• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.6B
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• pp.617-625
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• 2010

The selection of a site where strong wind blows is important to increase effectively the electricity of wind power in proportion to the cube of the wind speed. It is advisable to establish the wind turbine in the coastal area with strong wind speed rather than in the inland. And the development of offshore wind energy is expected to solve the noise problem that is one of the important weaknesses in the wind turbine. In the process of the development business of wind energy, knowing forehead the wind power possibility in any area is one of the essential factors to choose the most optimum site of wind power. In this paper, the potential of wind power around JeJu coastal area is examined by using the wind data that Korea Meteorological Administration has surveyed for 10 years in 14 observation points. Wind speed data is revised to wind speed in 80 meters assuming installation height of the wind turbine, and wind power density and annual wind energy are also calculated. And annual electricity generation and percent of energy efficiency in all the observation points are estimated by using the information about 3,000 KW wind turbine.

• The Korean Journal of Franchise Management
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• v.7 no.1
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• pp.21-29
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• 2016

Purpose - The primary purpose of this study is to employ effective marketing methods using market segmentation of coffee shops by determining how motivations to visit coffee shops have different impacts on demographic profile of visitors and characteristics of coffee shop visits, so as to draw out a better understanding of customers of coffee market. Research design, data, and methodology - Data were collected using surveys of self-administered questionnaires toward coffee shop users in Daejeon, Korea. A number of samples used in data analysis were 253 excluding unusable responses. The data were analyzed through frequency, reliability, and factor analysis using SPSS 20.0. Factor analysis was conducted through the principal component analysis and varimax rotation method to derive factors of one or more eigen values. In addition, the cluster analysis, multivariate ANOVA, and cross-tab analysis were used for the market segmentation based on the types of motivation for coffee shop visits. The process of the cluster analysis is as follows. Four clusters were derived through hierarchical clustering, and k-means cluster analysis was then carried out using mean value of the four clusters as the initial seed value. Result - The factor analysis delineated four dimensions of motivation to visit coffee shops: ostentation motivation, hedonic motivation, esthetic motivation, utility motivation. The cluster analysis yielded four clusters: utility and esthetic seekers, hedonic seekers, utility seekers, ostentation seekers. In order to further specify the profile of four clusters, each cluster was cross tabulated with socio-demographics and characteristics of coffee shop visits. Four clusters are significantly different from each other by four types of motivations for coffee shop visits. Conclusions - This study has empirically examined the difference in demographic profile of visitors and characteristics of coffee shop visits by motivation to visit coffee shops. There are significant differences according to age, education background, marital status, occupation and monthly income. In addition, coffee shops use pattern characterization in frequency of visits to coffee shops, relationships with companion, purpose of visit, information sources, brand type, average expense per visit, important elements of selection attribute were significantly different depending on motivations for coffee shop visits.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.63-74
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• 2020

The assembly of modular construction requires a series of thoroughly-considered decisions for crane lifting including the crane model selection, crane location planning, and lift path planning. Traditionally, this decision-making process is empirical and time-consuming, requiring significant human inputs. Recently, research efforts have been dedicated to improving lift planning practices by leveraging cutting-edge technologies such as automated data acquisition, Building Information Modelling (BIM) and computational algorithms. It has been demonstrated that these technologies have advanced lift planning to some degree. However, the advancements tend to be fragmented and isolated. There are two hurdles prevented a systematic improvement of lift planning practices. First, the lack of formalized lift planning workflow, outlining the procedure and necessary information. Secondly, there is also an absence of a shared information environment, enabling storages, updates and the distribution of information to stakeholders in a timely manner. Thus, this paper aims to overcome the hurdles. The study starts with a literature review in combination with document analysis, enabling the initial workflow and information flow. These were contextualised through a series of interviews with Australian practitioners in the crane-related industry, and systematically analysed and schematically validated through an expert panel. Findings included formalized workflow and corresponding information exchanges in a traditional lift planning practice via a Business Process Model and Notation (BPMN). The traditional practice is thus reviewed to identify opportunities for further enhancements. Finally, a BIM-based lift planning workflow is proposed, which integrates the scattered technologies (e.g. BIM and computational algorithms) with the aim of supporting lift planning automation. The resulting framework is setting out procedures that need to be developed and the potential obstacles towards automated lift planning are identified.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.133-140
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• 2013

The purpose of this study is identifying the relationship among the business strategy, order receiving capability and leverage variables of a construction company using industry characteristic variables, in addition to the explanation variables used in the previous studies. The samples of this study were limited to the construction companies listed in Korean stock market. This study built multiple regression analysis models, which have been frequently used in traditional previous studies, in the explanation of company capital structure. Empirical analysis on Static Trade-off Theory and Pecking Order Theory was done by the built model. The study results suggested that the capital structure determination behavior of a construction company generally follows Static Trade-off Theory; however, profitability was found to follow Pecking Order Theory. The explanation variables used in the previous capital structure studies mostly produced significant results; however, the variables, which this study experimentally used, did not produce significant results. It is believed that it implies that additional studies are required in the selection of variables and study methodology. Consequently, a case that unconditionally supports a particular theory is scarce. It has been also found that a case can support both theories at the same time. Therefore, it is believed that development study methodology or introduction of new study methodology that can identify the dynamic characteristic of construction company capital structure formation is required.

• Journal of Venture Innovation
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• v.5 no.2
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• pp.15-34
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• 2022

Many countries, including Korea, have established and operated various startup supporting programs to revitalize youth entrepreneurship. This study aims to identify the current status and characteristics of the major startup supporting programs currently operated in Korea and propose development plans for future startup supporting programs through analysis of the startup supporting systems of major countries. By analyzing the success factors of domestic and foreign startup supporting systems, we suggested improvements that can be operated more effectively in the areas of financial support, selection process, education and mentoring, networking, publicity and branding, and follow-up management by operated startup supporting programs. In addition, improvements for performance evaluation indicators of startup supporting programs were suggested and limitations of the study were presented.

• Journal of the Korea Society of Computer and Information
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• v.29 no.6
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• pp.201-209
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• 2024

The COVID-19 pandemic has significantly impacted the aviation industry, leading to worldwide changes in travel restrictions and security measures. This study analyzes 59,818 reviews of 147 airlines from the SKYTRAX website between 2016 and 2023 to understand the changes in airline service satisfaction before and after the pandemic. Using sentiment analysis, the study compares overall satisfaction, review sentiment, and attributes influencing satisfaction. The results show a statistically significant (p<0.001) decrease in overall satisfaction post-COVID-19, with reduced positive sentiment and increased negative sentiment for all airline selection attributes, except cabin and in-flight services. Flight operation services had the most significant impact on overall satisfaction during both periods. This quantitative analysis of global major airlines' satisfaction attributes before and after COVID-19 contributes to enhancing future service satisfaction in the airline industry.

• Horticultural Science & Technology
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• v.30 no.1
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• pp.64-72
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• 2012

Phytophthora root rot has been causing a serious yield loss in pepper production. Since 2004, the year in which commercial cultivars resistant to the disease were firstly commercialized, it has been necessary to introduce the resistance into domestic pepper cultivars for dried red pepper. Therefore, developing molecular markers linked to the resistance is required for an accurate selection of resistant plants and increasing breeding efficiency. Until now, several markers associated with the major dominant gene resistant to Phytophthora root rot have been reported but they have some serious limitations for their usage. In this study, we aimed to develop molecular markers linked to the major dominant gene that can be used for almost of all genetic resources resistant to Phytophthora root rot. Two segregating $F_2$ populations derived from a 'Subicho' ${\times}$ 'CM334' combination and a commercial cultivar 'Dokyacheongcheong' were used to develop molecular markers associated with the resistance. After screening 1,024 AFLP primer combinations with bulked segregant analysis, three AFLP (AFLP1, AFLP2, and AFLP3) markers were identified and converted into three CAPS markers (M1-CAPS, M2-CAPS, and M3-CAPS), respectively. Among them, M3-CAPS marker was further studied in ten resistants, fourteen susceptibles, five hybrids and 53 commercial cultivars. As a result, M3-CAPS marker was more fitted to identify Phytophthora resistance than previously reported P5-SNAP and Phyto5.2-SCAR markers. The result indicated that the M3-CAPS marker will be useful for resistance breeding to Phytophthora root rot in chili pepper.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.9 no.1
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• pp.119-132
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• 2014

This study analyzed the failure prediction model of the firms listed on the KOSDAQ by considering whether there are embezzlement, malpractice and the largest shareholder changes or not. This study composed a total of 166 firms by using two-paired sampling method. For sample of failed firm, 83 manufacturing firms which delisted on KOSDAQ market for 4 years from 2009 to 2012 are selected. For sample of normal firm, 83 firms (with same item or same business as failed firm) that are listed on KOSDAQ market and perform normal business activities during the same period (from 2009 to 2012) are selected. This study selected 80 financial ratios for 5 years immediately preceding from delisting of sample firm above and conducted T-test to derive 19 of them which emerged for five consecutive years among significant variables and used forward selection to estimate logistic regression model. While the precedent studies only analyzed the data of three years immediately preceding the delisting, this study analyzes data of five years immediately preceding the delisting. This study is distinct from existing previous studies that it researches which significant financial characteristic influences the insolvency from the initial phase of insolvent firm with time lag and it also empirically analyzes the usefulness of data by building a firm's fail prediction model which considered embezzlement/malpractice and the largest shareholder changes as dummy variable(non-financial characteristics). The accuracy of classification of the prediction model with dummy variable appeared 95.2% in year T-1, 88.0% in year T-2, 81.3% in year T-3, 79.5% in year T-4, and 74.7% in year T-5. It increased as year of delisting approaches and showed generally higher the accuracy of classification than the results of existing previous studies. This study expects to reduce the damage of not only the firm but also investors, financial institutions and other stakeholders by finding the firm with high potential to fail in advance.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.1-23
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• 2014

Market forecasting aims to estimate the sales volume of a product or service that is sold to consumers for a specific selling period. From the perspective of the enterprise, accurate market forecasting assists in determining the timing of new product introduction, product design, and establishing production plans and marketing strategies that enable a more efficient decision-making process. Moreover, accurate market forecasting enables governments to efficiently establish a national budget organization. This study aims to generate a market growth curve for ICT (information and communication technology) goods using past time series data; categorize products showing similar growth patterns; understand markets in the industry; and forecast the future outlook of such products. This study suggests the useful and meaningful process (or methodology) to identify the market growth pattern with quantitative growth model and data mining algorithm. The study employs the following methodology. At the first stage, past time series data are collected based on the target products or services of categorized industry. The data, such as the volume of sales and domestic consumption for a specific product or service, are collected from the relevant government ministry, the National Statistical Office, and other relevant government organizations. For collected data that may not be analyzed due to the lack of past data and the alteration of code names, data pre-processing work should be performed. At the second stage of this process, an optimal model for market forecasting should be selected. This model can be varied on the basis of the characteristics of each categorized industry. As this study is focused on the ICT industry, which has more frequent new technology appearances resulting in changes of the market structure, Logistic model, Gompertz model, and Bass model are selected. A hybrid model that combines different models can also be considered. The hybrid model considered for use in this study analyzes the size of the market potential through the Logistic and Gompertz models, and then the figures are used for the Bass model. The third stage of this process is to evaluate which model most accurately explains the data. In order to do this, the parameter should be estimated on the basis of the collected past time series data to generate the models' predictive value and calculate the root-mean squared error (RMSE). The model that shows the lowest average RMSE value for every product type is considered as the best model. At the fourth stage of this process, based on the estimated parameter value generated by the best model, a market growth pattern map is constructed with self-organizing map algorithm. A self-organizing map is learning with market pattern parameters for all products or services as input data, and the products or services are organized into an $N{\times}N$ map. The number of clusters increase from 2 to M, depending on the characteristics of the nodes on the map. The clusters are divided into zones, and the clusters with the ability to provide the most meaningful explanation are selected. Based on the final selection of clusters, the boundaries between the nodes are selected and, ultimately, the market growth pattern map is completed. The last step is to determine the final characteristics of the clusters as well as the market growth curve. The average of the market growth pattern parameters in the clusters is taken to be a representative figure. Using this figure, a growth curve is drawn for each cluster, and their characteristics are analyzed. Also, taking into consideration the product types in each cluster, their characteristics can be qualitatively generated. We expect that the process and system that this paper suggests can be used as a tool for forecasting demand in the ICT and other industries.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.4
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• pp.135-149
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• 2020

As youth employment has become a social issue every year, the government is pushing for policies to support youth start-ups to create jobs voluntarily as a way to enhance the youth employment rate. In the case of young people in Gangwon Province, the number of people moving to other regions is increasing. This research is intended to empirically analyze the actual achievements of youth start-ups through the 'Youth Start-up Project' in Gangwon-do. It was divided into four categories: participation in government support, education completion, intellectual property right retention, and certification retention, which are characteristics of start-up companies, and hypotheses that they will have a positive impact on start-up performance (sales amount, duration of existence, or whether they are retained or not). Age and geographical factors (Yeongdong and Yeongseo) were injected as control variables to see how they affect them. Furthermore, empirical analysis was conducted by setting up a hypothesis that the characteristics of start-up companies and subsequent support between start-up performance would have a positive intermediary effect. The research results showed that the remaining characteristics, except for education completion, had a positive impact on sales, and that the more participation in government projects, the longer the duration of the company's existence. In addition, the level of participation in government support projects was significant in the direction of the government. The analysis results of the parameter, follow-up support, had a positive impact on the start-up performance, and the subsequent support mediating effect showed the mediating effect of the start-up performance, except for geographical factors. The results of this study suggest the need for customized support suitable for the characteristics of youth start-ups in order to enhance the performance of young start-ups. Support agencies need to refer to corporate characteristics for smooth management and selection. In the Gangwon-do area, the government should seek to provide timely and organic support for start-up companies in order to produce successful start-up cases.