Channel selection and pricing optimization in multichannel e-tailing
| Date | 11 February 2025 |
| Pages | 1162-1189 |
| DOI | https://doi.org/10.1108/IMDS-06-2024-0514 |
| Published date | 11 February 2025 |
| Author | Lei Chen,Lihong Cheng,Yuxing Cheng,Xuesong Xu |
Channel selection and pricing
optimization in multichannel e-tailing
Lei Chen
School of Management, Hefei University of Technology, Hefei, China
Lihong Cheng
Anhui Provincial Key Laboratory of Digital Intelligence Supply Chain,
School of Management, International Institute of Finance,
University of Science and Technology of China, Hefei, China
Yuxing Cheng
Anhui Provincial Key Laboratory of Digital Intelligence Supply Chain,
School of Management, University of Science and Technology of China,
Hefei, China, and
Xuesong Xu
Department of Frontier Interdisciplinary,
Hunan University of Technology and Business, Changsha, China
Abstract
Purpose –This paper considers an e-tailer planning to distribute a product under one direct sales channel and
multiple asymmetric agency platforms. Based on the multinomial logit (MNL) choice model, this study
optimizes the pricing strategy and channel selection strategy to maximize the e-tailer’s profit.
Design/methodology/approach –A two-stage channel selection and pricing problem is formulated, where the
profit-maximizing e-tailer first optimally selects a specified number of agency platforms from a set of
alternatives to distribute the product and then determines the optimal prices in those channels.
Findings–An optimal pricing strategy is proposed to maximize the e-tailer’s total profit on multiple asymmetric
channels. The results show that the e-tailer can obtain a higher profit by selling products on more asymmetric
agency platforms. Moreover, an effective channel selection algorithm is provided to help the e-tailer optimally
select the M agency platforms from N alternatives.
Originality/value –This study enriches the relevant research on multichannel selection and pricing by
proposing an optimal pricing strategy and an effective channel selection algorithm. Evaluation results based on
real-world industrial data show that the proposed optimal multichannel pricing strategy in this paper can
significantly improve the profit of a real-world e-tailer compared to the e-tailer’s actual profit.
Keywords Channel selection, Multichannel pricing, MNL choice model, E-commerce,
Data-driven optimization
Paper type Research paper
1. Introduction
Recent advances in internet and e-commerce technologies have enabled more and more
traditional retailing firms to adopt a multiplatform e-tailing strategy. In other words, a product
can be sold on multiple e-commerce platforms, such as Tmall, JD, and Amazon, to attract a
broader range of consumers and increase sales. Meanwhile, these firms may also build and
keep their direct channels, typically called official malls or flagship stores, that sell their
products to consumers directly and compete with the indirect channels. As a result, a typical
IMDS
125,3
1162
The authors thank the co-editor and the anonymous referees for their valuable comments, constructive
suggestions and encouragement. The quality of this article improved substantially as a result of their
valuable feedback.
Funding: This work is funded by the National Natural Science Foundation of China (Nos: 72301264,
71991463/71991464/71991460, 72091210 and 71921001) and the China Postdoctoral Science
Foundation (No: 2022M720135).
The current issue and full text archive of this journal is available on Emerald Insight at:
https://www.emerald.com/insight/0263-5577.htm
Received 1 June 2024
Revised 9 September 2024
2 December 2024
Accepted 2 January 2025
IndustrialManagement & Data Systems
Vol.125 No. 3, 2025
pp.1162-1189
©Emerald Publishing Limited
e-ISSN:1758-5783
p-ISSN:0263-5577
DOI10.1108/IMDS-06-2024-0514
e-commerce firm distributes its products through two main kinds of channels: a direct sales
channel and an indirect channel; the latter is usually called online retailing or platform agency
selling. For example, Suzhou Babyonline, the partner in this research paper, is a cross-border
e-commerce clothing firm in China that mainly sells women’s dresses, full dresses, wedding
gowns, and other wedding accessories. Babyonline sells these through channels that can be
divided into the two classes mentioned above; one is the Babyonlinedress website
(babyonlinedress.com), which is regarded as the official online mall, and the rest are
multiple third-party agency platforms, including Amazon (amazon.com), AliExpress
(aliexpress.com), and DHgate (dhgate.com).
When an e-tailer sells the same product on multiple platforms, it may set different prices in
different distribution channels, with a possible explanation that consumers’ different
valuations on the product quality and channel service are significantly associated with
different channels. For example, considering a specific evening dress from Babyonline with
SKU (CPA887),its selling prices on Amazon, AliExpress, and DHgate are $22.68, $21.40, and
$28.23, respectively, within a certain selling period. To further display the differences in
Babyonline’s pricing strategy in different channels, we analyze the sales data from January
2018 to December 2019 [1] and find a significant difference between the selling price and
corresponding purchasing cost in these four main channels, as shown in Figure 1. The
purchasing cost for each SKU is almost unchanging within the whole selling period, so for
simple display in figures, we use the value of unit selling price divided by the corresponding
unit purchasing cost for the SKU, denoted as “Price/Cost”, to show the variation of its price.
Figure 1 shows the average weekly “Price/Cost” of all SKUs that sold simultaneously on
the four channels (Babyonline, Amazon, AliExpress, and DHgate) within the selling period
from January 2018 to December 2019. From Figure 1, we can find that the value of “Price/
Cost” in each channel changes distinctively over the selling period. The “Price/Cost” of
Amazon and AliExpress vary slightly and smoothly, staying near the values of 4 and 2,
respectively, and DHgate’s price is slightly higher from 4 to 6. The direct channel’s
(Babyonline’s) “Price/Cost” varies in a wider range but usually falls between 4 and 10. In
summary, Figure 1 reveals a general phenomenon that the prices of Babyonline’s four selling
channels significantly differ, and the average price of the direct sales channel is considerably
higher than in the indirect agency channels. In addition, different prices appear on the three
agency platforms, with DHgate’s price being higher than Amazon’s,while AliExpress’s price
is the lowest.
When e-commerce enterprises distribute products through one direct sales channel and
multiple asymmetric agency platforms, it is imperative to optimize the pricing strategy and
channel selection strategy, which can increase sales volume and boost enterprises’
profitability. Specifically, we explore the following research questions: (1) What is the
optimal pricing strategy for the direct sales channel and multiple asymmetric agency
platforms? (2) How should e-tailers make the optimal channel selection decision when they
Source(s): Figure created by authors
Figure 1. Average weekly “Price/Cost” of Babyonline’sproducts sold from 2018.01 to 2019.12
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