Abstract
Scientific Productivity is a demand of policy makers for a judicious utilization of massive R&D budget allocated and utilized. A huge mass of intellectual assets is employed, which after investing manpower, infrastructure and lab consumables demand for a major outcome which contributes towards building nation’s economy. Scientific productivity was only measured through publications or patents. Patents, earmarked as a strong parameter for innovation generation, where, Word Intellectual Property Organisation generated a data on applications for the top 20 offices for patents, where Australia, Brazil and Canada occupied top 3 positions. India ranked 9th with the total patent applications rising from 39762 (2010) to 42854 (2014) i.e. 15%, whereas, it contributes around 2% Patents (innovative productivity) on global scale. Many studies have come forward interestingly within scientific and academic domains in the form of measurement of scientific performance, however, development of productivity indicators and calculation of Scientific Productivity (SP) as a holistic evaluation system is a significant demand. SP, a herculean task is envisaged for productivity analysis and would submit significant factors towards fabricating an effective measurement engine in a holistic manner viable for an individual and organization, being supplementary to each other. This review projects the significance of performance measurement system in R&D through identification and standardization of key parameters. It also includes emphasis on inclusion of standardized parameters, effective for performance measurement which is applicable for scientists, technical staff as well as lab as a facility. This review aims at providing an insight to the evaluators, policy makers, and high level scientific panels to stimulate the scientific intellects on identified indicators so that their work proceeds to generate productive outcome contributing to the economic growth.
Keywords: Performance measurement, performance indicators, R&D management, scientific productivity, sustainability, scientometrics analysis.
Graphical Abstract
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