Open AccessUsing Statistical Models For Market Selection
Author(s) -
Kenneth M. Johnson
Publication year - 2011
Publication title -
journal of applied business research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.149
H-Index - 22
eISSN - 2157-8834
pISSN - 0892-7626
DOI - 10.19030/jabr.v2i2.6586
Subject(s) - selection (genetic algorithm) , task (project management) , order (exchange) , process (computing) , computer science , industrial organization , statistical model , economics , operations research , business , econometrics , management science , artificial intelligence , engineering , management , finance , operating system
Managers responsible for corporate development in growing firms are often called upon to identify promising new markets. Selecting such markets is a complex problem requiring the simultaneous consideration of many demographic, economic, business and competitive factors (Craig, et al, 1984). The need to examine a large pool of possible markets in order to identify those with the greatest potential further complicates the selection process. This article provides an overview of a statistical technique known as general linear modeling and explains how it can be successfully applied to the task of selecting markets.