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