Hongxin Yu

ORCID: 0000-0001-6944-4898
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Research Areas
  • Advanced Technologies in Various Fields
  • FinTech, Crowdfunding, Digital Finance
  • Blockchain Technology Applications and Security
  • Supply Chain Resilience and Risk Management
  • Business Strategy and Innovation
  • Financial Reporting and Valuation Research
  • Supply Chain and Inventory Management
  • Energy Load and Power Forecasting
  • Construction Project Management and Performance
  • AI and HR Technologies
  • Forecasting Techniques and Applications
  • Stock Market Forecasting Methods
  • Market Dynamics and Volatility
  • Organizational and Employee Performance
  • Climate Change Policy and Economics
  • Financial Markets and Investment Strategies
  • Collaboration in agile enterprises
  • Taxation and Compliance Studies
  • Energy, Environment, and Transportation Policies
  • BIM and Construction Integration
  • Corporate Taxation and Avoidance
  • Innovation and Knowledge Management
  • Innovation Diffusion and Forecasting
  • Industrial Technology and Control Systems
  • IoT and Edge/Fog Computing

Shanghai Business School
2019-2024

Northeast Petroleum University
2010

Bank of China
2007

Northeastern University
2006

Abstract This study aims to examine the green innovation effect of carbon emissions pilot policy in China. First, using difference-in-differences method and regressions instrumental variables data from Chinese listed firms, we verify that promotes among regulated firms is more pronounced state-owned enterprises, eastern region, those with lower financing constraints. Furthermore, this positive spreads downstream relative through input–output linkages, but reduces upstream firms. Accordingly,...

10.1186/s40854-022-00359-0 article EN cc-by Financial Innovation 2022-06-01

10.1007/s10257-019-00414-x article EN Information Systems and e-Business Management 2019-07-09

To strengthen the development of enterprises and optimize knowledge management strategies, current situation enterprise (EKM) is investigated evaluation indicators EKM strategies are analyzed. The specific structure principles neural network algorithms studied using big data. Finally, networks (NNs) technology used to evaluate calculate weight strategy application results show that with support data, use NNs can analyze not only but also different by enterprises. When analyzing collected...

10.1016/j.jik.2022.100273 article EN cc-by-nc-nd Journal of Innovation & Knowledge 2022-09-30

With the gestation and development of new technologies, products, formats, models, venture capital investment, as one most important forms open innovation in large companies, plays an increasingly role mature companies entrepreneurial enterprises. To deal with complex dynamic environment, niche Corporate Venture Capital (CVC) ecological community is investigated from perspective ecosystem. By analyzing CVC use logistic expansion model, this paper analyzes stability evolution game through...

10.1155/2020/6327218 article EN cc-by Complexity 2020-08-28

In the financial market, because of information asymmetry, investors often ignore private information. Herding behavior in markets has become an important research branch behavioral finance. China stock market implemented Shanghai‐Hong Kong Stock Connect (SHKSC) policy and introduced mature funds, however, it alleviated herd effect? This article empirically verifies existence China's before after implementation SHKSC policy. The this found that not changed herding behavior. On contrary,...

10.1155/2022/7278023 article EN cc-by Discrete Dynamics in Nature and Society 2022-01-01

Summary Based on the analysis of existing traditional supply chain financial model, this article proposes an edge intelligence‐enabled model based Business‐to‐Business (B2B) platforms, combines operation mechanism and quantitative thinking financing. This uses to construct evaluates cost–benefit dealers, manufacturers, B2B e‐business platforms in perspective finance for platforms. In order further explore strategy member enterprises, also explores selection financing objects optimization...

10.1002/cpe.6353 article EN Concurrency and Computation Practice and Experience 2021-05-07
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