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Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE's Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
New product development (NPD) is considered to be one of the best strategies to handle the rapid changes that occur in the market for a product, in order to sustain competitive position. Though some researchers attempt to study factors that affect the capability of NPD by a firm; none of them tried to quantify them. Quantification of the factors is essential in order to achieve adequate control over the product development activities. In this paper, a neural network based methodology is developed in MATLAB code to quantify the NPD capability. This may help a firm to develop a selected set of capabilities into core competences in long run. The networks are used at two stages and the output of the neural network model at stage-2 is the quantified value of NPD capability. A feed forward network with one hidden layer is used for both stages. For case study, data is taken from the literature. The data is available over a selected time span and neural network is trained, tested and validated for the available data.