Date: April 26, 2021

Time: 14:30 - 17:00 pm

Venue: Room 0411, Teaching Building 0#, Jiuli Campus

Event Details:

Lecturer: Professor Zhang, Yucheng

About the Lecturer:

Zhang Yucheng, graduated from the Australian School of Business of the University of New South Wales. He is the professor and doctoral supervisor of the School of Economics and Management of Hebei University of Technology. He is the editor of international journals such as Journal of Business Ethics (FT50 journal, JCR area 1, SSCI impact factor: 2.329), Journal of Vocational Behavior (JCR area, SSCI impact factor: 3.89) and so on. He presided over a number of national, provincial and ministerial projects such as the National Natural Science Foundation of China, the Youth Project, the Humanities and Social Sciences Project of the Ministry of Education, and the Hebei Provincial Natural Science General Project. He is also the winner of the Hebei Provincial Social Science Outstanding Achievement Award and the Best Paper Award of the Academy of Management Conference. He serves as a reviewer for several journals such as Journal of Applied Psychology, Human Relations, Human Resource Management, and other mainstream journals in the fields of management and business. He is a visiting scholar at the London School of Economics (LSE) and other well-known universities at home and abroad. His research fields are Repetitive Research in Management, Abuse Management, Family-friendly Human Resource Practices, Management Big Data, Multi-layer Analysis Models, Meta-analysis Methods, etc. Since 2014, Professor Zhang Yucheng has published more than 40 papers in the Journal of Applied Psychology, Journal of Management, Journal of Vocational Behavior, Journal of Business Ethics, Journal of Business Research, "Management World", and other top management journals at home and abroad, including many ESI top 1% highly cited papers. In terms of research methods, Professor Zhang Yucheng specializes in meta-analysis and related research method development, and has achieved many important results.

About the Lecture:

Knowledge graph, also known as bibliometric method, is one of the important methods of bibliometric review. This research method is widely used to analyze the dynamic nature of literature in specific research fields (Chen, 2006). It uses various analysis tools to graphically depict the structure and evolution of published research (Börner et al., 2010; Chen, 2006). Specifically, the knowledge graph is a graphical method that describes the mining, analysis, construction, drawing, and display of knowledge resources and their carriers through visualization technology (Chen, 2009). CiteSpace is a visualization tool specially used for academic literature analysis. Its main function is to detect hot topics and their evolution in a discipline or field based on co-citation analysis theory and specific algorithms, thereby revealing the research frontier and its changes in the evolution of the subject field trend. This study collected all the big data related research in business research, and used Citespace to analyze the quantitative data in its literature records and obtained visual networks (such as co-cited networks, cooperative networks, and keyword co-occurrences analysis, etc.). This lecture will focus on how to predict future research directions based on the literature evolution and development process of big data literature.