YourCabs aggregates radio cabs from multiple taxi operators in Bangalore. For each model type, the supply shifts dynamically and depends on the number of drivers logged in. If cabs are unavailable, Yourcabs incurs cost on either upgrading the passenger or losing the sale. If several cabs do not have bookings, there is some loss of relationship with the supplier. Thus, YourCabs needs to be able to predict the demand for each cab type at an hourly basis so it can reach out to taxi operators and plan the number of drivers logging into its system.
Our analysis aims to reveal insights from monthly international passenger traffic data in the three major U.S. Airways hubs, Charlotte (CLT), Philadelphia (PHL), and Phoenix (PHX), to predict future implications at the newest international hub, Phoenix. Operations in PHX international hub began more recently (2007) than the other two hubs (2000), leading us to focus on creating a forecasting model to predict the monthly flow of international passengers to and from the PHX hub with fuller accuracy using the combination of insights.
Vliegtarieven.nl is an online booking agency for air tickets. The project goal is to determine the factors affecting online customers' intention of returning to Vliegtarieven.nl to purchase airline tickets, based on a large survey of their customers (we thank Prof Otto Koppius from RSM Erasmus for sharing the data and problem)
The project goal was to evaluate the role of the physical environment in vehicle accidents that result in injuries, and specifically to identify variables of physical environment that increase the probability of injuries in vehicular accidents, and to predict the probability of injuries in accidents based on the selected variables of physical environment. The data used are from the U.S. Bureau of Transportation Statistics (part of the U.S. Dept. of Transportation)
The goal of the project was to create a model that can predict delays in domestic flights departing from Washington DC Metro Area before the actual flight day, using data from the U.S. Bureau of Transportation Statistics
The goal of this project was to find the major factors explaining flight delays on route from Washington, DC to Honolulu, Hawaii. The findings of this analysis that are under control of travelers, can then be used to make better decisions on when to travel or avoid traveling, which Washington, DC airport to use and which airline to fly
An airline recently offered promotion to members of its frequent flyer club via direct mail. The response rate was less than desired, and the airline would like to target consumers most likely to accept offer.
The project objective is to create a model that classifies frequent flier club members based on their likelihood of accepting the promotion.
This report is intended to understand characteristics of a caravan insurance policy buyer. The
dataset consists of 9,822 customer records and includes socio‐demographic data of the area
where a customer lives and product ownership data of the customer. The aim of this profiling analysis
is to acquire managerial insights to create competitive strategies useful for making business decisions.