Measuring technological breadth and depth of patent documents using Rao's Quadratic Entropy

In this article we propose indices for technological breadth and depth of patent documents. We conceptually compare and contrast several indices that have been used in the existing literature, explaining main limitations. Motivated by the drawbacks of those we demonstrate how Rao's Quadratic Entropy, a statistical index used in ecology for measuring biodiversity, can be decomposed to separately measure technological breadth and depth. The properties of breadth and depth are then investigated using patents for business data processing. For the technological domains with the highest patenting activity, we show how the novel measures of technological breadth and depth can be used to rank the patenting entities by average breadth, and identify ones with inventions that on average exceed the domain-specific average depth. Practical implications of the proposed indices are also exemplified and discussed in the context of competitor analysis for entrepreneurial ventures in the area of network security for business data processing.