About the Journal

Journal of Economic Theory and Business Management is peer-reviewed journal of Southern United Academy of Sciences published in the field of Economics, Finance and Business. The journal registers independent DOI and ARK for each article. The DOI prefix is ​​10.70393 and the ARK prefix is ​​40704.

ISSN 3006-4953 (Print), ISSN 3006-4961 (Online), International CODEN (CAS): JETBAU

The journal focuses on the following fields:

  • Economy - Macroeconomics, Microeconomics, Development Economics
  • Finance - Corporate Finance, Investment Banking, Personal Finance
  • Business - Entrepreneurship, Business Strategy, Business Ethics
  • Trading - International Trade, Forex Trading, Commodity Trading
  • Commerce - E-Commerce, Retail Management, Wholesale Trade
  • Logistics - Supply Chain Management, Inventory Management, Freight Forwarding
  • Transportation - Public Transportation, Transportation Engineering, Logistics Optimization
  • Tax - Tax Policy, Tax Planning, International Taxation
  • Management - Project Management, Operations Management, Strategic Management
  • Accounting - Financial Accounting, Managerial Accounting, Auditing
  • Industrial Economy - Industrial Policy, Industrial Organization, Industrial Development
  • Supervision - Regulatory Supervision, Corporate Governance, Risk Management
  • Law - Commercial Law, Contract Law, Intellectual Property Law

All articles published by JCTAM are indexed by OpenAIRE, BASE, WorldCat and ICI.

(OpenAIRE - DataSources | BASE - Bielefeld Academic Search Engine | WorldCat - OCLC)

All articles published are rigorously reviewed meeting the Journal Quality standards.

Announcements

Current Issue

Vol. 2 No. 2 (2025)
View Vol. 2 No. 2 (2025)

All articles published in this issue have undergone a thorough peer review process, and stringent checks for repetition rates have been implemented to ensure the integrity of the content.

Total number of articles in this issue: 3
Total number of pages in this issue: 23

For inquiries regarding the content of specific articles, please feel free to contact the respective authors via their provided email addresses. For questions related to the journal itself, please reach out directly to SUAS Press.

Published: 2025-04-18

Articles

  • The Theoretical Logic and Practical Path of Promoting High-Quality Development In Xinjiang with Historical and Cultural Resource Endowments
    DOI Icon DOI: 10.70393/6a6574626d.323830
    DOI Icon ARK: ark:/40704/JETBM.v2n2a01
    Authors: Si Chen
    Resource Type: Article
    Disciplines: Development Economics | Subjects: Cultural Empowerment
    Publication ID: v2n2a01
    Abstract: Committee of the Political Bureau of the Central Committee, Secretary of the Secretariat of the Central Committee, and President of China, emphasizes that ' culture is an important fulcrum to promote high-quality development '. he also...
    1-7
    DOI Icon Abstract views: 43 | DOI Icon PDF downloads: 18 | DOI Icon references: 8
  • Big Data-Driven ESG Quantitative Investment Strategy
    DOI Icon DOI: 10.70393/6a6574626d.323837
    DOI Icon ARK: ark:/40704/JETBM.v2n2a02
    Authors: Bingxing Wang
    Resource Type: Article
    Disciplines: Finance | Subjects: Investment Banking
    Publication ID: v2n2a02
    Abstract: With sustainability becoming more important worldwide, investors are looking more closely at environmental, social, and governance (ESG) factors. This paper looks at how big data could help investors use ESG information effectively in quantitative...
    8-13
    DOI Icon Abstract views: 96 | DOI Icon PDF downloads: 40 | DOI Icon references: 15
  • Real-time Early Warning of Trading Behavior Anomalies in Financial Markets: An AI-driven Approach
    DOI Icon DOI: 10.70393/6a6574626d.323838
    DOI Icon ARK: ark:/40704/JETBM.v2n2a03
    Authors: Boyang Dong, Toan Khang Trinh
    Resource Type: Article
    Disciplines: Finance | Subjects: Investment Banking
    Publication ID: v2n2a03
    Abstract: This paper introduces a novel AI-driven approach for real-time early warning of trading behavior anomalies in financial markets. The proposed system integrates advanced deep learning architectures with traditional statistical methods to enhance...
    14-23
    DOI Icon Abstract views: 105 | DOI Icon PDF downloads: 35 | DOI Icon references: 47
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