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

Der-Chiang Li, Yao San Lin, Yu Cheng Huang

研究成果: Article同行評審

7 引文 斯高帕斯(Scopus)

摘要

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.

原文English
頁(從 - 到)2525-2533
頁數9
期刊Expert Systems With Applications
36
發行號2 PART 1
DOIs
出版狀態Published - 2009 3月 1

All Science Journal Classification (ASJC) codes

  • 工程 (全部)
  • 電腦科學應用
  • 人工智慧

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