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

Khine Mi Mi Hmu Tin, Henry Lau

Research output: Contribution to journalArticlepeer-review

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.
Original languageEnglish
Pages (from-to)57-79
Number of pages23
JournalInternational Journal of Industrial and Systems Engineering
Volume35
Issue number1
DOIs
Publication statusPublished - 2020

Keywords

  • business enterprises
  • decision making
  • decision support systems

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