id cris-123456789-1496
recordtype dspacecris
spelling cris-123456789-14962018-02-08T10:56:37Z A logistic regression model for the determination of the predictive factors for the demand by customers of bank loans in Greece Frangos, Christos C. Fragkos, Konstantinos C. Sotiropoulos, Ioannis Gikas, Grigoris Valvi, Aikaterini C. Manolopoulos, Ioannis Τράπεζες και τραπεζικές εργασίες--Εξυπηρέτηση πελατών Banks and banking--Customer services Τραπεζικά δάνεια Bank loans Επιτόκια Interest rates Λογιστική παλινδρομική ανάλυση--Ελλάδα Logistic regression analysis--Greece Commercial Banks need to determine the factors that customers base their decision to receive loans from them. This is appropriate for developing successful marketing strategies. A general population sample of Greek citizens was chosen to examine this aspect. We present the results of a sample survey on 277 citizens. Our instrument was validated through confirmatory factor analysis, which presented good fit. Binary logistic regression showed that significant predictors of taking loans were Personal Marital Status, Customer service, shop design (number of ATM MACHINES, bank branches and personnel education) and Interest Rates whose odds ratios were all significantly above 1. These results have important implication for bank managers who should focus giving loans to single individuals as well as change their interest rates policy by decreasing the rates for all kinds of loans, especially housing loans. Through this they will achieve creating a more sensitive image to calls for a more balanced and fair social policy pursued by the banks. 2011 Paper http://cris.teiep.gr/jspui/handle/123456789/1496 978-960-86583-7-0 en pp. 309-323 Σύγχρονη επιχείρηση και παγκόσμιο οικονομικό περιβάλλον. Νέες προκλήσεις μετά την κρίση. 4ο Διεθνές επιστημονικό συνέδριο. Οκτώβριος, 13-14, 2011
institution T.E.I. of Epirus
collection DSpace CRIS
language English
topic Τράπεζες και τραπεζικές εργασίες--Εξυπηρέτηση πελατών
Banks and banking--Customer services
Τραπεζικά δάνεια
Bank loans
Επιτόκια
Interest rates
Λογιστική παλινδρομική ανάλυση--Ελλάδα
Logistic regression analysis--Greece
spellingShingle Τράπεζες και τραπεζικές εργασίες--Εξυπηρέτηση πελατών
Banks and banking--Customer services
Τραπεζικά δάνεια
Bank loans
Επιτόκια
Interest rates
Λογιστική παλινδρομική ανάλυση--Ελλάδα
Logistic regression analysis--Greece
Frangos, Christos C.
A logistic regression model for the determination of the predictive factors for the demand by customers of bank loans in Greece
abstract Commercial Banks need to determine the factors that customers base their decision to receive loans from them. This is appropriate for developing successful marketing strategies. A general population sample of Greek citizens was chosen to examine this aspect. We present the results of a sample survey on 277 citizens. Our instrument was validated through confirmatory factor analysis, which presented good fit. Binary logistic regression showed that significant predictors of taking loans were Personal Marital Status, Customer service, shop design (number of ATM MACHINES, bank branches and personnel education) and Interest Rates whose odds ratios were all significantly above 1. These results have important implication for bank managers who should focus giving loans to single individuals as well as change their interest rates policy by decreasing the rates for all kinds of loans, especially housing loans. Through this they will achieve creating a more sensitive image to calls for a more balanced and fair social policy pursued by the banks.
format Paper
author Frangos, Christos C.
author-letter Frangos, Christos C.
author2 Fragkos, Konstantinos C.
Sotiropoulos, Ioannis
Gikas, Grigoris
Valvi, Aikaterini C.
Manolopoulos, Ioannis
author2Str Fragkos, Konstantinos C.
Sotiropoulos, Ioannis
Gikas, Grigoris
Valvi, Aikaterini C.
Manolopoulos, Ioannis
title A logistic regression model for the determination of the predictive factors for the demand by customers of bank loans in Greece
title_short A logistic regression model for the determination of the predictive factors for the demand by customers of bank loans in Greece
title_full A logistic regression model for the determination of the predictive factors for the demand by customers of bank loans in Greece
title_fullStr A logistic regression model for the determination of the predictive factors for the demand by customers of bank loans in Greece
title_full_unstemmed A logistic regression model for the determination of the predictive factors for the demand by customers of bank loans in Greece
title_sort logistic regression model for the determination of the predictive factors for the demand by customers of bank loans in greece
publishDate 2011
url http://cris.teiep.gr/jspui/handle/123456789/1496
isbn 978-960-86583-7-0
physical pp. 309-323
conferencename Σύγχρονη επιχείρηση και παγκόσμιο οικονομικό περιβάλλον. Νέες προκλήσεις μετά την κρίση. 4ο Διεθνές επιστημονικό συνέδριο. Οκτώβριος, 13-14, 2011
_version_ 1646089612278366208
score 11.368918