How Artificial Intelligence-Enabled Customer Behavior Analytics Reshapes Value Creation in E-Commerce Business Models

Xianpeng Jiang; Liping Zhang; Moldabekova Aisulu

doi:10.47297/wspeiWSP2516-253517.20261003

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How Artificial Intelligence-Enabled Customer Behavior Analytics Reshapes Value Creation in E-Commerce Business Models

Volume 10, Issue 3

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How Artificial Intelligence-Enabled Customer Behavior Analytics Reshapes Value Creation in E-Commerce Business Models
How Artificial Intelligence-Enabled Customer Behavior Analytics Reshapes Value Creation in E-Commerce Business Models
Farabi International Business School, Al-Farabi Kazakh National University, Almaty, 050040, Kazakhstan
Vol. 10, Issue 3, Pages: 86-90(2026)
Online First：13 August 2026，

Published：30 June 2026
DOI：10.47297/wspeiWSP2516-253517.20261003
Accepted：

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Jiang Xianpeng,Zhang Liping,Aisulu Moldabekova.How Artificial Intelligence-Enabled Customer Behavior Analytics Reshapes Value Creation in E-Commerce Business Models[J].Entrepreneurship and Innovation,2026,10(03):86-90.
DOI：

Jiang Xianpeng,Zhang Liping,Aisulu Moldabekova.How Artificial Intelligence-Enabled Customer Behavior Analytics Reshapes Value Creation in E-Commerce Business Models[J].Entrepreneurship and Innovation,2026,10(03):86-90. DOI： 10.47297/wspeiWSP2516-253517.20261003.

摘要

Abstract

On the largest e-commerce platforms

artificial intelligence is no longer a supplementary tool but the operating logic through which value is created

delivered

and captured. Marketing research has treated the personalization side of that shift; service research has treated the automation side. The business-model consequence has been left under-theorized: how the three canonical components of value creation are rewired when customer behavior analytics runs continuously in the loop. This paper builds a conceptual framework linking three tiers of AI-enabled analytics (descriptive

predictive

and generative) to three business-model components (value proposition

value delivery

and value capture). Drawing on secondary evidence from Amazon

Alibaba

Shein

and Shopee

we argue that AI-enabled analytics does not merely optimize existing offerings; it changes what value is being created

from products to continuously personalized experiences. Three governance tensions follow—transparency

privacy

and algorithmic dependence—which we read not as side effects but as constitutive of the reshaped model. The paper contributes a bridge between the marketing-analytics literature and business-model theory

together with a set of testable propositions for later empirical work.

关键词

Keywords

references

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