8/8/2019 Ins Call for Papers Jan2010
1/3
Editor in ChiefW. PedryczDept. of Electrical and Computer
EngineeringUniversity of AlbertaElectrical & Comp
EngineeringResearch FacilityEdmonton, T6G 2V4,
[email protected]
______________________Guest EditorsProf. Dr. Desheng Dash
Wu,Affiliated Professor, RiskLab,Director of RiskChina
ResearchCenter,
University of TorontoToronto, ON M5S 3G3
[email protected],[email protected]
Prof. Dr. Shu-Heng Chen, Director,AI-ECON Research Center, Dep.
ofEconomics, National ChengchiUniversity, Taipei,Taiwan
11623,[email protected]
Prof. Dr. David L. Olson
James and H.K. StuartChancellor's DistinguishedChair,Dep. of
ManagementUniversity of NebraskaLincoln, NE
[email protected]
______________________
Important datesPaper submission:15-11-2010
Acceptance notification:15-08-2011
Final papers:01-10-2011
______________________
Call for Papers
A Special Issue of Information Sciences
On Business Intelligence in Risk Management
Introduction
Risks exist in every aspect of our lives, and can mean
different
things to different people, while negatively in general they
always
cause a great deal of potential damage and inconvenience for
the
stakeholders. For example, recent disaster risks include
terrorism
leading to the gassing of the Japanese subway system, to
9/11/2001, to bombings of Spanish and British transportation
systems, and the SARS virus disrupting public and business
activities, particularly in Asia. More recently, the H1N1 virus
has
sharpened the awareness of the response system world-wide;
the
financial crisis has resulted in recession in all aspects of
theeconomy(Wu and Olson 2009).
Risk management has become a vital topic in both academia
and practice during the past several decades. Integrated
approaches
are required to manage risks facing an organization;
sometimes
effective risk-taking strategies may involve new business
philosophies such as enterprise risk management.
Most business intelligence tools have been used for
enhancing risk management, and the risk management tools
benefit
from business intelligence approaches. For example,
artificial
intelligence models such as neural networks and support
vector
machines have been widely used for establishing the early
warning
system for monitoring a companys financial status (e.g.,
Martens
et al. 2007; Alfaro et al. 2008; Lin and Chen 2007).
Agent-based
theories are employed in supply chain risk management (e.g.,
Julka
et al. 2002; Liang and Huang, 2006). Business intelligence
models
are also useful in hedging financial risks by incorporating
market
risks, credit risks, and operational risks (Wu and Olson
2009).
Investigation of business intelligence tools in risk management
is
beneficial to both practitioners and academic researchers.
8/8/2019 Ins Call for Papers Jan2010
2/3
About the issue
This special issue of Information Sciences is intended to
present the recent advances in using business
intelligence for enterprise risk management. Authors are
encouraged to submit both theoretical and
applied articles addressing this theme in this special
issue.
Topics
Potential topics include, but are not limited to:
Artificial intelligence in enterprise risk management
Agent-based supply chain risk management
Portfolio selection of various financial instruments
Credit scoring using data mining
Data mining in managing market risks
Intelligence multi-criteria decision making in financial
services
Agent-based simulation in operational risk management
Game agents in risk management
Artificial intelligence for natural disasters risk
management
Many other uses of business intelligence for enterprise risk
management
Submission format
The submitted papers must be written in English and describe
original research which is not published nor currentlyunder review
by other journals or conferences. Author guidelines for preparation
of manuscript can be found at
http://www.ees.elsevier.com/ins For more information, please
contact the Editor-in-Chief:W. [email protected]
or
managing guest editor:
Desheng Dash WU ([email protected])
Submission Guideline
All manuscripts and any supplementary material should be
submitted through Elsevier Editorial System (EES).The authors must
select asSpec.Iss: Business Intelligence in Risk when they reach
the Article Type step inthe submission process. The EES website is
located at:
http://www.ees.elsevier.com/ins
