Multigene Genetic Programming Based Fuzzy Regression for Modelling Customer Satisfaction Based on Online Reviews

H. Yakubu, C. K. Kwong

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)

Abstract

As markets become increasingly competitive, most businesses have adopted modern practices that helps them to enhance the competitiveness of their products. Such practices involve the use of internet though which companies gain insights into the concerns of their customers. For instance, the proliferation of e-commerce websites has enabled consumers to voice their opinions on the products they have purchased. This study proposes a methodology for modelling customer satisfaction (CS) based on online reviews using a new multigene genetic programming based fuzzy regression (MGGP-FR). Polynomial structures of CS models were developed by employing the multigene genetic programming method. The fuzzy coefficients of the polynomial structures were then determined using the fuzzy regression analysis. The proposed method was illustrated using an electronic hair dryer as a case study. The validation test results indicated that MGGP-FR the outperformed the genetic programming based fuzzy regression and the fuzzy regression analysis in terms of prediction errors.

Original languageEnglish
Title of host publication2019 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2019
PublisherIEEE Computer Society
Pages1541-1545
Number of pages5
ISBN (Electronic)9781728138046
DOIs
Publication statusPublished - Dec 2019
Event2019 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2019 - Macao, Macao
Duration: 15 Dec 201918 Dec 2019

Publication series

NameIEEE International Conference on Industrial Engineering and Engineering Management
ISSN (Print)2157-3611
ISSN (Electronic)2157-362X

Conference

Conference2019 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2019
Country/TerritoryMacao
CityMacao
Period15/12/1918/12/19

Keywords

  • customer satisfaction models
  • fuzzy regression
  • multigene genetic programming
  • online reviews

ASJC Scopus subject areas

  • Business, Management and Accounting (miscellaneous)
  • Industrial and Manufacturing Engineering
  • Safety, Risk, Reliability and Quality

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