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A business process decision model for client evaluation using fuzzy AHP and TOPSIS

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  • Khine Mi Mi Hmu Tin
  • Henry Lau

Abstract

Customer selection is one of multi-criteria decision-making problems and is of strategic importance for most companies. The purpose of this paper is to develop a business process decision model to assess the potential and profitable customers in order to select the best performing customers using a digital marketing (DM) company's customer data and create multiple selection criterions from them. The existing problem in most business firms is the challenges in choosing a proper model which can be accurately assessed their customer performances. The proposed models in this study can provide a better insight for planning and implementing to gain competitive advantage in this area. This study proposes two multi-criteria decision making (MCDM) techniques, fuzzy analytical hierarchy process (FAHP) and technique for order of preference by similarity to ideal solution (TOPSIS), and apply these methods to analyse customer performance in a digital marketing company.

Suggested Citation

  • Khine Mi Mi Hmu Tin & Henry Lau, 2020. "A business process decision model for client evaluation using fuzzy AHP and TOPSIS," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 35(1), pages 57-79.
    • Handle: RePEc:ids:ijisen:v:35:y:2020:i:1:p:57-79
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