Predicting customer lifetime value in bidding fee auctions
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URL
Journal Title
Journal ISSN
Volume Title
School of Business |
Master's thesis
Authors
Date
2022
Department
Major/Subject
Mcode
Degree programme
Information and Service Management (ISM)
Language
en
Pages
69
Series
Description
Thesis advisor
Wallenius, JyrkiMalo, Pekka
Keywords
customer lifetime value, machine learning, regression, stochastic models, SMOGN, bidding fee auctions