App Adoption: The Effect on Purchasing of Customers Who Have Used a Mobile Website Previously

Abstract

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Analyzing User Behaviour and Page Views Based on Visitor Traffic in Kolej Universiti Poly-Tech Mara Website Using Google Analytic

“…This indicates that to retain visitors' interest, the information provided must be compelling enough. The further the interactions or the deeper the interactions indicates more user engagement (Liu et al, 2019;Minatogawa et al, 2020).…”

“…Mobile's access websites or applications also said to be a widely used method for marketing medium as it may attract the consumer easily. This is due to the application, or mobile version website is designed perfectly to the small screen of the handphone (Liu et al, 2019) Therefore, in order to gauge the effectiveness of the design, the website traffic and user navigation patterns were analyzed. User behaviour has been studied over the years to determine the design effectiveness (Bufquin et al, 2019;Cyr & Head, 2013;Dianat et al, 2019;Guan et al, 2014;Scholz et al, 2018).…”

Analysing the Effect of Platform and Operating System Features on Predicting Consumers’ Purchase Intent using Machine Learning Algorithms

“…In addition, customer experience is important in improving attribution outcomes (e.g., conversion rates) by combining clickstream and survey data to understand consumers' decision processes. Finally, in (Liu et al, 2019) authors explored whether consumers' app adoption stimulates additional purchases and how this change in purchase behaviour differs across customers with different levels of spending share for different product categories and customer loyalty. Transactional data from a Chinese online retailer were used.…”

“…The most common approach taken by many recent studies is to identify the next buyer or the buyer intent using machine learning algorithms such as deep learning (Salehinejad and Rahnamayan, 2016), (Korpusik et al, 2016), other works such as (Kim et al, 2003) used multiple classifier while authors in (Qiu et al, 2015) and (Raphaeli et al, 2017) used unsupervised learning such as association rules. Moreover, consumers buying behaviour is analysed using different methods such as statistical methods (Gupta and Pathak, 2014) and hidden Markov model (Norouzi and Alizadeh, 2016) to identify and recommend a given product or service (Martínez et al, 2020), (Raphaeli et al, 2017), (Bang et al, 2013) (Wang et al, 2015), (Kaatz et al, 2019) and (Liu et al, 2019).…”

The Influence of Brand Trust in Mediating Consumer Online Behavior Against Buying Interest in Online Stores (Case Study of Hypermart Online Shop in Indonesia)

“…It can be concluded that consumers have no interest in shopping online in e-commerce or market places that are not yet known. E-commerce and well-known market places certainly have a good reputation in the minds of consumers and are more attractive (Casalo et al, 2007;Liu et al, 2019). Based on this matter, it is certainly rather difficult for new business actors in the world of online shopping to be able to attract consumers to buy instantly.…”