Maintaining or increasing R&D efficiency and productivity is a constant challenge for R&D-driven businesses, and companies in these sectors often explore strategies seen be effective in related sectors, for example the adoption of ‘open’ innovation by the pharmaceutical sector, based on its observed success in the information technology sector as reported by Chesbrough. The papers in this thesis address two gaps in the research literature: (1) the relative lack of established quantitative measures of the performance of open or other innovation strategies, and (2) the continuing challenge of assessing the effectiveness or otherwise of the OI paradigm outside its original high-tech industry focus. The pharmaceutical industry has been claimed as one of the pioneering industries where the principle of OI has been applied. In view of the limitations of prior research on R&D efficiency and OI in this industry, the question of whether OI is the best or only prescription for innovation in the pharmaceutical industry remains a strategic one. The first paper in the sequence identifies and explores systematic measures of innovation by investigating the adaptation and application of DEA as a candidate technique for analysing the R&D efficiency performance, using data on China’s high-tech industry sectors. The second paper explores how such ‘indices of innovation’ could be used to measure performance in terms of changes in R&D efficiency over time, in a case study of Procter and Gamble, a company widely recognised as an early adopter of OI. The third paper builds on the first two, using DEA and MI as ‘indices of innovation’ to measure whether adopting OI is leading to increased R&D efficiency in the pharmaceutical sector. Taken together, these papers explore (a) the feasibility if DEA and MI as new quantitative econometric ‘indices of innovation’, (b) their correlation with a known case of open innovation, and (c) to test the hypothesis that open innovation is increasing R&D efficiency in the pharmaceutical industry.