Call for paperes
The 3nd edition of the E-Conference on Multidisciplinary Research
- Education, E-learning, Virtual university
- Management Science, Social Science and Human Behaviour
- Economics and Finance
- Environment and Health management
- Logistics and Industry management
- Information system and ICT for organizations
Quantitative and Qualitative techniques :
- Data analysis, Data Science for quantitative and qualitative analysis
- Data mining for quantitative and qualitative analysis
- Machine learning, Big Data for quantitative and qualitative analysis
- Statistics approaches for quantitative analysis
- Mathematic Modeling and Econometrics
- Research Methodology
- Scientific communication, writing and publication
- Research design and Systematic literature review
- Inquiry design for qualitative/quantitative research
- Qualitative analysis with NVIVO and IRAMUTEQ
- Quantitative analysis with SPSS, SPSS AMOS and SmartPLS
- Data mining with R and Python
- Machine learning with Python
- Big data and data science methods for management and social research
– After this conference, the authors of selected papers will be invited to submit their extended article to next issues of MJQR (DOAJ, Proquest)
- All submissions should be original, professional and have not been published elsewhere. Paper length should exceed 3 pages followed (Max 5 pages) and it need be formatted strictly according to the Template.
- Submissions must be original, unpublished work, and not have been submitted to another conference or journal for publication. All submission will be peer-reviewed roughly by at least 2-3 experts.
- Authors are invited to submit English papers. Please confirm your papers with clear argumentation, close core, sufficient theoretical analysis, proper language and standard grammar in English.
- Submission of a paper implies that should the paper be accepted for formal publication, at least one of the authors will register and present the paper in the conference. Plagiarism in any form is not allowed.
QQR’21 uses the i-Thenticate software to detect instances of overlapping and similar text in submitted manuscripts. i-Thenticate software checks content against a database of periodicals, the Internet, and a comprehensive article database.