PurposeAlternative payment means have been expanding rapidly in recent years. The need to identify the segments of customers that are targetable for both financial and nonfinancial institutions is growing. The purpose of this paper is to use two different methods, discriminant analysis and decision trees, in order to compare the effectiveness of the two methods for segmentation and identify critical consumer characteristics which determine behavior and preference in relation to the use of payment means.Design/methodology/approachUsing data from 321 bank customers, decision tree and discriminant analysis methods are used, first to test the same set of variables differentiating the customers and then to compare the respective results and prediction ability of the two methods.FindingsResults show that discriminant analysis has a better model fit and segments the customers in a more effective way than the decision tree method. In addition, each method shows different variables to differentiate the customer groups.Research limitations/implicationsThe findings are limited to the sector and country of the study, as well as the convenience sample that has been used.Practical implicationsSuggestions for financial managers to better understand their customers’ behavior and target the right group are discussed.Originality/valueThis is the first attempt to compare decision trees and discriminant analysis as alternative segmentation methods for payment means.
International Journal of Bank Marketing – Emerald Publishing
Published: Apr 3, 2018
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.
All for just $49/month
Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly
Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.
Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.
Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.
All the latest content is available, no embargo periods.
“Hi guys, I cannot tell you how much I love this resource. Incredible. I really believe you've hit the nail on the head with this site in regards to solving the research-purchase issue.”Daniel C.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud
“I must say, @deepdyve is a fabulous solution to the independent researcher's problem of #access to #information.”@deepthiw
“My last article couldn't be possible without the platform @deepdyve that makes journal papers cheaper.”@JoseServera