Optimal Pricing and Refund Policy Considering Risk Fairness and Loss Fairness in Advance Selling

Abstract

With the continuous development of technology, global e-commerce has reached a fantastic market size, and has been growing and expanding. Some disadvantages of traditional marketing have begun to be exposed, unable to adapt to the current rapid development trend and cannot meet the needs of consumers. As a result, some new marketing models constantly rise, especially advance selling applied widely in various industries. Advance selling refers to the idea that sellers allow consumers to buy products or services before the regular selling period, but obtain the products or services until the regular selling period. In recent years, advance selling has been pushed into a new wave with the help of e-commerce platforms. Advance selling not only helps suppliers solve inventory problems, but also increases market demand and alleviates its uncertainty. In addition, advance selling brings more choices to consumers, satisfies their purchase desire, and increases consumption interest.

The strategy of advance selling is also attracted attention in the field of research. Some scholars point out that advance selling can predict the potential market demand, reduce uncertainty and competition, increase consumer surplus, and improve the seller's profit, which is proved to be an effective marketing tool. They also emphasize the research on advance selling in different contexts, and the combination with practical applications. With the strategy of advance selling, the separation between purchase and consumption results in the uncertainty of consumer valuation for products, thus some scholars have started to study return policy and its influence on optimal decisions. From the perspective of refund fees, they often discuss which one is the optimal among no refund, partial refund, and full refund. With the variety of channels, some scholars focus on refund policy under different channels, including single-channel, dual-/multi-channel, and omni-channel, as well as cross-channel return policy. Although the existing literature has studied advance selling in different aspects, lack of research on the combination of advance selling and behavior factors, especially that related to fairness concern. Therefore, the dissertation focuses on the combination of refund strategy with fairness concerns with advance selling to explore the influence of risk, loss, and distributive fairness concerns on the optimal decision of consumers and sellers, as well as operation optimization and coordination.

Under wine futures with quality uncertainty, based on the analysis results of psychology experiments about risk fairness concern in the context of advance selling, the dissertation argues that in addition to the risk undertaken by consumers, they also consider the disutility caused by risk fairness concern. The dissertation combines risk and fairness concern, explores how consumers with different willingness-to-pay whether to buy and when to buy, and how a winemaker response to make optimal decisions by constructing a mathematical model when consumers consider risk fairness. The results show that consumers' risk fairness concern might be beneficial to the winemaker. In addition, in some situations, the winemaker can set an optimal wine future price to make consumers with different willingness-to-pay buy in different periods, which provides some management insights to sellers for distinguishing consumers.

In addition to the perspective of risk, the dissertation also considers fairness concern from the loss perspective, exploring that when a seller applies the strategy of advance selling, consumers are concerned about the inequity of loss between both parties. In practice, consumers often pay attention to their potential loss when buying products with valuation uncertainty. Although sellers would provide refund policy, for fair-minded consumers, if the refund fees charged by sellers are so high that the potential loss of consumers is relatively large, they might prefer giving up some surplus to obtain a fair outcome. Based on the above, the dissertation analyzes how the seller makes the optimal refund policy to induce consumers with loss fairness concern to purchase in advance by developing a mathematical analytical framework, and when spot selling is optimal compared with advance selling. The results illustrate that the firm’s partial refund policy might be affected by consumers’ loss fairness concern. In addition, these conclusions can be extended into more periods, which has reference significance for dynamic pricing strategy. Besides, a mechanism is proposed to help sellers relieve consumers' loss fairness concern.

Date of Award	13 Sept 2023
Original language	English
Awarding Institution	City University of Hong Kong
Supervisor	Shaofu DU (External Supervisor) & Shaoyi Stephen LIAO (Supervisor)