-------- Forwarded Message --------
CALL FOR PAPERS
Special Issue on Big Data Driven Risk and Contingency Management
(BRCM
2018) in International Journal of Risk and Contingency Management
The International Journal of Risk and Contingency Management
(ISSN:
2160-9624 e-ISSN: 2160-9632) (
http://www.igi-global.com/journal/international-journal-risk-contingency-management/53135)
is covered in risk and contingency management, and is abstracted
and
indexed in ACM Digital, INSPEC, Bacon's Media Directory, Cabell's
Directories, Google Scholar, Index Copernicus, (SCOPUS is in
progress).
Risk is the effect of uncertainty on goals. Where there is
uncertainty,
there is risk. Where there is risk, there should have contingency
management. Therefore, uncertainty, risk and contingency are
ubiquitous,
and are always a topic for our research and development. However,
the
dramatic development of the Internet leads to global uncertainty
in
economy, military, industry, etc. Big data intensifies global
uncertainty
and risk in many areas including management decision making,
healthcare,
finance, banking, privacy and security.
Big data has become a strategic asset for industry, business, and
national
security. Big Data is also a key enabler of exploring business
insights and
economics of services. Big Data is characterized with at least six
bigs:
big volume, big velocity, big variety, big value, big veracity,
and big
market. Big data has brought about big challenge for risk and
contingency
management. For example, what big data driven approach can improve
risk and
contingency management in the age of big data? How can we manage
big data
driven risk and contingency in industry, finance, business and
other
sectors.
1 Objective and topics
The objective of this Special Issue in International Journal of
Risk and
Contingency Management is to present the current state of research
and
practical experiences on big data driven risk and contingency
management.
Topics of interest include, but are not limited to, the following:
1. Fundamentals of Risk and Contingency Management
* New computational models
* Mathematical fundamentals
* Statistical modelling
* Machine learning
* Optimization techniques
* Business models
2. Big Data Driven Approach for Risk and Contingency Management
* Risks and contingency management in economics and finance, risk
transfer, underwriting;
* Risk versus uncertainty, macro-level studies of risk-sensitive
industries; certainty, determinism;
* Comparative studies of risk or contingency management across
organizations;
* Comparative analysis of risks and/or contingency across
disciplines and
workplace functions;
* Global economic recession critical analysis;
* Significant global events/impacts (global warming, flooding,
tsunamis,
earth quakes, terrorism, etc.);
* Crisis and incident management, contingency planning, risk
mitigation;
* Big data driven security & privacy
* Big data analytics for risk and contingency management
* Big data analytics for risk assessment
* Big data driven uncertainty analytics
3. Applications of Big Data Driven Risk and Contingency Management
Cross
Disciplines and Industries including
* Web services
* E-commerce
* Healthcare
* Cloud computing
* Social networking platforms and services
* Banking
* Insurance
* National security
Notes for Intending Authors
We are seeking original, genuine, innovative, scientifically
rigorous
research articles on big data driven approach for risk and
contingency
management. Empirical research, case studies or theory based
qualitative
and quantitative studies on big data driven risk management and
contingency
management are also welcome.
Submitted papers should not have been previously published nor be
currently
under consideration for publication elsewhere. Submitted
manuscripts
should be structured as technical papers and may not exceed 8000
words. All
submissions will be anonymously reviewed by at least two reviewers
based on
originality, correctness, technical strength, significance,
quality of the
manuscript. Submissions must be uploaded to the IJRCM system with
the
special information in the title page, “This is a manuscript for
Special
Issue on Big Data Driven Risk and Contingency Management” at:
http://www.igi-global.com/submission/manuscripts/?jid=53135
The title page of any submission for this special issue must be
emailed to
zhaohao.sun@gmail.com.
Questions may be emailed to the editor of this special issue at
zhaohao.sun@gmail.com.
The tentative title and abstract consisting of less than 150 words
should
be submitted to the editor at one’s earliest convenience for
constructive
suggestion.
For more information, please visit the following web site.
*
http://www.igi-global.com/calls-for-papers-special/international-journal-risk-contingency-management/53135
*
http://www.wikicfp.com/cfp/servlet/event.showcfp?eventid=58071
Important dates:
* Full paper submission: September 30, 2018
* Notification of acceptance: October 30, 2018
* Revised submission: November 30, 2018
* Final acceptance notification: December 30, 2018
* Publication: March, 2019
Guest Editors
Prof. Dr Zhaohao Sun, Ph.D.
Director & HoD
Research Center of Big Data Analytics and Intelligent Systems
(BAIS)
Department of Business Studies
PNG University of Technology, Lae, PNG,
Email:
zhaohao.sun@pnguot.ac.pg, or
zhaohao.sun@gmail.com
https://www.researchgate.net/profile/Zhaohao_Sun
Prof. Dr Ken Strang
School of Business & Economics
State University of New York, Plattsburgh at Queensbury, NY 12804,
USA
kenneth.strang@plattsburgh.edu
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