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Seulki Lee
Department of Architectural Engineering, Kwangwoon University, Seoul 01897, Korea

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Journal article
Published: 09 August 2021 in Sustainability
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Many studies have been conducted to define the critical success factors (CSFs) for off-site construction (OSC) activation, but there has been a lack of identification of the relationship with the identified CSFs. However, it is necessary to clearly identify the hierarchy and relationships with the success factors in order to develop specific strategies for OSC activation. This work presents a study that was conducted to identify the CSFs for OSCs and establish the relationships of the identified CSFs for OSC. First, 20 CSFs for OSCs were identified through prior study reviews related to CSFs for OSC. Next, the interpretive structural modeling (ISM), which has advantages in developing an understanding of complex relationships, was leveraged in order to analyze the relationships between 20 CSFs for OSC to derive a hierarchical model consisting of seven levels. The CSFs for OSC were classified into four groups using MICMAC analysis, which is useful for classifying factors by the strength of the relationship with factors based on driving power and dependence power. This proposed model can be used as a basis for developing management measures for OSC project success.

ACS Style

SeoYoung Jung; Seulki Lee; Jungho Yu. Identification and Prioritization of Critical Success Factors for Off-Site Construction Using ISM and MICMAC Analysis. Sustainability 2021, 13, 8911 .

AMA Style

SeoYoung Jung, Seulki Lee, Jungho Yu. Identification and Prioritization of Critical Success Factors for Off-Site Construction Using ISM and MICMAC Analysis. Sustainability. 2021; 13 (16):8911.

Chicago/Turabian Style

SeoYoung Jung; Seulki Lee; Jungho Yu. 2021. "Identification and Prioritization of Critical Success Factors for Off-Site Construction Using ISM and MICMAC Analysis." Sustainability 13, no. 16: 8911.

Journal article
Published: 29 December 2020 in Applied Sciences
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The cause of cracks in concrete is traditionally estimated by analyzing information such as patterns and locations of the cracks and whether other defects are present, followed by aggregating the findings to estimate the cause. This method is highly dependent on the expert’s knowledge and experience in the process of identifying the cause of the cracks by compiling information related to the occurrence of the cracks, and it is likely that each expert will make a different diagnosis or an expert with insufficient knowledge and experience will make an inaccurate diagnosis. Therefore, we propose automated technology using the ontology to improve the consistency and accuracy of crack diagnosis results in this research. The proposed approach uses information on the crack patterns, locations, and penetration status, as well as the occurrence of other defects, to automatically infer the causes of cracks. We developed ontology that can infer the cause of cracks using the information on their appearance and applied actual cases of cracks to verify the ontological operation. In addition, the consistency and accuracy of the ontology were validated using eight actual cases of crack. The approach of this study can support expert decision-making in the crack diagnosis process, thereby reducing the possibility of various errors caused by the intervention of inaccurate judgments in the crack diagnosis process and improving the efficiency of the crack diagnosis tasks.

ACS Style

SeoYoung Jung; Seulki Lee; Jungho Yu. Ontological Approach for Automatic Inference of Concrete Crack Cause. Applied Sciences 2020, 11, 252 .

AMA Style

SeoYoung Jung, Seulki Lee, Jungho Yu. Ontological Approach for Automatic Inference of Concrete Crack Cause. Applied Sciences. 2020; 11 (1):252.

Chicago/Turabian Style

SeoYoung Jung; Seulki Lee; Jungho Yu. 2020. "Ontological Approach for Automatic Inference of Concrete Crack Cause." Applied Sciences 11, no. 1: 252.

Journal article
Published: 03 August 2020 in Applied Sciences
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The Korean domestic market is focused on the introduction of BIM (Building Information Modeling) owing to an influx of investment due to increased interest and mandatory application of BIM. However, the rate of BIM introduction is high, while BIM user proficiency is low. Against these problems, the authors proposed an acceptance model for BIM in construction organizations in 2012. As the number of BIM application cases increases and the number of BIM‐trained users increases as time goes on, BIM usersʹ positive perception of BIM values are expected to increase, which may change the BIM acceptance mechanism. Therefore, we conducted a longitudinal study of the 2012 BIM acceptance model against 2019 data to estimate changes in factors affecting BIM acceptance attitudes as well as the mechanism of the relationships between factors over time spent using the technology. To generalize the results, the respondents were spread across construction sites. The data obtained 119 samples from a sample of experienced users of BIM. We used AMOS 21.0 for hypothesis testing of structural equation modeling (SEM), and the 2019 BIM acceptance model was compared against the 2012 acceptance model using an independent sample t‐test. As a result, it was confirmed that the 2012 BIM acceptance model is still suitable for describing the BIM acceptance mechanism of the construction organization, and there was a difference between the 2012 model and the 2019 model. This seems to have changed the mechanism of BIM acceptance by being change perception of BIM users as time goes on. The results of this study can be used to establish a BIM activation strategy for each BIM acceptance stage and are expected to be applicable to establishing a BIM activation strategy for construction organizations or countries with similar BIM acceptance stage.

ACS Style

Seulki Lee; Jungho Yu. Longitudinal Study on Construction Organization’s BIM Acceptance. Applied Sciences 2020, 10, 5358 .

AMA Style

Seulki Lee, Jungho Yu. Longitudinal Study on Construction Organization’s BIM Acceptance. Applied Sciences. 2020; 10 (15):5358.

Chicago/Turabian Style

Seulki Lee; Jungho Yu. 2020. "Longitudinal Study on Construction Organization’s BIM Acceptance." Applied Sciences 10, no. 15: 5358.

Journal article
Published: 04 September 2019 in Applied Sciences
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Mobile Building Information Modeling (BIM) is noted for tools that enable the systematic interchange of information and contribute to enhancing collaborative performance through BIM. BIM programs, which are continuously available in the mobile environment, have been developed. Moreover, in some sites, mobile BIM is applied to generate benefits in projects. Various efforts are being made to use mobile BIM; however, its utilization is low. Also, mobile BIM has lacked an analysis of the factors that affect actual users’ acceptance of mobile BIM. Therefore, this study analyzes the factors that affect the acceptance of mobile BIM by construction practitioners and presents the association of factors as a model to activate mobile BIM use. To this end, this study analyzed a literature review for suggesting the factors that were expected to affect mobile BIM acceptance. The assessment items were decided based on the analysis result. Second, 111 copies were received by surveying the construction practitioners. Third, it identified factors that significantly affected the acceptance of mobile BIM and proposed models through factor analysis and structural equation models. Finally, based on the analysis, it presented the findings. This study expects to contribute to enhanced acceptance of mobile BIM technology by managing the significant factors properly. Also, it is expected that the result can be used to develop a variety of mobile BIM that is more easily acceptable to them. This study presented a model for accepting mobile BIM based on the survey results of Korean practitioners; therefore, it is necessary to explore ways to generalize the model in the future.

ACS Style

Sim-Hee Hong; Seul-Ki Lee; In-Han Kim; Jung-Ho Yu; Hong; Lee; Kim; Yu. Acceptance Model for Mobile Building Information Modeling (BIM). Applied Sciences 2019, 9, 3668 .

AMA Style

Sim-Hee Hong, Seul-Ki Lee, In-Han Kim, Jung-Ho Yu, Hong, Lee, Kim, Yu. Acceptance Model for Mobile Building Information Modeling (BIM). Applied Sciences. 2019; 9 (18):3668.

Chicago/Turabian Style

Sim-Hee Hong; Seul-Ki Lee; In-Han Kim; Jung-Ho Yu; Hong; Lee; Kim; Yu. 2019. "Acceptance Model for Mobile Building Information Modeling (BIM)." Applied Sciences 9, no. 18: 3668.

Journal article
Published: 05 March 2019 in Automation in Construction
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Various green building certifications have been discussed as a part of efforts to realize sustainable development. In some countries, it is mandatory to acquire certifications for buildings above a certain scale. As a result, the demand for green building certifications has increased. Various studies have been conducted on the efficient performance of green building certification tasks. To improve the tasks for material information management, the following problems should be addressed: 1) Evaluation of material selection is difficult because of limitations on the amount and quality of the collected information; 2) Unnecessary duplication of work occurs because the important information created at each stage of a project is not delivered efficiently to the next step; 3) Information management for material information, which requires continuous updating, is not sufficient. Therefore, this study proposes an automated process of collecting and classifying Green Building Material Information (GBMI) using “web crawling” and “ontology” to improve the work efficiency of material information management. The proposed process is verified for interior finishing materials, which are a part of green building certification tasks. The proposed process can reduce the time required for the information management of building materials and eliminate human errors.

ACS Style

Sim-Hee Hong; Seul-Ki Lee; Jung-Ho Yu. Automated management of green building material information using web crawling and ontology. Automation in Construction 2019, 102, 230 -244.

AMA Style

Sim-Hee Hong, Seul-Ki Lee, Jung-Ho Yu. Automated management of green building material information using web crawling and ontology. Automation in Construction. 2019; 102 ():230-244.

Chicago/Turabian Style

Sim-Hee Hong; Seul-Ki Lee; Jung-Ho Yu. 2019. "Automated management of green building material information using web crawling and ontology." Automation in Construction 102, no. : 230-244.

Journal article
Published: 17 April 2018 in Sustainability
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In recent years, the awareness of the seriousness of the damage caused by fugitive dust and the need to manage it have increased. In particular, construction sites comprise 84% of business places that have reported fugitive dust generation, and they are required to have inspection and management to prevent the occurrence of fugitive dust at construction sites. However, the number of complaints in the construction industry due to fugitive dust has increased. The reason for this increase is the fact that existing control measures are defined based on emission processes rather than construction work types, which makes it difficult to apply fugitive dust control measures to construction sites. Therefore, this research evaluated the effectiveness of fugitive dust control measures for construction sites in Korea through a Delphi study. This Delphi study was conducted in two rounds with 12 experts in an on-site panel, and the factors that were determined to be effective control measures were convergence, the content validity ratio (CVR), and stability. This study’s results will be utilized to direct the establishment of future guidelines for fugitive dust control measures based on types of construction work.

ACS Style

Hyun-Jun Noh; Seul-Ki Lee; Jung-Ho Yu. Identifying Effective Fugitive Dust Control Measures for Construction Projects in Korea. Sustainability 2018, 10, 1206 .

AMA Style

Hyun-Jun Noh, Seul-Ki Lee, Jung-Ho Yu. Identifying Effective Fugitive Dust Control Measures for Construction Projects in Korea. Sustainability. 2018; 10 (4):1206.

Chicago/Turabian Style

Hyun-Jun Noh; Seul-Ki Lee; Jung-Ho Yu. 2018. "Identifying Effective Fugitive Dust Control Measures for Construction Projects in Korea." Sustainability 10, no. 4: 1206.