개발도상국의 BIM 도입 장벽과 BIM 구현 가속화 전략: 미얀마 건설 산업 사례 연구

Barriers to BIM Adoption and Strategies for Accelerating BIM Implementation in Developing Countries: A Case Study of Myanmar’s Construction Industry

Building Information Modeling (BIM) holds considerable promise for enhancing the efficiency of construction processes, including design, construction, and maintenance. Nevertheless, the adoption and utilization of BIM remains insufficiently advanced within the Architecture, Engineering, and Construction (AEC) industries of both developed and developing nations. This study investigates the barriers to BIM adoption and strategies to fast-track its implementation among construction firms in Myanmar. Through a literature review, 28 barriers and 16 strategies to overcome them were identified and refined through a questionnaire survey with 56 construction professionals in Myanmar. The findings reveal that inadequate government policies and legislation, the absence of mandatory requirements, a lack of support from the government, inadequate BIM project experience, and a lack of BIM awareness and understanding constitute the most significant barriers to BIM adoption. The recommended strategies to facilitate adoption include enhancing BIM awareness and understanding, developing BIM guidelines, providing BIM-related IT training, offering additional training opportunities, and providing government support for the use of BIM. These findings highlight the necessity for a comprehensive strategy encompassing education, standardization, upskilling, and policy advocacy in order to promote BIM adoption and integration within the Myanmar construction industry. This study helps filling the gap of research on BIM adoption issues in developing countries and provides a rich information source for stakeholders who plan BIM implementation in analogous contexts. This study acknowledges the limitation of sample size which included 56 respondents that did not adequately represent the broader context of the Myanmar construction industry. Therefore caution should be taken when generalizing the finding. Future studies should include a larger and more diverse sample in order to improve validity.