Predicting mobile wallet resistance: A two-staged structural equation modeling-artificial neural network approach |
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Institution: | 1. Department of Marketing and Market Research, University of Granada, Spain;2. Faculty of Economics, University of Kragujevac, Serbia;1. Technology and Innovation Management, University of Kassel, Nora-Platiel-Str. 4, 34109 Kassel, Germany;2. Technology and Innovation Management, Saarland University, Faculty of Human and Business Sciences, P.O. 15 11 50, 66041 Saarbrücken, Germany |
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Abstract: | The advancement in mobile technology has enabled the application of the mobile wallet or m-wallet as an innovative payment method to substitute the traditional functions of the physical wallet. However, because of pro-innovation bias, scholars have a focus on the adoption of technology and very little attention has been given to the resistance of innovation, especially in the m-wallet context. This study addressed this absence by examining the inhibitors of m-wallet innovation adoption through the lens of innovation resistance theory (IRT). By applying a sophisticated two-staged structural equation modeling-artificial neural network (SEM-ANN) approach, we successfully extended the IRT by integrating socio-demographics and perceived novelty. The study has unveiled the noncompensatory and nonlinear relationships between the predictors and m-wallet resistance. Significant predictors from SEM analysis were taken as the ANN model’s input neurons. According to the normalized importance obtained from the multilayer perceptrons of the feed-forward-back-propagation ANN algorithm, we found significant effects of education, income, usage barrier, risk barrier, value barrier, tradition barrier, and perceived novelty on m-wallet innovation resistance. The ANN model can predict m-wallet innovation resistance with an accuracy of 76.4 %. We also discussed several new and useful theoretical and practical implications for reducing m-wallet innovation resistance among consumers. |
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Keywords: | Mobile wallet resistance Innovation resistance theory Perceived novelty Socio-demographics Artificial neural network |
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