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SSRN Electronic Journal
Article . 2020 . Peer-reviewed
Data sources: Crossref
https://dx.doi.org/10.48550/ar...
Article . 2020
License: arXiv Non-Exclusive Distribution
Data sources: Datacite
DBLP
Article . 2020
Data sources: DBLP
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Sales Policies for a Virtual Assistant

Authors: Wenjia Ba; Haim Mendelson; Mingxi Zhu;

Sales Policies for a Virtual Assistant

Abstract

We study the implications of selling through a voice-based virtual assistant (VA). The seller has a set of products available and the VA decides which product to offer and at what price, seeking to maximize its revenue, consumer- or total-surplus. The consumer is impatient and rational, seeking to maximize her expected utility given the information available to her. The VA selects products based on the consumer's request and other information available to it and then presents them sequentially. Once a product is presented and priced, the consumer evaluates it and decides whether to make a purchase. The consumer's valuation of each product comprises a pre-evaluation value, which is common knowledge, and a post-evaluation component which is private to the consumer. We solve for the equilibria and develop efficient algorithms for implementing the solution. We examine the effects of information asymmetry on the outcomes and study how incentive misalignment depends on the distribution of private valuations. We find that monotone rankings are optimal in the cases of a highly patient or impatient consumer and provide a good approximation for other levels of patience. The relationship between products' expected valuations and prices depends on the consumer's patience level and is monotone increasing (decreasing) when the consumer is highly impatient (patient). Also, the seller's share of total surplus decreases in the amount of private information. We compare the VA to a traditional web-based interface, where multiple products are presented simultaneously on each page. We find that within a page, the higher-value products are priced lower than the lower-value products when the private valuations are exponentially distributed. Finally, the web-based interface generally achieves higher profits for the seller than a VA due to the greater commitment power inherent in its presentation.

37 pages, 8 figures, 1 table

Related Organizations
Keywords

FOS: Economics and business, FOS: Computer and information sciences, Computer Science - Computer Science and Game Theory, Economics - Theoretical Economics, Theoretical Economics (econ.TH), Computer Science and Game Theory (cs.GT)

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    popularity
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Average
Average
Average
Green
bronze