M-banking is a channel through which banks interact with customers via mobile devices. M-banking is an emerging mobile commerce application. It is a challenging task for banks to encourage customers to continue using m-banking services, and attract new customers to the service. This study clarifies the differences in the thinking paths of users of m-banking services, and consumers who have not yet used m-banking services, in terms of their involvement. We prove that consumers equipped with more product knowledge tend to pay more attention to the information in relation to product attributes, rather than the peripheral information, which does not consider the advantages and disadvantages of products. These findings can serve as reference for banks in the formulation of different marketing strategies and promotional campaigns targeted at both existing users and consumers who have not adopted m-banking services.
PurposeThe purpose of this paper is to present a model and a supporting approach for effective supplier selection decisions.Design/methodology/approachStructural equation modeling (SEM) and confirmatory factor analysis are applied to test the evaluation principles and samples. Next, the data tested by SEM is used for artificial neural network (ANN) by Likert and fuzzy scales to structure a classification model, accompanying with canonical discriminate analysis (CANDISC) to diminish variables. After the training and test of the model, multiple discriminate analysis is applied to compare the accuracy of the classification. Last, the CANDISC variable reduction method with ANN classification model utilized in the study is applied.FindingsThe supplier selection model designed with ANN classification model and fuzzy scales will be more effective than with the traditional statistics analysis.Research limitations/implicationsThe new paradigm for decision making includes a combination of several effective methods and analysis.Practical implicationsThis research provides an integrated model for internal auditors and managers to classify their supplier selection decisions.Originality/valueThis paper contributes to the new approach of the decision model building process for computer auditing and improves the classification accuracy effectively.
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