Assessing Artificial Neural Networks (ANNS) Adequacy Against Econometric Models for Decision Making Approaches in Bankin
The purpose of this paper is to test the effect of non-parametric methodology of ANNs on enhancing decision-making procedures compared to classic multivariate Regression models. We implement the two methods on decision-making for loan allowances and on a
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Alexandra Horobet Persefoni Polychronidou Anastasios Karasavvoglou Editors
Business Performance and Financial Institutions in Europe Business Models and Value Creation Across European Industries
Contributions to Economics
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Alexandra Horobet Persefoni Polychronidou Anastasios Karasavvoglou •
•
Editors
Business Performance and Financial Institutions in Europe Business Models and Value Creation Across European Industries
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Editors Alexandra Horobet Bucharest University of Economic Studies Bucharest, Romania
Persefoni Polychronidou Department of Economics International Hellenic University Serres, Greece
Anastasios Karasavvoglou International Hellenic University Kavala, Greece
ISSN 1431-1933 ISSN 2197-7178 (electronic) Contributions to Economics ISBN 978-3-030-57516-8 ISBN 978-3-030-57517-5 (eBook) https://doi.org/10.1007/978-3-030-57517-5 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland
Preface
Exploring business performance is a challenging endeavour now as ever, but recent times ha
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