• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.531-537
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• 2023

Interior construction is required to estimate the quantity of material and the cost expected from 2D drawing in design phase and look for the reasonable method of work. Therefore, exact estimation for quantity and budgeting are very important processes, as a measure of judging the profitability of interior construction. These processes are mostly based on 2D drawing, so time and experienced staff are required. Error and omission can occur because the experienced staff also calculates the area using 2D based drawing. Interior market is currently based on 3D modeling from planning to final design. Accordingly, estimating quantity based on 3D modeling is emerging as a way of reducing error and omission. This paper will present the methodology on calculating area, the basic element of estimating quantity based on 3D Modeling in interior field.

• Journal of Korean Port Research
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• v.12 no.1
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• pp.55-64
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• 1998

Directed graphic algorithm was applied to an empirical analysis of traffic occupant fatalities based on a model by Crandall. In this paper, Crandall's data on U.S. traffic fatalities for the period 1947-1981 are focused and extended to include 1982-1993. Based on the 1947-1981 annual data, the directed graph algorithms reveal that occupant traffic deaths are directly caused by income, vehicle miles, and safety devices. Vehicle mileage is caused by income and rural driving. The estimation is conducted using three stage least squares regression. Those results show a difference between the traditional regression methodology and causal graphical analysis. It is also found that forecasts from the directed graph based model outperform forecasts from the regression-based models, in terms of mean squared forecasts error. Furthermore, it is demonstrates that there exists some latent variables between all explanatory variables and occupant deaths.

• Journal of the Korean Geotechnical Society
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• v.22 no.2
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• pp.55-68
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• 2006

For the reliable prediction of spatial geotechnical data, a procedure to build the Geotechnical Information System (GTIS) based on geo-knowledge within the frame of GIS technology was developed by introducing a couple of new concepts of the extended area containing the study area and the additional site visit for acquiring surface geological data. To build the GTIS for Gyeongju as the case study of regional model application, intensive site investigations and pre-existing geotechnical data collections were performed and additional site visit was also carried out for acquiring surface geo-layer data in accordance with the developed procedure. Within the GTIS based on geo-knowledge for Gyeongiu area, the spatially distributed geo-layers across the extended area were predicted using the geostatistical kriging method and those for the study area were extracted. Furthermore, the spatial distribution maps for the thickess of geo-layers and the depth to bedrock were constructed for the practical use in geotechnical field. It was evaluated that the GTIS based on geo-knowledge developed in this study is superior to the conventional geotechnical GIS in terms of both the standard deviation and the geological expert judgment.

• Journal of the Korea Society of Computer and Information
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• v.14 no.4
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• pp.161-169
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• 2009

Republic of Korea is actively adopting IT fusion technologies to achieve the goal of 'Advanced National Defense'. This study is aiming to directly contribute to the ongoing DHRMIS project by analyzing its any discovered and substantial problems as well as suggesting improvements. Current difficulties include the efficient estimation on project cost, the lack of statistics for cross-referencing, the inefficient development methodology, compliance with global quality control standard, and the separated command centers. This study suggests the budget appraisal process prior to the actual execution, the introduce of regulatory business registration system, applying an efficient development methodologies as well as ISO9126 standard for quality control, and a centralized command department. We expect this study would contribute to following researches in advancing our national defense.

• Journal of Korea Trade
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• v.27 no.2
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• pp.96-114
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• 2023

Purpose - This paper elucidates a nexus between the occurrence of rare disaster events and the volatility of economic growth by distinguishing the likelihood of rare events from stochastic volatility. We provide new empirical facts based on a quarterly time series. In particular, we focus on the role of financial liberalization in spreading the economic crisis in developing countries. Design/methodology - We use quarterly data on consumption expenditure (real per capita consumption) from 44 countries, including advanced and developing countries, ending in the fourth quarter of 2020. We estimate the likelihood of rare event occurrences and stochastic volatility for countries using the Bayesian Markov chain Monte Carlo (MCMC) method developed by Barro and Jin (2021). We present our estimation results for the relationship between rare disaster events, stochastic volatility, and growth volatility. Findings - We find the global common disaster event, the COVID-19 pandemic, and thirteen country-specific disaster events. Consumption falls by about 7% on average in the first quarter of a disaster and by 4% in the long run. The occurrence of rare disaster events and the volatility of gross domestic product (GDP) growth are positively correlated (4.8%), whereas the rare events and GDP growth rate are negatively correlated (-12.1%). In particular, financial liberalization has played an important role in exacerbating the adverse impact of both rare disasters and financial market instability on growth volatility. Several case studies, including the case of South Korea, provide insights into the cause of major financial crises in small open developing countries, including the Asian currency crisis of 1998. Originality/value - This paper presents new empirical facts on the relationship between the occurrence of rare disaster events (or stochastic volatility) and growth volatility. Increasing data frequency allows for greater accuracy in assessing a country's specific risk. Our findings suggest that financial market and institutional stability can be vital for buffering against rare disaster shocks. It is necessary to preemptively strengthen the foundation for financial stability in developing countries and increase the quality of the information provided to markets.

• The Journal of Fisheries Business Administration
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• v.54 no.2
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• pp.1-14
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• 2023

The sustainability of fishing villages is threatened by manpower shortages due to population aging and poor settlement conditions. In the reality of poor fishing villages, the importance of women's labor is more emphasized than that of the past because female workers are key workers in fishing labor, processing and sales of marine products. However, policy support for female fishermen is not sufficient. The reason for this is that policy makers did not properly recognize the labor value of female fishermen. In fact, fishing villages have emphasized the importance of female workforce as a slogan, but there has been no attempt to estimate the labor value. There was not even a review of the methodology for estimating the value of labor that was attempted in similar fields. As a result, the policy importance of female fishermen was underestimated for there was no attempt to evaluate their value even though women had been continuously participating in the fishery from the past. Female fishermen's labor is under the dual labor structure of housework and fishing labor. Therefore, in this study, housework and fishing labor were estimated separately and the total labor value was calculated. The basic data necessary for estimating the labor value of female fishermen were obtained through a survey. The method of estimating the labor value of female fishermen was used in combination with the present income method and the total replacement cost method. As a result of the study, the total labor value of female fishermen was about 4.4 trillion won, which is about half of the total fishery production of 9 trillion won in Korea.

• The Journal of Economics, Marketing and Management
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• v.6 no.4
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• pp.1-16
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• 2018

Purpose - This study will investigate and identify the relationship between brand image, brand attitude and intent to purchase based on subjects that have remembered or watched more than one storytelling marketing ad related to airlines. The purpose of the project is to secure market competitiveness by presenting the basis for and use of the marketing strategy using storytelling, which can capture the goodwill of the aerospace competition market in the future. Research, design, data, and methodology - Prior to the research model and hypothesis testing phase, a verification factor analysis was conducted to assess internal consistency among each measurement item and to ensure reliability and validity of the measurement tool. Further, the organization was assessed for validity by calculating the mean variance estimation (AVE) and the construction concept reliability (CCR) through a positive factor analysis. Hypothesis verification was analyzed through a structural equation model, and each concept set in the hypothesis was entered as a potential variable, and each measurement item was entered as an observation variable. Results - Airline's storytelling marketing has a significant impact on the brand image and two emotional and cognitive responses have been shown to influence the brand image. In addition, airline storytelling marketing has a significant impact on brand attitudes and airline storytelling marketing derived from factor analysis has shown two emotional and cognitive responses to brand attitudes. Conclusions - The parts derived based on the research results show that storytelling marketing has a strong influence on the airline's brand image and attitude, and that it is necessary for airlines to have a brand image and attitude. Also, forming a favorable brand image has a significant impact on brand attitudes. We believe that by presenting basic data to the aviation industry in future research on airline storytelling, we will be able to increase understanding and contribution to development of storytelling marketing in aviation.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.152-152
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• 2022

Only employing historical data limits the estimation of the full distribution of probable Tropical Cyclone (TC) risk due to the insufficiency of samples. Addressing this limitation, this study introduces a semi-physical TC rainfall model that produces spatially and temporally resolved TC rainfall data to improve TC risk assessments. The model combines a statistical-based track model based on the Markov renewal process to produce synthetic TC tracks, with a physics-based model that considers the interaction between TC and the atmospheric environment to estimate TC rainfall. The simulated data from the combined model are then fitted to a probability distribution function to compute the spatially heterogeneous risk brought by landfalling TCs. The methodology is employed in South Korea as a case study to be able to implement a country-scale-based vulnerability inspection from damaging TC impacts. Results show that the proposed model can produce TC tracks that do not only follow the spatial distribution of past TCs but also reveal new paths that could be utilized to consider events outside of what has been historically observed. The model is also found to be suitable for properly estimating the total rainfall induced by landfalling TCs across various points of interest within the study area. The simulated TC rainfall data enable us to reliably estimate extreme rainfall from higher return periods that are often overlooked when only the historical data is employed. In addition, the model can properly describe the distribution of rainfall extremes that show a heterogeneous pattern throughout the study area and that vary per return period. Overall, results show that the proposed approach can be a valuable tool in providing sufficient TC rainfall samples that could be an aid in improving TC risk assessment.

• Korean Journal of Cognitive Science
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• v.34 no.3
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• pp.197-226
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• 2023

Generative Text Summarization is one of the Natural Language Processing tasks. It generates a short abbreviated summary while preserving the content of the long text. ROUGE is a widely used lexical-overlap based metric for text summarization models in generative summarization benchmarks. Although it shows very high performance, the studies report that 30% of the generated summary and the text are still inconsistent. This paper proposes a methodology for evaluating the performance of the summary model without using the correct summary. AggreFACT is a human-annotated dataset that classifies the types of errors in neural text summarization models. Among all the test candidates, the two cases, generation summary, and when errors occurred throughout the summary showed the highest correlation results. We observed that the proposed evaluation score showed a high correlation with models finetuned with BART and PEGASUS, which is pretrained with a large-scale Transformer structure.

• The Korean Journal of Franchise Management
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• v.14 no.4
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• pp.35-50
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• 2023

Purpose: This study aims to uncover the mechanism of how initial fees are determined in the restaurant franchise business. Since the initial fees can be considered as a price of utilizing business models and operational knowledge of a certain franchise brand, it is critical to understand the fee decision-making process based on the strategic pricing theories. Therefore, this study investigates the influence of operational value on the determination of initial franchise fees grounded on a value-based pricing strategy. The Operational value is specifically categorized into profitability, growth, and stability of the franchise system. Research design, data, and methodology: The data used were collected through franchise disclosure documents and brand equity index provided by Korea Management Association Consulting. Data from 44 franchise restaurants during 2018 to 2021 are included in the sample. The panel dataset was analyzed by using generalized least squares estimation with R-Studio. Results: Profitability and stability positively influence initial franchise fees. However, growth did not influence initial franchise fees. Conclusions: The results of the study demonstrate that the operational value plays a critical role in determining the franchise fees. Specifically, franchisees recognize how much revenue a franchise system generates for them (i.e., profitability) and how stable the entire system is for operating business (i.e., stability) when they make purchasing decisions for franchise. The findings extend the pricing literature by applying pricing theories in the franchise fee context. Also, the study contributes to franchising and restaurant management literature by providing knowledge of how franchise fees are determined.