• International conference on construction engineering and project management
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• 2020.12a
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• pp.343-352
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• 2020

Modular integrated construction (MiC) is an innovative construction method where components of a building are manufactured in an offsite factory, trucked to the job site in sections, set in place with cranes, and assembled together to form a whole building. Where circumstances merit, favorable conditions exist and implemented effectively; MiC improves project performance. However, several key factors need to converge during implementation to realize the full benefits of MiC. Thus, a thorough understanding of the factors which are critical to the success of MiC projects is imperative. Drawing on a systematic review of 47 empirical studies, this research identified 25 key success factors (KSFs) for MiC projects. Of these, the five topmost cited KSFs for MiC projects include effective working collaboration and communication among project participants; standardization, optimization, automation and benchmarking of best practices; effective supply chain management; early design freeze and completion; and efficient procurement method and contracting. The study further proposed a conceptual model of the KSFs, highlighting the interdependences of people, processes, and technology-related KSFs for the effective accomplishment of MiC projects. The set of KSFs is practically relevant as they constitute a checklist of items for management to address and deal with during the planning and execution of MiC projects. They also provide a useful basis for future empirical studies tailored towards measuring the performance and success of MiC projects. MiC project participants and stakeholders will find this research useful in reducing failure risks and achieving more desired performance outcomes. One potential impact of the study is that it may inform, guide, and improve the successful implementation of MiC projects in the construction industry. However, the rigor of the analysis and relative importance ranking of the KSFs were limited due to the absence of data.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.47 no.1
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• pp.41-50
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• 2024

Korea is facing a significant problem with historically low fertility rates, which is becoming a major social issue affecting the economy, labor force, and national security. This study analyzes the factors contributing to the regional gap in fertility rates and derives policy implications. The government and local authorities are implementing a range of policies to address the issue of low fertility. To establish an effective strategy, it is essential to identify the primary factors that contribute to regional disparities. This study identifies these factors and explores policy implications through machine learning and explainable artificial intelligence. The study also examines the influence of media and public opinion on childbirth in Korea by incorporating news and online community sentiment, as well as sentiment fear indices, as independent variables. To establish the relationship between regional fertility rates and factors, the study employs four machine learning models: multiple linear regression, XGBoost, Random Forest, and Support Vector Regression. Support Vector Regression, XGBoost, and Random Forest significantly outperform linear regression, highlighting the importance of machine learning models in explaining non-linear relationships with numerous variables. A factor analysis using SHAP is then conducted. The unemployment rate, Regional Gross Domestic Product per Capita, Women's Participation in Economic Activities, Number of Crimes Committed, Average Age of First Marriage, and Private Education Expenses significantly impact regional fertility rates. However, the degree of impact of the factors affecting fertility may vary by region, suggesting the need for policies tailored to the characteristics of each region, not just an overall ranking of factors.

• Geomechanics and Engineering
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• v.37 no.4
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• pp.307-321
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• 2024

This paper delves into the critical assessment of predicting sidewall displacement in underground caverns through the application of nine distinct machine learning techniques. The accurate prediction of sidewall displacement is essential for ensuring the structural safety and stability of underground caverns, which are prone to various geological challenges. The dataset utilized in this study comprises a total of 310 data points, each containing 13 relevant parameters extracted from 10 underground cavern projects located in Iran and other regions. To facilitate a comprehensive evaluation, the dataset is evenly divided into training and testing subset. The study employs a diverse array of machine learning models, including recurrent neural network, back-propagation neural network, K-nearest neighbors, normalized and ordinary radial basis function, support vector machine, weight estimation, feed-forward stepwise regression, and fuzzy inference system. These models are leveraged to develop predictive models that can accurately forecast sidewall displacement in underground caverns. The training phase involves utilizing 80% of the dataset (248 data points) to train the models, while the remaining 20% (62 data points) are used for testing and validation purposes. The findings of the study highlight the back-propagation neural network (BPNN) model as the most effective in providing accurate predictions. The BPNN model demonstrates a remarkably high correlation coefficient (R2 = 0.99) and a low error rate (RMSE = 4.27E-05), indicating its superior performance in predicting sidewall displacement in underground caverns. This research contributes valuable insights into the application of machine learning techniques for enhancing the safety and stability of underground structures.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.263-286
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• 2022

This study acquires NBA statistical information for a total of 32 years from 1990 to 2022 using web crawling, observes variables of interest through exploratory data analysis, and generates related derived variables. Unused variables were removed through a purification process on the input data, and correlation analysis, t-test, and ANOVA were performed on the remaining variables. For the variable of interest, the difference in the mean between the groups that advanced to the playoffs and did not advance to the playoffs was tested, and then to compensate for this, the average difference between the three groups (higher/middle/lower) based on ranking was reconfirmed. Of the input data, only this year's season data was used as a test set, and 5-fold cross-validation was performed by dividing the training set and the validation set for model training. The overfitting problem was solved by comparing the cross-validation result and the final analysis result using the test set to confirm that there was no difference in the performance matrix. Because the quality level of the raw data is high and the statistical assumptions are satisfied, most of the models showed good results despite the small data set. This study not only predicts NBA game results or classifies whether or not to advance to the playoffs using machine learning, but also examines whether the variables of interest are included in the major variables with high importance by understanding the importance of input attribute. Through the visualization of SHAP value, it was possible to overcome the limitation that could not be interpreted only with the result of feature importance, and to compensate for the lack of consistency in the importance calculation in the process of entering/removing variables. It was found that a number of variables related to three points and errors classified as subjects of interest in this study were included in the major variables affecting advancing to the playoffs in the NBA. Although this study is similar in that it includes topics such as match results, playoffs, and championship predictions, which have been dealt with in the existing sports data analysis field, and comparatively analyzed several machine learning models for analysis, there is a difference in that the interest features are set in advance and statistically verified, so that it is compared with the machine learning analysis result. Also, it was differentiated from existing studies by presenting explanatory visualization results using SHAP, one of the XAI models.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.6
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• pp.25-37
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• 2022

The purpose of this study is to survey startup founders within 7 years of founding the importance and satisfaction of the components of the scale-up entrepreneurial ecosystem at the national level in Korea and analyze the direction of scale-up policy by component using IPA (importance-performance analysis). Since the perception of founders, who are the subjects of the entrepreneurial ecosystem, affects the quantity and quality of start-ups, research is needed to analyze and diagnose the perception of scale-up components. For the development of the national economy and entrepreneurial ecosystem, companies that emerge from startups to scale-up and unicorns must be produced, and for this, elements for the scale-up entrepreneurial ecosystem are needed. The results of this study are as follows. First, the importance ranking of the components of the scale-up entrepreneurial ecosystem recognized by founders was in the order of "Financial support by growth stage," "Support for customized scale-up for enterprises," "Improvement of regulations," "Funds dedicated to scale-up," "large-scale investment," and "nurturing technical talents." Second, the factors that should be intensively improved in the importance-satisfaction matrix in the future were 'Pan-Government Integration Promotion Plan', 'Scale-Up Specialized Organization Operation', 'Company Customized Scale-Up Support', 'Regulatory Improvement', and 'Building a Korean Scale-Up Model'. As a result, various and large financial capital for the scale-up entrepreneurial ecosystem, diversification of scale-up programs by business sector, linkage of start-ups and scale-up support, deregulation of new technologies and new industries, strengthening corporate-tailored scale-up growth capabilities, and providing overseas networking opportunities can be derived. In addition, it is expected to contribute to policy practice and academic work with research that derives the components of the domestic scale-up entrepreneurial ecosystem and diagnoses its perception.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.4
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• pp.417-428
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• 2020

The characteristics of the construction project involved various stakeholders' involvement from the planning stage until completion of the object, which caused the uncertainty to increase. Successful construction projects require risk analysis and appropriate responses. Therefore, this study aimed to confirm the influence of risk management factors on the success of river disaster prevention construction in construction projects and the effect of moderating communication between stakeholders involved in the construction process. The Delphi method was used to derive the risk management factors of the construction process. The survey used a snow ball sampling method. For analysis, SPSS Statistic 20 and SmartPLS 2.0 were used. As a result of the study, the impact of risk management factors on project performance was found to be large in the order of time risk, quality risk, cost risk, safety risk, and construction environment risk. In addition, the impact of the communication moderating effect was large in the order of cost risk, quality risk, construction environment risk, time risk, and safety risk. In this study, it was confirmed that communication between stakeholders related to river disaster prevention work has a moderating effect that changes the ranking of impacts on project performance. This shows the importance of communication in the construction process of river disaster prevention works. This study has important significance in that it identifies the importance of risk management factors and communication in river disaster prevention works.

• Journal of Service Research and Studies
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• v.7 no.4
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• pp.51-68
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• 2017

Financial technology (FinTech) is an emerging financial service sector include innovations in financial literacy and investment, retail banking, education, and crypto-currencies like bitcoin. One of the crucial branch of financial technology-third-party payment (TPP) is undergoing rapid growth, with online/mobile systems replacing offline financial systems. System quality and user attitudes are key perceptions driving third-party payment usage, the importance of these perceptions, however, may be different with countries as users' thinking varies from country to country. Thus, the purpose of this study is to elaborate how factors differ from China to Korea by drawing on the unified theory of acceptance and use of technology (UTAUT2). Additionally, this study also aims to propose a multi-attribute evaluation of the third-party online payment system based on analytic hierarchy process (AHP), fuzzy sets and technique for order performance by similarity to ideal solution (TOPSIS), to examine the relative importance of the perceptions influencing new technology adoption intention. The results showed that the price value has the most significant influence on Chinese perceptions, while the perceived credibility has the most significant effect on Korean perceptions. Sub-criteria also performs different results to Chinese and Korean third-party online payment system.

• Korean Journal of Construction Engineering and Management
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• v.14 no.2
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• pp.3-11
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• 2013

Recently according to increasement of the single family and dual-earner couples, the number of infants and young children stays on a long time to the childcare facilities. this is increasing the importance to improve the physical environment. However, the operating and maintenance costs of the national-public childcare facilities have taken effect of the unfair support issues of municipality's financial situation. Especially, because of the lack of the operating and maintenance costs of the facility and the shortage of facilities equipment maintenance repair costs, nursery operations and Maintenance items are needed to distribute appropriately. Therefore, this study is to estimate the importance to facility operations and maintenance items based on "Kindergarten and Childcare Facilities"presented at the Child Care Policy Study. we are expected to allocate appropriately of operation and maintenance cost of a limited budget. In particular, those can be considered for operation and maintenance cost about the National-Public Childcare Facilities and be determined to a safe and pleasant environment to kindergartens through the appropriate operations and maintenance support.

• Journal of Korean Home Economics Education Association
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• v.18 no.2 s.40
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• pp.29-45
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• 2006

This study was to investigate the perception of middle school students on the management of the curriculum $\ulcorner$Technology Home Economics$\lrcorner$ according to the 7th National Curriculum. The subjects were 494 third grade students from middle schools located in Seoul, in order to inquire into their perceptions through the questionnaire. The collected data was analyzed with the descriptive statistics, Pearson Chi-Square, t-test, and one-way ANOVA by SPSS Win ver. 12.0 program. The major findings were as follows: Firstly there were gender differences on the interests for the subject of $\ulcorner$Technology Home Economics$\lrcorner$. The girls who were interested in the subject were much more numerous than the boys, but only in the technology part of it, the boys were more interested than the girls. Secondly the students recognized that the experiment & practice for learning $\ulcorner$Technology Home Economics$\lrcorner$ was important. They, however, recognized that its operation in school was not enough to understand the contents. The higher a student viewed the importance of the experiment & practice on $\ulcorner$Technology Home Economics$\lrcorner$, the higher his perception of its usefulness in real life. Thirdly the highest ranking of its usefulness for the contents of the subject $\ulcorner$Technology Home Economics$\lrcorner$ was identified as 'the Computer and Information Processing' and 'the Nutrients and Diet in Adolescence'. These findings suggest that the importance of the experiment & practice was enhanced and the gender differences on the usefulness of the experiment & practice on the each units were considered in order to increase the degree of the students' interest and usefulness of the $\ulcorner$Technology Home Economics$\lrcorner$

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.6
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• pp.1001-1012
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• 2018

Regarding the small- and medium-sized enterprises in Korea that manufacture the railway vehicle parts, there are over 250 related companies. And they have been surviving in the form of producing and delivering the parts of the railway vehicles by importing the technologies and the products of the foreign countries rather than possessing their own technological abilities. Due to this, regarding the industry of the core components of the railroads, the dependence on the overseas has been high. As such, although, for supporting the small- and medium-sized enterprises that manufacture the railway vehicle parts, the government has been strengthening the diverse policy supports, it is a fact that the effectiveness of the support is not high. And, in order to effectively support these, there is a need to understand clearly and definitely what the important promotion factors are in the process of the technology commercialization. Accordingly, through the precedent researches regarding the factors that promote the technology commercializations of the small- and medium-sized enterprises that manufacture the railway vehicle parts, this research had extracted 10 main items. And the level of the importance of these indices was analyzed by using the AHP (Analytic Hierarchy Process). As a result of the AHP analysis, the factors within a corporation appeared to be the most important factor. And, as for the lower-ranking item, the commercialization capability was analyzed to be the most important item. It is highly expected that the contents and the results of this research will be usefully used when formulating the planning of the support program and the support policy for the technology commercializations by the public research organizations and the railroad management organization, which is an organization that supports the small- and medium-sized enterprises that manufacture the railway vehicle parts.