Bargaining over Data and Analytics: Sellers, Buyers and Consultants

Most firms routinely gather vast amounts of data as part of doing business. Monetizing this proprietary data is an increasingly attractive revenue stream for many of these firms. Two fundamental decisions need to be made when deciding to sell, the first involving a choice between selling exclusively to a single buyer or nonexclusively to many, and the second related to what exactly should be sold—just the data or a data product that bundles data with analytics services. As firms often resort to bargaining to arrive at sale agreements, we analyze these decisions through the lens of a bargaining framework. When the buyer needs help from a third-party consultant, she too needs to make a decision—between negotiating separately with the seller and the consultant, and with both of them simultaneously. We find that there are situations where sellers can benefit from bundling the data with analytics services even when their analytics capabilities are weak relative to those of external consultants. Simultaneous negotiations enable buyers to extract more of the consultant’s contribution, making them preferable to buyers when consultants add substantial value. Broadly, this study provides a road map for structuring contracts to firms considering the sale of their proprietary data.

Authors

Institutions

Publication Details

Journal
Information Systems Research
Published
2026-04-21
DOI
https://doi.org/10.1287/isre.2023.0404
Primary Topic
Auction Theory and Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Bargaining over Data and Analytics: Sellers, Buyers and Consultants

Vijay Mookerjee, Syam Menon, Jyotishka Ray
Information Systems Research
Auction Theory and Applications
article

Bargaining over Data and Analytics: Sellers, Buyers and Consultants

Vijay Mookerjee, Syam Menon, Jyotishka Ray
article en

Abstract

Most firms routinely gather vast amounts of data as part of doing business. Monetizing this proprietary data is an increasingly attractive revenue stream for many of these firms. Two fundamental decisions need to be made when deciding to sell, the first involving a choice between selling exclusively to a single buyer or nonexclusively to many, and the second related to what exactly should be sold—just the data or a data product that bundles data with analytics services. As firms often resort to bargaining to arrive at sale agreements, we analyze these decisions through the lens of a bargaining framework. When the buyer needs help from a third-party consultant, she too needs to make a decision—between negotiating separately with the seller and the consultant, and with both of them simultaneously. We find that there are situations where sellers can benefit from bundling the data with analytics services even when their analytics capabilities are weak relative to those of external consultants. Simultaneous negotiations enable buyers to extract more of the consultant’s contribution, making them preferable to buyers when consultants add substantial value. Broadly, this study provides a road map for structuring contracts to firms considering the sale of their proprietary data.

Information Systems Research
University of Dayton (US), The University of Texas at Dallas (US)
Openalex Percentile: Top 11%
Auction Theory and Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.