Journal of Management Science and Engineering

Aims & Scope

The Journal of Management Science and Engineering (JMSE) is an international, peer-reviewed, scholarly journal that publishes scientific research on the latest developments and practices of management science and engineering, emphasizing modeling, optimization, computation, and data analytics for identifying and solving management problems, making business decisions, and managing risks in complex management systems.

JMSE strives to stimulate research resulting from the interconnection of technological disruption, the changing atlas of the global economy, and the current common challenges of human beings.

This journal serves the entire management science and engineering community, including researchers, practitioners, educators, and students.

We encourage studies addressing research questions based on management and business practice, works focusing on new management topics originating from social and technology advancement, and interdisciplinary research and cross-functional studies on management and business.

Both empirical and theoretical contributions are welcome.

Metrics & Ranking

Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Directory of Open Access Journals (DOAJ)
• Web of Science

Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Business, Management and Accounting, Decision Sciences and Engineering, designed to support cutting-edge academic discovery.

Licensing & Copyright

This journal operates under an Open Access model. Articles are freely accessible to the public immediately upon publication. The content is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0), allowing users to share and adapt the work with proper attribution.

Copyright remains with the author(s), and no permission is required for non-commercial use, provided the original source is cited.

Policy Links

This section provides access to essential policy documents, guidelines, and resources related to the journal’s publication and submission processes.

• Aims scope
• Homepage
• Oa statement
• Author instructions
• License terms
• Review url
• Board url
• Copyright url
• Plagiarism url
• Preservation url
• Apc url
• License

Plagiarism Policy

This journal follows a plagiarism policy. All submitted manuscripts are screened using reliable plagiarism detection software to ensure originality and academic integrity. Authors are responsible for proper citation and acknowledgment of all sources, and any form of plagiarism, including self-plagiarism, will not be tolerated.

For more details, please refer to our official: Plagiarism Policy.

APC Details

The journal’s Article Processing Charge (APC) policies support open access publishing in Business, Management and Accounting, Decision Sciences and Engineering, ensuring accessibility and quality in research dissemination.

This journal does not charge a mandatory Article Processing Charge (APC). However, optional open access publication may incur fees based on the publisher’s policies.

Explore journals without APCs for alternative publishing options.

Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• A systematic review of a digital twin city: A new pattern of urban governance toward smart cities

  Citation: 264

  Authors: Tianhu, Keren, Zuo-Jun (Max)

• Social responsibility portfolio optimization incorporating ESG criteria

  Citation: 92

  Authors: Li, Lipei, Jun, Helu, Zhongbao

• Internet-of-things enabled supply chain planning and coordination with big data services: Certain theoretic implications

  Citation: 62

  Authors: Longfei, Mei, Bin

• Is bitcoin a safe haven or a hedging asset? Evidence from China

  Citation: 61

  Authors: Gangjin, Yanping, Chi, Shou

• A combined machine learning algorithms and DEA method for measuring and predicting the efficiency of Chinese manufacturing listed companies

  Citation: 59

  Authors: Nan, Chuanjin, Ali

• Firm Characteristics and Chinese Stocks

  Citation: 47

  Authors: Fuwei, Guohao, Guofu

• Supply chain and logistics innovations with the Belt and Road Initiative

  Citation: 45

  Authors: Hau L., Zuo-Jun (Max)

• The role of oil futures intraday information on predicting US stock market volatility

  Citation: 44

  Authors: Yusui, Xiao, M.I.M., Feng

• A supplier evaluation model based on customer demand in blockchain tracing anti-counterfeiting platform project management

  Citation: 40

  Authors: Aijun, Taoning, Jian, Ruiyao

• Structural analysis and forecast of gold price returns

  Citation: 38

  Authors: Jian, Chenyu, Yi, Zhe George