Study on the attractiveness of social e-commerce platforms from the consumers’ perspective based on the AISAS model

The traditional e-commerce’s traffic dividend is gradually declining, while social e-commerce as a new business model has attracted numerous enterprises to jump into by virtue of the advantages of viral traffic aggregation and efficient conversion. How to improve the core competitiveness and stand out from the Red Ocean battle of traffic competition is of great significance for the healthy and sustainable development of social e-commerce platforms. In view of this, this study focuses on the issues related to the attractiveness of social e-commerce platforms from the consumer’s perceptive, with the aim of providing theoretical support for social e-commerce platforms to enhance their core competitiveness and formulate relevant development strategies and decision-making mechanisms. First, four key factors affecting the attractiveness of social e-commerce platforms based on the AISAS model are proposed: the ability to attract consumers to access, promote consumers’ purchase conversion, maintain consumers’ platform loyalty, and attract to share experiences. Second, an attractiveness assessment model for social e-commerce platform including four secondary indicators and corresponding 14 tertiary indicators is constructed by using Analytic Hierarchy Process, and an arithmetic example is demonstrated. Finally, management suggestions to enhance the attractiveness of social e-commerce platforms are presented.

Authors

Institutions

Publication Details

Journal
Journal of Computational Methods in Sciences and Engineering
Published
2024-08-14
DOI
https://doi.org/10.3233/jcm-247477
Citations
1
Primary Topic
E-commerce and Technology Innovations
Type
article
Field-Weighted Citation Impact
0.68
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Study on the attractiveness of social e-commerce platforms from the consumers’ perspective based on the AISAS model

Yong Yang, QI Li-li, Qiaolun Gu, Jinbo Zhang et al.
1 citations
Journal of Computational Methods in Sciences and Engineering
E-commerce and Technology Innovations
0.68
article

Study on the attractiveness of social e-commerce platforms from the consumers’ perspective based on the AISAS model

Yong Yang, QI Li-li, Qiaolun Gu, Jinbo Zhang, Jing Li, Rui-Qi Yue, Wei Lin
article en
1 citations

Abstract

The traditional e-commerce’s traffic dividend is gradually declining, while social e-commerce as a new business model has attracted numerous enterprises to jump into by virtue of the advantages of viral traffic aggregation and efficient conversion. How to improve the core competitiveness and stand out from the Red Ocean battle of traffic competition is of great significance for the healthy and sustainable development of social e-commerce platforms. In view of this, this study focuses on the issues related to the attractiveness of social e-commerce platforms from the consumer’s perceptive, with the aim of providing theoretical support for social e-commerce platforms to enhance their core competitiveness and formulate relevant development strategies and decision-making mechanisms. First, four key factors affecting the attractiveness of social e-commerce platforms based on the AISAS model are proposed: the ability to attract consumers to access, promote consumers’ purchase conversion, maintain consumers’ platform loyalty, and attract to share experiences. Second, an attractiveness assessment model for social e-commerce platform including four secondary indicators and corresponding 14 tertiary indicators is constructed by using Analytic Hierarchy Process, and an arithmetic example is demonstrated. Finally, management suggestions to enhance the attractiveness of social e-commerce platforms are presented.

Journal of Computational Methods in Sciences and EngineeringVol. 24(4-5)
Tianjin University of Technology and Education (CN)
Openalex Percentile: Top 26%
E-commerce and Technology Innovations
0.68
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.