Failure Model of Peopleware Factors: A Neuro-Computing Approach

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.

Authors and Affiliations

Bikrampal Kaur and Dr. Himanshu Aggarwal

Keywords

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  • EP ID EP26472
  • DOI -
  • Views 470
  • Downloads 10

How To Cite

Bikrampal Kaur and Dr. Himanshu Aggarwal (2011). Failure Model of Peopleware Factors: A Neuro-Computing Approach. International Journal of Engineering, Science and Mathematics, 1(2), -. https://europub.co.uk/articles/-A-26472