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Journal of Theoretical and Applied Electronic Commerce Research is published by MDPI from Volume 16 Issue 3 (2021). Previous articles were published by another publisher in Open Access under a CC-BY 3.0 licence, and they are hosted by MDPI on mdpi.com as a courtesy and upon agreement with Faculty of Engineering of the Universidad de Talca.
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Article

Personality-Based Personalization of Online Store Features Using Genetic Programming: Analysis and Experiment

by
Alireza Kazeminia
1,
Marjan Kaedi
1 and
Beenazir Ganji
2
1
University of Isfahan, Faculty of Computer Engineering, Isfahan, Iran
2
Payame Noor University (PNU), Department of Computer Science, Tehran, Iran
J. Theor. Appl. Electron. Commer. Res. 2019, 14(1), 16-29; https://doi.org/10.4067/S0718-18762019000100103
Submission received: 5 August 2017 / Accepted: 16 January 2018 / Published: 1 January 2019
Versions Notes

Abstract

The decisions made by the customers in online environments are influenced by their personality characteristics. Each customer in an online environment relies more heavily on certain features of a store to make decisions while ignoring others. Thus, personalizing these features may streamline the decision-making process and increase satisfaction. In this paper, an intelligent method for personalizing the features of an online store according to the users’ personality is presented. In the proposed method, using genetic programming several equations are developed to estimate how users with different personality characteristics prefer various features of an online store. These equations are then used for personalization of the store features to increase customers’ satisfaction and persuade them to make larger purchases. The evaluation on a sample of 194 individuals indicates that the obtained equations are able to estimate the user’s preferences with over 80% accuracy in most cases. In addition, empirical assessment of the obtained equations shows that the proposed personalization method improves the user satisfaction.
Keywords: Personalization; Online shopping; Personality; Decision-making style; Genetic Programming Personalization; Online shopping; Personality; Decision-making style; Genetic Programming

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MDPI and ACS Style

Kazeminia, A.; Kaedi, M.; Ganji, B. Personality-Based Personalization of Online Store Features Using Genetic Programming: Analysis and Experiment. J. Theor. Appl. Electron. Commer. Res. 2019, 14, 16-29. https://doi.org/10.4067/S0718-18762019000100103

AMA Style

Kazeminia A, Kaedi M, Ganji B. Personality-Based Personalization of Online Store Features Using Genetic Programming: Analysis and Experiment. Journal of Theoretical and Applied Electronic Commerce Research. 2019; 14(1):16-29. https://doi.org/10.4067/S0718-18762019000100103

Chicago/Turabian Style

Kazeminia, Alireza, Marjan Kaedi, and Beenazir Ganji. 2019. "Personality-Based Personalization of Online Store Features Using Genetic Programming: Analysis and Experiment" Journal of Theoretical and Applied Electronic Commerce Research 14, no. 1: 16-29. https://doi.org/10.4067/S0718-18762019000100103

APA Style

Kazeminia, A., Kaedi, M., & Ganji, B. (2019). Personality-Based Personalization of Online Store Features Using Genetic Programming: Analysis and Experiment. Journal of Theoretical and Applied Electronic Commerce Research, 14(1), 16-29. https://doi.org/10.4067/S0718-18762019000100103

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