| Title |
A Text Mining?Based Empirical Analysis of the Relationship Between Specialized Construction Work Types and Trades |
| Authors |
김성일(Kim, Sung-Il) ; 장철기(Chang, Chul-Ki) |
| DOI |
https://doi.org/10.5659/JAIK.2026.42.7.373 |
| Keywords |
Specialty Construction Work; Work Field; Type of Construction Worker; Text Mining |
| Abstract |
The construction industry, especially specialty construction sectors, requires a wide range of skilled workers because technical requirements
and trade composition vary by construction type and process. Despite this, empirical research on labor input structures by trade remains
limited. This study identifies the demand structure for skilled construction workers across specialty fields using text mining techniques. It
combines prime and subcontract data from the Construction Project Registry database of KISCON with worker retirement records from the
Retirement Mutual Aid Association, where trade classifications are recorded. Through this linked data and analysis, the study systematically
reveals demand patterns for skilled workers in different specialty construction fields. The results highlight trade-specific labor input patterns
across various types of construction work. They also support the development of classification frameworks that reflect these trade-specific
input patterns, providing a basis for more effective workforce allocation and for setting registration requirements based on core trades within
each specialty sector. |