The Double-Edged Sword of Social Interactions: Revenue Management of Network Goods Under Demand Uncertainty

Hu, Ming; Wang, Zizhuo; Feng, Yinbo

doi:10.2139/ssrn.2248311

Cited by 3 publications

(2 citation statements)

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“…consider a firm selling two substitutable products to a stream of consumers who arrive sequentially and whose purchasing decisions can be influenced by earlier purchases. Candogan et al (2012) and Hu and Wang (2013) study optimal pricing strategies in social networks with positive externalities. Tereyagoglu and Veeraraghavan (2012) consider a setting in which consumers may use their purchases to display their social status.…”

Section: Literature Reviewmentioning

confidence: 99%

Dynamic Pricing in the Presence of Social Learning and Strategic Consumers

2017

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When a product of uncertain quality is first introduced, consumers may be enticed to strategically delay their purchasing decisions in anticipation of the product reviews of their peers. This paper investigates how the presence of social learning interacts with the adoption decisions of strategic consumers and the dynamicpricing decisions of a monopolist firm, within a simple two-period model. When the firm commits to a price path ex ante (pre-announced pricing), we show that the presence of social learning increases the firm's ex ante expected profit, despite the fact that it exacerbates consumers' tendency to strategically delay their purchase. As opposed to following a price-skimming policy which is always optimal in the absence of social learning, we find that, for most model parameters, the firm will announce an increasing price plan. When the firm does not commit to a price path ex ante (responsive pricing), interestingly, the presence of social learning has no effect on strategic purchasing delays. Under this pricing regime, social learning remains beneficial for the firm and prices may either rise or decline over time, with the latter being ex ante more likely.Furthermore, we illustrate that contrary to results reported in existing literature, in settings characterized by social learning, price-commitment is generally not beneficial for a firm facing strategic consumers.

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Section: Literature Reviewmentioning

confidence: 99%

Dynamic Pricing in the Presence of Social Learning and Strategic Consumers

2017

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“…More recently, Candogan et al (2012); Bloch and Quérou (2013); Cohen and Harsha (2017); Hu and Wang (2013) study the effect of network externalities on optimal pricing and revenue management over networks in a monopoly setting.…”

Section: Are Among Many Examples Of Products With Positivementioning

confidence: 99%

Sales-Based Rebate Design

Ajorlou

Jadbabaie

2019

SSRN Journal

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We study rebate mechanisms according to which a monopolist selling a product introduces rebates as function of the volume of buyers. This enables the firm to induce payoff externalities that ordinarily do not exist. The monopoly firm sells an indivisible good to a mass of consumers with uncertain valuations corresponding to two sources of uncertainty: a systemic uncertainty corresponding to the realized quality, and an idiosyncratic uncertainty modeling the diversity of consumers' tastes. Analyzing the equilibria of the induced global game among the consumers, we show that introducing positive externality via an increasing aggregate reward program reduces the profit. Using variational optimization techniques, we identify several key characteristics of the optimal reward program: the optimal solution is a "full-refund or nothing" policy, fully reimbursing the buyers if the realized quality falls in one of the finitely many refund-eligible intervals. The number of intervals, though finite, grow unboundedly as consumers' tastes become less diverse and valuations concentrate around the true quality. While finding the optimal reward program is in general an intractable problem, we fully characterize the optimal solution in two important instances: one with constraints on the reward size and the other with bounds on the rate of change of the reward with sales volume. Despite their simple and intuitive structures, the corresponding optimal reward programs asymptotically recover the optimal solution. Our analysis sheds light on the potential role of novel technology-enabled features of crowd-based markets in developing new revenue management strategies.

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