Research Background
Research articles are information carriers in academia. Information changes with time. It may be replaced, be merged, or cease to be effective. Researchers must read a large number of research articles to understand the major research topics and trends in a field. In 2013, China’s electronic commerce (EC) trading scale surpassed that of the United States and it became the largest EC market with the fastest development worldwide. The processes of knowledge development and economic development are closely related to academic groups that generate knowledge, which has in turn generated a large number of research results on EC in China. EC is a hot topic in the fields of information and business that attracts the attention of scholars and experts in the fields of computer science, economy, management, and information. Numerous research papers on EC have been published in international journals. These papers address different EC-related topics (Yu, McLee, & Lee, 2008) and provide different perspectives to people who are interested to discuss, research, and read these topics.
Although some scholars have investigated the hot spots and development of EC research (Duan & Zhao, 2016; Liu & Yang, 2017; Ngai & Wat, 2002; Zhang & Li, 2019), we could not obtain clear contemporary trends in EC research in China by reviewing relevant papers individually. The role of Chinese EC and the research direction of Chinese EC in different times are unclear. The EC policies and trends in academia and research in China are also unclear. When investigating the large amounts of data in academic databases, researchers must spend considerable time and effort to rapidly unearth useful data, understand current research trends, or find highly relevant and valuable data from a wide range of information.
Research Motivation
Co-word analysis has been used effectively to indicate the research trends in many academic disciplines. Co-words are keywords that map the content of research topics. Co-word analysis involves performing statistical analysis on co-words to investigate the internal connections between the literature and academic subject structures. Since its introduction in the 1970s, co-word analysis has been widely used to investigate the research development trends of various academic disciplines, such as environmental crisis management (Dai, Duan, & Zhang, 2020); the evolution of Omega products (Wang et al., 2020); higher education institutions (Vilchez-Roman, Sanguinetti, & Mauricio-Salas, 2020); technology education (Fang, 2016); science, technology, engineering, and mathematics education (Wen, Sun, & Liu, 2020); information ecology (Wang, Guo, Yang, Chen, & Zhang, 2017); and biodiversity (Nita et al., 2019). However, few studies comprising co-word analysis have investigated EC in China. Previously, people manually reviewed and classified papers or conducted cross-sectional analysis to determine research trends for a certain topic. Researchers can search academic databases, such as Web of Science (WoS), Scopus, EBSCOhost, China National Knowledge Infrastructure (CNKI), or the Airiti Library, to obtain relevant studies regarding the field to be analyzed. Thus, they can obtain relevant information and field trends to understand the overall research trend and development of a topic (Kauffman, 2001; Ngai & Wat, 2002; Chen & Lu, 2019).
The aforementioned discussion reveals that from the perspectives of EC policies, EC responses to globalization, and the demands in global competitiveness, we cannot fully understand the research topics and the activities in the EC development in China as well as the knowledge dissemination process. Understanding said aspects (i.e., EC research topics, activities, and knowledge dissemination) is thus an urgent, wide, and critical topic in today’s knowledge-economy-based society. It is also a critical topic for the entire world and EC scholars. Therefore, this study conducted co-word analysis on journal articles regarding EC in China from the WoS database to understand the EC research trends in China.