Information Acquisition Through Customer Voting Systems

Marinesi, Simone; Girotra, Karan

doi:10.2139/ssrn.2191940

Cited by 15 publications

(7 citation statements)

References 27 publications

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“…Finally, this paper also contributes to a recent line of work which studies operational decisions in the context of Internet-enabled business models. Among others, Marinesi and Girotra (2013) examine how customer voting systems should be designed when firms seek to acquire information to improve pricing and product-design decisions; Ye et al (2015) investigate how an online retailer should combine sponsored-search marketing with dynamic pricing; Balseiro et al (2014) consider the problem faced by a web publisher in deciding how to allocate advertising slots between spot markets (ad exchanges) and pre-arranged contracts (reservations). In this paper, we investigate how the information-provision policy of an online platform can be used to influenced the decisions of its users.…”

Section: Related Literaturementioning

confidence: 99%

Crowdsourcing Exploration

2018

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Motivated by the proliferation of online platforms that collect and disseminate consumers' experiences with alternative substitutable products/services, we investigate the problem of optimal information provision when the goal is to maximize aggregate consumer surplus. We develop a decentralized multi-armed bandit framework where a forward-looking principal (the platform designer) commits upfront to a policy that dynamically discloses information regarding the history of outcomes to a series of short-lived rational agents (the consumers). We demonstrate that consumer surplus is non-monotone in the accuracy of the designer's information-provision policy. Because consumers are constantly in "exploitation" mode, policies that disclose accurate information on past outcomes suffer from inadequate "exploration." We illustrate how the designer can (partially) alleviate this inefficiency by employing a policy that strategically obfuscates the information in the platform's possession -interestingly, such a policy is beneficial despite the fact that consumers are aware of both the designer's objective and the precise way by which information is being disclosed to them.More generally, we show that the optimal information-provision policy can be obtained as the solution of a large-scale linear program. Noting that such a solution is typically intractable, we use our structural findings to design an intuitive heuristic that underscores the value of information obfuscation in decentralized learning. We further highlight that obfuscation remains beneficial even if the designer can directly incentivize consumers to explore through monetary payments.At any time, the history of service outcomes (i.e., the system state x t ) is not directly observable to the consumers. Instead, there is a platform designer who commits upfront to a "messaging policy" that acts as an instrument of information-provision to the consumers. 7 This policy specifies the message that is displayed on the platform, given any underlying system state; in §7.2, we extend 4 The general analysis in §6 can be readily extended to the case of |S| > 2 providers. 5 The probability density function of a Beta(s, f ) random variable is given by g(x; s, f ) = x s−1 (1−x) f −1 B(s,f ), for x ∈ [0, 1]. 6 The platform and the consumers hold the same prior belief, so that platform actions (e.g., choice of informationprovision policy) do not convey any additional information on provider quality to the consumers (e.g., Bergemann and Välimäki 1997, Bose et al. 2006, Papanastasiou and Savva 2016.7 Commitment is a reasonable assumption in the context of online platforms, where information provision occurs on the basis of pre-decided algorithms and the large volume of products/services hosted renders ad-hoc adjustments of the automatically-generated content prohibitively costly (see also §5.4, where this assumption is relaxed).

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Section: Related Literaturementioning

confidence: 99%

Crowdsourcing Exploration

2018

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“…Papanastasiou et al (2018) study a platform's information control policy to influence the crowd to take consumer-surplus optimal actions; our basic problem is different in that our fundamental decision is not to control information but rather to decide what size crowd is needed per assessment. Marinesi and Girotra (2013) formally study customer voting systems in the context of product development and pricing; they show that when customers vote on product development, firm and customer interests are aligned, whereas, when customers vote on product pricing, the voting systems are ineffective because of misaligned objectives. Similarly, Caldentey and Araman (2013) study the use of crowdvoting to determine the timing of new product introductions.…”

Section: Literature Reviewmentioning

confidence: 99%

Crowdvoting Judgment: An Analysis of Modern Peer Review

Wagner

2020

Stochastic Systems

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In this paper, we propose and analyze models of self policing in online communities, in which assessment activities, typically handled by firm employees, are shifted to the “crowd.” Our underlying objective is to maximize firm value by maintaining the quality of the online community to prevent attrition, which, given a parsimonious model of voter participation, we show can be achieved by efficiently utilizing the crowd of volunteer voters. To do so, we focus on minimizing the number of voters needed for each assessment, subject to service-level constraints, which depends on a voting aggregation rule. We focus our attention on classes of voting aggregators that are simple, interpretable, and implementable, which increases the chance of adoption in practice. We consider static and dynamic variants of simple majority-rule voting, with which each vote is treated equally. We also study static and dynamic variants of a more sophisticated voting rule that allows more accurate voters to have a larger influence in determining the aggregate decision. We consider both independent and correlated voters and show that correlation is detrimental to performance. Finally, we take a system view and characterize the limit of a costless crowdvoting system that relies solely on volunteer voters. If this limit does not satisfy target service levels, then costly firm employees are needed to supplement the crowd.

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“…Araman and Caldentey [9] deal with the detailed modeling of the firm's optimal timing to stop the voting and start or abandon launching the product. In a different set of new product launching, Marinesi and Girotra [10] focus on forwardlooking customer behavior and the intended use of the acquired information. Wessel et al [11] assess the effects of nongenuine social information on consumers' decisionmaking in the context of reward-based crowdfunding.…”

Section: Literature Reviewmentioning

confidence: 99%

Pricing Decisions on Reward-Based Crowdfunding with Bayesian Review System Facing Strategic Consumers

Chen

Zhang

Liu

2019

Discrete Dynamics in Nature and Society

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Crowdfunding marks a popular and sustainable means by which small and microentrepreneurs obtain financial resources for their innovative project. Consumers increasingly rely on online reviews to make purchase decisions. However, the crowdfunding nowadays lacks a form type of review system. This paper is designed to extend research on the optimal pricing decision with review system for the reward-based crowdfunding. Firstly, a Bayesian analysis is established to construct consumers’ belief update process in presence of review system. Secondly, we take the strategies without the review system as a benchmark to explore the impacts of review system under preannounced pricing and responsive pricing. Finally, through the equilibrium analysis, we find that the review system has a positive impact on the creator under responsive pricing policy. The fraction of favorable review has a large effect on the profit of preannounced pricing. When the fraction is about 80%, the profit is the maximum. Generally speaking, the review system will make more profit for the creator.

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Information Acquisition Through Customer Voting Systems

Cited by 15 publications

References 27 publications

Crowdsourcing Exploration

Crowdsourcing Exploration

Crowdvoting Judgment: An Analysis of Modern Peer Review

Pricing Decisions on Reward-Based Crowdfunding with Bayesian Review System Facing Strategic Consumers

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