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Massachusetts Institute of Technology

Big Data and Firm Risk

Abstract

dc:description.abstract

This paper investigates the impact of firm data collection and analysis of collected data on the riskiness of firm cash flows. I use a scraped data set of the third party resources loaded on firms’ websites as a measure of firm data collection and analysis practices. I find that firm use of less effective web analytics is associated with an increase in the variance of sales, inventory, and both fixed and variable costs. This effect is despite a lack of change in the level of these variables. Looking at the effect of treatment on the treated, there is higher profit and sales variance during times of higher uncertainty. I use differences in web analytics technology and a change in their relative effectiveness as my identification strategy. As a case study of a large negative demand shock, I look at differences in firm reactions to COVID-19 based on their web analytics usage.

Degree

thesis:*
Name thesis:degree_name
Master
Department dc:contributor.department
Sloan School of Management
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2022

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Paine, Fiona
Advisor dc:contributor.advisor
  • Palmer, Christopher

Rights

dc:rights
Statement dc:rights
  • In Copyright - Educational Use Permitted
  • Copyright MIT

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/1721.1/145178
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/145178

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
related terms
citation

Paine, Fiona. Big Data and Firm Risk. Massachusetts Institute of Technology, 2022. https://hdl.handle.net/1721.1/145178