التفاصيل البيبلوغرافية
| العنوان: |
Toward an extended framework of exhaust data for predictive analytics: An empirical approach. |
| المؤلفون: |
O'Leary, Daniel E.1 (AUTHOR) oleary@usc.edu |
| المصدر: |
Intelligent Systems in Accounting, Finance & Management. Jun2024, Vol. 31 Issue 2, p1-28. 28p. |
| مصطلحات موضوعية: |
*MOBILE commerce, INTERNET traffic, TRAFFIC estimation, PREDICTION models |
| الشركة/الكيان: |
GOOGLE Inc. GOOG |
| Reviews & Products: |
WIKIPEDIA |
| مستخلص: |
Summary: We investigate applying and extending an exhaust data framework, using an empirical analysis to explore and compare different predictive analytic capabilities of both internal and external exhaust data for estimating sales. We use internal exhaust data that explores the relationship between app usage and web traffic data and estimation of sales and find the ability to predict sales at least 4 days ahead. We also develop predictive models of sales, using external data of Google searches, extending the previous research to include additional macroeconomic Google variables and Wikipedia pageviews, finding that we can predict at least 4 months ahead, suggesting a portfolio of exhaust data be used. We introduce the roles of internal and external exhaust data, direct and indirect exhaust data and transformed exhaust data, into an exhaust data framework. We examine what appear to be different levels of information fineness and predictability from those exhaust data sources. We also note the importance of the types of devices (e.g., mobile) and the types of commerce (e.g., mobile commerce) in creating and finding different types of exhaust. Finally, we apply an existing exhaust data framework to develop macroeconomic data exhaust variables, as the means of capturing inflation and unemployment information, using Google searches. [ABSTRACT FROM AUTHOR] |
|
Copyright of Intelligent Systems in Accounting, Finance & Management is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| قاعدة البيانات: |
Business Source Index |