• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.9
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• pp.5955-5967
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• 2015

This study targets to recognize needs of adopting public management system in Urban Renewal Project. and to establish evaluation level of public management system using policy evaluation framework for establishing perspective and systemic level. Also, this study constructed basic principles as expanded concept like Public, expertise, participation, rationality, and sustainability based on previous studies and expert opinion. AHP analysis results are following. In case of upper level, post management and continuity are important factors. Also in case of under level, making stable economic system, honest operating system, reducing development costs, local development with self-sufficiency were important factors. through empirical results, the implications are following. First, public management system needs to develop a consistent principle from planning step to post management. Second, it is essential point that continuous retraining between involved people and drawing residents participate in progress activity. Third, when evaluating public management system, it is need that emphasize non-physical factor like conflict issue between stakeholder.

• International Journal of Highway Engineering
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• v.12 no.3
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• pp.87-92
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• 2010

As the Concept "how environmental friendly" becomes more and more important in road construction. However, so far there is no estimation method. Environmental friendly concept can be incorporated at the plan level in order to influence decision making, and support policies that affect environment. The overall goal of this study was to develop environmental friendly concept measures for the national highway and to develop a methodology to implement a more environmental friendly concept. The research identified 8 performance measures through a project analysis that could address environmental impact assessment system's ten strategic goals - Topography, Wildlife, hydrology, landuse, air quality, water quality, soil, waste, noise, landscape. The qualitatively and quantitatively evaluation approach was selected as the decision support framework and performance measure were investigated using the AHP(Analytic Hierarchy Process) and pilot corridor for a 10 section and calculate the index values. The methodology was applied to a pilot corridor comprised of a 120km section of national highway in korea. The methodology made it possible to identify the specific performance measures that need improvement to enhance the overall environmental friendly concept. It is fairly intuitive, based on readily available data, and is easy to apply. It provides a powerful tool for government to assess the relative environmental friendly conceptof their transportation corridors now and in the future. It allows for comparisons within a corridor and with other corridors and identifies the improvements needed to enhance the environmental friendly concept.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.707-725
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• 2021

Energy management systems (EnMS) contribute to sustainable energy saving and greenhouse gas reduction by emphasizing the role of energy management in production-oriented economies. Although understanding the methods used to measure energy performance is a key factor in constructing successful EnMS, few attempts have been made to examine these methods, their applicability, and their utility in practice. To fill this research gap, this study aimed to deepen the understanding of energy performance measures by focusing on four energy performance indicators (EnPIs) proposed by ISO 50006, namely the measured energy value, ratio between measured values, linear regression model, and nonlinear regression model. This paper presents policy and managerial implications to facilitate the effective use of these measures. An analytic hierarchy process (AHP) analysis was conducted with 41 experts to analyze the preference for EnPIs and their key selection criteria by the industry sector, and organization and user type. The findings suggest that the most preferred EnPI is the ratio between the measured values followed by the measured energy value. The ease of use was considered to be most important while choosing EnPIs.

• Journal of Korean Society for Quality Management
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• v.50 no.4
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• pp.647-664
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• 2022

Purpose: The purpose of this study is to derive major policies that domestic small and medium-sized manufacturing companies should consider to maximize productivity and quality improvement by utilizing manufacturing data and AI, and to find priorities and implications. Methods: In this study, domestic and international issues and literature review by country were conducted to derive major considerations such as manufacturing AI technology, manufacturing AI talent, manufacturing AI data and manufacturing AI ecosystem. Additionally, the questionnaire survey targeting 46 experts of manufacturing data and AI industry were conducted. Finally, the major considerations and detailed factors importance were derived by applying the Analytic Hierarchy Process (AHP). Results: As a result of the study, it was found that 'manufacturing AI technology', 'manufacturing AI talent', 'manufacturing AI data', and 'manufacturing AI ecosystem' exist as key considerations for domestic manufacturing AI. After empirical analysis, the importance of the four key considerations was found to be 'manufacturing AI ecosystem (0.272)', 'manufacturing AI data (0.265)', 'manufacturing AI technology (0.233)', and 'manufacturing AI talent (0.230)'. The importance of the derived four viewpoints is maintained at a similar level. In addition, looking at the detailed variables with the highest importance for each of the four perspectives, 'Best Practice', 'manufacturing data quality management regime, 'manufacturing data collection infrastructure', and 'manufacturing AI manpower level of solution providers' were found. Conclusion: For the sustainable growth of the domestic manufacturing AI ecosystem, it should be possible to develop and promote manufacturing AI policies in a balanced way by considering all four derived viewpoints. This paper is expected to be used as an effective guideline when developing policies for upgrading manufacturing through domestic manufacturing data and AI in the future.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.79-96
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• 2012

As the pace of competition dramatically accelerates and the complexity of change grows, a variety of research have been conducted to improve firms' short-term performance and to enhance firms' long-term survival. In particular, researchers and practitioners have paid their attention to identify promising technologies that lead competitive advantage to a firm. Discovery of promising technology depends on how a firm evaluates the value of technologies, thus many evaluating methods have been proposed. Experts' opinion based approaches have been widely accepted to predict the value of technologies. Whereas this approach provides in-depth analysis and ensures validity of analysis results, it is usually cost-and time-ineffective and is limited to qualitative evaluation. Considerable studies attempt to forecast the value of technology by using patent information to overcome the limitation of experts' opinion based approach. Patent based technology evaluation has served as a valuable assessment approach of the technological forecasting because it contains a full and practical description of technology with uniform structure. Furthermore, it provides information that is not divulged in any other sources. Although patent information based approach has contributed to our understanding of prediction of promising technologies, it has some limitations because prediction has been made based on the past patent information, and the interpretations of patent analyses are not consistent. In order to fill this gap, this study proposes a technology forecasting methodology by integrating patent information approach and artificial intelligence method. The methodology consists of three modules : evaluation of technologies promising, implementation of technologies value prediction model, and recommendation of promising technologies. In the first module, technologies promising is evaluated from three different and complementary dimensions; impact, fusion, and diffusion perspectives. The impact of technologies refers to their influence on future technologies development and improvement, and is also clearly associated with their monetary value. The fusion of technologies denotes the extent to which a technology fuses different technologies, and represents the breadth of search underlying the technology. The fusion of technologies can be calculated based on technology or patent, thus this study measures two types of fusion index; fusion index per technology and fusion index per patent. Finally, the diffusion of technologies denotes their degree of applicability across scientific and technological fields. In the same vein, diffusion index per technology and diffusion index per patent are considered respectively. In the second module, technologies value prediction model is implemented using artificial intelligence method. This studies use the values of five indexes (i.e., impact index, fusion index per technology, fusion index per patent, diffusion index per technology and diffusion index per patent) at different time (e.g., t-n, t-n-1, t-n-2, ${\cdots}$) as input variables. The out variables are values of five indexes at time t, which is used for learning. The learning method adopted in this study is backpropagation algorithm. In the third module, this study recommends final promising technologies based on analytic hierarchy process. AHP provides relative importance of each index, leading to final promising index for technology. Applicability of the proposed methodology is tested by using U.S. patents in international patent class G06F (i.e., electronic digital data processing) from 2000 to 2008. The results show that mean absolute error value for prediction produced by the proposed methodology is lower than the value produced by multiple regression analysis in cases of fusion indexes. However, mean absolute error value of the proposed methodology is slightly higher than the value of multiple regression analysis. These unexpected results may be explained, in part, by small number of patents. Since this study only uses patent data in class G06F, number of sample patent data is relatively small, leading to incomplete learning to satisfy complex artificial intelligence structure. In addition, fusion index per technology and impact index are found to be important criteria to predict promising technology. This study attempts to extend the existing knowledge by proposing a new methodology for prediction technology value by integrating patent information analysis and artificial intelligence network. It helps managers who want to technology develop planning and policy maker who want to implement technology policy by providing quantitative prediction methodology. In addition, this study could help other researchers by proving a deeper understanding of the complex technological forecasting field.

• Journal of Korea Port Economic Association
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• v.35 no.4
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• pp.1-16
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• 2019

The purpose of this study is to Analyze the problems that container shipping companies exist through the commercialization of container shipping for Non-Arctic countries and the opportunity factors for the transport of the Arctic shipping to improve cooperation cross-border relation Arctic policy and the use of transport. In order to design a hierarchy analysis method study model, four high and 17 low factors were extracted by designing a hierarchy analysis method study model based on results by prior study and in-depth interview. The first of the higher factors is the internal strength of assessing the value of the Arctic, the will and capabilities of the shipping companies in creating new markets with the vision and goals of the shipping companies. Second, the internal constraints associated with the shipping companies advance to the NSR mean the negative factors for the entry into the NSR and the internal weaknesses that cause the shipping companies capacity limitations. Third, the economic benefits from the use of NSR are external factor for shipping companies in cooperation with the future economic value of the Arctic and with respect to Arctic sea and Arctic advance and development from Arctic coastal countries. Finally, external pre-emptive tasks means to respond to use NSR by external restrictions on transport to prepare the possibility of severe weather conditions, the customs policy change of coastal countries.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.6
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• pp.27-42
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• 2020

Startup accelerators have emerged as new investment entities that help early startups, which are not easy to survive continuously due to lack of funds, commercialization capabilities, and experiences. As their positive performance on early startups and the ecosystem has been proven, the number of early startups which want to receive their investment is also increasing. However, they are vaguely preparing to attract accelerators' investment because they do not have any information on what factors the accelerators consider important. In addition, researches on startup accelerators are also at an early level, so there are no remarkable prior studies on factors that decide on investment. Therefore, this study aims to help startups prepare for investment attraction by looking at what factors are important for accelerators to invest, and to provide meaningful implications to academia. In the preceding study, we derived five upper level categories, 26 lower level accelerators' investment determinants through the qualitative meta-synthesis method, secondary data analysis, observation on US accelerators and in-depth interviews. In this study, we want to derive important implications by deriving priorities of the accelerators' investment determinants. Therefore, we used AHP that are evaluated as the suitable methodology for deriving importance and priority. The analysis results show that accelerators value market-related factors most. This means that startups that are subject to investment by accelerators are early-stage startups, and many companies have not fully developed their products or services. Therefore, market-related factors that can be evaluated objectively seem to be more important than products (or services) that are still ambiguous. Next, it was found that the factors related to the internal workforce of startups are more important. Since accelerators want to develop their businesses together with start-ups and team members through mentoring, ease of collaboration with them is very important, which seems to be important. The overall priority analysis results of the 26 investment determinants show that 'customer needs' and 'founders and team members' understanding of customers and markets' (0.62) are important and high priority factors. The results also show that startup accelerators consider the customer-centered perspective very important. And among the factors related to startups, the most prominent factor was the founder's openness and execution ability. Therefore, it can be confirmed that accelerators consider the ease of collaboration with these startups very important.

• Korean Journal of Construction Engineering and Management
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• v.17 no.4
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• pp.103-115
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• 2016

The 106 buildings of 200 meters' height or greater were completed around the world in 2015 (CTBUH, The Council on Tall Buildings and Urban Habitat). They beat every previous year on record, including the previous record high of 99 completions in 2014. This brings the total number of 200-meter-plus buildings in the world to 1,040, exceeding 1,000 for the first time in history and marking a 392% increase from the year 2000, when only 265 existed. South Korea recorded three completions during 2015 - improving slightly over 2014, in which it had one. This study focused on the fact that high-rise building development project risks have not reduced in Korea in spite of numerous studies and measures. And it attempted to examine whether existing studies and measures have been presented on the basis of the accurate analysis of existing studies and measures and classify and analyze the characteristics of each phase' s risk factors in the hope that its results would be one reference point as to the measure to prevent high-rise building development project risks in the future. A high-rise building development project is the high risk project as compared with the low-rise project. Because a high-rise development project takes long and is very sensitive to the changing environment. Therefore, in order to succeed the project it becomes necessary to effectively manage the risk involved in the process of the high-rise building development project. The result of this study can be used as the guideline to make the risk management system for the high-rise development project.

• Korean Chemical Engineering Research
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• v.57 no.5
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• pp.637-651
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• 2019

In the event of a major accident such as an explosion in a refinery or a petrochemical plant, it has caused a serious loss of life and property and has had a great impact on the insurance market. In the case of catastrophic incidents occurring in process industries such as refinery and petrochemical plants, only the proximate causes of loss have been drawn and studied from inspectors or claims adjustors responsible for claims of property insurers, incident cause investigators, and national forensic service workers. However, it has not been done well for conducting root cause analysis (RCA) and identifying the factors that contributed to the failure and establishing preventive measures before leading to chemical plant's catastrophic incidents. In this study, the criteria of warning signs on CCPS catastrophic incident waning sign self-assessment tool which was derived through the RCA method and the contribution factor analysis method using the swiss cheese model principle has been reviewed first. Secondly, in order to determine the major incident warning signs in an actual chemical plant, 614 recommendations which have been issued during last the 17 years by loss control engineers of global reinsurers were analyzed. Finally, in order to facilitate the assessment index for catastrophic incident warning signs, the criteria for the catastrophic incident warning sign index at chemical plants were grouped by type and classified into upper category and lower category. Then, a catastrophic incident warning sign index for a chemical plant was developed using the weighted values of each category derived by applying the analytic hierarchy process (pairwise comparison method) through a questionnaire answered by relevant experts of the chemical plant. It is expected that the final 'assessment index for catastrophic incident warning signs' can be utilized by the refinery and petrochemical plant's internal as well as external auditors to assess vulnerability levels related to incident warning signs, and identify the elements of incident warning signs that need to be tracked and managed to prevent the occurrence of serious incidents in the future.

• Journal of Korean Elementary Science Education
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• v.42 no.4
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• pp.560-576
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• 2023

The purpose of this investigation is to: (1) to derive an improvement factor for inquiry-based simulated teaching-learning in pre-service teacher training programs, and pre-service teachers practice simulated teaching that reflect the improvement factor, (2) to analyze the difference in science intrinsic motivation according to science self-efficacy and inquiry-based simulated teaching-learning experience. To achieve these goals, we recruited five elementary and secondary teachers as experts to help us develop an improvement factor based on expert interviews. Subsequently, third-year pre-service teachers of a university of education participated in our analysis of differences in science intrinsic motivation, according to their level of science self-efficacy and experience with inquiry-based simulated teaching-learning. Our methodology involved applying the analytic hierarchy process to expert interviews to derive improvement factor for inquiry-based simulated teaching-learning, followed by a two-way ANOVA to identify significant differences in science intrinsic motivation between groups with varying levels of science self-efficacy. We also conducted post-analysis through MANOVA statements. The results of our study indicate that inquiry-based simulated teaching-learning can be improved through activities that foster digital literacy, ecological literacy, democratic citizenship, and scientific inquiry skills. Moreover, small group activities and student-centered teaching-learning approaches were found to be effective in developing core competencies and promoting science achievements. Specifically, pre-service teachers prepared a teaching-learning course plan and inquiry-based simulated teaching-learning in seventh-grade in the Earth and Space subject area. Pre-service teachers' science intrinsic motivation analyze significant differences in all levels of science self-efficacy before and after simulated teaching-learning and significant difference in the interaction effect between simulated teaching-learning and scientific self-efficacy. Particularly, group with low scientific self-efficacy, the difference in science intrinsic motivation according to simulated teaching-learning was most significant. Teachers' scientific self-efficacy and intrinsic motivation are needed to improve science achievement and affective domains of students in class. Therefore, this study contributes to suggest inquiry-based simulated teaching-learning reflecting school practices from the pre-service teacher curriculum.