Patent indicators as output variables of DEA to evaluate the efficiency of the computer communication equipment industry in United States

Abstract

This study uses Data Envelopment Analysis (DEA) and several statistical approaches to evaluate the efficiency of the computer communication equipment industry in the US from the perspective of patent performance. There are two output variables – patent counts and patent citations – and three input variables – total assets, R&D expenditures and employee productivity – in this study. The efficiency scores of the Charnes, Cooper and Rhodes (CCR) and Banker, Charnes and Cooper (BCC) models in this industry are 17.21% and 24.56%. Besides, this study finds out that there is ‘the advantage of firm size’ for patent performance, and demonstrates that R&D expenditures and employee productivity have positive effects on patent performance in this industry. Furthermore, this study applies cluster analysis to divide the sample into three groups named ‘Giant Enterprises’, ‘Indistinct Enterprises’ and ‘Ameba Enterprises’. This study points out that ‘Indistinct Enterprises’ have the worst efficiency, because ‘Giant Enterprises’ have the advantages of firm size, R&D resources and employee productivity and ‘Ameba Enterprises’ possess the advantage of flexibility, but ‘Indistinct Enterprises’ don’t have any advantage.