A review of input–output model application hot spots in the energy and environment fields based on co-words network analysis

Abstract

Leontief’s input–output model (IOM) is a widely applied method for tracing energy or emissions embodied in economic activities. The economic IOM used in environmental science has aroused broad concerns from both economists and environmentalists. The aim of this study is to review the hotspots of application of IOM in the energy and environmental science fields based on a bibliometric method by using co-words network analysis. All 4938 publications in this study were retrieved from Science Citation Index, Social Science Citation Index, Conference Proceedings Citation Index – Science, and Conference Proceedings Citation Index – Social Science & Humanities. The keywords and frequently cited articles were studied to reveal the evolution of hot spots related to IOM applications in the field of energy and environment from 1998 to 2016. The features of the co-words network analysis of keywords were analyzed by four network indicators including modularity, number of clusters, closeness coefficient, and average path length. The results showed that “energy”, “CO2 emissions”, “GHG”, “LCA”, “industrial ecology”, “carbon footprint”, “China”, and “international trade” were the major application fields of IOM. In different stages the boundary of hot spots became overlapped and the whole network tightness became stronger. According to the analysis of frequently cited articles, we found those articles on CO2 or GHG emissions embodied in trade had been the most frequently cited articles since 2007 with negotiations on climate change. Based on our findings, using IOM to analyze important environmental problems is the key point to popularize IOM applications. Future research opportunities exist to apply IOM to wider environment issues, such as combined emissions and resources.