| Vol 10, No 5 (2025) | 
Full Issue
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Table of Contents
| Original Research Article 
			by 									Fei Teng,									Zhang Naiwen,									Qiao Hui Li,									shanying Jia,									Tongjinxin /										 
				Finan Mar
				2025,
													10(5);
								doi: 10.18686/fm.v10i5.14176						
			 
				15 Views,
				        
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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						
			 
				11 Views,
				        
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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						
			 
				13 Views,
				        
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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						
			 
				14 Views,
				        
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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.
			 | 
| Original Research Article 
			by 									YAN JIAWEI										 
				Finan Mar
				2025,
													10(5);
								doi: 10.18686/fm.v10i5.14180						
			 
				10 Views,
				        
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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						
			 
				14 Views,
				        
											0 PDF Downloads
												 
				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						
			 
				15 Views,
				        
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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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