2021 International Conference on Public Management and Big Data Analysis (PMBDA 2021)
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2021 International Conference on Public Management and Big Data Analysis  (PMBDA 2021) will bring together leading researchers, engineers and scientists in the domain of interest from around the world.

Topics of interest for submission include, but are not limited to:

Public Management:
Big Data Analysis

The environmental protection

The energy management

Digital city

The project management

Urban management

Service science

Information management

Information security

Logistics management

Risk management

Operations management

Supply chain management

Technical management

Systems engineering

Big data Management

Traffic and Transportation management

Industrial Engineering and management

Safety engineering and management

Civil and structural engineering

Logistics and supply chain management

New product development and product engineering

Operations research

New public management theory

Public affairs research

Urban public management and public services

Administration and International Administration

Changes in public governance

Public utility environmental studies

The origin and development of public administration

Public administration and traditional administrative mode

Research on control mode and operation mechanism

The safety management

Social governance

Social management system innovation and exploration

Public service quality management

Sustainable urban development

Big data analysis search algorithm and system

Big data search algorithms and systems

Big data analytics, analytics and metrics

Big data analysis architecture

Big data models and algorithms

Big data Architecture

Big data Management

Big data protection, integrity and privacy

Big data security applications

Big data search and mining

Big data for business, government and society

Block chain

Economic statistics under big data

Big data analysis of business model innovation

Big data analysis for business, government and society

Large number in enterprise performance management

Enterprise transformation of big data

Economic growth and technological innovation

Basic model of big data

Presentation format of multimedia big data

Privacy protection big data analysis

Big data visualization analysis

Data mining algorithm

Algorithms and programming techniques for big data processing

Cloud computing technology for big data

Big data analysis and measurement

Big data services

Big data encryption

Open platform for big data

Big data quality and management

Models and languages for big data protection

Distributed and point-to-point search

Machine learning based on big data

Big data in enterprise performance management

Big data for business model innovation

Big data in mobile and pervasive computing

All papers, both invited and contributed, will be reviewed by two or three experts from the committees. After a careful reviewing process, all accepted papers of PMBDA 2021 will be submitted for indexing by EI Compendex and Scopus.

Submission Methods

1.The submitted papers must not be under consideration elsewhere.

2.Please send the full paper(word+pdf) to SUBMISSION SYSTEM

3.Please submit the full paper, if presentation and publication are both needed.

4.Please submit the abstract only, if you just want to make presentations.

5.Templates Downlow:Templates

6.Should you have any questions, or you need any materials in English, please contact the conference secretary.


1) Both Abstract and Full Paper are welcomed. The author can make an oral presentation after the Abstract is accepted and the payment is finished.

2) All submitted articles should report original, previously unpublished research results, experimental or theoretical. Articles submitted to the conference should meet these criteria and must not be under consideration for publication elsewhere. We firmly believe that ethical conduct is the most essential virtual of any academic. Hence any act of plagiarism is a totally unacceptable academic misconduct and cannot be tolerated.