基于销量更新规则和锚定效应的在线产品动态定价研究

doi:10.16381/j.cnki.issn1003-207x.2023.0753

摘要/Abstract

摘要：

折扣预售是线上销售的主要模式，双因素锚定行为是影响消费者购买决策的重要因素。折扣预售期间，消费者被价格锚定表现出强烈的购买意愿，该阶段产生的高额销量又通过销量锚定效应影响消费者决策行为，对产品的动态定价产生重要影响。然而，在平台销量更新规则的约束下，这种积极影响并非持续，它将在一段时间后消失。基于此，本文在折扣预售背景下，利用多项式Logit模型，考虑消费者被产品的价格和销量锚定，建立n阶段动态定价模型，分析双因素锚定效应和平台销量更新规则对在线零售商产品动态定价、销量和利润的影响。研究发现，受锚定效应影响，折扣预售更适用于在线零售商的新产品销售，并能够带来预售“红利”。不过，受销量更新规则的制约，这种预售“红利”将在一段时间后消失，在线零售商必须采取相应措施提高消费者估值，以应对之后的销售低谷期。本文的研究结果将为在线零售商的动态定价提供理论指导和决策依据。

关键词: 折扣预售, 锚定效应, 销量更新规则, 在线产品定价

Abstract:

Customers’ two-factor anchoring behaviour gives them incredible resilience in the rapidly evolving e-commerce landscape. Businesses need to figure out how to attract them and sway their buying habits with low-priced preorders. Businesses can enjoy the extraordinary benefit of becoming “price anchored” as customers exhibit outstanding purchase intent during the eagerly awaited pre-sale discount period. Furthermore， after the end of the discount presale， the high sales volume generated during the presale period will continue to enhance consumer purchase intent through “sales anchored”. However， due to limitations imposed by the platform’s sales update restrictions， this beneficial effect will wear off eventually. In this context， under the background of discount presales， with a focus on dynamic pricing， it is crucial to explore the intricate mechanisms of the price-sales dual-factor anchoring effect on consumer behavior and the complexities arising from the constraints of sales update rules on pricing and marketing strategy formulation for online retailers. So， in this paper， the Multinominal Logit Model （MNL） in the context of discount presale is used to build an n-stage dynamic pricing model considering consumers being anchored by product price and sales， and the effects of the two-factor anchoring effect and sales update rules on the dynamic pricing， sales， and profit of online retailers are also analyzed.

In the model construction， the price-sales dual-factor anchoring effect is incorporated into the utility function， and the consumer’s purchasing choice behavior in the dynamic pricing problem of products is simulated based on the MNL model. During the presale period， online retailers simultaneously disclose the presale price and the regular price， resulting in consumers being anchored by both price and sales factors. At this moment， the utility gained by consumers choosing to purchase the product incorporates both price anchoring and sales anchoring terms. These terms are represented by anchoring coefficients multiplied by the differences between the current product price/sales and the consumer’s price/sales anchoring points. Consumers who choose to purchase during the regular sales period are not price-anchored but are influenced only by the sales anchoring effect. In this case， if consumers choose to buy the product， the utility they gain includes the sales anchoring effect term. The term is represented by sales anchoring coefficient multiplied by the difference between the current cumulative sales and the consumer’s psychological sales anchor point. Furthermore， by transforming the profit function into a function of purchase probability， it has been proven that the profit function is concave. The optimal dynamic pricing of the product， along with the corresponding sales and profit， has been derived.

Numerical experiments are conducted to analyze the optimal dynamic pricing， sales， and profit variations of the product throughout its entire lifecycle， considering the dual-factor anchoring effect of consumers on price and sales. It also compares the differences in optimal dynamic pricing， sales， and profit for online retailers under regular mode and Taobao mode. Furthermore， the research focuses on the sales accumulation period and explores the disparities in product pricing， sales， and profit under different sales update rules.

It is found that， under the influence of the anchoring effect， discount presales are applicable to online retailers’ new product sales and can bring a presale “bonus”. However， due to sales update rules， this presale “bonus” will dissipate over time， and online retailers will have to take measures to increase consumer valuations in order to cope with subsequent sales downturns. The results of this paper will provide theoretical guidance for the dynamic pricing of online retailers.

Key words: discount presale, anchoring effect, sales update rules, online product pricing

中图分类号:

F274

刘旭旺,张玉洁,齐微, 等. 基于销量更新规则和锚定效应的在线产品动态定价研究[J]. 中国管理科学, 2026, 34(1): 200-211.

Xuwang Liu,Yujie Zhang,Wei Qi, et al. Study on Dynamic Pricing of Online Product Based on Sales Update Rule and Anchoring Effect[J]. Chinese Journal of Management Science, 2026, 34(1): 200-211.

图/表 11

表1

基本符号及模型参数说明"

基本符号/模型参数	说明
$U s i$	消费者在预售期购买单位产品的总效用（ $i = 1,2, …, t$ ）
$U o i$	第i个Δt时段进入市场的消费者购买单位产品的总效用（ $i = t + 1, t + 2, …, n$ ）
β	预售期折扣率，且 $β ∈ (0.5,1)$
c	单位成本
$Q f$	销量锚点
$1 / n$	每Δt时段进入市场的总人数所占市场规模的比例
Q_i	开始销售至第i个Δt时段内的产品累积销量
v	消费者对产品的估值
$θ s$	销量锚定系数
$θ c$	价格锚定系数
ε	未观测到的效用/误差

表1

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