Constructing marketing decision support systems using data diffusion technology: A case study of gas station diversification

Authors:
Der-Chiang Li;Yao-San Lin;Yu-Cheng Huang
Affiliations:
Department of Industrial and Information Management, National Cheng Kung University, 1, University Road, Tainan City, Taiwan;Department of Management Information Science, Chung Hwa University of Medical Technology, No.89, Wenhwa 1st St., Rende Shiang, Tainan County, Taiwan;ChiaNan Office, Marketing Business Division, CPC Corporation, Taiwan No. 16, ChengKung Road, Tainan City, Taiwan
Venue:
Expert Systems with Applications: An International Journal
Year:
2009

Citing 9
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Abstract

Building a decision support system (DSS) using small data sets usually results in uncertain knowledge, likely leading to incorrect decisions and causing a large losses. However, gathering sufficient samples for building a DSS often has significant costs in many cases. To solve this problem, a case study of a particular business decision-making procedure in which only small data sets are available is discussed. The learning accuracy for the modeling phase in the DSS was improved using the mega-trend-diffusion technique, which includes two learning tools: Back-propagation network and Bayesian network. The case study, a business diversification decision for an oil company, shows that the proposed technique contributes to increasing the prediction precision using very limited experience.