Online AI algorithmic purchase decision pathways: shopping via mobile application

Nguyen, Thi Minh Tam

Abstract

In recent years, online shopping has become a popular option for buying goods and services. Accordingly, this study was conducted in order to observe consumers’ decision-making behaviour in an online buying environment via phone applications. The study focused on students, young people with a high potential for learning and using online shopping systems. This study looked at a number of outstanding factors selected for customer decision-making processes using the Throughput model.
In order to understand the different decision-making paths of customers in the range of online shopping on mobile applications in this study, the author has applied quantitative methods with convenient sampling combined with online surveys to investigate respondents of the study and introduce the importance of the study to respondents. In addition, quantitative data were analysed by SmartPLS software (version 3.0) which explains the structural equation model (SEM).
The findings of the study help to facilitate the development of the proposed model to explain the routes for the online consumers to make a decision when shop in the internet environment. It can be noticed that the flux model is not only good for marketing, management or financial areas, but it is also an effective decision-making model applied in the field of consumer behaviour judgement. Also, the study also proves that different buying decision-making routes for consumers in the online shopping environment are completely real. These findings contribute to the theoretical and practical aspects of finding online customer decision-making pathways depending on different products on mobile applications not only in Danang, Vietnam but also in other areas in the world. The findings from this study could be useful for e-commerce researchers, businesses, and online retailers to understand the consumer decision paths in particular and the customer behaviour in general, thereby guiding solid steps in producing, introducing products and persuading consumers.

Citation

Nguyen, T. M. T. (2022). Online AI algorithmic purchase decision pathways: shopping via mobile application. (Thesis). University of Hull. https://hull-repository.worktribe.com/output/4912628

• Thesis Type: Thesis
• Deposit Date: Nov 12, 2024
• Publicly Available Date: Jan 6, 2025
• Keywords: Online purchase decision; Algorithmic purchase decision pathways; Mobile shopping; Online shopping; Throughput Model
• Public URL: https://hull-repository.worktribe.com/output/4912628
• Additional Information: Business School; University of Hull
• Award Date: Jul 1, 2022