Customers’ loyalty model in the design of e-commerce recommender systems

Recommender systems have been adopted in most modern online platforms to guide users in finding more suitable items that match their interests. Previous studies showed that recommender systems impact the buying behavior of e-commerce customers. However, service providers are more concerned about the...

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Main Author:	Abumalloh, Rabab Ali
Format:	Thesis
Language:	English
Published:	2021
Subjects:	QA75 Electronic computers Computer science
Online Access:	http://eprints.utm.my/id/eprint/101511/1/RababAliAbumallohPSC2021.pdf
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id	my-utm-ep.101511
record_format	uketd_dc
spelling	my-utm-ep.1015112023-06-21T10:24:01Z Customers’ loyalty model in the design of e-commerce recommender systems 2021 Abumalloh, Rabab Ali QA75 Electronic computers. Computer science Recommender systems have been adopted in most modern online platforms to guide users in finding more suitable items that match their interests. Previous studies showed that recommender systems impact the buying behavior of e-commerce customers. However, service providers are more concerned about the continuing behavior of their customers, specifically customers’ loyalty, which is an important factor to increase service providers’ share of wallet. Therefore, this study aimed to investigate the customers’ loyalty factors in online shopping towards e-commerce recommender systems. To address the research objectives, a new research model was proposed based on the Cognition-Affect-Behavior model. To validate the research model, a quantitative methodology was utilized to gather the relevant data. Using a survey method, a total of 310 responses were gathered to examine the impacts of the identified factors on customers’ loyalty towards Amazon’s recommender system. Data was analysed using Partial Least Square Structural Equation Modelling. The results of the analysis indicated that Usability (P=0.467, t=5.139, p<0.001), Service Interaction (P=0.304, t=4.42, p<0.001), Website Quality (P=0.625, t=15.304, p<0.001), Accuracy (P=0.397, t=6.144, p<0.001), Novelty (P=0.289, t=4.406, p<0.001), Diversity (P=0.142, t=2.503, p<0.001), Recommendation Quality (P=0.423, t=7.719, p<0.001), Explanation (P=0.629, t=15.408, p<0.001), Transparency (P=0.279, t=5.859, p<0.001), Satisfaction (P=0.152, t=3.045, p<0.001) and Trust (P=0.706, t=14.14, p<0.001) have significant impacts on customers’ loyalty towards the recommender systems in online shopping. Information quality, however, did not affect the quality of the website that hosted the recommender system. The findings demonstrated that accuracy-oriented measures were insufficient in understanding customer behavior, and other quality factors, such as diversity, novelty, and transparency could improve customers’ loyalty towards recommender systems. The outcomes of the study indicated the significant impact of the website quality on customers’ loyalty. The developed model would be practical in helping the service providers in understanding the impacts of the identified factors in the proposed customers’ loyalty model. The outcomes of the study could also be used in the design of recommender systems and the deployed algorithm. 2021 Thesis http://eprints.utm.my/id/eprint/101511/ http://eprints.utm.my/id/eprint/101511/1/RababAliAbumallohPSC2021.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:150616 phd doctoral Universiti Teknologi Malaysia Faculty of Engineering - School of Computing
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	QA75 Electronic computers Computer science
spellingShingle	QA75 Electronic computers Computer science Abumalloh, Rabab Ali Customers’ loyalty model in the design of e-commerce recommender systems
description	Recommender systems have been adopted in most modern online platforms to guide users in finding more suitable items that match their interests. Previous studies showed that recommender systems impact the buying behavior of e-commerce customers. However, service providers are more concerned about the continuing behavior of their customers, specifically customers’ loyalty, which is an important factor to increase service providers’ share of wallet. Therefore, this study aimed to investigate the customers’ loyalty factors in online shopping towards e-commerce recommender systems. To address the research objectives, a new research model was proposed based on the Cognition-Affect-Behavior model. To validate the research model, a quantitative methodology was utilized to gather the relevant data. Using a survey method, a total of 310 responses were gathered to examine the impacts of the identified factors on customers’ loyalty towards Amazon’s recommender system. Data was analysed using Partial Least Square Structural Equation Modelling. The results of the analysis indicated that Usability (P=0.467, t=5.139, p<0.001), Service Interaction (P=0.304, t=4.42, p<0.001), Website Quality (P=0.625, t=15.304, p<0.001), Accuracy (P=0.397, t=6.144, p<0.001), Novelty (P=0.289, t=4.406, p<0.001), Diversity (P=0.142, t=2.503, p<0.001), Recommendation Quality (P=0.423, t=7.719, p<0.001), Explanation (P=0.629, t=15.408, p<0.001), Transparency (P=0.279, t=5.859, p<0.001), Satisfaction (P=0.152, t=3.045, p<0.001) and Trust (P=0.706, t=14.14, p<0.001) have significant impacts on customers’ loyalty towards the recommender systems in online shopping. Information quality, however, did not affect the quality of the website that hosted the recommender system. The findings demonstrated that accuracy-oriented measures were insufficient in understanding customer behavior, and other quality factors, such as diversity, novelty, and transparency could improve customers’ loyalty towards recommender systems. The outcomes of the study indicated the significant impact of the website quality on customers’ loyalty. The developed model would be practical in helping the service providers in understanding the impacts of the identified factors in the proposed customers’ loyalty model. The outcomes of the study could also be used in the design of recommender systems and the deployed algorithm.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Abumalloh, Rabab Ali
author_facet	Abumalloh, Rabab Ali
author_sort	Abumalloh, Rabab Ali
title	Customers’ loyalty model in the design of e-commerce recommender systems
title_short	Customers’ loyalty model in the design of e-commerce recommender systems
title_full	Customers’ loyalty model in the design of e-commerce recommender systems
title_fullStr	Customers’ loyalty model in the design of e-commerce recommender systems
title_full_unstemmed	Customers’ loyalty model in the design of e-commerce recommender systems
title_sort	customers’ loyalty model in the design of e-commerce recommender systems
granting_institution	Universiti Teknologi Malaysia
granting_department	Faculty of Engineering - School of Computing
publishDate	2021
url	http://eprints.utm.my/id/eprint/101511/1/RababAliAbumallohPSC2021.pdf
_version_	1776100715393974272

Customers’ loyalty model in the design of e-commerce recommender systems

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