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Cloud computing in manufacturing: The next industrial revolution in Malaysia?

This study explores how performance expectancy (PE), effort expectancy (EE), firm size (FS), top management support (MS) and absorptive capacity (AC) of cloud computing technology can lead to innovativeness (IN) and firm performance (FP) among the manufacturing firms. Data gathered from 188 manageri...

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Main Authors: Ooi, Keng Boon, Lee, Voon Hsien, Tan, Garry Wei Han, Hew, Teck Soon, Hew, Jun Jie
Format: Article
Published: Elsevier 2018
Subjects:
HF Commerce
Online Access:http://eprints.um.edu.my/21059/
https://doi.org/10.1016/j.eswa.2017.10.009
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spelling my.um.eprints.210592019-04-24T06:53:30Z http://eprints.um.edu.my/21059/ Cloud computing in manufacturing: The next industrial revolution in Malaysia? Ooi, Keng Boon Lee, Voon Hsien Tan, Garry Wei Han Hew, Teck Soon Hew, Jun Jie HF Commerce This study explores how performance expectancy (PE), effort expectancy (EE), firm size (FS), top management support (MS) and absorptive capacity (AC) of cloud computing technology can lead to innovativeness (IN) and firm performance (FP) among the manufacturing firms. Data gathered from 188 managerial positions were analysed using Partial Least Squares (PLS) Structural Equation Modelling (SEM) analysis, together with the Artificial Neural Network (ANN) analysis. Findings revealed that PE, FS, AC have a positive significant influence on IN; while IN positively influences FP. This study offers valuable perspective on the applicability of cloud computing technology to improve IN and FP, and subsequently be aligned with Industry 4.0, the next industrial revolution. Elsevier 2018 Article PeerReviewed Ooi, Keng Boon and Lee, Voon Hsien and Tan, Garry Wei Han and Hew, Teck Soon and Hew, Jun Jie (2018) Cloud computing in manufacturing: The next industrial revolution in Malaysia? Expert Systems with Applications, 93. pp. 376-394. ISSN 0957-4174 https://doi.org/10.1016/j.eswa.2017.10.009 doi:10.1016/j.eswa.2017.10.009
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
topic HF Commerce
spellingShingle HF Commerce
Ooi, Keng Boon
Lee, Voon Hsien
Tan, Garry Wei Han
Hew, Teck Soon
Hew, Jun Jie
Cloud computing in manufacturing: The next industrial revolution in Malaysia?
description This study explores how performance expectancy (PE), effort expectancy (EE), firm size (FS), top management support (MS) and absorptive capacity (AC) of cloud computing technology can lead to innovativeness (IN) and firm performance (FP) among the manufacturing firms. Data gathered from 188 managerial positions were analysed using Partial Least Squares (PLS) Structural Equation Modelling (SEM) analysis, together with the Artificial Neural Network (ANN) analysis. Findings revealed that PE, FS, AC have a positive significant influence on IN; while IN positively influences FP. This study offers valuable perspective on the applicability of cloud computing technology to improve IN and FP, and subsequently be aligned with Industry 4.0, the next industrial revolution.
format Article
author Ooi, Keng Boon
Lee, Voon Hsien
Tan, Garry Wei Han
Hew, Teck Soon
Hew, Jun Jie
author_facet Ooi, Keng Boon
Lee, Voon Hsien
Tan, Garry Wei Han
Hew, Teck Soon
Hew, Jun Jie
author_sort Ooi, Keng Boon
title Cloud computing in manufacturing: The next industrial revolution in Malaysia?
title_short Cloud computing in manufacturing: The next industrial revolution in Malaysia?
title_full Cloud computing in manufacturing: The next industrial revolution in Malaysia?
title_fullStr Cloud computing in manufacturing: The next industrial revolution in Malaysia?
title_full_unstemmed Cloud computing in manufacturing: The next industrial revolution in Malaysia?
title_sort cloud computing in manufacturing: the next industrial revolution in malaysia?
publisher Elsevier
publishDate 2018
url http://eprints.um.edu.my/21059/
https://doi.org/10.1016/j.eswa.2017.10.009
_version_ 1643691454856429568
score 13.211869

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