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Probabilistic Selling Strategy Considering Consumers’ Information Update
- DAI Rui, WU Mingxia
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2024, 33(3):
133-139.
DOI: 10.12005/orms.2024.0089
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Currently, the emerging consumption model of probabilistic sales has penetrated widely into various mass consumer industries such as clothing, food, tourism and accommodation, car rentals, beauty products, cultural and creative goods, etc., with the industry experiencing rapid development. Unlike conventional products, probabilistic products (also known as blind boxes) refer to goods whose specific styles or other information consumers cannot know beforehand, and thus they possess random attributes. The method of selling probabilistic products is referred to as probabilistic selling. One major characteristic of probabilistic selling lies in the fact that sellers always have information advantages related to the products, while consumers are often at an information disadvantage. Specifically, due to the high uncertainty of blind boxes, the probability information regarding their extraction is usually the seller’s private information, and is often undisclosed to consumers.
In business practice, sellers hold different views on whether to disclose information: some choose to proactively disclose the probability value of their probabilistic products, while others choose not to disclose it. If under an undisclosed case, consumers will update their estimations of the extraction probability by collecting online product reviews and other means, thereby engaging in information updating behavior. Besides, under probabilistic selling, consumers who are dissatisfied with the purchased products often act to resell them to second-hand markets. Therefore, consumer satisfaction rate is also a key factor that cannot be ignored in probabilistic selling. The interactive influence between the operational strategies of relevant sellers and consumer behavior is an urgent management problem which is open and needed to be addressed, and it is also the main research objective of this paper. Contributions of this study mainly include the following aspects: Firstly, on the basis of existing researches, this paper considers consumer information updating behavior, making the study more aligned with real observations, and hence expanding the scope of related research. Secondly, by capturing consumer resale behavior, this paper introduces consumer resale into research context, aiming to conclude from the perspective of consumers about the impacts of the uncertainty of probabilistic selling.
In summary, this paper describes the probabilistic sales scenario based on the Hotelling model, characterizes consumer information updating behavior via the Bayesian updating model, and comprehensively considers consumer product resale behavior. It constructs optimization models for seller’s pricing strategies under scenarios with and without information disclosure, solves and compares product prices and seller’s profits under different scenarios. Accordingly, this paper summarizes the impacts of key factors such as information accuracy on sell’s pricing, information disclosure strategy selection and profit when consumers update information. The main conclusions are as follows: (1)In scenarios where information is not disclosed, product prices are lower than in scenarios where information is disclosed. Besides, under information updating, as information accuracy improves, product price in scenarios with undisclosed information also increases. This is because if a company discloses information, the uncertainty of information about the product decreases, enhancing consumer willingness to purchase, and thus enabling the seller to set a relatively higher product price. (2)The impact of information accuracy on the seller’s profit is non-monotonic. This is because enhanced information accuracy has two effects: first, it improves consumers’ accuracy in valuing probabilistic products; second, it leads to an increase in the price of probabilistic product. The former benefits consumers by increasing the utility, while the latter decreases consumer utility. Therefore, the overall impact of information accuracy on the seller’s profit mainly depends on the comparative strength of these two effects. (3)When information accuracy is low, and consumer satisfaction rate is low, or the resale price is high, the seller’s profit will be higher in scenarios where information is not disclosed than in scenarios with disclosed information. Therefore, the seller should choose not to disclose information related to the extraction probabilities of products. However, if the opposite conditions prevail, the seller should implement an information transparency strategy by disclosing relevant information. (4)When consumer satisfaction is low and the resale price of probabilistic products is high, sellers will benefit from the existence of the second-hand market. This is because if consumers are aware that the probability of obtaining unsatisfied product is low, their willingness to pay will increase correspondingly. Additionally, once consumers can obtain certain compensation at a higher resale price from the second-hand market, the product sales will be stimulated. When both conditions are met, sales of probabilistic products will always see significant improvement, thereby increasing the seller’s profit.
