• Asia pacific journal of information systems
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• v.22 no.2
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• pp.21-38
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• 2012

Until recently, successful implementation of ERP systems has been a popular topic among ERP researchers, who have attempted to identify its various contributing factors. None of these efforts, however, explicitly recognize the need to identify disparities that can exist between organizational information requirements and ERP systems. Since ERP systems are in fact "packages" -that is, software programs developed by independent software vendors for sale to organizations that use them-they are designed to meet the general needs of numerous organizations, rather than the unique needs of a particular organization, as is the case with custom-developed software. By adopting standard packages, organizations can substantially reduce many of the potential implementation risks commonly associated with custom-developed software. However, it is also true that the nature of the package itself could be a risk factor as the features and functions of the ERP systems may not completely comply with a particular organization's informational requirements. In this study, based on the organizational memory mismatch perspective that was derived from organizational memory theory and cognitive dissonance theory, we define the nature of disparities, which we call "mismatches," and propose that the mismatch between organizational information requirements and ERP systems is one of the primary determinants in the successful implementation of ERP systems. Furthermore, we suggest that customization efforts as a coping strategy for mismatches can play a significant role in increasing the possibilities of success. In order to examine the contention we propose in this study, we employed a survey-based field study of ERP project team members, resulting in a total of 77 responses. The results of this study show that, as anticipated from the organizational memory mismatch perspective, the mismatch between organizational information requirements and ERP systems makes a significantly negative impact on the implementation success of ERP systems. This finding confirms our hypothesis that the more mismatch there is, the more difficult successful ERP implementation is, and thus requires more attention to be drawn to mismatch as a major failure source in ERP implementation. This study also found that as a coping strategy on mismatch, the effects of customization are significant. In other words, utilizing the appropriate customization method could lead to the implementation success of ERP systems. This is somewhat interesting because it runs counter to the argument of some literature and ERP vendors that minimized customization (or even the lack thereof) is required for successful ERP implementation. In many ERP projects, there is a tendency among ERP developers to adopt default ERP functions without any customization, adhering to the slogan of "the introduction of best practices." However, this study asserts that we cannot expect successful implementation if we don't attempt to customize ERP systems when mismatches exist. For a more detailed analysis, we identified three types of mismatches-Non-ERP, Non-Procedure, and Hybrid. Among these, only Non-ERP mismatches (a situation in which ERP systems cannot support the existing information needs that are currently fulfilled) were found to have a direct influence on the implementation of ERP systems. Neither Non-Procedure nor Hybrid mismatches were found to have significant impact in the ERP context. These findings provide meaningful insights since they could serve as the basis for discussing how the ERP implementation process should be defined and what activities should be included in the implementation process. They show that ERP developers may not want to include organizational (or business processes) changes in the implementation process, suggesting that doing so could lead to failed implementation. And in fact, this suggestion eventually turned out to be true when we found that the application of process customization led to higher possibilities of failure. From these discussions, we are convinced that Non-ERP is the only type of mismatch we need to focus on during the implementation process, implying that organizational changes must be made before, rather than during, the implementation process. Finally, this study found that among the various customization approaches, bolt-on development methods in particular seemed to have significantly positive effects. Interestingly again, this finding is not in the same line of thought as that of the vendors in the ERP industry. The vendors' recommendations are to apply as many best practices as possible, thereby resulting in the minimization of customization and utilization of bolt-on development methods. They particularly advise against changing the source code and rather recommend employing, when necessary, the method of programming additional software code using the computer language of the vendor. As previously stated, however, our study found active customization, especially bolt-on development methods, to have positive effects on ERP, and found source code changes in particular to have the most significant effects. Moreover, our study found programming additional software to be ineffective, suggesting there is much difference between ERP developers and vendors in viewpoints and strategies toward ERP customization. In summary, mismatches are inherent in the ERP implementation context and play an important role in determining its success. Considering the significance of mismatches, this study proposes a new model for successful ERP implementation, developed from the organizational memory mismatch perspective, and provides many insights by empirically confirming the model's usefulness.

• Horticultural Science & Technology
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• v.29 no.6
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• pp.633-640
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• 2011

Brassica rapa is an A genome model species for Brassica crop genetics, genomics, and breeding. With the completion of sequencing the B. rapa genome, functional analysis of the genome is forthcoming issue. The expressed sequence tags are fundamental resources supporting annotation and functional analysis of the genome including identification of tissue-specific genes and promoters. As of July 2011, 147,217 ESTs from 39 cDNA libraries of B. rapa are reported in the public database. However, little information can be retrieved from the sequences due to lack of organized databases. To leverage the sequence information and to maximize the use of publicly-available EST collections, the Brassica rapa tissue-specific EST database (BrTED) is developed. BrTED includes sequence information of 23,962 unigenes assembled by StackPack program. The unigene set is used as a query unit for various analyses such as BLAST against TAIR gene model, functional annotation using MIPS and UniProt, gene ontology analysis, and prediction of tissue-specific unigene sets based on statistics test. The database is composed of two main units, EST sequence processing and information retrieving unit and tissue-specific expression profile analysis unit. Information and data in both units are tightly inter-connected to each other using a web based browsing system. RT-PCR evaluation of 29 selected unigene sets successfully amplified amplicons from the target tissues of B. rapa. BrTED provided here allows the user to identify and analyze the expression of genes of interest and aid efforts to interpret the B. rapa genome through functional genomics. In addition, it can be used as a public resource in providing reference information to study the genus Brassica and other closely related crop crucifer plants.

• Journal of Distribution Science
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• v.10 no.1
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• pp.43-52
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• 2012

With the slowdown in environmental issues and the change of environmental consciousness, ecotourism is being discussed in various social fields. Ecotourism is being popularized for environmental protection, and now it is becoming a mainstream product from one of mass tourism. Ecotourism's emphasis on sustainable development in the tourism destination's society, economy, and environment, through ecotourism study and education, enable people to understand the core value of the ecological environment. 2011 was nominated as "the Year of World Forest" by the UN. In the recent years, forests are becoming increasingly important with their own values and functions in environment, economy, society, and culture. In particular, the global environmental issues caused by climate change are becoming an international agenda. Forests are the only effective solution for the carbon dioxide that causes global warming. Moreover, forests constitute a major part of ecotourism, and are now most used by ecotourists. For example, Korea, wherein 60% of the land is forest, attracts ecotourists. With the increasing interests in environment, the number of tourists visiting the ecosystem forest, which is highly valued for its conservation, is increasing significantly every year and is receiving considerable attention from the government. However, poor facilities in the forest ecotourism sites and improper market strategies are the reasons for the poor running of these sites. Furthermore, tourists' environmental awareness affects ecology environmental pollution or the optimization of forest ecotourism. In order to verify the relationships among tourist attractiveness, environmental consciousness, charm degrees of the attractions, and attitudes after tours, we established some scales based on existing research achievement. Then, using these scales, the researcher completed the questionnaire survey. From December 20, 2010 to February 20, 2011, after conducting surveys for 12 weeks, we finally obtained 582 valid questionnaires, from a total of 700 questionnaires, that could be used in statistical analysis. First, for the method of research and analysis, the researcher initially applied the Cronbach's (Alpha) for verifying the reliability, and subsequently applied the Exploratory factor analysis for verifying the validity. Second, in order to analyze the demographics, the researcher makes use of the Frequency analysis for the AMOS, measurement model, structural equation model computing, and also utilizes construct validity, convergent validity, discriminant validity, and nomological validity. Third, for the analysis of the ecotourists' environmental consciousness, impacts on tourist attractiveness, charm degrees of the attractions, and attitudes after the tour, the researcher uses AMOS 19, with the path analysis and equation of structure. After the research, researchers found that high awareness of natural protection lead to high tourist motivation and satisfaction and more positive attitude after the tour. Moreover, this research shows the psychological and behavioral reactions of the ecotourists to the ecotourist development. Accordingly, environmental consciousness does not affect the tourist attractiveness that has been interpreted as significant. Furthermore, people should focus on the change of natural protection consciousness and psychological reaction of ecotourists while ensuring the sustainable development of ecotourists and developing some ecotourist programs.

• Journal of Distribution Science
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• v.9 no.2
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• pp.131-140
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• 2011

On 1 July 2000, as the over-65 year-old population numbered 3,371,000 and accounted for over 7.1% of Korea's total population, an aging society was revealed. The over-65 percentage climbed to 11.0% by late 2010. A truly aged society is expected soon, by 2019. This aging society requires marketing research concerning the consumer behaviour and well-being of the elderly, because the 'silver generation' is emerging as a large part of the consumer market. The purpose of this study is to empirically analyse one effect among several satisfaction factors in the consuming cycle of various health functional products on consumer's well-being and the effect of product knowledge on the relationship between product satisfaction and well-being. To achieve this purpose, we established a research model after reviewing previous studies on product satisfaction, product knowledge, and consumer's well-being. The following hypotheses were developed from the research model. Hypothesis 1: When elderly consumers' satisfaction with health functional products increases, their well-being will increase. Hypothesis 2: The effect of their satisfaction with health functional products on their well-being will be strengthened according to the level of their knowledge of the products. Those hypotheses were tested by multiple and moderated regressions to the empirical data through a questionnaire survey. As a result, Hypothesis 1 was totally adopted, and Hypothesis 2 was only partially adopted. The study has many practical implications for well-being marketing. First, in order to heighten the elderly consumer's well-being, the level of his or her satisfaction with the health functional products has to be raised in every stage: during the acquisition, preparation, use, maintenance, and disposition of the consumption cycle. Moreover, promoting positive emotional experiences while diminishing negative ones requires effort because a consumer's well-being is made up of various needs. Second, the marketing of health functional products should be invigorated in order to raise the level of elderly consumers' knowledge of them. In other words, it is important to give them an expertise in the health functional products through different channels. A statistical analysis showed, however, that their knowledge has a decisive effect on only two satisfaction stages, preparation and maintenance. Nevertheless, this merely confirmed the intuitive assumption that the knowledge of health functional products is most relevant to their preparation and maintenance. In conclusion, this study is timely because few empirical studies exist on the relationships between silver consumer behaviour and well-being marketing. It contributes to our understanding of this subject by revealing the causality between the silver consumer's satisfaction and his or her well-being in the consumption cycle and by discovering the moderating influence of knowledge in that process.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.241-254
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• 2011

Financial time-series forecasting is one of the most important issues because it is essential for the risk management of financial institutions. Therefore, researchers have tried to forecast financial time-series using various data mining techniques such as regression, artificial neural networks, decision trees, k-nearest neighbor etc. Recently, support vector machines (SVMs) are popularly applied to this research area because they have advantages that they don't require huge training data and have low possibility of overfitting. However, a user must determine several design factors by heuristics in order to use SVM. For example, the selection of appropriate kernel function and its parameters and proper feature subset selection are major design factors of SVM. Other than these factors, the proper selection of instance subset may also improve the forecasting performance of SVM by eliminating irrelevant and distorting training instances. Nonetheless, there have been few studies that have applied instance selection to SVM, especially in the domain of stock market prediction. Instance selection tries to choose proper instance subsets from original training data. It may be considered as a method of knowledge refinement and it maintains the instance-base. This study proposes the novel instance selection algorithm for SVMs. The proposed technique in this study uses genetic algorithm (GA) to optimize instance selection process with parameter optimization simultaneously. We call the model as ISVM (SVM with Instance selection) in this study. Experiments on stock market data are implemented using ISVM. In this study, the GA searches for optimal or near-optimal values of kernel parameters and relevant instances for SVMs. This study needs two sets of parameters in chromosomes in GA setting : The codes for kernel parameters and for instance selection. For the controlling parameters of the GA search, the population size is set at 50 organisms and the value of the crossover rate is set at 0.7 while the mutation rate is 0.1. As the stopping condition, 50 generations are permitted. The application data used in this study consists of technical indicators and the direction of change in the daily Korea stock price index (KOSPI). The total number of samples is 2218 trading days. We separate the whole data into three subsets as training, test, hold-out data set. The number of data in each subset is 1056, 581, 581 respectively. This study compares ISVM to several comparative models including logistic regression (logit), backpropagation neural networks (ANN), nearest neighbor (1-NN), conventional SVM (SVM) and SVM with the optimized parameters (PSVM). In especial, PSVM uses optimized kernel parameters by the genetic algorithm. The experimental results show that ISVM outperforms 1-NN by 15.32%, ANN by 6.89%, Logit and SVM by 5.34%, and PSVM by 4.82% for the holdout data. For ISVM, only 556 data from 1056 original training data are used to produce the result. In addition, the two-sample test for proportions is used to examine whether ISVM significantly outperforms other comparative models. The results indicate that ISVM outperforms ANN and 1-NN at the 1% statistical significance level. In addition, ISVM performs better than Logit, SVM and PSVM at the 5% statistical significance level.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.21-44
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• 2018

In recent years, the rapid development of internet technology and the popularization of smart devices have resulted in massive amounts of text data. Those text data were produced and distributed through various media platforms such as World Wide Web, Internet news feeds, microblog, and social media. However, this enormous amount of easily obtained information is lack of organization. Therefore, this problem has raised the interest of many researchers in order to manage this huge amount of information. Further, this problem also required professionals that are capable of classifying relevant information and hence text classification is introduced. Text classification is a challenging task in modern data analysis, which it needs to assign a text document into one or more predefined categories or classes. In text classification field, there are different kinds of techniques available such as K-Nearest Neighbor, Naïve Bayes Algorithm, Support Vector Machine, Decision Tree, and Artificial Neural Network. However, while dealing with huge amount of text data, model performance and accuracy becomes a challenge. According to the type of words used in the corpus and type of features created for classification, the performance of a text classification model can be varied. Most of the attempts are been made based on proposing a new algorithm or modifying an existing algorithm. This kind of research can be said already reached their certain limitations for further improvements. In this study, aside from proposing a new algorithm or modifying the algorithm, we focus on searching a way to modify the use of data. It is widely known that classifier performance is influenced by the quality of training data upon which this classifier is built. The real world datasets in most of the time contain noise, or in other words noisy data, these can actually affect the decision made by the classifiers built from these data. In this study, we consider that the data from different domains, which is heterogeneous data might have the characteristics of noise which can be utilized in the classification process. In order to build the classifier, machine learning algorithm is performed based on the assumption that the characteristics of training data and target data are the same or very similar to each other. However, in the case of unstructured data such as text, the features are determined according to the vocabularies included in the document. If the viewpoints of the learning data and target data are different, the features may be appearing different between these two data. In this study, we attempt to improve the classification accuracy by strengthening the robustness of the document classifier through artificially injecting the noise into the process of constructing the document classifier. With data coming from various kind of sources, these data are likely formatted differently. These cause difficulties for traditional machine learning algorithms because they are not developed to recognize different type of data representation at one time and to put them together in same generalization. Therefore, in order to utilize heterogeneous data in the learning process of document classifier, we apply semi-supervised learning in our study. However, unlabeled data might have the possibility to degrade the performance of the document classifier. Therefore, we further proposed a method called Rule Selection-Based Ensemble Semi-Supervised Learning Algorithm (RSESLA) to select only the documents that contributing to the accuracy improvement of the classifier. RSESLA creates multiple views by manipulating the features using different types of classification models and different types of heterogeneous data. The most confident classification rules will be selected and applied for the final decision making. In this paper, three different types of real-world data sources were used, which are news, twitter and blogs.

• The Journal of Korean Society for Radiation Therapy
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• v.27 no.1
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• pp.73-78
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• 2015

Purpose : Under the assumption of change to the amplitude based sorting, the study will use four dimensional computed tomography imaging (4DCT) arrayed using the phase based sorting to analyze the respiratory phase difference. Materials and Methods : The study analyzed the 4DCT (4-dimensional computed tomography) images of 10 liver cancer patients that were treated with respiratory gated radiotherapy from 2015 February to March. Using RPM respiratory gating (RPM 1.7.5, Varian, USA) equipment, imaging according to respiratory cycle of phase based sorting was acquired and using a treatment planning system (Pinnacle 9.2, Philips, USA) the acquired imaging according to respiratory cycle was used to measure the abdominal movement value by respiratory cycle. The measuring point was the point where the center point of the Marker Block and the body surface met in the 50% phase image and here the coordinate values Lateral, Vertical, Longitudinal (X, Y, Z) were set as reference points, and on the X, Z plane identical to the reference point, using the identical method the Y axis coordinate value of each 0%, 30%, 40%, 50%, 60%, 80% phase images were acquired to quantitatively measure the variation of distance to the Y axis. The abdominal movement value according to respiration was applied to the theoretical model that the value decreases linearly from maximum inhalation to maximum exhalation to divide the variation of my value to predict as amplitude value by respiratory cycle and conversely the variation in amplitude was recalculated with the phase variation deviation value to analyze. Results : The deviation value between expected value and actual location was the largest in the 30% phase with 0.24 cm, and standard deviation was also the largest in 30% phase with 0.13 cm. The effective value of the deviation value derived from the average of the deviation squared value of each patient appeared as minimum 0.7 cm, maximum 0.18 cm, average 0.12 cm, and standard deviation 0.4 cm. Also by dividing the actual movement distance value with the peak expiration value then converting it into %Phase, the deviation value with actual phase 16.5% in 30% phase, 10.0% and 40% phase, 10.0% and 60% phase, 15.4% and 80% phase, and overall average about 13%, and arraying based on amplitude, phase shift occurred and further it was from peak expiration the chance of deviation occurrence was increasingly measured. Conclusion : Based on the results of the study there were differences between value acquired based on theoretical model and actual value. Therefore in respiratory gated radiotherapy using external surrogates, there needs to be establishment of respiration gated radiation system that avoids the combination of two Sorting methods considering that there will be occurrence of treatment and corresponding clinical differences due to the phase difference that occur due to the Amplitude based Phase Sorting.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.4
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• pp.407-414
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• 2010

Until now, the pore size distribution, PSD, of soil profile has been calculated from soil moisture characteristic data by water release method or mercury porosimetry using the capillary rise equation. But the current methods are often difficult to use and time consuming. Thus, in this work, theoretical framework for an easy and fast technique was suggested to estimate the PSD from unsaturated hydraulic conductivity data in an undisturbed field soil profile. In this study, unsaturated hydraulic conductivity data were collected and simulated by the variation of soil parameters in the given boundary conditions (Brooks and Corey soil parameters, ${\alpha}_{BC}=1-5L^{-1}$, b = 1 - 10; van Genuchten soil parameters, ${\alpha}_{VG}=0.001-1.0L^{-1}$, m = 0.1 - 0.9). Then, $K_s$ (1.0 cm $h^{-1})$ was used as the fixed input parameter for the simulation of each models. The PSDs were estimated from the collected K(h) data by model simulation. In the simulation of Brooks-Corey parameter, the saturated hydraulic conductivity, $K_s$, played a role of scaling factor for unsaturated hydraulic conductivity, K(h) Changes of parameter b explained the shape of PSD curve of soil intimately, and a ${\alpha}_{BC}$ affected on the sensitivity of PSD curve. In the case of van Genuchten model, $K_s$ and ${\alpha}_{VG}$ played the role of scaling factor for a vertical axis and a horizontal axis, respectively. Parameter m described the shape of PSD curve and K(h) systematically. This study suggests that the new theoretical technique can be applied to the in situ prediction of PSD in undisturbed field soil.

• Proceedings of the Korean Society of Postharvest Science and Technology of Agricultural Products Conference
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• 2004.10a
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• pp.67-72
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• 2004

Quality of fresh-cut tomato slices was compared during cold storage under various modified atmosphere packaging conditions. Chilling injury of slices in containers sealed with Film A was higher than with Film B; these films had oxygen transmission rates of 87.4 and 60.0 ml $h^{-1}\;m^{-2}\;atm^{-1}$ at $5^{\circ}C\;and\;99\%$ RH, respectively. While slices in containers with an initial atmospheric composition of air, $4\%\;CO_2+1\;or\;20\%\;O_2,\;8\%\;CO_2+1\;or\;20\%\;O_2,\;or\;12\%\;CO_2+20\%\;O_2$ showed fungal growth, slices in containers with $12\%\;CO_2+1\%\;O_2$ did not. Low ethylene in containers enhanced chilling injury. Modified atmosphere packaging provided good quality tomato slices with a shelf-life of 2 weeks or more at $5^{\circ}C$. Experiments were conducted to compare changes in quality of slices of red tomato (Lycopersicon esculentum Mill. 'Sunbeam') fruit from plants grown using black polyethylene or hairy vetch mulches under various foliar disease management systems including: no fungicide applications (NF), a disease forecasting model (Tom-Cast), and weekly fungicide applications (WF), during storage at $5^{\circ}C$ under a modified atmosphere. Slices were analyzed for firmness, soluble solids content (SSC), titratable acidity (TA), pH, electrolyte leakage, fungi, yeasts, and chilling injury. With both NF and Tom-Cast fungicide treatments, slices from tomato fruit grown with hairy vetch (Vicia villosa Roth) mulch were firmer than those from tomato fruit grown with black polyethylene mulch after 12 days storage. Ethylene production of slices from fruit grown using hairy vetch mulch under Tom-Cast was about 1.5- and 5-fold higher than that of slices from WF and NF fungicide treatments after 12 days, respectively. The percentage of water-soaked areas (chilling injury) for slices from tomato fruit grown using black polyethylene mulch under NF was over 7-fold that of slices from tomato fruit grown using hairy vetch under Tom-Cast. When stored at $20^{\circ}C$, slices from light-red tomato fruit grown with black polyethylene or hairy vetch mulches both showed a rapid increase in electrolyte leakage beginning 6 hours after slicing. However, slices from tomato fruit grown using the hairy vetch mulch tended to have lower electrolyte leakage than those grown with black polyethylene mulch. These results suggest that tomato fruit from plants grown using hairy vetch mulch may be more suitable for fresh-cut slices than those grown using black polyethylene mulch. Also, use of the disease forecasting model Tom-Cast, which can result in lower fungicide application than is currently used commercially, resulted in high quality fruit for fresh-cut processing. Experiments were conducted to determine if ethylene influences chilling injury, as measured by percentage of slices exhibiting water-soaked areas in fresh-cut tomato slices of 'Mountain Pride' and 'Sunbeam' tomato (Lycopersicon esculentum Mill.). Ethylene concentration in containers without ventilation significantly increased during storage at $5^{\circ}C$, whereas little or no accumulation of ethylene occurred in containers with one or six perforations. Chilling injury was greatest for slices in containers with six perforations, compared to slices in containers with one perforation, and was over 13-fold greater than that of slices in control containers with no perforations. An experiment was also performed to investigate the effectiveness of including an ethylene absorbent pad in containers on subsequent ethylene accumulation and chilling injury. While ethylene in the no-pad controls increased continually during storage of both 'Mountain Pride' and 'Sunbeam' tomatoes at $5^{\circ}C$ under modified atmosphere conditions, no increase in accumulation of ethylene was observed in containers containing ethylene absorbent pads throughout storage. The ethylene absorbent pad treatment resulted in a significantly higher percentage of chilling injury compared with the no-pad control. In studies aimed at inhibiting ethylene production using AVG during storage of slices, the concentration of ethylene in control containers (no AVG) remained at elevated levels throughout storage, compared to containers with slices treated with AVG. Chilling injury in slices treated with AVG was 5-fold greater than that of controls. Further, we tested the effect of ethylene pretreatment of slices on subsequent slice shelf-life and quality. In slices treated with ethylene (0, 0.1, 1, or $10\;{mu}L\;L^{-1}$) immediately after slicing, ethylene production in non-treated controls was greater than that of all other ethylene pre-treatments. However, pretreatment of slices 3 days after slicing resulted in a different pattern of ethylene production during storage. Ihe rate of ethylene production by slices treated with 1 L $L^{-1}$ ethylene 3 days after slicing was greater during storage than any of the other ethylene treatments. With slices pre-treated with ethylene, both immediately and 3 days after slicing, the rate of ethylene production tended to show an negative correlation with chilling injury. Chemical name used: 1-aminoethoxyvinylglycine (AVG).

• 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.