Location

Hilton Waikoloa Village, Hawaii

Event Website

http://www.hicss.hawaii.edu

Start Date

1-4-2017

End Date

1-7-2017

Description

This paper aims to investigate mobile banking (MB) usage through the theoretical lens of UTAUT model with its four pillars. The research model will be tested via a hybrid neural networks-based structural equation modeling (SEM-NN) to reveal significant factors. Universal structural modeling (USM) will be then utilized to find the hidden paths and nonlinearity in our research model. To the best of our knowledge, this is the first study to examine the role of subjective and objective experience on MB usage using a multi-analytical approach. Neural network (NN) and USM can identify the most significant determinants and hidden interaction effects, respectively. Thus, both techniques would help to complement SEM and increase our understanding of the influential factors on MB usage. Preliminary results are presented and discussed. Potential contribution and conclusion are communicated to both academia and industry.

Share

COinS
 
Jan 4th, 12:00 AM Jan 7th, 12:00 AM

The Impact of Subjective and Objective Experience on Mobile Banking Usage: An Analytical Approach

Hilton Waikoloa Village, Hawaii

This paper aims to investigate mobile banking (MB) usage through the theoretical lens of UTAUT model with its four pillars. The research model will be tested via a hybrid neural networks-based structural equation modeling (SEM-NN) to reveal significant factors. Universal structural modeling (USM) will be then utilized to find the hidden paths and nonlinearity in our research model. To the best of our knowledge, this is the first study to examine the role of subjective and objective experience on MB usage using a multi-analytical approach. Neural network (NN) and USM can identify the most significant determinants and hidden interaction effects, respectively. Thus, both techniques would help to complement SEM and increase our understanding of the influential factors on MB usage. Preliminary results are presented and discussed. Potential contribution and conclusion are communicated to both academia and industry.

http://aisel.aisnet.org/hicss-50/da/data_text_web_mining/7