Journal
COMPUTERS IN INDUSTRY
Volume 47, Issue 2, Pages 199-214Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/S0166-3615(01)00147-6
Keywords
location selection; artificial neural network; error back-propagation learning algorithm; convenience store (CVS)
Ask authors/readers for more resources
Location selection plays a very prominent role in retailing due to its high and long-term investments. It is very difficult to make up once an inappropriate convenience store (CVS) location has been established, The conventional approaches to location selection can only provide a set of systematic steps for problem-solving without considering the relationships between the decision factors globally. Therefore, this study aims to develop a decision support system for locating a new CVS. The proposed system consists of four components: (1) hierarchical structure development for fuzzy analytic hierarchy process (fuzzy AHP), (2) weights determination, (3) data collection, and (4) decision making. In the first component, the hierarchical structure of fuzzy AHP is formulated by reviewing the related references and interviewing the retailing experts. Then, a questionnaire survey is conducted to determine the weight of each factor in the second component, while the corresponding data are collected through some government publications and actual investigation. Finally, a feedforward neural network with error back-propagation (EBP) learning algorithm is applied to study the relationship between the factors and the store performance. The results show that proposed system is able to provide more accurate result than regression model in accuracy. (C) 2002 Elsevier Science B.V. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available