R&D Personnel’s Individual Variables And Patent Output Efficiency

With the advent of the knowledge-based economy era, technological innovation has replaced capital investment and labor inputs and become the main driving force of economic growth. At the same time, patent output has become the primary measurement of innovation productivity of a country or district. The existing literature about the impacting factors of innovation productivity has mainly focused on organizational environment, performance evaluation and incentive mechanism. Other factors of R & D personnel’s individual variables such as age, gender, training, etc was also involved, but a through study on the R&D input-output efficiency from the angle of R&D human resource input structure is absent. In this paper, we use a sample data of R&D personnel covering all the industries and regions of the country to research the individual variable’s impact on the patent output efficiency and its mechanism, based on a comprehensive review on domestic and international literatures. On this basis, we compare the importance order of the individual variables through orthogonal analysis, and conclude that education>title>age. According to that, we give suggestions of identifying and encouraging the efficient patent producer to the policy makers and R&D organization managers.This paper will fully integrate the observable variables of R&D personnel’s individual level (such as age, education, job title, industry, gender, organizational attributes) into the analysis to look at the influence of these variables on the number of patent output efficiency. The full text is divided into five parts:Chapter one is an introduction of the study background, purpose, significance, as well as the content and methods of this research. Chapter two reviews the related domestic and international literatures on the influence factors of innovation productivity, in particular the R & D staff individual variables’impact on patent productivity. Based on that and the sample data, we determine the study scope of individual variables, including age, education, job title, industry, gender and organizational attributes.Chapter three researches separate impact of particular individual variable on patent output efficiency. Through qualitative and quantitative analysis of each individual variable’s impact on patent output efficiency, we are trying to validate the six hypotheses presented in Chapter three.Chapter four researches the comprehensive impact of different individual variables on patent output efficiency. Based on the conclusions of previous chapter, we use an orthogonal analysis to identify the importance order of the individual variables which have notable impact on patent output efficiency in the separate level, and conclude that industry>education>title>age.Chapter five is the conclusion and discussion part, which lists major findings and discuss the value and innovation of this study. And we also give advice on future research on this subject.At last, we find that education, title, age and industry are those variables which have notable impact on R&D personnel’s patent output efficiency. And the impacting significance order is as follows: industries> qualifications> title> age. As a result, the most efficient patent producers are those R&D personnel who work in the high-tech industry, such as information technology or biotechnology industry; or who have the characteristics in the order below: (1) have an above-bachelor degree; (2) have a professional title; (3) and smaller in age.