-------- Weitergeleitete Nachricht -------- Betreff: [AISWorld] CFP: Special Issue on Big Data Driven Risk and Contingency Management in IJRCM Datum: Sun, 16 Oct 2016 10:43:28 +1000 Von: Zhaohao Sun zhaohao.sun@gmail.com An: BISC-Group bisc-group@eecs.berkeley.edu, IRMA ListServ irma-l@irma-international.org, irma-list@irma-international.org, aisworld@lists.aisnet.org
CALL FOR PAPERS
Special Issue on Big Data Driven Risk and Contingency Management (BRCM 2017)
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-man...) 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
· Big data as discipline
· Big data analytics as a science and technology
· 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-ris...
· http://www.wikicfp.com/cfp/servlet/event.showcfp?eventid=58071
*Important dates*:
· Full paper submission: January 1, 2017
· Notification of acceptance: February 15, 2017
· Revised submission: March 15, 2017
· Final acceptance notification: April 30, 2017
· Camera ready final version of paper: June 30, 2017
· Publication: July – December, 2017
* Guest Editors*
Dr Zhaohao Sun, Ph.D.
Associate Professor and HoD
Director of Research Centre of Big Data Analytics and Intelligent Systems (BAIS)
Department of Business Studies, PNG University of Technology, Lae, PNG,
Email: zsun@dbs.unitech.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 _______________________________________________ AISWorld mailing list AISWorld@lists.aisnet.org