Measuring the underlying structure of classic topics in construction engineering and management : an SNA-based analysis

Abstract

As an academic field, construction engineering and management (CEM) emerged and developed into a mutual academic field in the past several decades. CEM is characterized by the high level of mixed knowledge from other disciplines (i.e. physics and computer science) to facilitate the application of engineering skills and models to execute the effective organizations in a complex environment. Therefore, understanding the latent topics in CEM is an important task. This study explores the classic topics of CEM and maps their structure by using SNA techniques from a large amount of data, providing relatively unbiased and convinced results.