A Bibliometric Analysis of the Technological Innovation in China

Introduction

For the past 20 years, China becoming the “world factory” has changed the structure of the global trade market. During this process, in addition to dedicating on building its own production capability, China has not neglected to enhance its technological innovation capabilities (Altenburg, Schmitz, & Stamm, 2008), which has led to breakthrough development in many technological research fields. For example, the aerospace industry and the wind turbine industry, which are the development priorities under China’s national support policies, have seen increased global market share and heightened research funding invested, and this has led to the wind tunnel testing technological researches flourished and closely follows after United States in recent years (Mo, Fu, & Ho, 2018). As China becomes the great political, economic and technology power, its reliance on foreign technology imports has also declined. Take low-carbon clean energy technology as an example, China’s technological innovation capability has led to a technology transfer model, i.e. reversing itself from a major technology import country to an export country (Urban, 2018). Under this trend, China's technological innovation has gradually attracted the attention of the academic field, and its processes and problems were being explored from different scientific research areas. For example, eco-innovation drivers and their impact on business performance (Cai & Li, 2018), innovative technology developments in China's aircraft and space manufacturing (Yang, Hong, Song, & Hong, 2017) or companies use public venture capital funds to improve innovation and financial performance (Y.B. Wang, Li & Furman, 2017). Thousands of scientific research related papers were published reveals the importance of China's technological innovation, as well as providing the necessary data sets to explore the overall trends and details in the area of technological research and development.

Upon reviewing relevant research literature, it’s evident that most of the papers on China's technological innovations start from specific industry or issue, such as logistics, renewable energy, and agricultural technology (Cui, Su, & Hertz, 2012; Huang et al., 2012; Z. Li & Zhang, 2013). As an emerging research area, there’s hardly any paper taking a retrospective view on the overall development. Therefore, this study retrieved the relevant papers from the Social Citation Index Expanded and the Social Science Citation Index of the Web of Science database. From 1990 to 2018, a total of 1,875 articles were collected as the data set for our analysis. Then we explore the overall development of China's technological innovation researches using document analysis approach. The final results would help scholars to quickly establish a comprehensive and in-depth understanding in this area, and inspire them derive their own interest research topics. Since this study uses all the literatures in the database, it would be a highly labor-intensive and time-consuming project should we adopt an eye-reviewing approach to summarize the development of the overall scientific researches. Based on the fact that the authors of a paper should know the best which papers are most relevant to their research topics, we consider the direct citation as a critical analytical basis to extract the overall development direction of their research area. While direct citation in a paper represents the relative importance of papers in this field, commonly used measures like total citation number quantifies an individual scholar's overall citation impact. Here we use the direct citation in papers as the relationship network to show the major themes of the technological innovation among key researchers in China. We also adopt the relatedness measure as the basis of cluster analysis, which classifies five main research development groups related to the technological innovation in China. We then review the core papers under each group to illustrate the detailed development of each group. As we use algorithms to determine the five major development groups, and identify 60 key papers under each, researchers can directly find papers that are most relevant to their research topics from the key papers list. They can also refer our results to identify the key papers in each development group and understand the influential research that may lead to the important technological innovations in China.