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Case Code: OPER136
Case Length: 9 Pages 
Period: 2014-2015      
Pub Date: 2019
Teaching Note: Available
Price:Rs.300
Organization : Uber Technologies, Inc.
Industry :Transportation
Countries : United States
Themes: Logistics & Supply Chain/Analytics/Statistics/ Big Data Strategy
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Forecasting in the Platform Economy: The Uber Way

 

ABSTRACT

 
The case study discusses the importance and challenges of forecasting at Uber. The company used its own Time Series data for forecasting. Time Series is a dataset containing values over a period of time. The time period could be seconds, minutes, hours, days, months, years, etc. Time Series data was analyzed using time series basics to forecast the demand for Uber cabs. Regression analysis was also used to forecast demand. The addition of different variables obtained from varied sources also lends credence to the analysis. The choice of variables for this analysis is important. Combining data from different sources to make the analysis actionable is a key insight.
 
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Issues

The case is structured to achieve the following teaching objectives:
  • To have a basic understanding of the platform economy and business model of Uber in the context of the platform economy.
  • To understand how to accomplish data wrangling before using data for analysis.
  • To understand the importance of forecasting.
  • To understand time series forecasting as a technique.
  • To understand the use of different data sources to enrich the analysis.
Contents
INTRODUCTION
ABOUT PLATFORM ECONOMY
ABOUT UBER
UBER’S BUSINESS MODEL
FORECASTING AT UBER
DISCUSSION QUESTIONS
EXHIBITS

Keywords

Python; Multiple Regression; Forecasting; Platform Economy; Data Wrangling; Time Series forecasting

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