• Journal of Applied Tourism Food and Beverage Management and Research
• /
• v.16 no.2
• /
• pp.175-199
• /
• 2005

Family Restaurant is a service business of a kind. The role of service operator is to improve a sales of service goods through maximizing the service value with customer satisfaction at the moment of MOT(moment of truth). Family Restaurant come to the great growth on the face of it. In future, it will place emphasis more and more on not hardware but software including service quality. The purpose of this study, therefore, is to research the effect on service quality of the job satisfaction of Family Restaurant's service staff. Data was collected from the employee who are working at Family Restaurant located in Taegu. The empirical research has been done over 50days from 1April, 2004 to 20May, 2004. In conclusion of empirical analysis, 4 hypotheses were significant among 7 hypotheses suggested in this study. The research showed as follows : First, the organic trait among the effect factor of job satisfaction perceived by Family Restaurant service staff showed positive influence on job satisfaction. Second, the personal trait among the effect factor of job satisfaction perceived by Family Restaurant service staff showed positive influence on service quality. Third, the official trait among the effect factor of job satisfaction perceived by Family Restaurant service staff showed negative influence on job satisfaction. Fourth, the organic trait among the effect factor of job satisfaction perceived by Family Restaurant service staff showed positive influence on service quality. Fifth, the personal trait among the effect factor of job satisfaction perceived by Family Restaurant service staff showed negative influence on service quality. Sixth, the organic trait among the effect factor of job satisfaction perceived by Family Restaurant service staff showed negative influence on service quality. Seventh, the job satisfaction of Family Restaurant service staff showed positive influence on service quality. Besides, the critical points of this study are as follows; First, we designated the subject of research to the employee of Family Restaurant only. Second, multi-situations(time, holiday) which can happen as service was offered, wasn't concerned. Third, as service quality was estimated by general service quality, the research in future should subdivide service quality more. I, finally, applied the pervious researches on job satisfaction and service quality in the employee of Family Restaurant. To extend more this research model in future, the variables like customer satisfaction should be added.

• Journal of the Korean Magnetics Society
• /
• v.26 no.4
• /
• pp.124-128
• /
• 2016

We have investigated the electronic structures of intermetallic multilayer (ML) films of [$Co(2{\AA})/Pd(x{\AA})$] (x: the thickness of the Pd sublayer; x = $1{\AA}$, $3{\AA}$, $5{\AA}$, $7{\AA}$, $9{\AA}$) by employing soft X-ray absorption spectroscopy (XAS) and soft X-ray magnetic circular dichroism (XMCD). Both Co 2p XAS and XMCD spectra are found to be similar to one another, as well as to those of Co metal, providing evidence for the metallic bonding of Co ions in [Co/Pd] ML films. By analyzing the measured Co 2p XMCD spectra, we have determined the orbital magnetic moments and the spin magnetic moments of Co ions in [$Co(2{\AA})/Pd(x{\AA})$] ML films. Based on this analysis, we have found that the orbital magnetic moments are enhanced greatly when x increases from $1{\AA}$ to $3{\AA}$, and then do not change much for $x{\geq}3{\AA}$. This finding suggests that the interface spin-orbit coupling plays an important role in determining the perpendicular magnetic anisotropy in [Co/Pd] ML films.

• Progress in Medical Physics
• /
• v.22 no.2
• /
• pp.72-78
• /
• 2011

The aim of this study is to evaluate the patient's setup errors in TomoTherapy (Hi-Art II, TomoTherapy, USA) Bodyfix system (Medical Intelligence, Ele-kta, Schwabmuchen, Germany) pressure in the vacuum compression, depending on and were evaluated. Bodyfix immobilization system and vacuum pressure was compression applied to the patients who received Tomotherapy thoracic and abdominal area, 21 patients were selected and TomoTehpay treatment total 477 of MVCT images were obtained. The translational (medial-lateral: ML, anterior-posterior: AP, superior-inferior: SI directions) and rolling were recorded and analyzed statistically. Using Pearson's product-moment coefficient and One-way ANOVA, the degree of correlation depending on the different vacuum pressure levels were statistically analyzed for setup errors from five groups (p<0.05). The largest average and standard deviation of systematic errors were 6.00, 5.95 mm in the AP and SI directions, respectively. The largest average of random errors were 4.72 mm in the SI directions. The correlation coefficients were 0.485, 0.244, and 0.637 for the ML-Roll, AP-Vector, and SI-Vector, respectively. SI-Vector direction showed the best relationship. In the results of the different degree of vacuum pressure in five groups (Pressure range: 30~70 mbar), the setup errors between the ML, SI in both directions and Roll p=0.00 (p<0.05) were shown significant differences. The average errors of SI direction in the vacuum pressure of 40 mbar and 70 mbar group were 4.78 mm and -0.74 mm, respectively. In this study, the correlation between the vacuum pressure and the setup-errors were statistically analyzed. The fact that setup-errors in SI direction is dependent in vacuum pressure considerly setup-errors and movement of interal organs was identified. Finally, setup-errors, and it, based on the movement of internal organs in Bodyfix system we should apply more than 50 mbar vacuum pressure. Based on the results of this study, it is suggested that accuracy of the vacuum pressure and the quantitative analysis of movement of internal organs and the tumor should be studied.

• Culinary science and hospitality research
• /
• v.22 no.7
• /
• pp.267-280
• /
• 2016

Customer Experience Management (CEM) appeared as a complementary solution to overcome CRM limitations. CEM enhances profitability through building long-term relations with customers by understanding their experiences. This study aims at investigating the impact of customer experience quality on the willingness to pay more through customer satisfaction in the hotel businesses. The survey for this study was carried out on customers who had domestic hotel experience s within the last 6 months. Out of the 306 questionnaires retrieved, 225 valid responses were used for the empirical analysis that utilizied the statistical package programs SPSS 18.0 and AMOS 18.0. The research findings may be summarized as follows. First, as an outcome of the research hypothesis that each component of customer experience management would influence satisfaction, 'the peace of mind' & 'the moment of truth' were shown to have a significantly positive (+) impact on it. On the other hand, 'the product experience' was shown not to significantly influence it in a positive (+) way. Second, as an outcome of the research hypothesis that satisfaction would influence willingness to pay more. From the findings of the study, theoretical implications are as follows. It can be predicted that customer experience management will likely make customers more profitable because customers are willing to pay more with a sense of loyalty built through satisfaction of the hotel industry. In the practical implications, the dimension of experience quality examined by the study can be used as an index to measure and manage customer experience in the hotel industry.

• Proceedings of the Korean Society of Crop Science Conference
• /
• 2017.06a
• /
• pp.95-95
• /
• 2017

Lodging is a serious issue in rice production, because it drastically decreases the biomass production and grain yield. Since the Green Revolution, the lodging resistance has been increased by lowering the moment of above-ground parts due to the short culm by the semi-dwarf gene sd1. However, it has been pointed out that sd1 alone has suppressive effects for biomass production and yield. To increase rice yield, the long-culm and large panicle type varieties with a superior lodging resistance need to be developed. To improve the lodging resistance and yield of these type varieties, it would be effective to identify novel alleles for these traits underlying natural variations in rice and to pyramid these alleles to a single rice variety. In order to perform this strategy, we have developed new rice lines derived from crosses among varieties with superior alleles. At first, TULT-gh-5-5 was selected from a cross between strong culm and high biomass variety Leaf Star and high-yielding variety Takanari, and TUAT-32HB was selected from a cross between high-yielding variety Akenohoshi and Takanari. Then, we developed the super thick-culm and super grain-bearing line, LTAT-29 derived from a cross between TULT-gh-5-5 and TUAT-32HB. In the current study, to identify the QTLs and genes relating to the strong culm and the high yield of LTAT-29, we performed QTL analysis using SNPs markers with $F_2$ population derived from a cross between LTAT-29 and Takanari. LTAT-29 has never lodged throughout the growth period despite it had long culms and heavy panicles. LTAT-29 had a larger outer diameter of the culm and twice the size of the section modulus than Takanari. As a result, the bending moment at breaking of LTAT-29 was significantly larger than that of Takanari. Brown rice yield of LTAT-29 was $9.2t\;ha^{-1}$ about 10% higher than that of Takanari due to the larger number of spikelets per panicle. LTAT-29 had a greater number of secondary branches per panicle. In the $F_2$ population between LTAT-29 and Takanari, we found continuous frequency distributions in the section modulus and the spikelet number per panicle. Two QTLs increased the section modulus by the alleles of LTAT-29 were detected on Chr.1L and Chr.2L. One QTL increased the spikelet number per panicle of Takanari by the allele of LTAT-29 was detected on Chr.1L, and two QTLs increased the number of secondary branches per panicle by the alleles of LTAT-29 were detected on Chr.1L and Chr.4L. It was found that the alleles of these QTLs were the japonica type originated from Leaf Star or Akenohoshi. The novel QTLs for the traits related to super thick-culm and super grain-bearing and their combinations could be utilized for improving the lodging resistance and yield in rice varieties.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.1 no.1
• /
• pp.33-42
• /
• 1981

Current standard code for R.C. design consists of two conventional design parts, so called WSD and USD, which are based on ACI 318-63 and 318-71 code provisions. The safety factors of our WSD and USD design criteria which are taken primarily from ACI 318-63 code are considered to be not appropriate compared to out country's design and construction practices. Furthermore, even the ACI safety factors are not determined from probabilistic study but merely from experiences and practices. This study investigates the safety level of R.C. flexural members designed by the current WSD safety provisions based on Second Moment Reliability theory, and proposes a rational but efficient way of determining the nominal safety factors and the associated flexural allowable stresses of steel bars and concretes in order to provide a consistent level of target reliability. Cornell's Mean First-Order Second Moment Method formulae by a log normal transformation of resistance and load output variables are adopted as the reliability analysis method for this study. The compressive allowable stress formulae are derived by a unique approach in which the balanced steel ratios of the resulting design are chosen to be the corresponding under-reinforced sections designed by strength design method with an optimum reinforcing ratio. The target reliability index for the safety provisions are considered to be ${\beta}=4$ that is well suited for our level of construction and design practices. From a series of numerical applications to investigate the safety and reliability of R.C. flexural members designed by current WSD code, it has been found that the design based on WSD provision results in uneconomical design because of unusual and inconsistent reliability. A rational set of reliability based safety factors and allowable stress of steel bars and concrete for flexural members is proposed by providing the appropriate target reliability ${\beta}=4$.

• Geotechnical Engineering
• /
• v.2 no.1
• /
• pp.27-44
• /
• 1986

The measured soil data are analyzed to the descriptive statistics and classified into the four models of uncorrelated-normal (UNNO), uncorrelated-nonnormal (VNNN), correlatedonnormal(CONN), and correlated-nonnormal(CONN) . This paper presents the comparisons of reliability index and check points using the advanced first-order second-moment method with respect to the four models as well as BASIC Program. A sin91e-mode Performance function is consisted of the basic design variables of bearing capacity and settlements on shallow foundations and input the above analyzed soil informations. The main conclusions obtained in this study are summarized as follows: 1. In the bearing capacity mode, cohesion and bearing-capacity factors by C-U test are accepted for normal and lognormal distribution, respectively, and negatively low correlated to each other. Since the reliability index of the CONN model is the lowest one of the four model, which could be recommended a reliability.based design, whereas the other model might overestimate the geotechnical conditions. 2. In the case of settlements mode, the virgin compression ratio and preccnsolidation pressure are fitted for normal and lognormal distribution, respectively. Constraining settlements to the lower ones computed by deterministic method, The CONN model is the lowest reliability of the four models.

• Journal of Climate Change Research
• /
• v.2 no.4
• /
• pp.297-307
• /
• 2011

This study investigates relation of food safety incidents with climate. Therefore food safety incidents and climate data during 1999 to 2009 have been analyzed. In situ observations of monthly mean temperature, maximum temperature, minimum temperature, precipitation, and relative humidity in 60 observation stations of Korean Meteorological Administration (KMA) have been used in this study. Food safety incidents data have been constructed by searching media reports following Park's method (2009) during the same period. According to the Park's method, 729 events were collected. To analyze its relations, food safety incidents data have been classified into chemical, biological, and physical hazards. Pearson product-moment correlation coefficients have been applied to analyze the relations. The correlation of food safety incidents has negative one with precipitation (-0.48), and positive one with minimum temperature(0.45). Precipitation has been correlated with biological and physical hazards more than chemical hazard. Temperatures (mean temperature, maximum temperature, and minimum temperature) have been correlated closely with chemical hazard than others. Food safety incidents data has been interblended with human behavior factor through decision-making processes in food manufacturing, processing, and consumption phases of "farm-totable" food processing. Act in the preventing damage will be obvious if the hazard were apparent. Therefore abnormal condition could be more dangerous than that of apparent extreme events because apparent events or extreme events become one of alarm over hazards. Therefore, human behavior should be considered as one of the important factors for analysis of food safety incidents. The result of this study can be used as a better case study for food safety researches related to climate change.

• Management & Information Systems Review
• /
• v.22
• /
• pp.137-165
• /
• 2007

It seems high time to increase productivity by adopting e-business to overcome challenges posed by both external factors including the appreciation of Korean won, oil hikes and fierce global competition and domestic issues represented by disparities between large corporations and small and medium enterprises (SMEs), Seoul metropolitan and local cities, and export and domestic demand all of which weaken future growth engines in the Korean economy. The demands of the globalization era are for innovative changes in businessprocess and industrial structure aiming for creating new values. To this end, e-business is expected to play a core role in the sophistication of the Korean economy through new values and innovation. In order to examine business performance in e-business-adopting industries, this study analyzed the home shopping industry by closely looking into the financial ratios including the ratio of net profit to sales, the ratio of operation income to sales, the ratio of gross cost to sales cost, the ratio of gross cost to selling, general and administrative (SG&A) expense, and return of investment (ROI). This study, for best outcome, referred to corporate financial statements as a main resource to calculate financial ratios by utilizing Data Analysis, Retrieval and Transfer System (DART) of the Financial Supervisory Service, one of the Korea's financial supervisory authorities. First of all, the result of the trend analysis on the ratio of net profit to sales is as following. CJ Home Shopping has registered a remarkable increase in its ratio of net profit rate to sales since 2002 while its competitors find it hard to catch up with CJ's stunning performances. This is partly due to the efficient management compared to CJ's value of capital. Such significance, if the current trend continues, will make the front-runner assume the largest market share. On the other hand, GS Home Shopping, despite its best organized system and largest value of capital among others, lacks efficiency in management. Second of all, the result of the trend analysis on the ratio of operation income to sales is as following. Both CJ Home Shopping and GS Home Shopping have, until 2004, recorded similar growth trend. However, while CJ Home Shopping's operating income continued to increase in 2005, GS Home Shopping observed its operating income declining which resulted in the increasing income gap with CJ Home Shopping. While CJ Home Shopping with the largest market share in home shopping industryis engaged in aggressive marketing, GS Home Shopping due to its stability-driven management strategies falls behind CJ again in the ratio of operation income to sales in spite of its favorable management environment including its large capital. Companies in the Group B were established in the same year of 2001. NS Home Shopping was the first in the Group B to shift its loss to profit. Woori Home Shopping has continued to post operating loss for three consecutive years and finally was sold to Lotte Group in 2007, but since then, has registered a continuing increase in net income on sales. Third of all, the result of the trend analysis on the ratio of gross cost to sales cost is as following. Since home shopping falls into sales business, its cost of sales is much lower than that of other types of business such as manufacturing industry. Since 2002 in gross costs including cost of sales, SG&A expense, and non-operating expense, cost of sales turned out to have remarkably decreased. Group B has also posted a notable decline in the same sector since 2002. Fourth of all, the result of the trend analysis on the ratio of gross cost to SG&A expense is as following. Due to its unique characteristics, the home shopping industry usually posts ahigh ratio of SG&A expense. However, more than 80% of SG&A expense means the result of lax management and at the same time, a sharp lower net income on sales than other industries. Last but not least, the result of the trend analysis on ROI is as following. As for CJ Home Shopping, the curve of ROI looks similar to that of its investment on fixed assets. As it turned out, the company's ratio of fixed assets to operating income skyrocketed in 2004 and 2005. As far as GS Home Shopping is concerned, its fixed assets are not as much as that of CJ Home Shopping. Consequently, competition in the home shopping industry, at the moment, is among CJ, GS, Hyundai, NS and Woori Home Shoppings, and all of them need to more thoroughly manage their costs. In order for the late-comers of Group B and other home shopping companies to advance further, the current lax management should be reformed particularly on their SG&A expense sector. Provided that the total sales volume in the Internet shopping sector is projected to grow over 20 trillion won by the year 2010, it is concluded that all the participants in the home shopping industry should put strategies on efficient management on costs and expenses as their top priority rather than increase revenues, if they hope to grow even further after 2007.

• Journal of Intelligence and Information Systems
• /
• v.24 no.4
• /
• pp.1-32
• /
• 2018

In addition to stakeholders including managers, employees, creditors, and investors of bankrupt companies, corporate defaults have a ripple effect on the local and national economy. Before the Asian financial crisis, the Korean government only analyzed SMEs and tried to improve the forecasting power of a default prediction model, rather than developing various corporate default models. As a result, even large corporations called 'chaebol enterprises' become bankrupt. Even after that, the analysis of past corporate defaults has been focused on specific variables, and when the government restructured immediately after the global financial crisis, they only focused on certain main variables such as 'debt ratio'. A multifaceted study of corporate default prediction models is essential to ensure diverse interests, to avoid situations like the 'Lehman Brothers Case' of the global financial crisis, to avoid total collapse in a single moment. The key variables used in corporate defaults vary over time. This is confirmed by Beaver (1967, 1968) and Altman's (1968) analysis that Deakins'(1972) study shows that the major factors affecting corporate failure have changed. In Grice's (2001) study, the importance of predictive variables was also found through Zmijewski's (1984) and Ohlson's (1980) models. However, the studies that have been carried out in the past use static models. Most of them do not consider the changes that occur in the course of time. Therefore, in order to construct consistent prediction models, it is necessary to compensate the time-dependent bias by means of a time series analysis algorithm reflecting dynamic change. Based on the global financial crisis, which has had a significant impact on Korea, this study is conducted using 10 years of annual corporate data from 2000 to 2009. Data are divided into training data, validation data, and test data respectively, and are divided into 7, 2, and 1 years respectively. In order to construct a consistent bankruptcy model in the flow of time change, we first train a time series deep learning algorithm model using the data before the financial crisis (2000~2006). The parameter tuning of the existing model and the deep learning time series algorithm is conducted with validation data including the financial crisis period (2007~2008). As a result, we construct a model that shows similar pattern to the results of the learning data and shows excellent prediction power. After that, each bankruptcy prediction model is restructured by integrating the learning data and validation data again (2000 ~ 2008), applying the optimal parameters as in the previous validation. Finally, each corporate default prediction model is evaluated and compared using test data (2009) based on the trained models over nine years. Then, the usefulness of the corporate default prediction model based on the deep learning time series algorithm is proved. In addition, by adding the Lasso regression analysis to the existing methods (multiple discriminant analysis, logit model) which select the variables, it is proved that the deep learning time series algorithm model based on the three bundles of variables is useful for robust corporate default prediction. The definition of bankruptcy used is the same as that of Lee (2015). Independent variables include financial information such as financial ratios used in previous studies. Multivariate discriminant analysis, logit model, and Lasso regression model are used to select the optimal variable group. The influence of the Multivariate discriminant analysis model proposed by Altman (1968), the Logit model proposed by Ohlson (1980), the non-time series machine learning algorithms, and the deep learning time series algorithms are compared. In the case of corporate data, there are limitations of 'nonlinear variables', 'multi-collinearity' of variables, and 'lack of data'. While the logit model is nonlinear, the Lasso regression model solves the multi-collinearity problem, and the deep learning time series algorithm using the variable data generation method complements the lack of data. Big Data Technology, a leading technology in the future, is moving from simple human analysis, to automated AI analysis, and finally towards future intertwined AI applications. Although the study of the corporate default prediction model using the time series algorithm is still in its early stages, deep learning algorithm is much faster than regression analysis at corporate default prediction modeling. Also, it is more effective on prediction power. Through the Fourth Industrial Revolution, the current government and other overseas governments are working hard to integrate the system in everyday life of their nation and society. Yet the field of deep learning time series research for the financial industry is still insufficient. This is an initial study on deep learning time series algorithm analysis of corporate defaults. Therefore it is hoped that it will be used as a comparative analysis data for non-specialists who start a study combining financial data and deep learning time series algorithm.