Prof. Xi LI
Director, Asia Case Research Centre
Associate Director, Institute of Digital Economy and Innovation

3917 7271

KK 836

The Bright Side of Inequity Aversion

Modern consumers are concerned about not only their material payoff, but also the fairness of the transaction when making purchasing decisions. In this paper, we investigate how consumers’ inequity aversion affects a manufacturer who sources inputs from upstream suppliers. We find that, when the manufacturer sources from a single supplier or when consumers observe the manufacturer’s cost, inequity aversion hurts both the supplier’s and manufacturer’s profits. However, when the manufacturer sources from multiple suppliers and consumers do not observe the manufacturer’s cost, inequity aversion reduces both the suppliers’ and manufacturer’s margins, which significantly alleviates the double marginalization problem, increases consumer demand, and improves channel efficiency. As a result, inequity aversion benefits the suppliers, manufacturer, and consumers alike, leading to a “win–win–win” outcome. By comparing cases in which consumers observe and do not observe the manufacturer’s cost, we also find that, when faced with inequity-averse consumers, a manufacturer may find it optimal to withhold its cost information to help secure lower procurement costs from upstream suppliers.

Channel Coordination of Storable Goods

Manufacturers of consumer-packaged goods invest heavily in trade promotions (i.e., temporary wholesale price discounts), but retailer stockpiling often yields trade promotions unprofitable. In this paper, we investigate how a manufacturer should respond to the retailer’s and consumers’ stockpiling ability by contracting with the retailer. Specifically, we examine when the manufacturer should restrict the retailer’s stockpiling ability and when it should issue trade promotions. Our analysis suggests the following. First, the manufacturer should restrict the retailer’s stockpiling ability when the storage cost is low; such restriction also benefits the retailer, resulting in a win-win outcome. Second, the manufacturer should offer trade promotions when the retailer cannot stockpile products and the storage cost is low but raise the wholesale price when the retailer can stockpile products. Third, stockpiling improves channel coordination and increases the manufacturer’s profit; therefore, the manufacturer should design products to be more storable.

Advance Selling in Marketing Channels

Manufacturers and retailers often advance sell seasonal products or services (e.g., holiday decorations, summer or winter entertainment). The authors examine advance selling in marketing channels to offer several insights. First, it is well established that a decentralized channel suffers from the issue of double marginalization; that is, the manufacturer and retailer both add positive margins when setting their prices, which results in inefficiently high retail prices. The authors find that, under a dynamic wholesale-price contract, advance selling can alleviate this double-marginalization problem and benefit the manufacturer, the retailer, and consumers. Second, the benefit of advance selling diminishes with the product's holding cost, the retailer's stockpiling ability, and the manufacturer's commitment to spot wholesale price. Third, with wholesale-price commitment, advance selling benefits the manufacturer and consumers but hurts the retailer; the manufacturer is better off making a price commitment only when its product's holding cost is sufficiently low and worse off otherwise. Last, the retailer's stockpiling ability decreases its own profit under a dynamic contract but increases it under a commitment contract.

Beating the Algorithm: Consumer Manipulation, Personalized Pricing, and Big Data Management

Problem definition: Firms heavily invest in big data technologies to collect consumer data and infer consumer preferences for price discrimination. However, consumers can use technological devices to manipulate their data and fool firms to obtain better deals. We examine how a firm invests in collecting consumer data and makes pricing decisions and whether it should disclose its scope of data collection to consumers who can manipulate their data. Methodology/results: We develop a game-theoretic model to consider a market in which a firm caters to consumers with heterogeneous preferences for a product. The firm collects consumer data to identify their types and issue an individualized price, whereas consumers can incur a cost to manipulate data and mimic the other type. We find that when the firm does not disclose its scope of data collection to consumers, it collects more consumer data. When the firm discloses its scope of data collection, it reduces data collection even when collecting more data is costless. The optimal scope of data collection increases when it is more costly for consumers to manipulate data but decreases when consumer demand becomes more heterogeneous. Moreover, a lower cost for consumers to manipulate data can be detrimental to both the firm and consumers. Lastly, disclosure of data collection scope increases firm profit, consumer surplus, and social welfare. Managerial implications: Our findings suggest that a firm should adjust its scope of data collection and prices based on whether the firm discloses the data collection scope, consumers’ manipulation cost, and demand heterogeneity. Public policies should require firms to disclose their data collection scope to increase consumer surplus and social welfare. Even without such a mandatory disclosure policy, firms should voluntarily disclose their data collection scope to increase profit. Moreover, public educational programs that train consumers to manipulate their data or raise their awareness of manipulation tools can ultimately hurt consumers and firms.

Superior Knowledge, Price Discrimination, and Customer Inspection

Firms in many industries obtain superior knowledge of customer preferences through industry experience or data analytics, whereas customers often need costly efforts to learn their match values. In this paper, we examine the situations under which a customer chooses whether to inspect upon observing her personalized price from a firm with superior knowledge. On the surface, it seems that the firm can use personalized prices to directly communicate the customers’ match value, and thus there is no need for customers to expend inspection efforts. However, we find that in equilibrium the firm may trick low-preference customers into overpaying more than their match value, even when the inspection cost is low. The opportunistic incentives induce customer suspicions, which may lead to excessive customer inspection that would be avoided if the firm were not capable of price discrimination. Therefore, personalized pricing cannot obviate customer inspection. Since inspection cost raises a deadweight loss in social welfare, public policies that prevent firms from price-discriminating against customers may benefit both firms and customers.

Combining Computational Intelligence into marketing – Dr. Xi LI

The reputation of HKU and the faculty’s strong connection with the Asian-Pacific business community can definitely help marketing scholars to conduct research more effectively, which in turn enables scholars to deliver update knowledge to students, and nurture high quality talents for the society.

Combining Computational Intelligence into Marketing – Dr. Xi LI

Born with a strong sense of curiosity, Dr. Xi Li is deeply interested in marketing strategies and economic phenomena. Impressed by the high quality of research and the rapid growth of HKU Business School, Dr. Li had officially joined us in July 2021 as an Associate Professor in Marketing.