Hyunjoung Lee

A study on knowledge structure and cognitive mapping of marketing using social network analysis

This research has been undertaken to identify the knowledge structure of the marketing field from 1991 to 2010. For this, 282 keywords extracted from 11,548 papers in international journals related to the marketing field were analyzed with co-word analysis and social network analysis. To investigate the knowledge structure, the following steps were carried out. The first step was to identify the frequency of keywords over a 20-year period (1991–2010). Keywords that consistently represented the marketing field were identified as trust, pricing, consumer behavior, advertising, retailing, market orientation, and customer satisfaction. Keywords from 2000 onward were categorized to represent established research areas. New research topics such as internet, e-commerce, relationship marketing, customer relationship management, b2b, sales management, and corporate social responsibility emerged. The second step investigated sub-research areas in marketing using co-word matrix. As a result, eight cohesive subgroups were identified through community analysis. Each of the groups consisted of keywords related to the group name – Group 1: service performance and recovery, Group 2: brand management, Group 3: marketing modeling and choice model, Group 4: new product diffusion and forecasting, Group 5: distribution channels and pricing, Group 6: customer relationship management and internet marketing, Group 7: channel management, and Group 8: strategic orientation. The third step provided a cognitive map to reflect research development trends in each subgroup research area. Following that map, Groups 3, 4, and 5 were connected to other research areas. Group 6 and 7 were unconstructed areas for which further research is required. In the last step, social network analysis was performed to identify the core keywords using centrality analysis. Keywords with a high degree of centrality – i.e., highly correlated betweenness centrality – over the entire 20-year period were marketing strategy, consumer behavior, and trust. Through identifying the trends in the marketing field and confirmed sub-study areas, and revealing core keywords, the results of this study provide valuable insights into understanding the knowledge structure of the marketing field. In addition, this study suggests further research directions for marketing researchers.

Fundamentals of Big Data Network Analysis for Research and Industry: Lee/Fundamentals of Big Data Network Analysis for Research and Industry

Featuring case studies drawn largely from the iron and steel industries, this book offers practical guidance which will enable readers to easily understand big data network analysis. Particular attention is paid to the methodology of network analysis, offering information on the method of data collection, on research design and analysis, and on the interpretation of results. A variety of programs including UCINET, NetMiner, R, NodeXL, and Gephi for network analysis are covered in detail.