Monopoly and Competition in the Markets for Information

Ma, Yingju

doi:10.2139/ssrn.3505101

Cited by 2 publications

(2 citation statements)

References 11 publications

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“…There is a growing literature on markets of information (see Bergemann & Bonatti, 2019, for an excellent survey). Research in this vein investigates the monetization of information by considering issues such as the sale of supplemental information (Babaioff et al., 2012; Bergemann et al., 2018), competition (Bimpikis et al., 2019; Ma, 2019), and privacy (Eliaz et al., 2019; Ghosh & Roth, 2015).…”

Section: Related Literaturementioning

confidence: 99%

An Approximation Scheme for Data Monetization

Mehta

Dawande

Janakiraman

et al. 2022

Production and Operations Management

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The unprecedented rate at which data are being generated has led to the growth of data markets where valuable data sets are bought and sold. A salient feature of this market is that a data-buyer (agent) is endowed with multidimensional private information, namely, her "ideal" record that she values the most and how her valuation for a given record changes as its distance from her ideal record changes. Consequently, the revenue-maximization problem faced by a data-seller (principal), who serves multiple buyers, is a multidimensional mechanism-design problem, which is well recognized as being difficult to solve. Our main result in this paper is an approximation scheme that guarantees a revenue within as close a positive amount from the optimal revenue as desired. The scheme generates a posted-price menu consisting of a set of item-price pairs-each entry in the menu consists of an item, that is, a set of records from the data set, and the price corresponding to that item. As a trade-off, the length of the menu resulting from the scheme increases as the desired guarantee gets closer to zero. For convenience in practice, data-sellers may want the ability to limit the length of the menu used by the scheme. To facilitate this, we extend our analysis to obtain a general approximation guarantee corresponding to a menu of any given length. We also demonstrate how the seller can exploit buyers' preferences to generate intuitive and useful rules of thumb for an effective practical implementation of the scheme.

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Section: Related Literaturementioning

confidence: 99%

An Approximation Scheme for Data Monetization

Mehta

Dawande

Janakiraman

et al. 2022

Production and Operations Management

View full text Add to dashboard Cite

show abstract

“…There is a growing literature on markets of information (see Bergemann & Bonatti, 2019, for an excellent survey). Research in this vein investigates the monetization of information by considering issues such as the sale of supplemental information (Babaioff et al, 2012;Bergemann et al, 2018), competition (Bimpikis et al, 2019;Ma, 2019), and privacy (Eliaz et al, 2019;Ghosh & Roth, 2015).…”

Section: Pricing Of Data and Informationmentioning

confidence: 99%