• Journal of Global Scholars of Marketing Science
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• v.17 no.4
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• pp.1-22
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• 2007

Customer satisfaction is important in an increasingly competitive and global marketplace. This implies that customer service is a critical factor for many organizations. In service encounter context, customer satisfaction is affected by employees' attitudes and behaviors. Accordingly, service firms have been focusing on selecting high quality of service employees, which resulted the ability to identify and select quality service- or customer- oriented employees to become critical for an organization's success. It was suggested that customer service orientation links to performance and subsequent organizational revenue. Moreover, it was found that service encounter failures were among the major reasons for customers' service switch. Therefore, the selection of customer service oriented employees is a key factor in establishing customer service - a potential source of sustained competitive advantage. However, the measurement of employee service orientation is more confusing than that of definitive answers. The difficulty of measuring service orientation is attributed to the use of broad versus narrow measures of personality. Advocates for the broad perspective prefer using basic personality constructs, such as the Big Five personality traits. On the contrary, the latter prefer a construct-oriented approach of personality research that provides a better measure of job performance because it requires the specification of the relationship of the personality traits with multiple dimensions of job performance. The customer service orientation was defined as "a set of basic individual predispositions and an inclination to provide service, to be courteous and to be helpful in dealing with customers and associates." Similarly, it is a fact that the Big five personality traits are predictors of customer orientation, and employee's self- and supervisor performance. They propose that basic personality traits may be too far removed from focal service behaviors to be able to predict specific service behaviors (customer orientation) and service worker performance. Also, customer orientation is defined as "an employee's tendency or predisposition to meet customer needs in an on-the-job context." This means that people who have job-relevant personality traits such as concern, empathy, and conscientiousness will be more adept at customer service than people who do not possess these traits. However, little attention has been given to the exploration of the service orientation of customer-contact employees who play a key role in creating satisfactory service encounters in the hospitality industry except for Kim, McCahon, & Miller (2003)'s study, especially in family restaurants context. Thus, the purposes of this study are to examine and validate the customer service orientation of customer-contact employees using the instrument developed by Donavan (1999) in Korean family restaurants, because the scale was developed to measure the personality traits related job behaviors. And this study explores the relationships between customer service orientation, job satisfaction, organizational commitment, and self service performance using structural equation modeling (SEM). And this study explores the relationships between customer service orientation, job satisfaction, organizational commitment, and self service performance using structural equation modeling (SEM). For these purposes the author developed several hypotheses as follows: H1: Employee's service orientation is associated with service performance. H2: Employee's service orientation is positively associated with job satisfaction. H3: Employee's service orientation is positively associated with organizational commitment. H4: Service performance is positively associated with job satisfaction. H5: Service performance is positively associated with organizational commitment. H6: Job satisfaction is negatively associated with organizational commitment. The data were collected from 278 employees in 5 deluxe hotels located in Pusan, Korea. The researcher contacted the manager of the restaurants, and managers consented to administer surveys to their employees. The survey was executed during one month period in the October of 2007. The data were analyzed with structural equation modeling with LISREL 8.7 W. The result of the overall model analysis appeared as follows: $X^2$=122.638 (p = 0.00), df=59, GFI=.936, AGFI=.901, NFI=.948, CFI=.971, RMSEA=.0625. Since the result of the overall model analysis demonstrated a good fit, we could further analyze our data. The findings can be summarized as follows: First, the greater the employee service orientation, the greater the service performance. Second, the greater the employee service orientation, the greater the job satisfaction. Third, the greater the employee service orientation, the greater the organizational commitment. Fourth, the greater the service performance, the greater the job satisfaction. Fifth, the greater the service performance, the greater the organizational commitment. Finally, the greater the job satisfaction, the greater the organizational commitment. Seventh, the greater the customer satisfaction, the greater the customer loyalty.

• Journal of the Korean Society of Food Science and Nutrition
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• v.45 no.6
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• pp.894-902
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• 2016

The purpose of this study was to analyze the attributes considered as important by parents in the selection of laver for infants through conjoint analysis techniques. A total of 917 questionnaires were distributed in January 2016, of which 211 were completed (23.0%). Statistical data analyses were performed using SPSS/Win 21.0 for descriptive statistics and conjoint analysis. The conjoint design was applied to evaluate the hypothetical laver for infants. According to the analysis of attributes and levels of laver for infants, the relative importance of each attribute was follows: seasoning (26.55%), flavor (19.33%), texture (18.75%), oil (15.15%), size (10.61%), and certification (9.61%). The results of the conjoint analysis indicate that parents raising infants preferred laver with the characteristics of non-seasoning, general flavor, softness, half-size, organic certification, and perilla oil. The most preferred laver for infants gained a 53.7% potential market share from choice simulation compared with laver being sold. Using utility and relative importance, the laver market for infants was classified into two segments. As a result of market segmentation, parents of cluster 1 preferred the laver model being sold (soy seasoning) while parents of cluster 2 preferred the optimized laver model (non-seasoning).

• Journal of Animal Science and Technology
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• v.46 no.4
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• pp.509-516
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• 2004

This study is to investigate the amount of biased estimates for heritability and genetic correlation according to data structure on marbling scores in Korean cattle. Breeding population with 5 generations were simulated by way of selection for carcass weight, Longissimus muscle area and latent values of marbling scores and random mating. Latent variables of marbling scores were categorized into five by the thresholds of 0, I, 2, and 3 SD(DSI) or seven by the thresholds of -2, -1, 0,1I, 2, and 3 SD(DS2). Variance components and genetic pararneters(Heritabilities and Genetic correlations) were estimated by restricted maximum likelihood on multivariate linear mixed animal models and by Gibbs sampling algorithms on multivariate threshold mixed animal models in DS1 and DS2. Simulation was performed for 10 replicates and averages and empirical standard deviation were calculated. Using REML, heritabilitis of marbling score were under-estimated as 0.315 and 0.462 on DS1 and DS2, respectively, with comparison of the pararneter(0.500). Otherwise, using Gibbs sampling in the multivariate threshold animal models, these estimates did not significantly differ to the parameter. Residual correlations of marbling score to other traits were reduced with comparing the parameters when using REML algorithm with assuming linear and normal distribution. This would be due to loss of information and therefore, reduced variation on marbling score. As concluding, genetic variation of marbling would be well defined if liability concepts were adopted on marbling score and implemented threshold mixed model on genetic parameter estimation in Korean cattle.

• Korean Journal of Remote Sensing
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• v.31 no.6
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• pp.531-548
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• 2015

Atmospheric Motion Vector (AMV) from satellite images have shown Slow Speed Bias (SSB) in comparison with rawinsonde. The causes of SSB are originated from tracking, selection, and height assignment error, which is known to be the leading error. However, recent works have shown that height assignment error cannot be fully explained the cause of SSB. This paper attempts a new approach to examine the possibility of SSB reduction of COMS AMV by using a new target tracking algorithm. Tracking error can be caused by averaging of various wind patterns within a target and changing of cloud shape in searching process over time. To overcome this problem, Gaussian Mixture Model (GMM) has been adopted to extract the coldest cluster as target since the shape of such target is less subject to transformation. Then, an image filtering scheme is applied to weigh more on the selected coldest pixels than the other, which makes it easy to track the target. When AMV derived from our algorithm with sum of squared distance method and current COMS are compared with rawindsonde, our products show noticeable improvement over COMS products in mean wind speed by an increase of $2.7ms^{-1}$ and SSB reduction by 29%. However, the statistics regarding the bias show negative impact for mid/low level with our algorithm, and the number of vectors are reduced by 40% relative to COMS. Therefore, further study is required to improve accuracy for mid/low level winds and increase the number of AMV vectors.

• Journal of Food Hygiene and Safety
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• v.29 no.4
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• pp.299-304
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• 2014

The dose-response models are important for the quantitative microbiological risk assessment (QMRA) because they would enable prediction of infection risk to humans from foodborne pathogens. In this study, we performed a comprehensive literature review and meta-analysis to better quantify this association. The meta-analysis applied a final selection of 193 published papers for total 43 species foodborne disease pathogens (bacteria 26, virus 9, and parasite 8 species) which were identified and classified based on the dose-response models related to QMRA studies from PubMed, ScienceDirect database and internet websites during 1980-2012. The main search keywords used the combination "food", "foodborne disease pathogen", "dose-response model", and "quantitative microbiological risk assessment". The appropriate dose-response models for Campylobacter jejuni, pathogenic E. coli O157:H7 (EHEC / EPEC / ETEC), Listeria monocytogenes, Salmonella spp., Shigella spp., Staphylococcus aureus, Vibrio parahaemolyticus, Vibrio cholera, Rota virus, and Cryptosporidium pavum were beta-poisson (${\alpha}=0.15$, ${\beta}=7.59$, fi = 0.72), beta-poisson (${\alpha}=0.49$, ${\beta}=1.81{\times}10^5$, fi = 0.67) / beta-poisson (${\alpha}=0.22$, ${\beta}=8.70{\times}10^3$, fi = 0.40) / beta-poisson (${\alpha}=0.18$, ${\beta}=8.60{\times}10^7$, fi = 0.60), exponential (r=$1.18{\times}10^{-10}$, fi = 0.14), beta-poisson (${\alpha}=0.11$, ${\beta}=6,097$, fi = 0.09), beta-poisson (${\alpha}=0.21$, ${\beta}=1,120$, fi = 0.15), exponential ($r=7.64{\times}10^{-8}$, fi = 1.00), betapoisson (${\alpha}=0.17$, ${\beta}=1.18{\times}10^5$, fi = 1.00), beta-poisson (${\alpha}=0.25$, ${\beta}=16.2$, fi = 0.57), exponential ($r=1.73{\times}10{-2}$, fi = 1.00), and exponential ($r=1.73{\times}10^{-2}$, fi = 0.17), respectively. Therefore, these results provide the preliminary data necessary for the development of foodborne pathogens QMRA.

• Journal of Bio-Environment Control
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• v.30 no.4
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• pp.419-428
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• 2021

In order to develope a mobile-based greenhouse energy calculation program, firstly, the overall thermal transmittance of 10 types of major covers and 16 types of insulation materials were measured. In addition, to estimate the overall thermal transmittance when the cover and insulation materials were installed in double or triple layers, 24 combinations of double installations and 59 combinations of triple installations were measured using the hotbox. Also, the overall thermal transmittance value for a single material and the thermal resistance value were used to calculate the overall thermal transmittance value at the time of multi-layer installation of covering and insulating materials, and the linear regression equation was derived to correct the error with the measured values. As a result of developing the model for estimating thermal transmittance when installing multiple layers of coverings and insulating materials based on the value of overall thermal transmittance of a single-material, the model evaluation index was 0.90 (good when it is 0.5 or more), indicating that the estimated value was very close to the actual value. In addition, as a result of the on-site test, it was evaluated that the estimated heat saving rate was smaller than the actual value with a relative error of 2%. Based on these results, a mobile-based greenhouse energy calculation program was developed that was implemented as an HTML5 standard web-based mobile web application and was designed to work with various mobile device and PC browsers with N-Screen support. It had functions to provides the overall thermal transmittance(heating load coefficient) for each combination of greenhouse coverings and thermal insulation materials and to evaluate the energy consumption during a specific period of the target greenhouse. It was estimated that an energy-saving greenhouse design would be possible with the optimal selection of coverings and insulation materials according to the region and shape of the greenhouse.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.43-61
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• 2019

Development of technologies in artificial intelligence has been rapidly increasing with the Fourth Industrial Revolution, and researches related to AI have been actively conducted in a variety of fields such as autonomous vehicles, natural language processing, and robotics. These researches have been focused on solving cognitive problems such as learning and problem solving related to human intelligence from the 1950s. The field of artificial intelligence has achieved more technological advance than ever, due to recent interest in technology and research on various algorithms. The knowledge-based system is a sub-domain of artificial intelligence, and it aims to enable artificial intelligence agents to make decisions by using machine-readable and processible knowledge constructed from complex and informal human knowledge and rules in various fields. A knowledge base is used to optimize information collection, organization, and retrieval, and recently it is used with statistical artificial intelligence such as machine learning. Recently, the purpose of the knowledge base is to express, publish, and share knowledge on the web by describing and connecting web resources such as pages and data. These knowledge bases are used for intelligent processing in various fields of artificial intelligence such as question answering system of the smart speaker. However, building a useful knowledge base is a time-consuming task and still requires a lot of effort of the experts. In recent years, many kinds of research and technologies of knowledge based artificial intelligence use DBpedia that is one of the biggest knowledge base aiming to extract structured content from the various information of Wikipedia. DBpedia contains various information extracted from Wikipedia such as a title, categories, and links, but the most useful knowledge is from infobox of Wikipedia that presents a summary of some unifying aspect created by users. These knowledge are created by the mapping rule between infobox structures and DBpedia ontology schema defined in DBpedia Extraction Framework. In this way, DBpedia can expect high reliability in terms of accuracy of knowledge by using the method of generating knowledge from semi-structured infobox data created by users. However, since only about 50% of all wiki pages contain infobox in Korean Wikipedia, DBpedia has limitations in term of knowledge scalability. This paper proposes a method to extract knowledge from text documents according to the ontology schema using machine learning. In order to demonstrate the appropriateness of this method, we explain a knowledge extraction model according to the DBpedia ontology schema by learning Wikipedia infoboxes. Our knowledge extraction model consists of three steps, document classification as ontology classes, proper sentence classification to extract triples, and value selection and transformation into RDF triple structure. The structure of Wikipedia infobox are defined as infobox templates that provide standardized information across related articles, and DBpedia ontology schema can be mapped these infobox templates. Based on these mapping relations, we classify the input document according to infobox categories which means ontology classes. After determining the classification of the input document, we classify the appropriate sentence according to attributes belonging to the classification. Finally, we extract knowledge from sentences that are classified as appropriate, and we convert knowledge into a form of triples. In order to train models, we generated training data set from Wikipedia dump using a method to add BIO tags to sentences, so we trained about 200 classes and about 2,500 relations for extracting knowledge. Furthermore, we evaluated comparative experiments of CRF and Bi-LSTM-CRF for the knowledge extraction process. Through this proposed process, it is possible to utilize structured knowledge by extracting knowledge according to the ontology schema from text documents. In addition, this methodology can significantly reduce the effort of the experts to construct instances according to the ontology schema.

• Journal of Korean Society of Forest Science
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• v.100 no.1
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• pp.52-61
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• 2011

Whereas recent researches have elucidated the positive ecological roles of large wood (LW) in fishbearing channels, LW is also recognized as a negative factor of log-laden debris flows and floods in densely populated areas. However in Republic of Korea, no study has investigated longitudinal variations of LW distribution and dynamic along the stream corridor. Hence to elucidate 1) physical factors controlling longitudinal distribution of LW and 2) their effect on variation in LW load amount, we surveyed the amount of LW with respect to channel morphology in a mountain stream, originated from Mt. Ki-ryong in Inje, Gangwondo. Model selection in the Generalized Linear Model procedure revealed that number of boulder (greater than or equal to 1.0 m in diameter), bankfull channel width and their interaction were the best predictors explaining LW load volume per unit channel segment area (unit LW load). In general, boulders scattered within small mountain streams influence LW retention as flow obstructions. However, in this study, we found that the effect of the boulders vary with the channel width; that is, whereas the unit LW load in the segment with narrow channel width increased continuously with increasing boulder number, it in the segment with wide channel width did not depend on the boulder number. This should be because that, in two channels having different widths, the rates of channel widths reduced by boulders are different although boulder numbers are same. Our findings on LW load varying with physical factors (i.e., interaction of boulder number and channel width) along the stream corridor suggest understanding for longitudinal continuum of hydrogeomorphic and ecologic characteristics in stream environments, and these should be carefully applied into the erosion control works for systematic watershed management and subsequent disaster prevention.

• Journal of the Korean Society of Earth Science Education
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• v.15 no.3
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• pp.335-344
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• 2022

This study was conducted for 4 weeks on the preparation of the science teaching/learning course plan for 109 students in 4 classes of the 2nd year intensive course at B University of Education. Pre-service elementary teachers attended a two-week field training practice after listening to a lecture on how to write a science teaching and learning course plan. Pre-service elementary teachers tried to find out about the selection of materials and the degree of connection between the course plan and the class to prepare the science teaching/learning course plan. The researcher completed the questionnaire by reviewing and deliberation on the questionnaire questions together with 4 pre-service elementary teachers. The questionnaire related to the writing of the science teaching and learning course plan consists of 8 questions. Preferred reference materials when writing the course plan, the level of interest in learning, the success or failure of the science course plan and class, the science preferred model, the evaluation method in unit time, and the science teaching and learning One's own efforts to write the course plan, the contents of this course are the science faculty. It is composed of the preparation of the learning process plan and how helpful it is to the class. The results of this study are as follows. First, it was found that elementary school pre-service elementary teachers preferred teacher guidance the most when drafting science teaching and learning curriculum plans. Second, it is recognized that the development stage is very important in the teaching and learning stage of the science department. Third, Pre-service elementary teachers believe that the science and teaching and learning process plan has a high correlation with the success of the class. Fourth, it was said that the student's level, the teacher's ability, and the appropriate lesson plan had the most influence on the class. Fifth, it was found that pre-service elementary teachers prefer the inquiry learning class model. Sixth, it was found that reports and activity papers were preferred for evaluation in 40-minute classes. Seventh, it was stated that the teaching and learning process plan is highly related to the class, so it will be studied and studied diligently. Eighth, the method of writing a science teaching and learning course plan based on the instructional design principle is interpreted as very beneficial.

• Journal of Korean Society of Forest Science
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• v.111 no.4
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• pp.622-629
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• 2022

The study aim was to derive a stem taper equation for Phyllostachys pubescens, a type of bamboo in South Korea, and to develop a stem volume table. To derive the stem taper equation, three stem taper models (Max & Burkhart, Kozak, and Lee) were used. Since bamboo stalks are hollow because of its woody characteristics, the outer and inner diameters of the tree were calculated, and connecting them enabled estimating the tree curves. The results of the three equations for estimating the outer and inner diameters led to selection of the Kozak model for determining the optimal stem taper because it had the highest fitness index and lowest error and bias. We used the Kozak model to estimate the diameter of Phyllostachys pubescens by stem height, which proved optimal, and drew the stem curve. After checking the residual degree in the stem taper equation, all residuals were distributed around "0", which proved the suitability of the equation. To calculate the stem volume of Phyllostachys pubescens, a rotating cube was created by rotating the stem curve with the outer diameter at 360°, and the volume was calculated by applying Smalian's method. The volume of Phyllostachys pubescens was calculated by deducting the inner diameter calculated volume from the outer diameter calculated volume. The volume of Phyllostachys pubescens was only 20~30% of the volume of Larix kaempferi, which is a general species. However, considering the current trees/ha of Phyllostachys pubescens and the amount of bamboo shoots generated every year, the individual tree volume was predicted to be small, but the volume/ha was not very different or perhaps more. The significance of this study is the stem taper equation and stem volume table for Phyllostachys pubescens developed for the first time in South Korea. The results are expected to be used as basic data for bamboo trading that is in increasing public and industrial demand and carbon absorption estimation.