Research and development in productivity measurement: An empirical investigation of the high technology industry

Abstract

The high tech industry has played a critical role in the economic growth of Taiwan over the past two decades. The main success factor in the high tech industry is posited to be improving R&D efficiency and performance. This study utilizes an empirical study to provide valuable managerial insights when measuring the impact of R&D activities and performance representation in the Taiwanese high tech industry. The multi factor R&D performance model is determined to provide improved performance measures within the framework of the developed model, and is adopted to further examine the R&D performance of high tech firms and industries. The few studies dealing with devising the influence of environmental factors on efficiency measures do not consider that inefficiency results partly from exogenous circumstances. This study develops a two-stage sequential technique for incorporating environmental effects into a method for evaluating R&D performance based data envelopment analysis (DEA) and ordinary least squares (OLS) regression with panel data to obtain an efficiency measurement. The study data comprised 194 high tech firms analyzed from a multi-source database. The empirical results demonstrate that the average pure technical efficiency, overall technical efficiency, and scale efficiency scores across all 194 firms are 0.535, 0.424, and 0.791, respectively. Based on those efficiency scores and two-stage DEA empirical, suggestions regarding resource allocation for inefficient firms are explored and can be used to monitor R&D performance and as a basis for making subsequent innovation activities improvements. Key words: High tech industry, performance, R&D productivity, two-stage data envelopment analysis, OLS regression.