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Highlights in Business, Economics and Management最新文献

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Selecting The Best Customer for A Plan to Reduce Wildlife Trade Based on A Comprehensive Evaluation Model 基于综合评估模型为减少野生动植物贸易计划选择最佳客户
Highlights in Business, Economics and Management Pub Date : 2024-07-22 DOI: 10.54097/5485sj37
Fan Xu, Qian Wang, Feiyang Yin, Minghao Xiao
{"title":"Selecting The Best Customer for A Plan to Reduce Wildlife Trade Based on A Comprehensive Evaluation Model","authors":"Fan Xu, Qian Wang, Feiyang Yin, Minghao Xiao","doi":"10.54097/5485sj37","DOIUrl":"https://doi.org/10.54097/5485sj37","url":null,"abstract":"In order to reduce the negative impact of illegal wildlife trade on ecology and socio-economic development, this article proposes a plan called \"Wildlife Trade Trap: Five Year Strategic Plan\", which covers key areas such as policy, publicity, education, economic development, and international cooperation. This article constructs a comprehensive evaluation model based on Analytic Hierarchy Process (AHP), which allocates indicators such as publicity, education, fundraising, and social impact according to weights. The report provides a comprehensive analysis of the strengths of WWF, Traffic, UN Environment, and IUCN in reducing the illegal wildlife trade. The results show that IUCN is the best customer for executing projects.","PeriodicalId":336504,"journal":{"name":"Highlights in Business, Economics and Management","volume":"19 22","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141815821","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Research On the Impact of China's Industrial Chain Security Under US-China Trade Friction Based on DID Methodology 基于 DID 方法的中美贸易摩擦下中国产业链安全影响研究
Highlights in Business, Economics and Management Pub Date : 2024-07-22 DOI: 10.54097/gq32ce73
Hanqing Cao, Binying Fang, Ziyi Qi
{"title":"Research On the Impact of China's Industrial Chain Security Under US-China Trade Friction Based on DID Methodology","authors":"Hanqing Cao, Binying Fang, Ziyi Qi","doi":"10.54097/gq32ce73","DOIUrl":"https://doi.org/10.54097/gq32ce73","url":null,"abstract":"This paper mainly studies the security of China's industrial chain under Sino-US trade friction. First, by considering the integrity, stability and competitiveness of the industrial chain, a comprehensive security level measurement system is established. Secondly, through the regression analysis based on the difference in differences model, it is found that the US restrictive policy on China has a negative impact on the security of China's industrial chain, but the measures taken by China to expand multilateral trade, increase exports and promote independent innovation have effectively mitigated the impact. Finally, the robustness test confirms the reliability of the conclusions, and the heterogeneity analysis of 21 industries shows that trade frictions mainly have a negative impact on capital - and technology-intensive industries, especially technology-intensive industries. Based on the conclusions of the model, this paper suggests that we should continue to improve China's industrial chain security monitoring and early warning system, while strengthening policy support for technology-intensive industries to cope with the challenges of international trade uncertainties.","PeriodicalId":336504,"journal":{"name":"Highlights in Business, Economics and Management","volume":"11 15","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141816229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Gaussian Process Regression Based on Stochastic Segmentation of Data and Its Application to Stock Price Prediction 基于数据随机分割的高斯过程回归及其在股价预测中的应用
Highlights in Business, Economics and Management Pub Date : 2024-07-22 DOI: 10.54097/aht26065
Zishun Liu
{"title":"Gaussian Process Regression Based on Stochastic Segmentation of Data and Its Application to Stock Price Prediction","authors":"Zishun Liu","doi":"10.54097/aht26065","DOIUrl":"https://doi.org/10.54097/aht26065","url":null,"abstract":"Gaussian Process Regression (GPR) is a powerful model for stock price prediction in both research and practice within financial markets. However, when applying GPR to stock price prediction, the model faces overfitting and underfitting problems. Moreover, when the amount of processed data is large, computational complexity and resource consumption become significant factors limiting its practical application. To address the above challenges, this study proposes a Gaussian process regression model based on stochastic data segmentation. It aims to optimize the computational efficiency of the model and improve the prediction performance. This method not only significantly reduces the computational complexity, but also improves the prediction performance through integrated learning of sub-models. It also improves the generalization ability of the model through the integrated learning of sub-models. In addition, the introduction of the model averaging strategy effectively mitigates the overfitting and underfitting problems by weighting the uncertainty measures of the sub-models. To verify the effectiveness of the proposed method, this study first analyzes a large number of simulation experiments. The performance of the model is systematically evaluated. Secondly, by selecting the stock data of listed companies in a number of different industries as the research object, the application value and robustness of this method in the real market environment are further confirmed.","PeriodicalId":336504,"journal":{"name":"Highlights in Business, Economics and Management","volume":"19 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141816291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Digital Inclusive Finance and Financing Constraints - A Study Based on Manufacturing Industry 数字普惠金融与融资约束--基于制造业的研究
Highlights in Business, Economics and Management Pub Date : 2024-07-22 DOI: 10.54097/88hk8954
Si Li, Zhe Huang, Jinxin Liu
{"title":"Digital Inclusive Finance and Financing Constraints - A Study Based on Manufacturing Industry","authors":"Si Li, Zhe Huang, Jinxin Liu","doi":"10.54097/88hk8954","DOIUrl":"https://doi.org/10.54097/88hk8954","url":null,"abstract":"As an important part of China's economy, manufacturing firms have a fundamental impact on promoting high-quality economic growth. Digital inclusive finance is developing rapidly with its characteristics of digitization and other features, which is expected to alleviate the financing constraints of manufacturing firms. This paper selects manufacturing enterprises from 2011 to 2022 as the research object, and empirically examines the role and influence mechanism of digital inclusive finance on the financing constraints of manufacturing enterprises.The findings from the study indicate that there exists a substantial inverse relationship between digital inclusive finance and the financial limitations faced by manufacturers.In particular, the digital inclusive finance index has a more important negative relationship with financing constraints for enterprises with a high average age of management and high digitization level. In addition, digital inclusive finance can also reduce firms' financing constraints by breaking information asymmetry and reducing firms' leverage.","PeriodicalId":336504,"journal":{"name":"Highlights in Business, Economics and Management","volume":"17 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141817119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Multidimensional Analysis of Development Indicators for New Energy Vehicles: A Study Based on Principal Component Analysis and Grey Correlation Analysis Model 新能源汽车发展指标的多维分析：基于主成分分析和灰色关联分析模型的研究
Highlights in Business, Economics and Management Pub Date : 2024-07-22 DOI: 10.54097/1mrjgt02
Jianya Zhao, Libing Chen, Xuhan Chen
{"title":"Multidimensional Analysis of Development Indicators for New Energy Vehicles: A Study Based on Principal Component Analysis and Grey Correlation Analysis Model","authors":"Jianya Zhao, Libing Chen, Xuhan Chen","doi":"10.54097/1mrjgt02","DOIUrl":"https://doi.org/10.54097/1mrjgt02","url":null,"abstract":"The recent rapid growth of the new energy vehicle(NEV)industry has established it as a pivotal force in sustainable development. Yet, challenges in technology, cost, market, and policy hinder its high-quality development. Understanding these factors is essential for policy-making, fostering innovation, and guiding investment. This paper study employed principal component analysis to examine primary indicators' impact on NEV development and a grey relational model to assess various secondary indicators' significance and correlation with industry progress. The study found that while policy measures in China have persistently hampered the industry, market factors have begun positively influencing it since 2019. Furthermore, NEV indicators increasingly shape their own development, with economic factors exerting relatively limited influence. Market and economic indicators like Per Capita GDP and Carbon Trading Price exhibit strong correlations, while indicators linked to NEV characteristics such as range, fuel prices, and vehicle prices closely drive industry advancement, particularly in China's NEV sector.","PeriodicalId":336504,"journal":{"name":"Highlights in Business, Economics and Management","volume":"18 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141816068","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A Study of Stock Price Prediction Models Based on Kernel Clustering Localized Sliced Inverse Regression and Bayesian Model Averaging 基于核聚类局部切片反回归和贝叶斯模型平均法的股价预测模型研究
Highlights in Business, Economics and Management Pub Date : 2024-07-22 DOI: 10.54097/s7fv9a29
Zhenpei Yang
{"title":"A Study of Stock Price Prediction Models Based on Kernel Clustering Localized Sliced Inverse Regression and Bayesian Model Averaging","authors":"Zhenpei Yang","doi":"10.54097/s7fv9a29","DOIUrl":"https://doi.org/10.54097/s7fv9a29","url":null,"abstract":"Multifactor prediction models are pivotal in quantitative finance research, yet face issues such as the curse of dimensionality, complex interconnections, and model overfitting. To address these challenges, this study introduces a machine learning predictive model grounded in sufficient dimension reduction and model averaging principles, tailored for stock price forecasting. This method innovatively employs kernel function-based clustering and weighting to refine classic Sliced Inverse Regression, thereby mitigating the curse of dimensionality while maximally preserving the efficacy of predictive factors on stock prices. Furthermore, this approach utilizes Bayesian Model Averaging to navigate the intricate relationships between factors and stock prices, alleviating the risks of overfitting and underfitting. Empirical analysis demonstrates that, compared to traditional quantitative prediction models, this approach produces lower mean squared error, absolute error, and relative error in stock price forecasting, thereby confirming its accuracy and robustness.","PeriodicalId":336504,"journal":{"name":"Highlights in Business, Economics and Management","volume":"16 24","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141816329","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Research On Investment in The New Energy Vehicle and Power Battery Market Based on Fundamentals and Technologies 基于基本面和技术的新能源汽车和动力电池市场投资研究
Highlights in Business, Economics and Management Pub Date : 2024-07-22 DOI: 10.54097/0f8qha13
Haoyi Zhang
{"title":"Research On Investment in The New Energy Vehicle and Power Battery Market Based on Fundamentals and Technologies","authors":"Haoyi Zhang","doi":"10.54097/0f8qha13","DOIUrl":"https://doi.org/10.54097/0f8qha13","url":null,"abstract":"The new energy vehicle market and the power battery industry showed steady growth, especially in April, although it was the off-season, the power battery market boomed. The concentration of China's power battery market has increased, led by CATL. The Ministry of Industry and Information Technology (MIIT) issued new specifications aimed at improving the quality and market concentration of battery products. Big technology companies at home and abroad are involved in the new energy vehicle market, indicating that new energy vehicles will be the dominant market in the future. The rise of a number of new energy vehicle brands is beneficial to CATL, and the cooperation may increase revenue and market value. The article analyzes the macro economy, the state of the new energy and lithium battery industries, and the development prospects of CATL. Technicals and stock market sector rotation are also included in the comprehensive analysis, looking forward to market investment opportunities and risks.","PeriodicalId":336504,"journal":{"name":"Highlights in Business, Economics and Management","volume":"30 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141816807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Data-Driven Financial Strategy Transformation: The Impact of Corporate Data Capital Utilization on The Level of Financial Asset Allocation 数据驱动的金融战略转型：企业数据资本利用对金融资产配置水平的影响
Highlights in Business, Economics and Management Pub Date : 2024-07-22 DOI: 10.54097/bkkrbs97
Jiayu He, Xinrui Kou
{"title":"Data-Driven Financial Strategy Transformation: The Impact of Corporate Data Capital Utilization on The Level of Financial Asset Allocation","authors":"Jiayu He, Xinrui Kou","doi":"10.54097/bkkrbs97","DOIUrl":"https://doi.org/10.54097/bkkrbs97","url":null,"abstract":"This paper empirically investigates the impact of corporate data capital utilization on the level of financial asset allocation and its underlying mechanisms, based on a sample of listed companies on the Shanghai and Shenzhen stock exchanges from 2010 to 2021. The study finds that the level of corporate data capital utilization has a significant positive effect on the level of financial asset allocation, a conclusion that remains robust after conducting various methods of robustness checks. Mechanism analysis indicates that operational acumen positively moderate the relationship between data capital utilization and the level of financial asset allocation.  Heterogeneity analysis reveals that the positive impact of corporate data capital utilization on financial asset allocation is more significant in companies located in central regions, non-state-owned enterprises, and companies with high ESG ratings. This research provides insights for promoting the transformation of corporate financial strategies and optimizing the structure of asset allocation.","PeriodicalId":336504,"journal":{"name":"Highlights in Business, Economics and Management","volume":"84 21","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141817499","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Research On Vegetable Replenishment and Pricing Optimization Decision Based on Time Series Prediction and Monte Carlo Simulation 基于时间序列预测和蒙特卡洛模拟的蔬菜补货和定价优化决策研究
Highlights in Business, Economics and Management Pub Date : 2024-07-22 DOI: 10.54097/dxhb6q85
Songling Fan
{"title":"Research On Vegetable Replenishment and Pricing Optimization Decision Based on Time Series Prediction and Monte Carlo Simulation","authors":"Songling Fan","doi":"10.54097/dxhb6q85","DOIUrl":"https://doi.org/10.54097/dxhb6q85","url":null,"abstract":"For large fresh supermarket, how to reasonably specify the replenishment and pricing strategy of vegetable commodities is very important. In order to give a reasonable replenishment decision, this paper conducts correlation analysis at first, including cost plus pricing strategy and correlation test. And then analyzes the relationship between sales volume and selling price by using neural network regression and scatter plot matrix, and finds that there is no obvious functional correlation between them. The paper use time series forecasting methods, including simple seasonal analysis and Winter multiplication model, to forecast sales volume and wholesale cost. Finally, the linear programming model was used to determine the total amount of replenishment and markup rate of each category of vegetables in the next week, and the corresponding income situation was obtained. The results of comprehensive analysis show that the replenishment volume, markup rate and income of different categories have dynamic fluctuations, reflecting the changes of demand and market.","PeriodicalId":336504,"journal":{"name":"Highlights in Business, Economics and Management","volume":"33 15","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141815439","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Exploring The Synergy: Combining Improved Sparrow Search Optimization with Long Short-Term Memory (LSTM) For Enhanced Stock Price Prediction 探索协同效应：将改进的麻雀搜索优化与长短期记忆（LSTM）相结合，增强股价预测能力
Highlights in Business, Economics and Management Pub Date : 2024-07-22 DOI: 10.54097/6mytfm47
Xin Zhang
{"title":"Exploring The Synergy: Combining Improved Sparrow Search Optimization with Long Short-Term Memory (LSTM) For Enhanced Stock Price Prediction","authors":"Xin Zhang","doi":"10.54097/6mytfm47","DOIUrl":"https://doi.org/10.54097/6mytfm47","url":null,"abstract":"The present study employs an improved Sparrow Search Optimization (SSA) technique to optimize hyperparameters in Long Short-Term Memory (LSTM) networks to predict stock prices. The present study adopts an innovative approach that leverages the augmented SSA's advanced capabilities to optimize the LSTM model's hyperparameters and enhance prediction accuracy. The evaluation measures are employed to test the performance of the proposed SSA-LSTM model on a specific stock market dataset. Our findings demonstrate that the SSA-LSTM model surpasses a conventional LSTM model when employing traditional tuning of hyperparameter methods. This gain showcases the improved synergy between the augmented SSA and the LSTM model, suggesting it can provide more precise stock price predictions.","PeriodicalId":336504,"journal":{"name":"Highlights in Business, Economics and Management","volume":"29 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141815451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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