Vol 10, No 5 (2025) |
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Table of Contents
Original Research Article
by Fei Teng, Zhang Naiwen, Qiao Li, shanying Jia, Tongjinxin
Finan Mar
2025,
10(5);
doi: 10.18686/fm.v10i5.14176
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Intelligent-driven technologies and blockchain empowerment present new opportunities for cultivating financial digital creative
talents. This study focuses on their synergistic effects, analyzing the roles of intelligent-driven technologies and blockchain empowerment in
talent cultivation. It explores how their integration can optimize curriculum systems, innovate teaching methods, and enhance practical abilities, thereby nurturing financial digital creative talents who meet the demands of the new era and driving industry development.
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Original Research Article
by Guan Jianguo
Finan Mar
2025,
10(5);
doi: 10.18686/fm.v10i5.14177
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Amid national strategies for common prosperity and rural revitalization, this study examines the impact of the digital economy on
industrial resilience and the urban–rural income gap using panel data from 30 Chinese provinces (2013–2022). Our analysis reveals an inverted U-shaped relationship between digital economic development and the income gap, with China currently on the widening segment of the
curve. Industrial resilience serves as a significant partial mediator, indicating that digital expansion can reduce disparity by strengthening rural industries. We also identify regional heterogeneity, with more pronounced effects in eastern and economically advanced provinces. Policy
measures are proposed to enhance rural digital adaptation, encourage technology market expansion, and promote digital integration in rural
industries.
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Original Research Article
by Haohong Zhang
Finan Mar
2025,
10(5);
doi: 10.18686/fm.v10i5.14178
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Against the backdrop of high-quality economic development in the new era, the imbalance in income distribution between urban
and rural areas has become an important bottleneck restricting China’s economic and social development. With the advent of the digital economy era, digital inclusive finance (DIF) has provided new impetus and vitality to rural areas, thanks to its unique advantages of improving
coverage and enhancing accessibility to financial services. This study constructs a theoretical analysis framework and empirical model based
on the panel data of Sichuan Province from 2015 to 2023, and the results show that the application of DIF significantly increases the income
of rural residents and facilitates the optimization of resource allocation.
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Original Research Article
by Xu LIU
Finan Mar
2025,
10(5);
doi: 10.18686/fm.v10i5.14179
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Accurate forecasting of daily order volumes is critical for businesses facing rapid fluctuations in demand, particularly during promotional events such as the Subsidy War. This paper proposes a hybrid forecasting model combining log-normal distribution, ARIMA, and
LSTM to predict order volumes during and after the promotional period for a milk tea shop. For the promotional period, we model the demand using a log-normal distribution to capture the skewed and heavy-tailed nature of the order volume. Post-promotion, we use an ARIMA
model to account for trend in the order data, augmented with external temperature data to handle residual errors via an LSTM neural network.
A weighted sum of the ARIMA forecast and a decaying trend function is used to generate the final predictions, ensuring stationarity and
reducing overfitting. The proposed hybrid approach provides a robust solution for managing demand fluctuations, offering valuable insights
into both promotional and non-promotional periods.
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Original Research Article
by YAN JIAWEI
Finan Mar
2025,
10(5);
doi: 10.18686/fm.v10i5.14180
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Predicting stock trends is a social hotspot and choosing a proper model is crucial for stock research. This paper uses the daily closing prices of the china’s big four banks on the Shanghai Stock Exchange from January 2019 to June 2025 and calculates daily returns via the
logarithmic return method. Then, it analyzes returns and volatility, and applies the Markov chain to predict the return changes of these banks.
The results show that the four banks have different risk characteristics. Only the predicted returns of the Construction Bank are accurate,
while the actual returns of the other three banks are higher than the predicted ones. This indicates that the Markov chain method can effectively predict the minimum returns of the big four banks and that its prediction accuracy are related to the risk characteristics of the predicted
stocks.
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Original Research Article
by Yu Zou
Finan Mar
2025,
10(5);
doi: 10.18686/fm.v10i5.14181
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This article investigates e-commerce management across three industries in China—retail, manufacturing, and services—through
case analysis of Hailan Home, Haier Smart Home, and Ctrip. The research adopts a multi-method approach integrating theoretical review,
case study methodology, and secondary data analysis. Key dimensions assessed include digital strategy, infrastructure, and organizational
transformation. Findings indicate that in e-commerce management models, all management objectives need to be grounded in a cyclic framework of target anchoring, capability building and dynamic iteration, which has been validated by the performance growth of Hailan Home,
Haier Smart Home, and Ctrip across retail, manufacturing, and services, thereby driving overall corporate performance development.
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Original Research Article
by Xu Manlin
Finan Mar
2025,
10(5);
doi: 10.18686/fm.v10i5.14182
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As an important tool for achieving the “dual-carbon” goals and sustainable development, the development of green finance cannot
be separated from the support of an institutional system. Economic law provides a systematic institutional guarantee for green finance by establishing incentive mechanisms, clarifying rights and responsibilities, and optimizing resource allocation. Starting from the three dimensions
of incentive functions, this paper analyzes the mechanism of action of economic law in the development of green finance and explores targeted paths for institutional design.
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