Retail expansion decision based on improved marginal analysis

Authors:
S. Li
Affiliations:
Department of Industrial Engineering and Management, Shanghai Jiao Tong University, Shanghai 200240, PR China
Venue:
Expert Systems with Applications: An International Journal
Year:
2011

Citing 10
Cited 0

Neural Networks: A Comprehensive Foundation

Neural Networks: A Comprehensive Foundation
An Approximation Scheme for Stochastic Integer Programs Arising in Capacity Expansion

Operations Research
Generation Capacity Expansion in Imperfectly Competitive Restructured Electricity Markets

Operations Research
Simulation-optimization mechanism for expansion strategy using real option theory

Expert Systems with Applications: An International Journal
Introducing functional classification theory to land use planning by means of decision tables

Decision Support Systems
Capacity expansion decision in supply chains: A control theory application

International Journal of Computer Integrated Manufacturing - THE CHALLENGES OF MANUFACTURING IN THE GLOBALLY INTEGRATED ECONOMY. GUEST EDITOR: ROBIN G. QIU
Forward recursive scheme with improved marginal analysis heuristic for machine expansion scheduling in a new job shop

Computers and Industrial Engineering
Online elicitation of Mamdani-type fuzzy rules via TSK-based generalized predictive control

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Deterministic approach to robust adaptive learning of fuzzy models

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Building Sugeno-type models using fuzzy discretization and orthogonal parameter estimation techniques

IEEE Transactions on Fuzzy Systems

Quantified Score

Hi-index	12.05

Visualization

Abstract

Marginal analysis (MA) is one of the most thriving methods of generating retail expansion strategy. However, traditional MA heavily relies on the current marginal index (MI), such as present marginal profit and marginal cost. Because things change quickly in the market, expansion decision based on conventional MA is always imperfect, that is, either missing the greatest profit or stoking the excess investment. The aim of this study is then to improve the accuracy of decision-making in retail expansion using the improved marginal analysis (IMA). We first identify the factors affecting retail expansion and define the future MI. Next, the future MI is calculated based on fuzzy decision method and two improvements are also provided: one is that adaptively to fuzzify decision variables according to their scattered distribution, and another is that to perfect the decision table according to the approximately quantitative relationship among decision variables. Finally, principles for expansion are proposed, that is, if the future MI is less than 1, there is a need for controlling the expansion scale; otherwise, it is sensible to expand the investment scale as much as possible within finical capacity.