ICIKS 2023
Mr Amine Belmejdoub Quotb, University of Portsmouth, UK (Amine.BelmejdoubQuotb@myport.ac.uk)
Dr Luis Madureira, NOVA IMS Information Management School, Portugal (lmadureira@novaims.unl.pt)
ICIKS 2023
At the heart of the Competitive Intelligence (CI) approach to strategy lies
the assumption that by applying a set of powerful analytical tools or
information gathering techniques, executives can predict the future of any
business accurately enough to allow them to choose a clear strategic
direction. However, when the environment is highly uncertain, no amount of
analysis will allow the prediction of future. Likewise, if the information
is dynamic and highly volatile, yesterday’s information will become obsolete
and irrelevant to current situation. A further concern is the highly
overwhelming volume of data and information to the degree that it becomes
unmanageable. This would lead to analysis paralysis and yield diminishing
returns, which will most likely distort the whole picture. One would also
question the ability of organizational policy makers to formulate the right
questions before requesting data gathering and analysis from CI
professionals; what if they misinterpret the analysed information? Recent
research purported that one must constantly remember that technology is
merely there to help with the process; it never explains why things happen
and rarely assists us in understanding the facts. In the same fashion, the
statistical analysis does not explain why or how things happen; it only
describes what has happened. Thus, in this track we are interested to
original and high-quality philosophical, theoretical and practical research
papers that advance research and practice on handling risk and uncertainly
to support Strategic Competitive Intelligence.
We particularly welcome submissions on the following topics (but not limited
to):