BEIJING, July 5, 2024 /PRNewswire/ -- In a world where
e-commerce platforms offer consumers an overwhelming array of
products, data assets are the linchpins of digital platform
operations as data-driven algorithm recommendations help users
discover and purchase their desired items. But what would happen if
these recommendations were turned off?
Sun Tianshu, CKGSB Dean's Distinguished Chair Professor of
Information Systems and Director of the Center for Digital
Transformation, has explored this question by quantifying the value
of personal data to e-commerce platforms through the world's first
large-scale randomized field experiment on 550,000 e-commerce users
in collaboration with Zhejiang
University and Alibaba, detailed in his recent paper published
at Management Science, a top management journal, titled,
"The Value of Personal Data in Internet Commerce: A High-Stake
Field Experiment on Data Regulation Policy."
The experiment uniquely assessed the significance of data assets
to the digital platform economy by disabling the algorithmic
recommendation system based on personal data on the platform's
homepage for the test group. The results were telling: when users
were denied access to information flows recommended to them based
on characteristics inferred from their personal data, ecommerce
platforms saw asymmetry in the products recommended, hurting the
diversity of products on platforms and leading to fewer
transactions and lower engagement rate.
Products recommended on the homepage dropped from 4 million to
around 280,000, and the top 1,000 products from leading brands took
up 90% of recommended slots for a disproportionately high exposure.
Customers' click-through rate (CTR) and page views (PV) went down
by 75.3% and 33.6% respectively and sellers' gross merchandise
value (GMV) and transaction volume plummeted by a whopping 81.1%
and 86%. Small and medium-sized sellers on the platform saw a 54%
decrease in pageviews and a 90% drop in GMV, suggesting they were
more impacted than leading sellers, whose PV fell by 27% and GMV by
79%. Research also found consumers with low purchasing power are
negatively impacted.
This paper provides a quantified basis for how to balance the
use of data assets and personal privacy protection through
large-scale experiments, but also helps businesses formulate more
informed digital economic policies.
Professor Sun leads CKGSB's Center for Digital Transformation,
focusing on digital business, digital technology and implication
for traditional businesses. This research underscores CKGSB's
commitment to pioneering knowledge that drive understanding and
innovation in the digital economy.
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