Modelling the acceptance factors to use green technology (MyHR2U) in a successful financial institution in Malaysia / Mohd Fadzel Juhari and Putri Anis Najwa Megat Mudzaffar

Green information technology can enhance the productivity of workers. Many organizations have implemented ubiquitous or required IT system for their employees but have not studied the acceptance of the technology by their employee populations. This study is aimed to determine the acceptance factors...

Full description

Saved in:
Bibliographic Details
Main Authors: Juhari, Mohd Fadzel, Megat Mudzaffar, Putri Anis Najwa
Format: Student Project
Language:English
Published: Faculty of Business and Management 2014
Subjects:
Online Access:http://ir.uitm.edu.my/id/eprint/25384/1/PPb_MOHD%20FADZEL%20JUHARI%20BM%20M%2014_5.pdf
http://ir.uitm.edu.my/id/eprint/25384/
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Green information technology can enhance the productivity of workers. Many organizations have implemented ubiquitous or required IT system for their employees but have not studied the acceptance of the technology by their employee populations. This study is aimed to determine the acceptance factors of Green Technology (MyHR2U) users in successful banking services in Malaysia. This is done by modelling modified Unified Theory of Acceptance and Use of Technology (UTAUT) into a framework to examine what factors are contributing to users’ Acceptance to Use Green Technology (AUGT). The selected factors in the framework are obtained from the original model, Performance Expectancy (PE), Effort Expectancy (EE), Social Influence (SI) and Facilitating Conditions (FC), with added two other variables in the framework Access to Financial (AF) and Access to Information (AI). Survey questionnaire was used to collect the data needed, which was adapted and modified from the previous researchers. The respondents were employee from one of the successful financial institution in Malaysia. Data collected was analysed using SPSS and the methods of analysis were frequency analysis, reliability analysis, descriptive statistics and Pearson’s correlation. The findings of this study revealed that there were significant correlation between PE (r=0.600, p=0.000), EE (r=0.474, p=0.000), SI (r=0.394, p=0.004), FC (r=0.458, p=0.001), AF (r=0.530, p=0.000), AI (r=0.569, p=0.000) and AUGT.