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dc.contributor.advisorPalmer, Christopher
dc.contributor.authorPaine, Fiona
dc.date.accessioned2022-08-29T16:38:24Z
dc.date.available2022-08-29T16:38:24Z
dc.date.issued2022-05
dc.date.submitted2022-06-09T14:33:31.306Z
dc.identifier.urihttps://hdl.handle.net/1721.1/145178
dc.description.abstractThis 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.
dc.publisherMassachusetts Institute of Technology
dc.rightsIn Copyright - Educational Use Permitted
dc.rightsCopyright MIT
dc.rights.urihttp://rightsstatements.org/page/InC-EDU/1.0/
dc.titleBig Data and Firm Risk
dc.typeThesis
dc.description.degreeS.M.
dc.contributor.departmentSloan School of Management
mit.thesis.degreeMaster
thesis.degree.nameMaster of Science in Management Research


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