International Journal of Managment, IT and Engineering
Year : 2011, Volume : 1, Issue : 2
First page : ( 31) Last page : ( 43)
Online ISSN : 2249-0558.

Failure Model of Peopleware Factors: A Neuro-Computing Approach

Kaur Bikrampal¹, Dr. Aggarwal Himanshu²

¹Department of Computer Sc. & Engg., Chandigarh Engineering College, Landran, Mohali

²Department of Computer Engineering, University College of Engineering, Punjabi University, Patiala

Online published on 10 June, 2013.

Abstract

Human Resource can play a critical role in the success and failure of Information systems in an organization. It has been established that even the best of Information systems do fail due to the neglect of the human factor. According to OASIG Report [1], 80–90% IT projects do fail mainly due to neglect of human factor. Therefore, in this paper an attempt has been made to propose an Artificial Neural Network(ANN) based approach that help us to study the failure/success of the Industry due to Peopleware(Human Resource) for an Information system. The study is particularly important because most of the studies make use of conventional approaches having their own limitations such as following an algorithmic approach. The ANNs do not suffer from such limitations and they process information in a similar way the human brain does. Neural networks learn by example. Thus this approach is likely to provide better results as it is done using the MATLAB R2007B programming by Neural Network programs. Hence, such a study will be of great importance with respect to the Indian Industry.

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Keywords

Neural Networks, Human resource factors, Company success, failure factors.

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