Attracting Potential Customers in E-Commerce Environments: A Comparative Study of Metaheuristic Algorithms

Reza Yazdani,Mohammad Javad Taghipourian,Seyed Shamseddin Hosseini,Mohammad Mahdi Pourpasha

doi:10.3390/pr10020369

Abstract

Internet technology has provided an indescribable new way for businesses to attract new customers, track their behaviour, customise services, products, and advertising. Internet technology and the new trend of online shopping have resulted in the establishment of numerous websites to sell products on a daily basis. Products compete to be displayed on the limited pages of a website in online shopping because it has a significant impact on sales. Website designers carefully select which products to display on a page in order to influence the customers’ purchasing decisions. However, concerns regarding appropriate decision making have not been fully addressed. As a result, this study conducts a comprehensive comparative analysis of the performance of ten different metaheuristics. The ant lion optimiser (ALO), Dragonfly algorithm (DA), Grasshopper optimisation algorithm (GOA), Harris hawks optimisation (HHO), Moth-flame optimisation algorithm (MFO), Multi-verse optimiser (MVO), sine cosine algorithm (SCA), Salp Swarm Algorithm (SSA), The whale optimisation algorithm (WOA), and Grey wolf optimiser (GWO) are some of the recent algorithms that were chosen for this study. The results show that the MFO outperforms the other methods in all sizes. MFO has an average normalised objective function of 81%, while ALO has a normalised objective function of 77%. In contrast, HHO has the worst performance of 16%. The study’s findings add new theoretical and practical insights to the growing body of knowledge about e-commerce environments and have implications for planners, policymakers, and managers, particularly in companies where an unplanned advertisement wastes the budget.

Highlights

Companies need to devise a strategy for attracting new customers and generating revenue in order to achieve long-term success [1,2]
A comprehensive metaheuristic analysis is proposed in this study to decide the items displayed on each page of a website
Based on the available information about consumer behaviour, the results showed that Moth-flame optimisation algorithm (MFO)

Summary

Introduction

Companies need to devise a strategy for attracting new customers and generating revenue in order to achieve long-term success [1,2]. In today’s competitive environment, the Internet enables businesses to keep track of their customers’ points of search and behaviour on a real-time basis [3,4]. In this manner, the information that is collected may be used to provide input for the customisation of products, services, prices, and improvements in the method of communication [5,6]. The progressively accumulated knowledge of consumer wants aids a business in improving the electronic presentation of products and services in order to ensure that they meet or exceed the customer’s expectations [12]. Effective online communication of information for sales promotion in a virtual environment and the quality of the information that is provided and conveyed to customers is key in their decision making

Objectives

Results

Discussion

Conclusion