A business process decision model for client evaluation using fuzzy AHP and TOPSIS Online publication date: Thu, 23-Apr-2020
by Khine Mi Mi Hmu Tin; Henry Lau
International Journal of Industrial and Systems Engineering (IJISE), Vol. 35, No. 1, 2020
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.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Industrial and Systems Engineering (IJISE):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook