation. Data were collected from 50 top-performing sports science accounts on each of the three platforms-Douyin, Weibo, and WeChat-over the period from 2022 to 2024. Key engagement metrics, including average interaction rates, comment sentiment distributions, and patterns of content sharing, are systematically examined to assess user responsiveness. The study further explores how platform-specific content formats, such as short-form videos on Douyin, real-time discussion threads on Weibo, and long-form informational articles on WeChat, influence audience retention, participation depth, and dissemination efficiency. Findings reveal distinct engagement dynamics across platforms. Douyin demonstrates superior reach and virality, primarily due to its algorithm-driven short video system and high-frequency content circulation. In contrast, WeChat fosters more sustained engagement and deeper cognitive involvement through in-depth reading and professional discourse. Weibo serves as an intermediary platform that encourages real-time exchanges and interactive discussions through features like hashtags, live Q&A sessions, and comment threads. These platform-specific patterns highlight the need for differentiated communication strategies in the dissemination of sports science information. Overall, this study provides practical insights for sports science communicators, educators, and institutions aiming to enhance digital outreach. By identifying the strengths and limitations of each platform, the research offers evidence-based strategies for optimizing audience engagement and improving the public understanding of sports science in the digital era. The findings contribute to the expanding field of digital science communication by presenting empirical evidence and methodological guidance for effective dissemination of sports-related knowledge across diverse online environments.
Trust as Capital: Confucian Ethics and the Moral Logic of Modern Finance
Trust constitutes the moral and institutional foundation of modern financial markets, influencing investment behavior, credit allocation, and market resilience. In East Asian economies shaped by Confucian ethics, the development and erosion of trust are not determined solely by legal or contractual enforcement but are also guided by embedded social norms emphasizing ren (benevolence), yi (righteousness), li (propriety), and xin (trustworthiness). Despite extensive research on social capital and financial governance, few studies have systematically linked Confucian moral philosophy with quantifiable mechanisms of trust in contemporary finance. This study addresses this gap by integrating Confucian ethical theory with empirical evidence from China's financial sector. Employing a mixed-methods approach, the analysis combines quantitative data from listed firms with qualitative case studies, including CEO social capital and debt cost data (2018-2024), regional trust and ESG performance metrics, and the collapse of the Ezubao peer-to-peer platform. The study identifies both constructive and destructive dynamics of trust. Results indicate that stronger social capital is associated with lower financing costs and improved governance outcomes, whereas failures in moral and institutional frameworks lead to systemic distrust. These findings contribute to a culturally grounded "economics of trust," illustrating how Confucian ethics can inform sustainable financial development and regulatory innovation in rapidly evolving markets.
From Protest to Policy: The Rocks Green Bans and the Transformation of Heritage Protection in Sydney
This paper examines the Rocks Green Bans (1971-1974) as a pivotal episode in the history of Sydney's urban planning and heritage protection. The Green Bans, imposed by the Builders Labourers Federation in collaboration with the Rocks Residents Action Group, halted large-scale modernist redevelopment proposed by the Sydney Cove Redevelopment Authority. Drawing on multi-source archival research, including newspapers, government records, and visual materials, the study reconstructs how grassroots mobilisation challenged state-led planning and reshaped the concept of heritage. The findings reveal three major contributions. First, the Green Bans contested the dominance of top-down modernist planning by legitimising community participation in shaping urban futures. Second, they broadened the notion of heritage beyond architectural preservation to encompass social and cultural values, particularly working-class identity and collective memory. Third, they laid the groundwork for institutional reforms, notably the establishment of the New South Wales Heritage Council in 1977. Beyond their historical significance, the Green Bans continue to influence contemporary debates on redevelopment and gentrification, demonstrating that heritage cannot be separated from principles of equity and justice. This case thus offers enduring insights for participatory planning and values-driven approaches to conservation in rapidly evolving urban contexts.
Symbolic Expression in Painting Therapy for Adolescents with Anxiety Disorders
Adolescents with anxiety disorders often face challenges in verbally expressing emotional distress, which can limit the effectiveness of traditional therapeutic approaches, such as cognitive-behavioral or pharmacological treatments. Painting therapy offers a non-verbal, symbolic avenue for expressing and reorganizing anxiety; however, prior research has primarily examined therapeutic outcomes while overlooking the underlying symbolic mechanisms of change. To address this gap, the present study develops and empirically validates a symbolic mediation framework linking emotional activation, symbolic formation, reflective dialogue, and integration. Using a mixed-method design, four adolescents aged 13-18 diagnosed with anxiety disorders participated in a twelve-session painting therapy program. Their artworks were analyzed with a coding scheme covering five symbolic motifs: enclosure, fragmentation, movement, contrast, and emergence, which were then correlated with standardized anxiety assessments. Results demonstrated a consistent progression from fragmented, chaotic imagery to coherent, open compositions, with the motifs of emergence and movement showing strong associations with reductions in anxiety. Symbolic transformation was observed to precede measurable improvement, confirming its mediating role in emotional regulation. These findings enhance theoretical understanding of non-verbal therapeutic mechanisms and provide clinicians with a structured model for identifying symbolic indicators of psychological recovery in adolescent anxiety treatment.
Beyond Words: Thomas Merton's Transformative Encounter with Tibetan Buddhism
This paper examines Thomas Merton's 1968 pilgrimage to Asia as a pivotal moment in the development of Buddhist-Christian dialogue. While Merton's journey is often remembered for its personal and spiritual significance, this study argues that it also represents an early example of comparative theology in practice. Drawing on his encounters with Chogyam Trungpa Rinpoche, the Fourteenth Dalai Lama, and Chatral Rinpoche, the paper explores how Merton moved beyond surface-level exchanges to engage deeply with Tibetan Buddhist contemplative traditions. Through his dialogue with Trungpa, he confronted the dangers of "spiritual materialism" and recognized parallels with the challenges faced by modern Western monasticism. In conversation with the Dalai Lama, he reflected on the renewal of contemplative life, learning that discipline, wisdom, and compassion must be integrated for authentic practice. His meeting with Chatral Rinpoche, who emphasized direct realization and mystical language, prepared him for the culminating experience at Polonnaruwa in Sri Lanka, where Merton articulated a vision of unity between emptiness and compassion. To frame this analysis, the paper draws on Catherine Cornille's account of the essential virtues for dialogue-humility, commitment, interconnection, empathy, and hospitality-and Francis X. Clooney's definition of comparative theology as "faith seeking understanding" across religious boundaries. The study concludes that Merton's pilgrimage anticipated later theological methods while offering a model of contemplative dialogue that is faithful to one's tradition yet open to transformation through encounter. His unfinished vision continues to inspire contemporary efforts toward interreligious understanding and peace.
Synthesis, Crystallographic Features, and Urease Inhibition Performance of Aromatic Dicarboxylate Copper-Based Architectures
A series of novel aromatic dicarboxylate copper complexes were designed and synthesized via hydrothermal and solvothermal methods, and their structural and biological properties were systematically investigated. Single-crystal X-ray diffraction revealed that the copper centers adopt either distorted octahedral or square planar geometries, with the ligands acting as bridging units to form one-, two-, or three-dimensional frameworks. Intermolecular interactions, including hydrogen bonding, π–π stacking, and van der Waals contacts, contribute to lattice stability and framework rigidity. Comprehensive structure-activity analysis demonstrated that the urease inhibitory performance of these complexes is strongly influenced by the electronic properties of the ligands, the accessibility of the copper centers, and the topology of the metal-organic frameworks. Complexes with electron-withdrawing substituents, partially exposed metal sites, and moderate structural flexibility exhibited the highest inhibitory potency. These findings highlight the importance of fine-tuning both ligand electronics and three-dimensional framework geometry in the rational design of metal-based enzyme inhibitors. This study provides valuable insights into the relationship between crystal structure and biological activity, offering guidance for the development of efficient urease inhibitors and other bioactive metal-organic materials.
Copper complex, Single-crystal X-ray diffraction
Strategic Planning Methodologies across Contemporary Professional Sectors: Trends, Challenges, and Transformative Practices
Strategic planning remains a fundamental mechanism for organizational success across diverse professional sectors, despite the increasing complexity and volatility of contemporary operational environments. This paper examines the evolution and application of strategic planning methodologies in multiple domains including technology development, construction management, architectural design, creative industries, and business strategy formulation. The research explores how traditional planning frameworks have adapted to accommodate rapid technological advancement, market disruption, and unprecedented global challenges such as pandemic-induced transformations. Through comparative analysis of sector-specific approaches, this study identifies common principles underlying effective strategic planning while recognizing the unique contextual demands of different professional fields. The investigation reveals that successful strategic planning in modern contexts requires balancing systematic frameworks with adaptive capacity, integrating digital technologies with human expertise, and maintaining organizational agility without sacrificing long-term vision. Findings demonstrate that contemporary strategic planning transcends conventional linear models, embracing iterative processes that facilitate continuous learning and real-time adjustment. This synthesis provides valuable insights for professionals seeking to enhance organizational performance through refined strategic planning practices tailored to their specific operational contexts.
The Dilemma of Choice: How Social Media Commerce Shapes and Undermines Consumer Autonomy
Social media commerce has fundamentally reshaped consumer decision-making by seamlessly integrating shopping functionalities into platforms such as TikTok, Instagram, and RedNote. These platforms offer highly engaging and interactive shopping experiences while leveraging persuasive design elements, algorithmic personalization, and influencer-driven marketing to subtly shape consumer behavior-frequently at the expense of genuine autonomy. This study investigates the mechanisms through which social media platforms influence purchasing decisions, emphasizing the tension between perceived autonomy and actual decision-making power. While algorithmically curated recommendations and targeted content can alleviate decision fatigue, streamline choice, and enhance efficiency for certain users, they often produce an illusion of choice, constraining critical self-reflection and the formation of authentic preferences. Moreover, social commerce practices-such as live-streaming promotions, curated reviews, and influencer endorsements-further reinforce behavioral guidance, sometimes without consumers' conscious awareness. The study concludes that social media commerce exerts a profound and multi-dimensional influence on consumer spending, decision-making processes, and self-perception. Drawing on these findings, the article offers ethical and practical recommendations for brands, platform designers, and consumers to cultivate a more transparent, responsible, and autonomy-preserving digital marketplace, balancing commercial innovation with consumer empowerment.
A Sustainability-Oriented Lifecycle Framework for Educational Technology Software
The rapid expansion of educational technology (EdTech) has profoundly reshaped global learning environments while raising growing concerns about software sustainability, including technical debt, excessive energy consumption, and limited product longevity. Current development models often emphasize functionality and scalability but rarely incorporate long-term ecological and pedagogical considerations. To address this gap, this study introduces the Sustainability-Oriented Educational Software Lifecycle (SESL) framework, which systematically embeds sustainability principles into every phase of software development. Drawing on a comparative case study of three representative platforms-Moodle, ClassDojo, and Coursera-the research integrates qualitative evidence from documentation analysis, stakeholder interviews, and lifecycle indicators to identify the primary drivers and inhibitors of sustainability in EdTech. The findings reveal five major sustainability drivers-modular architecture, community governance, ethical data practices, energy-efficient deployment, and pedagogical traceability-counterbalanced by barriers such as short product cycles, centralized control, and the lack of standardized evaluation metrics. The SESL framework establishes five iterative sustainability checkpoints throughout the software lifecycle, reframing sustainability from a terminal assessment into a continuous, feedback-oriented process. By bridging sustainable software engineering with educational technology design, this study provides both a theoretical and practical foundation for fostering resilient, inclusive, and ecologically responsible EdTech ecosystems.