@inproceedings{5bb62bb3672f474dba3270650bea4186,
title = "A study of measuring the impact of employee perception on business-IT alignment via neural network",
abstract = "In this study, an attempt has been made to investigate the connectivity strength of employee perception on the successful implementation of business-IT alignment. To be specific, we first justify and verify the connection between several employee perceptions and business-IT alignment through hypothesis testing, and then measure the relative importance of each perception onto business-IT alignment via neural network computation. Our findings suggested that perceived employee communication has the strongest relationship with business-IT alignment, followed by employee knowledge and employee trust. Specifically, employee communication and knowledge are two major perceptions that affect the success of the business-IT alignment.",
keywords = "Employee perception, business-IT alignment, neural network, relative importance",
author = "Wong, {T. C.} and Ngan, {Shing Chung} and Chan, {Felix T.S.} and Chong, {Alain Y.L.}",
note = "Copyright: Copyright 2012 Elsevier B.V., All rights reserved.; IEEE International Conference on Industrial Engineering and Engineering Management, IEEM2011 ; Conference date: 06-12-2011 Through 09-12-2011",
year = "2011",
doi = "10.1109/IEEM.2011.6117994",
language = "English",
isbn = "9781457707391",
series = "IEEE International Conference on Industrial Engineering and Engineering Management",
pages = "635--638",
booktitle = "IEEE International Conference on Industrial Engineering and Engineering Management, IEEM2011",
}