Hallo! Tracked shipping to Netherlands with Delivery Duty Paid for just €7 

Ship to
Netherlands
0

My Account

  • argentina
  • chile
  • colombia
  • españa
  • méxico
  • perú
  • estados unidos
  • internacional

menu

Select your country

Americas

Europe

Rest of the world

portada Data-Driven Decision-Making in Churn Prevention and Crew Scheduling
Type
Physical Book
Publisher
Author
Language
English
Pages
119
Format
Paperback
ISBN13
9783832554309

Data-Driven Decision-Making in Churn Prevention and Crew Scheduling

Theresa Gattermann-Itschert (Author) · Logos Verlag Berlin · Paperback

Data-Driven Decision-Making in Churn Prevention and Crew Scheduling - Theresa Gattermann-Itschert

New Book Imported to Netherlands
Delivery: 29 Sep - 02 Oct Shipping: 14 to 16 business days.
€ 76,22
Import costs and 9% BTW included in the price ✅
€ 76,22

Choose the list to add your product or create one New List

Go to My Wishlists
Calculate shipping cost

Synopsis "Data-Driven Decision-Making in Churn Prevention and Crew Scheduling"

This book deals with applying machine learning and mathematical optimization methods for data-driven decision-making. It contributes to research on building machine learning models that capture human behavior and human preferences and that can be used to improve operations and optimization processes. In the field of churn prevention, churn prediction models have primarily been trained on one time slice of data. This work evaluates an approach to train models on data from multiple time slices and identifies two effects that contribute to an improvement in predictive performance: an increase in sample size as well as training on samples from different time slices. The multi-slicing approach makes models more generalizable under changing conditions and allows for predictions that are more accurate. In a field experiment with B2B customers of a convenience wholesaler, this thesis demonstrates how customer churn can be decreased by basing targeting decisions and retention efforts on predicted churn probabilities. In the field of crew scheduling, this work shows how benefits from machine learning and optimization can be combined to deliver better solutions for complex planning problems. For a railway freight carrier, feedback from planners regarding crew schedules is used to train a machine learning model. This book introduces an approach to integrate predicted planner feedback into the optimization process for improving the expected planner acceptance of solutions.

Customers reviews

More customer reviews
  • 0% (0)
  • 0% (0)
  • 0% (0)
  • 0% (0)
  • 0% (0)

Frequently Asked Questions about the Book

Is the book original?

All books in our catalog are Original.

In what language is the book written?

The book is written in English.

What is the format of this book?

The binding of this edition is Paperback.

Questions and Answers about the Book

Do you have a question about the book? Login to be able to add your own question.

Opinions about Bookdelivery

More customer reviews