Effect of innovation practices of banks on customer loyalty: an SEM-ANN approach
Benchmarking: An International Journal
ISSN: 1463-5771
Article publication date: 13 January 2023
Issue publication date: 1 December 2023
Abstract
Purpose
The purpose of this study is to examine the effects of banking innovations (INNs) on customer experience (EXP), satisfaction (SAT) and loyalty (LOY).
Design/methodology/approach
The author evaluated the data using a structural equation method-artificial neural network (SEM-ANN) method. The author’s results show the presence of relationship between INN, EXP, SAT and LOY. In this study, the node layers of ANNs add an input layer, hidden layers and an output layer. Each “node” acts as an artificial neuron that communicates with others. The ANN model takes the variables from the SEM analysis as input neurons.
Findings
The author observed the significant effects between INN, EXP, SAT and LOY using the normalised importance generated by the multilayer perceptron used in the feed-forward back propagation of the ANN methodology. In this study, the ANN model can predict LOY through service innovation, with a forecast accuracy of 77.6%.
Originality/value
By applying neural network modelling, this research helps us understand how service innovation affects customer behaviour. For the first time, the author examined service innovations' direct and indirect impact on loyalty through EXP and SAT. The author made a significant conceptual contribution by using a non-compensatory model of ANNs to circumvent the limitations of linear models.
Keywords
Citation
Tiwari, P. (2023), "Effect of innovation practices of banks on customer loyalty: an SEM-ANN approach", Benchmarking: An International Journal, Vol. 30 No. 10, pp. 4536-4568. https://doi.org/10.1108/BIJ-06-2022-0392
Publisher
:Emerald Publishing Limited
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