The unpredictability of standard back propagation neural networks in classification applications

Article Abstract:

Tam and Kiang's (1992) introduction of a neural-net approach in performing classification in business research is a significant contribution to the field of management science. However, an extension of their work is required. It should be noted that standard back propagation neural networks in classification is highly unpredictable. This unpredictability is actually behind the inconsistent classification results reported by Tam and Kiang. A possible solution to this is the use of a global smoothing training strategy. This method holds that the back propagation neural network features monotonicity limitations generated during the training process that result in monotonic function. The monotonic neural network model has proven to be a good model in managerial classification.

Analysis, Computer networks, Neural networks, Discriminant analysis, Classification

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Technological infrastructure and the implementation of technological strategies

Article Abstract:

Problems associated with the strategic implementation of technological changes are explored. The external structure supporting technological change and the strategic implications of interacting with the external infrastructure are examined. Some of the implications of infrastructure for implementing technological strategy are explored including: institutionalization and radical technological change; institutionalization and the timing of technological change; and institutionalization and product technology leadership.

Technological innovations, Organizational change, Strategic planning (Business)

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