The competition of catering industry is increasing fierce in recent years, and the impacts of social media on consumers is gradually becoming obvious as well. As a result, digital marketing has become one of the most important marketing methods of how catering brands shape their images. Haidilao, which is a representative of service industry, is a typical research object since it is active on TikTok, Red Note, and Weibo. This study explores how Haidilao takes advantage of social media, especially short videos, User-Generated Content (UGC), and employee interaction, to improve customer engagement and brand loyalty, while also analyzing how its multi-platform strategy forms digital marketing ecosystem. By using literature analysis, this study concludes previous research toward digital marketing, UGC, and brand loyalty, while using case analysis to explain the strategies of Haidilao in Tiktok, RedNote, and Weibo. The findings show that Haidilao successfully enhances customer engagement and brand intimacy through short video, UGC, and employee interaction. It combines online content and offline service to create a digital ecosystem, while facing the challenges of content homogenization, rising management costs, and diffusion risks. This study provides management implications for future optimizing strategies.

This research analyzes the attraction mechanisms of large Chinese commercial complexes, explaining why this type of complex remains resilient in the digital shopping era. This paper begins with research on three mechanisms of spatial structure, atmospheric experience, and composite functions from both international and Chinese perspectives. This review shows that although these studies focus on similar points, existing research fails to form a unified explanation framework, due to the different country backgrounds and analytical views. To address this gap, this study introduces theories of behavioral economics and consumer psychology to understand how these three mechanisms operate. Building on this analysis, this research constructs an attraction model based on Stimulus, Organism, Response framework. Spatial structure, atmospheric cues, and composite functions work as environmental stimuli. They influence internal states such as pleasure, satisfaction, and loyalty, and then shape consumer behavior including dwell, exploration, and consumption tendency. This model provides a structured way to understand how Chinese commercial complexes guide consumer reactions. This research contributes to offer an integrated theoretical perspective by connecting fragmented findings into a unified framework. This provides a starting point for future empirical research that may examine mechanism strength, moderation effects, and regional differences. Therefore, this study pays a foundation for understanding the unique consumption logic in Chinese commercial complexes.

As takeout service participate in daily life of the public more and more deeply, the content related to platform coupon distribution have also attract widespread attention. This essay focus on how the takeout platforms employ a triple-track price discrimination system, which including product recommendations, coupon distribution and dynamic surcharge fee, to approximate the perfect price discrimination in a highly competition market. It systematically analyze the system influence on consumer behavior, platform profit, merchant response and market fairness. This study adopt the method of analyzing cases from public sources, research out that takeout platforms use methods such as user portrait and A/B testing to personalized pricing and profit maximizing. Furthermore, it also points out that the price discrimination system can strengthen the data flywheel effect and heighten the completive barriers. However, the price discrimination system always faces potential risk such as algorithm out of control, marchers resisting. Based on the research result, the study suggest that the regulatory authority should strengthen the investigation of relevant algorithm and protect the price transparency, while the platforms should shift to "value co-creation" strategy to enhance market health and trade fairness.

This paper puts forward the conception of designing Agarwood futures, integrating the logic of financial engineering and the long-term target of cultural sustainability, based on the classic theory of the futures market and new results about derivative design. The results show that Agarwood has the technical and economic conditions for a feasible futures contract. The design introduces the Alums Commodity Price Index (ACPI) and multi-level delivery and grading systems to solve problems such as authenticity identification, heterogeneity and low liquidity. It also adopts standardized quality standards, certified warehousing vouchers and blockchain tracking technologies to enhance transparency. The supply structure, storability and price fluctuation of Agarwood align with mature commodity markets. This study selects aloes as an example to incorporate cultural values into formal financial instruments.

As virtual shopping malls are springing up on e-commerce platforms, the online shopping experience has reached an even higher level. Particularly, due to the fast-replicability and connectivity of internet, Tea culture has been transmitted into metaverse era. Although marketing actions have already extended to such virchome world, limited researches have been conducted on this topic. In this research, it selects new tea brands such as HEYTEA and ChaPanda and analyzes three types of “virtual-real integration” behaviors-virtual check-in behavior, virtual product trial behavior and virtual community co-creation behavior. And it investigates the positive impact virtual marketing can create for product sales. By employing SEM to conduct a path analysis between various variables in the new consumer tea brand market, the findings demonstrate the important factors affecting product sales, along with the relationship between variables, enhancing the positive relationship between interaction quality and sales, an effect particularly observable in VR-marketing. The research outcomes may act as an external guidance for traditional Chinese tea companies and venture into e-commerce in Metaverse virtual reality commercial environment.

In the entrepreneurial ecology dominated by venture capital, "money-burning growth" has become a typical path for the rapid expansion of high-growth enterprises. This model relies on external capital injections to seize market share, yet it is prone to triggering structural risks such as tight money flow, governance imbalance and valuation bubbles. Taking Luckin Coffee as a case study, this research draws on startup financing theory, enterprise life cycle theory, and the dynamic capability framework to explore the antecedents of financial risks of enterprises in the model of "burning money growth" and their transformation mechanism to sustainable development. The study argues that while capital-driven growth can accelerate expansion, over-reliance on external financing erodes financial discipline and amplifies governance failures arising from information asymmetry. Based on Luckin's development trajectory, this paper constructs a three-stage mechanism model of "capital convergence-governance repair-financial resilience restructuring": capital convergence emphasizes returning to cash flow constraints from disorderly expansion, governance repair focuses on rebuilding internal control and incentive mechanisms after the crisis, and financial resilience restructuring reflects the enterprise’s ability to establish a stable profit model on the foundation of improved governance.

In recent years, China's pet economy showed explosive growth, from a marginalized segment of the market jumping to a high-profile “emotional new economy” pillar. This paper aims to systematically explore the multiple driving mechanisms behind this phenomenon. The study suggests that the rise of the pet economy is not caused by a single factor, but a complex system composed of endogenous driving force on the demand side and exogenous driving force on the supply side. On the demand side, the change of social structure and family mode, the profound transformation of values and the upgrading of consumption brought about by the increase of residents' income are the fundamental motivations; on the supply side, the Innovation and digitization of the industrial end, the influx of capital and the gradual improvement of the policy environment provide key support. In addition, the media and cultural communication as a catalyst to accelerate the “Personification” of the popularity of the concept of consumption. This paper further analyzes the positive effects and challenges brought by the pet economy and looks forward to its future trend of development towards refinement, intelligence, standardization and humanization, in order to provide a comprehensive analysis framework for the academic and industrial circles.

With the acceleration of digitalization, China’s elderly population faces a severe challenge of the “digital divide.” This paper adopts case studies and bibliometric analysis methods, selects two typical cases of “health code verification” and “QR code payment,” and deeply analyzes the survival dilemmas faced by the elderly in the digital age in different social scenarios. The study found that the dilemma in the health code verification case mainly stems from the “deprivation of rights” caused by the lack of mandatory policies and technical adaptability; while the dilemma in the QR code payment case comes from the “social exclusion” caused by insufficient social support and trust crisis. Based on this, this paper proposes a “two-dimensional analytical framework for the digital divide.” From a comparative perspective between China and other countries, it proposes to build a digital social governance strategy of “tiered inclusion,” emphasizing “inclusive innovation” and intergenerational support. The aim is to provide theoretical reference and practical pathways for reducing digital inequality in an aging society.

Driven by the rapid development of big data, artificial intelligence and other technologies, the digital economy is reshaping all trades and professions in the world. In this background, companies are facing not only opportunities but also challenges. What’s more, companies really need to innovate management practices and improve efficiency. This article explores how the digital economy can reshape the business environment and drive companies to use innovative management models. Research has found that digital technology can achieve flatter organizational structures, smarter decision-making and quicker processes, which can help to improve operational efficiency and competitiveness. This paper summarizes practical paths for management innovation, including flattening organizational hierarchies and adopting Artificial Intelligence (AI) driven human resources systems. Moreover, strategics also be thought to improve financial, operational and labor efficiency. Through integrating these opinions, this study emphasizes the importance of aligning companies’ management with digital transformation and provides theory and practical opinions for maintaining competitive advantage in the digital age.

Predicated on a critical review of the Efficient Market Hypothesis within the modern financial landscape, this research supposes that social media functions work as a barometer of public sentiment, conveying emotional data that potentially possesses predictive utility for the financial market volatility. Research using the S&P 500 index and text-sensitive stocks as the study objects, this paper analyzes Twitter text data from 2021–2022. By consolidating econometric GARCH-type models with machine learning techniques (LSTM and XGBoost), the study performs sentiment quantification and forecasts market volatility. The study reveals that traditional econometric methods are unable to identify the predictive link between market sentiment and volatility. However, the LSTM model outperforms conventional GARCH (1,1) and GARCH-X models by capturing nonlinear relationships and effectively extracting predictive signals to create a robust forecasting model. Moreover, the results highlight an asymmetric effect: positive sentiment drives market volatility more intensely than negative sentiment. In conclusion, social media sentiment holds predictive potential for financial markets. Yet its relationship with volatility is complex and nonlinear—deep learning models are required to fully capture the relationship. Also, the effect of sentiment on volatility is asymmetric.