Smart Construction Technology Competitiveness: Matrix-Based Evaluation and International Cooperation Strategies

Jeewon Lee; Jaehyun Hwang; Junwoo Baik; Dohyun Yang; Seokho Chi

doi:10.55785/JCAR.4.3.10

All Issue

2025 Vol.4, Issue 3 Preview Page Next Page

Research Article

Smart Construction Technology Competitiveness: Matrix-Based Evaluation and International Cooperation Strategies 기술정의 매트릭스를 활용한 스마트건설 기술경쟁력 분석 및 협력 전략 방안 제안

30 September 2025. pp. 10-16

PDF XML

Abstract

Smart construction, integrating BIM, digital twins, robotics, modular/OSC, and AI–IoT-based management, has emerged as a transformative approach to address persistent challenges in the construction industry, including low productivity, safety risks, and labor shortages. However, variations in institutional frameworks and industrial capacities across countries have created disparities in technology adoption, underscoring the importance of international cooperation. This study introduces a Technology Evaluation Matrix with 29 indicators to quantitatively assess 12 countries across four dimensions: Technology, People, Governance, and Impact. The results show the U.S. leads in research outputs, patents, and market impact; China in research volume and market size; Japan in policy and infrastructure; and the U.K. in human networks, while Korea demonstrates strong governance but weaker industrial and human resources. Based on a subsequent SWOT analysis, tailored cooperation strategies are proposed to accelerate adoption and enhance global competitiveness.

Keywords

International Collaboration

Construction Management

Smart Construction

Technology Level Analysis

Cooperation Strategy

스마트건설은 BIM, 디지털 트윈, 로봇 ∙ 자동화 시공, 모듈러 ∙ OSC, AI ∙ IoT 기반 관리 등을 통합한 기술로, 건설산업의 생산성 저하, 안전 문제, 인력 부족 등 구조적 한계를 극복할 혁신 수단으로 부상하고 있다. 그러나 국가별 제도적 기반과 산업 인프라의 차이로 기술의 발전 속도와 적용 범위가 서로 달라 기술의 국가 간 격차를 해소하고 글로벌 경쟁력을 강화하기 위해 국제협력이 필요하다. 본 연구는 스마트건설의 특성을 반영하여, 29개의 지표로 구성된 기술정의 매트릭스를 개발하였으며 12개국의 기술수준을 Technology, People, Governance, Impact의 네 영역에서 정량적으로 평가하였다. 미국은 논문 ∙ 특허와 시장 영향력, 중국은 연구성과와 시장 규모, 일본은 제도 ∙ 산업 인프라, 영국은 인적 네트워크에서 강점을 보였으며, 한국은 스마트건설 거버넌스는 강하나 인적 ∙ 산업 기반이 취약했다. 이어 SWOT 분석을 통해 구체적인 협력 전략을 도출하였다. 분석 결과를 통해 도출된 협력 전략은 국가별 차별적 강점을 상호 보완적으로 활용하여 기술 도입 가속화, 글로벌 시장 확장 및 지속 가능한 건설산업 혁신에 기여할 것으로 기대된다.

키워드

국제협력

건설관리

스마트건설

기술수준분석

협력전략

References

Archibugi, D., and Coco, A. (2004). A new indicator of technological capabilities for developed and developing countries. World Development, 32(4), pp. 629-654. https://doi.org/10.1016/j.worlddev.2003.10.008

10.1016/j.worlddev.2003.10.008

Chung, S., Lim, S., Chang, T., and Chi, S. (2024). Diagnosis of the current status of smart construction in Korea compared to the global markets. KSCE Journal of Civil Engineering, 28(9), pp. 3575-3590. https://doi.org/10.1007/s12205-024-2467-4

10.1007/s12205-024-2467-4

Fink-Hafner, D., Dagen, T., Dousak, M., Novak, M., and Hafner-Fink, M. (2019). Delphi method: Strengths and weaknesses. Metodološki zvezki, 16(2), pp. 1-19. https://doi.org/10.51936/fcfm6982

10.51936/fcfm6982

Grimpe, C., and Hussinger, K. (2013). Formal and informal knowledge and technology transfer from academia to industry: Complementarity effects and innovation performance. Industry and Innovation, 20(8), pp. 683-700. https://doi.org/10.1080/13662716.2013.856620

10.1080/13662716.2013.856620

Harty, C. (2006). Innovation in construction: A sociology of technology approach. Building Research & Information, 33(6), pp. 512-522. https://doi.org/10.1080/09613210500288605

10.1080/09613210500288605

Heggond, S. (2025). Artificial intelligence and machine learning for smart construction: Enhancing real-time monitoring and decision making, Deep Science.https://doi.org/10.70593/978-93-49307-33-9

10.70593/978-93-49307-33-9

Li, S., Lan, T., Nguyen, H. -X., and Tran, P. (2024). Frontiers in construction 3D printing: Self-monitoring, multi-robot, drone-assisted processes. Progress in Additive Manufacturing, 10, pp. 2001-2030. https://doi.org/10.1007/s40964-024-00794-8

10.1007/s40964-024-00794-8

Melenbrink, N., Werfel, J., and Menges, A. (2020). On-site autonomous construction robots: Towards unsupervised building. Automation in Construction, 119, Article 103312. https://doi.org/10.1016/j.autcon.2020.103312

10.1016/j.autcon.2020.103312

Ministry of Land, Infrastructure and Transport (MOLIT) (2018). A study on the establishment of a roadmap for smart construction technology. Research Report, MOLIT, Korea.

Saliu, L. O., Monko, R., Zulu, S., and Maro, G. (2024). Barriers to the integration of building information modeling (BIM) in modular construction in Sub-Saharan Africa. Buildings, 14(8), Article 2448. https://doi.org/10.3390/buildings14082448

10.3390/buildings14082448

Ulku, H. (2004). R&D, innovation, and economic growth: An empirical analysis, IMF Working Paper No. WP/04/185, IMF, Washington D.C., USA. https://doi.org/10.5089/9781451859447.001

10.5089/9781451859447.001

Vershinin, I. (2021). Disadvantages of patent performance indicators in performance-based research funding systems. Scientific Papers of the University of Pardubice, Series D: Faculty of Economics and Administration, 29(2), Article 1341. https://doi.org/10.46585/sp29021341

10.46585/sp29021341

Information

Publisher :Korean Society of Automation and Robotics in Construction
Publisher(Ko) :(사)한국건설자동화·로보틱스학회
Journal Title :Journal of Construction Automation and Robotics
Journal Title(Ko) :건설자동화·로보틱스 논문집
Volume : 4
No :3
Pages :10-16
Received Date : 2025-09-04
Revised Date : 2025-09-15
Accepted Date : 2025-09-15
A Correction to this article was published on 30 December 2025.

This article has been updated.
DOI :https://doi.org/10.55785/JCAR.4.3.10

Journal of Construction Automation and Robotics ISSN:2800-0552(Print) 2951-116X(Online) 건설자동화·로보틱스 논문집

All Issue