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Predicting Online Consumer Transaction from Big Data: Influential Factors and Strategic Planning
Wirel. Commun. Mob. Comput. ; 2021:9, 2021.
Article in English | Web of Science | ID: covidwho-1457447
ABSTRACT
Online transaction has recently benefited from coronavirus;however, the sales of e-commerce in some areas are substantially on the decline. The current study proposes a theoretically constructed and empirically viable way for predicting the relevant factors that may detract or foster e-commerce success. We apply web analytics (one of the big data techniques) to simultaneously, generalizably, and objectively measure the influential factors of e-commerce success. The findings indicate that (1) pageviews is an important key for consumers to make transactions. (2) Bounce rate of the website should not be a member factor of e-commerce success. (3) Adhesion strategy and repeatability strategy can be used to induce consumer online transaction. Several theoretical contributions and practical implications are also provided.

Full text: Available Collection: Databases of international organizations Database: Web of Science Type of study: Prognostic study Language: English Journal: Wirel. Commun. Mob. Comput. Year: 2021 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Web of Science Type of study: Prognostic study Language: English Journal: Wirel. Commun. Mob. Comput. Year: 2021 Document Type: Article