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来源类型Working Paper
规范类型报告
DOI10.3386/w24334
来源IDWorking Paper 24334
The Impact of Big Data on Firm Performance: An Empirical Investigation
Patrick Bajari; Victor Chernozhukov; Ali Hortaçsu; Junichi Suzuki
发表日期2018-02-19
出版年2018
语种英语
摘要In academic and policy circles, there has been considerable interest in the impact of “big data” on firm performance. We examine the question of how the amount of data impacts the accuracy of Machine Learned models of weekly retail product forecasts using a proprietary data set obtained from Amazon. We examine the accuracy of forecasts in two relevant dimensions: the number of products (N), and the number of time periods for which a product is available for sale (T). Theory suggests diminishing returns to larger N and T, with relative forecast errors diminishing at rate 1/√N+1/√T. Empirical results indicate gains in forecast improvement in the T dimension; as more and more data is available for a particular product, demand forecasts for that product improve over time, though with diminishing returns to scale. In contrast, we find an essentially flat N effect across the various lines of merchandise: with a few exceptions, expansion in the number of retail products within a category does not appear associated with increases in forecast performance. We do find that the firm’s overall forecast performance, controlling for N and T effects across product lines, has improved over time, suggesting gradual improvements in forecasting from the introduction of new models and improved technology.
主题Econometrics ; Estimation Methods ; Industrial Organization ; Industry Studies
URLhttps://www.nber.org/papers/w24334
来源智库National Bureau of Economic Research (United States)
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资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/582007
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Patrick Bajari,Victor Chernozhukov,Ali Hortaçsu,et al. The Impact of Big Data on Firm Performance: An Empirical Investigation. 2018.
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