中国
电流(流体)
业务
建筑工程
工程类
政治学
电气工程
法学
作者
Simin Zhou,Rui Yu,Min Pan,Jian Zuo,Bocun Tu,Na Dong
出处
期刊:Journal of Management in Engineering
[American Society of Civil Engineers]
日期:2024-02-26
卷期号:40 (3)
被引量:1
标识
DOI:10.1061/jmenea.meeng-5439
摘要
Building information modeling (BIM) is critical to the digital transformation and upgrading of the construction industry. With its continuous promotion, the demand for BIM professionals is increasing, which can be seen from the large number of job recruitment ads on the Internet. Mining the massive recruitment information is conducive to understanding current demand for BIM professionals. After 5,033 pieces of BIM-related recruitment information in China being collected and preprocessed, statistical analysis was applied to reveal the demand for BIM professionals at the macro level. Then cluster analysis was carried out to classify different posts, with their corresponding required skills being visualized through a word cloud. Subsequently, based on the extracted keywords, an index system including 11 first-level indicators and 61 second-level indicators was constructed to comprehensively evaluate the competencies of BIM professionals. Finally, correlation analysis was introduced to quantify the relationships between different skills and posts. Through the recruitment data mining, it is possible to understand the overall demand for BIM professionals, available BIM posts, and their requirements which can provide reference for both BIM professionals training and BIM job hunting. Furthermore, it sheds light on the application of text mining in construction industry.
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