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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