This paper aims to examine the profound change of consumer behavior in the period of economic fluctuations, that is, from passive price recipients to active value seekers. Focusing on the coexistence of “lipstick effect” and so-called “consumption degradation”, this paper proposes a concept of “rational...

Pinduoduo has achieved explosive growth in user base and transaction volume by relying on the “social + e-commerce” viral model. Due to information asymmetry and lagging regulation, platforms have rapidly seized the lower-tier markets. Due to the emergence of the “lemon market” and the increasing pressure...

With the rapid development of social media, influencer marketing has become a mainstream advertising approach. Its main function integrates social identity and imitative consumption. Firstly, this paper introduce three core concepts, which are influencer marketing, social identity, and imitative consumption....

In the current era, due to the electric industry’s growth, esports are booming. With the development of esports, it has attracted more audiences and investors, which also represents its increasingly obvious economic benefits. In this context, this study combines academic achievements in audience participation,...

Digital economy development and breakthrough in artificial intelligence have introduced radical shifts to the cross-border e-commerce. The current paper will discuss the ways in which the cross-border e-commerce industry is transforming its business models and marketing strategies due to the introduction...

The global luxury apparel market is growing rapidly and fiercely competitive, with China accounting for a significant share of the market. It has become a key driver of the growth in the global luxury apparel market, reshaping the regional landscape. Digital communication has revolutionized luxury advertising...

The pet market in China also has the advertising strategy that is undergoing a change towards digital marketing compared to traditional advertising, which is gradually becoming digital marketing. The paper is devoted to the digital marketing area, and methods: literature review, data analysis, and case...

As the world’s largest smartphone market, China has both significant opportunities and complex challenges for global technology companies like Apple Inc. This study analyzes Apple Inc.’s marketing strategy in the competitive Chinese smartphone market by using the 4Ps framework (Product, Price, Place,...

With the rapid growth of China’s medical aesthetics sector, the challenge faced by providers, like competition, information asymmetry, persistent trust and safety concerns becomes more intensive. These factors undermine the long-term viability of growth strategies which driven primarily by traffic and...

This paper discusses Estee Lauder’s digital marketing strategy using the AARRR framework. There has been a significant transformation of the global beauty industry in the digital sector, marked by the introduction of social media, e-commerce, and smart technologies, which has essentially redefined the...

Amid radical shifts in the digital media ecosystem and the continued growth of China’s beauty market new media marketing has turned into the most essential avenue of Chinese brands to trigger a growth breakthrough and establish a competitive base. This paper discusses Proya, which is a sample Chinese...

This article undertakes a thorough and systematic assessment of the influence of brand collaborations within games on consumer psychology and behavioral patterns. This article fills the important research gap identified by the disorganized nature of previous research. By thoroughly synthesizing the existing...

As the Internet becomes commonplace in the world, games have come to grab some form of attention of the people. The gaming market in China has taken an upslope trajectory to evolve compared to most of the foreign markets, and the studies in this field are not adequate. As such, there is need to determine...

This article investigates Luckin Coffee’s approach to the private domain traffic operation in digital transformation. In 2020, with the financial crisis, Luckin Coffee took full advantage of digital tools like mobile apps, WeChat mini-programs, and the enterprise WeChat communities to strengthen and...

The development of live e-commerce has turned digital retail into an interaction-driven relationship ecosystem. Although studies have shown that it has a certain impact on the purchase intention, the literature has the characteristics of fragmentation and short-sightedness, and has not systematically...

With the development of the information age, Generation Z is becoming the main consumer group in the fashion industry. Their preferences for authenticity, sustainability, individual expression and social media-driven trends pose significant digital transformation challenges to traditional fashion brands....

Based on the theory of digital marketing, combined with cross-cultural communication, brand management and Internet consumption behavior, this paper systematically analyzes the channel evolution, growth mechanism, practical dilemma and upgrading path of online sales of Western musical instruments in...

With the rapid rise of the entertainment industry in the Chinese market, it is becoming increasingly important to understand how an international company is adapting their marketing strategies to better fit into the local market. This study examines The Walt Disney Company’s marketing strategy in the...

In the era of digital economy, enterprises face rapidly changing markets and increasingly diverse customer demands. In the meanwhile, traditional marketing methods often lead to an unclear positioning and poor resource use. So it may lead to weaken customer relationships. The author finds that these...

In the era of digital economy, how to transform traditional cultural resources into brand assets with extensive influence and lasting vitality has become an important issue. Although the digitalisation of traditional cultural intellectual property (IP) is becoming increasingly widespread, there is still...

Based on the increasing proportion of the elderly population, an increasing number of countries have gradually entered the aging society, and the consumption power of elderly consumers has been increasingly recognized by the market, playing an increasingly important role. This paper comprehensively studies...

Over a few decades, the admission system in China has experienced a change from sequential mechanism to parallel admission mechanism, with 28 out of 31 provinces completing the transformation by 2012. However, the existing models ignore the differences in information between rural and urban areas, which...

This paper examines the background and historical evolution of the fashion industry, focusing on the popularisation of fashion brands and related consumer behaviour research, which has become a key topic in the digital economy era. Existing studies have explored social media’s impact on fashion marketing,...

With the continuous development of the Internet, the popular trend of e-commerce shopping has increased, and the single offline and single real economy of clothing has been hit hard. This issue has received widespread attention from many people. However, how to promote the harmonious development of online...

With the rapid development of electronic technology, more and more new electronic brands have emerged in the market. However, among these brands, Apple Company has stood out among the numerous competitors through its “hunger marketing” strategy. The main topic of this research aims to explore Apple’s...

In the context of the booming sports industry and the fierce competition in the Chinese market, the relationship between consumer characteristics and brand building is a key issue for sports retailers. The case of this study is Decathlon, a global multi-sport retailer. The study investigates the evolution...

This is crucial in predicting the value of pension liabilities and longevity risks, as they require proper forecasts of mortality. In the traditional stochastic models of mortality there are parametric assumptions of a linear nature that do not adequately represent non-linear integrated dependencies...

With the widespread adoption of buy-now-pay-later (BNPL) in the consumption of high-priced goods, installment payments have not only enhanced the accessibility of consumption but also increased the exposure to default risks. Moreover, a single traditional indicator is no longer sufficient to accurately...

Nowadays, since the capital market is expanding increasingly, more and more listed companies are coming to show their promise. However, the number of their credit risk exposures has surged; this phenomenon not only influences the reputation and financial performance of these listed companies but also...

Live broadcast e-commerce has developed rapidly, which has also attracted the attention of many researchers. However, most studies do not fully consider the psychology of consumers. This paper analyzes three marketing methods commonly used in live broadcasting: scarcity marketing, authority marketing...

The traditional credit reporting system has obvious limitations in covering people and updating data. A large number of people who lack traditional credit records find it difficult to obtain financial services and the rise of alternative data provides a new way for credit scoring. This paper summarizes...

In the process of continuous development of the medical insurance industry, the pricing mechanism of medical insurance is gradually maturing. In this context, it has become a key issue to carry out more scientific and reasonable medical cost prediction and insurance pricing based on individual risk characteristics....

The research presented in this paper assumes the Formula One (F1) driver market as the research setting and focuses on the major problems that the current junior development system faces. The career development of the drivers is heavily reliant on team-based, Junior Driver Programmes in the current institutional...

In the digital era, artificial intelligence has become an important driving force for the digital transformation of brand marketing in the online sales scene. While creating operational value for enterprises, it also brings risks such as privacy disclosure, cross-border data compliance disputes, and...

With the advent of the Arificial Intelligence (AI) era, Generative AI has become a key driver of digital marketing transformation. As a pillar of the experience economy, tourism’s intelligent transition has also drawn growing attention. Generative AI is actively used in the tourism industry at present,...

The coming together of artificial intelligence and augmented reality has opened new roads for individualized experiences in mobile business, but the ways through which content led by AI that is personalized affects consumers’ making of decisions are still not sufficiently researched. With Sephora’s Virtual...

This paper takes place in the period of changes in enterprise marketing under the digital economy. Research has been carried out on the role of digital technology in enterprise marketing innovation, how digital marketing meets consumers’ individualised and diverse needs, and theoretical support and practical...

Retail sales forecasting plays a crucial role in inventory management, marketing planning, and supply-chain optimization, and the choice of model directly influences how well retailers respond to demand volatility, promotions, and seasonal patterns. With the growing complexity of retail sales forecasting,...

This study explores the challenge of achieving a balance in performance when predicting credit defaults on imbalanced datasets. In this paper, a probability-weighted ensemble model is proposed to integrate the advantages of the two basic models, i.e., logistic regression and random forests. It studied...

Accurate used car price prediction has become increasingly important as the second-hand vehicle market continues to grow. Buyers and sellers often struggle to agree on fair prices because of information gaps. Expert-based pricing, while common, tends to be slow and inconsistent across different markets....

Bank liquidity risk is the core issue of financial system stability, and its essence comes from the term conversion mechanism of commercial banks supporting long-term assets with short-term liabilities. The bankruptcy of Silicon Valley Bank (SVB) in 2023 reflects the rapid evolution of liquidity risk...

Diamond price prediction is an attribute-based regression problem in which observable diamond characteristics explain a substantial but incomplete part of market price. This paper converts a public Diamonds-dataset baseline into a controlled empirical study of modelling choices. The workflow reproduces...

In the 21st century, global economic fluctuations have intensified, and black swan events such as the COVID-19 pandemic occurred frequently in 2020. Traditional financial models are unable to cope with sudden market shocks and the problem of prediction failure has become increasingly prominent. Therefore,...

With the background of significant fluctuations in the global financial market, traditional single investment strategy has demonstrated characteristics such as high volatility, and poor risk diversification. To enhance the stability of investment strategies, increase the rate of return, and address the...

In the current market, the high noise and non-stationary characteristics of stock price time series make accurate prediction extremely challenging. This study focuses on LVMH Group (MC.PA), the most representative blue chip asset in Europe, and extracts its real transaction data from January 2020 to...

Machine learning will be employed in this paper to investigate the joint effects of market sentiment and corporate financial indicators on short-term stock prices. Natural language processing is used to collect and process sentiment data from financial news and social media, and at the same time, financial...

This project investigates whether product-level information can predict the popularity of Sephora products. The target variable is the loves count, defined as the number of users who have saved or expressed interest in a product. Because the raw loves count is heavily right-skewed, the analysis models...

Purchase intention prediction supports conversion management in e-commerce, but evaluation can be misleading when purchase sessions are imbalanced and conversion-related features dominate prediction. This study examines session-level purchase intention prediction using XGBoost, four imbalance-handling...

Volatility prediction is still required for the whole of financial risk control, and due to its instability, changes in stock prices can be quite sudden. The standard linear model cannot explain the pronounced fluctuations in the concentrated stock market. This paper examines the prediction accuracy...

With the rapid growth of online shopping, e-commerce businesses face intense competition and need better ways to understand consumers. Customer segmentation has become an essential part of business analytics, helping companies recognise different customer groups and design personalised marketing plans....

Based on the historical trading data of the Nasdaq Composite Index, this paper constructs three prediction models—a traditional econometric model (ARIMA), a machine learning model (XGBoost), and a deep learning model (LSTM)—under a unified experimental setting on the same dataset and train/test split....

Credit card fraud is becoming increasingly serious in recent years for people at home and abroad. The three representative ways in this paper are: Deep Neural Networks for multi-feature integration; a hybrid Convolutional Neural Network - Long Short-Term Memory (CNN-LSTM) with attention mechanisms for...

Environmental, Social, and Governance (ESG) ratings are increasingly recognized as potential drivers of stock volatility. However, the quarterly frequency of ESG ratings mismatches daily returns, posing a methodological challenge for forecasting. This study addresses this gap by systematically comparing...

Predicting personal credit default is a vital part of managing financial risk for lenders. This paper proposes an explainable machine learning approach for predicting whether a credit card customer will default in the next month. The experiment employed the complete dataset of credit card clients from...

The experiment used the public Kaggle Loan Approval Prediction Dataset, which contains 4,269 applications. The paper treated loan status as a two-class target and kept the preprocessing workflow deliberately simple: removing the identifier field, checking missing values, encoding categorical variables,...

In the financial field, accurate prediction of price changes and risks is an important reference for making decisions and now the combination of machine learning and statistical models has shown advantages. This study combines dynamic regulation based on market environmental factors with the Glosten-Jagannathan-Runkle...

With the rapid development of the social economy, loan scales have expanded quickly. While banks and other financial institutions can generate considerable profits, this also means a significant increase in the risk of loan defaults. Given the vast amount of high-dimensional customer data, machine learning...