• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5D
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• pp.695-703
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• 2008

China water market has huge potential for increased use of BOT mode and one of the most attractive markets of doing business. However, the current China water BOT market shows that many foreign companies are retreating from the market while Chinese water companies fast growing. From the view no domestic companies have track records in China BOT water market, the research identified twenty market access barriers in terms of construction laws, regulations, BOT-related policy and the recent market situation. These are evaluated based on interview results with 10 professionals direct or indirect having a China water BOT experience. All the factors are found to be highly influential to foreign company's decision on the market participation. Among those, no fixed return policy and low water price, difficulty in water price adjustment and approval, and no government guarantees, all directly related to the project viability and under the control of government, were the most critical factors, implying government's role is the key in increasing the market competition by attracting more foreign participation on the market. In addition, new construction law regulating foreign EPC contractor's construction work, namely Decree 113, and requirement of applying competitive bidding in selecting EPC contractor in a BOT project are also considered signigicant barriers on foreign participation, which contradicts international norm and therefore necessitates an adjustment on current decision process in domestic companies.

• The Korean Journal of Franchise Management
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• v.9 no.3
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• pp.19-29
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• 2018

Purpose - Due to the increase in coffee consumption and competition, domestic coffee franchise companies are currently entering the overseas market. Therefore, coffee franchise companies are pursuing a variety of marketing strategies to meet customer needs and gain competitive advantage in overseas markets. From this perspective, overseas franchise companies need to ensure that their servicescapes meet the needs of their overseas customers. For these purposes, the study is to identify the impact servicescapes on customer satisfaction and customer loyalty focused on Global Coffee Franchise Company "C", which extended its business worldwide in Mongolia. Research design, data, and methodology - The data were collected from customers who had visited the stores of 'C' company in Ulaanbaatar, Mongolia. 435 valid questionnaires collected through online survey coded and analyzed using frequency, confirmatory factor analysis, correlations analysis, and structural equation modeling with SPSS 24 and SmartPLS 3.0. Result - Firstly, seating comfort, facility aesthetics, and cleanliness, ambient conditions among servicescapes influenced customer satisfaction. Secondly, servicescapes didn't affect the loyalty directly. Third, customer satisfaction had positive effect on loyalty. Fourthly, cleanliness which was ranked lower in Korea had a great effect on customer satisfaction in Mongolia. Fifthly, IPMA(Importance-performance map analysis) shows that the importance of servicescapes is higher for women than for men, and facility aesthetics for female and cleanliness is the most important for male. Conclusions - The results of this study show that there is a positive (+) effect on customer satisfaction in order of cleanliness, ambient conditions, aesthetics, and seating comfort. Therefore, franchise companies considering or advancing into Mongolia should consider importance in order of cleanliness, ambient conditions and aesthetics when entering Mongolia market. For example, franchise managers should select Monday as a "clean day," and all merchants should spend all of their open hours and keep their stores clean in accordance with the head office manual. In addition, franchise managers need to hire a VMD (visual merchandising) experts to build up a physical environment that will effectively highlight the space-specific display of the store so that Mongolian local customers can have a satisfactory climate and aesthetics. And, the IMPA analysis between servicescapes and customer satisfaction shows that women are more susceptible to servicescapes than men. Especially, in the case of women, the importance of esthetics is high, but the performance is low. Thus, if the aesthetics are actively improved, customer satisfaction can be effectively increased.

• Asia Marketing Journal
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• v.15 no.1
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• pp.83-105
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• 2013

During recent decades, the number of mixed attribute products (henceforth mixed products), which have both utilitarian and hedonic benefits, has increased dramatically. Despite these products' growing popularity, academic research has paid little attention to them, and there remains a gap between theory and the real world. Hence, our study was undertaken to understand consumers' perceptions about and behaviors toward mixed products, as well as factors affecting the evaluation and choice of these products. We divided mixed attribute products into two categories: mixed utilitarian products (utilitarian products adding hedonic attributes) and mixed hedonic products (hedonic products adding utilitarian attributes). We then showed how adding different attributes affects consumers' perception, willingness to pay (WTP), and the choice of mixed attribute products compared to pure utilitarian or pure hedonic products. We conducted an experiment using a within-subject design. A total of 160 office workers and college students participated in the study. The pure utilitarian product used in the study was orange juice, and the mixed utilitarian product was carbonated orange juice. The pure hedonic product was chocolate, and the mixed hedonic product was polyphenol enriched chocolate. Results showed that consumers perceived a mixed utilitarian product to be less utilitarian, less pleasurable and more guilty than a pure utilitarian product. On the other hand, a mixed hedonic product was perceived to be more utilitarian, less pleasurable and less guilty than a pure hedonic product. Also, WTP for a mixed hedonic product was higher than WTP for a pure hedonic product, but WTP was lower for a mixed utilitarian product than for a pure utilitarian product. Furthermore, mixed hedonic products were likely to be evaluated more favorably when they were presented together with pure hedonic products, more so than when they were presented alone. Finally, when compared to low self-control participants, high self-control participants chose mixed hedonic products more frequently. The present study contributes to the existing literature on utilitarian and hedonic consumption by adding to the sparse literature on the consumption of products that have both utilitarian and hedonic purposes. Also, our research findings provide several useful implications for practitioners in related fields. First, the current study provides marketers with a useful guide for understanding consumers' perceptions of these types of products, and helps to predict how adding different attributes influences these products. Second, this study has examined the conditions that may moderate the evaluation and choice of hedonic base products and this finding will serve as a good reference for marketers of mixed hedonic products in marketing communication strategy, in-store marketing and targeting. Specifically, comparative advertising with a pure hedonic product will be beneficial for a mixed hedonic product. Also, displaying mixed hedonic products near pure hedonic products may enhance the effectiveness of in-store marketing of mixed hedonic products.

• Korean Security Journal
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• no.38
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• pp.7-32
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• 2014

This study is aimed to analyze problems of police budgetary execution and to suggest better ways for establishing effective budget implementation as well as legitimacy of securing budget in the field of police work. For this purpose, this paper analyzed the annual reports on police budgetary execution, from 2009 to 2012, conducted by National Assembly Budget Office. In result, most parts of the police budgetary execution were not satisfied with the audit standard, and especially in terms of management of budgetary execution, it showed 40% in inappropriateness. In addition, excessive and underestimate appropriation in the police budgetary execution, which happened frequently in other offices, was recorded on the second place. 10% of the amount of budget was executed for ordinance violence. Given results analyzed from each division, Transportation Division occupied 40% of the amount of related problems and all of types in the field did not meet the audit standard, thus it is required to manage budgetary execution effectively. In terms of Public Safety Division, the problem was related to budgetary allocation prior to execution, such as overlap in other works, excessive and underestimate appropriation, and inappropriate business plans. Director General for Planning and Coordination did not meet the standard of law system maintenance, Given the light of the result of analyzing programs, traffic safety and securing communication was the most problematic and support for police administration, crime prevention and protecting the disadvantaged, educating professional police officers, and establishment of policing infrastructure were required to be reformed in sequence. In order to resolve these problems, it is demanded to check budgetary execution and the process in business plans on a regular basis. Additionally, in case of using budget in inappropriate parts, tough penality including reduction of budget in related to the local police should be implemented to increase the importance of budgetary execution. Moreover, because of the fact that a part of problem of budgetary execution was originally caused by the budgetary allocation, it is advised to allocate police budget using the budget proposal of National Finance Act and Ministry of Strategy and Finance.

• Journal of agricultural medicine and community health
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• v.31 no.1
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• pp.21-34
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• 2006

Objectives: The purpose of this study was to investigate the knowledge, attitude and practice toward sanitary administration of the new restaurateurs, to carry out the sanitary management of business for improvement of sanitary level, and to provide basic data which were necessary for sanitary education of the restaurateurs. Methods: The self-recording survey on the attitude and the knowledge toward the sanitation, the sanitary administration, and its education was conducted against new 393 restaurateurs by the administrative division of Gwangju city in charge of the food industry which put in the regular sanitary education annually for the new restaurateurs. Results: In regard to food sanitation, some 87.9% to 94.4% got the right knowledge about the reason and precaution of food poisoning, storage methods of frozen or cold food, and the disposal of product after expiration of validity term. But it was about 56.0% to 63.0% who knew right about the cause and the major precaution of food poisoning, storage temperature in the refrigerator. 30.6% of the subject placed an emphasis on personal sanitation of the workers as the most important thing in the sanitary management. 83.6% replied that it was necessary to improve the sanitary level. Concerning the health examination, 78.3% replied it was needed. 76.4% pointed the need for education, but respondents with higher educational level less emphasized its needs. It was most frequently pointed out by 71.6% restaurateur's poor awareness about it. 36.7% indicated the environmental sanitation like facilities in the restaurants as the first thing to be improved. The rate of personal sanitation was 43.7%. Conclusions: To improve the poor sanitary conditions of the food service business, it was recommended to offer institutional backing and financial aid from administrative office, to encourage restaurateurs to take pride in their job, and to conduct the sanitary education effectively by the technical education institution.

• Korean Journal of Health Education and Promotion
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• v.15 no.1
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• pp.79-95
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• 1998

The purpose of this study was to investigate the sanitation affairs of general restaurants. The questionnaire survey on the attitude and knowledge toward sanitation, the attitude for sanitary administration and the sanitary education was conducted against new 600 restaurateurs who were educated from June 20 to July 11, 1996, at the administration hall's division of Kyungsangbook-do in charge of food industry that offered regular sanitary education to new restaurateurs annually. And the visit survey on sanitary practice was also conducted over 93 restaurateurs who obtained the commercial license for food service business. The findings from the survey were as follows; In regard to food sanitation, some 87.1 to 88.3% got the right knowledge about the reason and precaution of food poisoning, food's frozen or cold-storage, and the disposal of products after expiration of validity term. But it was about 20.8% to 50.0% who knew right about major precaution, storage temperature in refrigerator, fermented milk product's storage temperature and validity term. There was therefore a necessity for education in food sanitation. 38.2% of the subjects placed an emphasis on sanitary storage of foodstuffs as the most important thing in sanitary management. 33.8% emphasized cooking sanitation. The environmental sanitation was counted as the most important thing by 19.2%, and personal sanitation of worker was counted by 8.8%. There was differences in what they thought the most important thing was, according to the respondent's educational level and cooker. 86.6% replied it necessary to improve the sanitary level. The respondents who were younger or had better educational level emphasized more the need for it. Concerning health examination, 90.2% replied it necessary. 81.4% answered the reason was because there was a potentiality Quests might be infected with contagious disease. 78.5% pointed the need for sanitary education, but respondents with higher educational level less emphasized its needs. As the reason for poor sanitation, restaurateur's poor awareness about it was most frequently pointed out, by 46.9%. Cooking sanitation was most frequently counted, by 38.5%, as the first thing to be improved. As the most critical point in sanitary education, 34.5% indicated food's sanitary Quality control 30.9% mentioned sanitary treatment of kitchen facilities and peripheral environment, and 27.1% emphasized the summary of the general food sanitation. 77.7% answered to correct immediately in case of violating the Food Hygiene Law, and 12.0% replied to correct in the same case if they would get the order from public official or administrative action would be taken. Respondents with higher educational level answered more to correct immediately. What they wanted the government office to do toward sanitary improvement was a fund aid an facilities and management which was pointed out by 38.9%, a periodical sanitary education by 26.3% and a on-the-spot guidance of sanitary officials by 22.3%. In view of the food service business's sanitary practice, the rate of wearing a sanitary clothes was 32.9% in city and 35.0% in county. The rate of hand-washing without soap or non-washing at cooking was 73.9%, 85%, respectively. The rate of personnel sanitation was 34.2% in city and 50.0% in county. These things indicated the sanitation was not well practiced. To improve the poor sanitary conditions of the food service businesses, it is recommended to offer institutional backing and financial aid from administrative office, and encourage restaurateurs to take pride in their job. and conduct the sanitary education effectively by sanitary education institution.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.71-89
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• 2016

Sentiment analysis is used for identifying emotions or sentiments embedded in the user generated data such as customer reviews from blogs, social network services, and so on. Various research fields such as computer science and business management can take advantage of this feature to analyze customer-generated opinions. In previous studies, the star rating of a review is regarded as the same as sentiment embedded in the text. However, it does not always correspond to the sentiment polarity. Due to this supposition, previous studies have some limitations in their accuracy. To solve this issue, the present study uses a supervised sentiment classification model to measure a more accurate sentiment polarity. This study aims to propose an advanced sentiment classifier and to discover the correlation between movie reviews and box-office success. The advanced sentiment classifier is based on two supervised machine learning techniques, the Support Vector Machines (SVM) and Feedforward Neural Network (FNN). The sentiment scores of the movie reviews are measured by the sentiment classifier and are analyzed by statistical correlations between movie reviews and box-office success. Movie reviews are collected along with a star-rate. The dataset used in this study consists of 1,258,538 reviews from 175 films gathered from Naver Movie website (movie.naver.com). The results show that the proposed sentiment classifier outperforms Naive Bayes (NB) classifier as its accuracy is about 6% higher than NB. Furthermore, the results indicate that there are positive correlations between the star-rate and the number of audiences, which can be regarded as the box-office success of a movie. The study also shows that there is the mild, positive correlation between the sentiment scores estimated by the classifier and the number of audiences. To verify the applicability of the sentiment scores, an independent sample t-test was conducted. For this, the movies were divided into two groups using the average of sentiment scores. The two groups are significantly different in terms of the star-rated scores.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.39-54
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• 2013

Recent explosive increase of electronic commerce provides many advantageous purchase opportunities to customers. In this situation, customers who do not have enough knowledge about their purchases, may accept product recommendations. Product recommender systems automatically reflect user's preference and provide recommendation list to the users. Thus, product recommender system in online shopping store has been known as one of the most popular tools for one-to-one marketing. However, recommender systems which do not properly reflect user's preference cause user's disappointment and waste of time. In this study, we propose a novel recommender system which uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user's preference. The research data is collected from the real-world online shopping store, which deals products from famous art galleries and museums in Korea. The data initially contain 5759 transaction data, but finally remain 3167 transaction data after deletion of null data. In this study, we transform the categorical variables into dummy variables and exclude outlier data. The proposed model consists of two steps. The first step predicts customers who have high likelihood to purchase products in the online shopping store. In this step, we first use logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. We perform above data mining techniques using SAS E-Miner software. In this study, we partition datasets into two sets as modeling and validation sets for the logistic regression and decision trees. We also partition datasets into three sets as training, test, and validation sets for the artificial neural network model. The validation dataset is equal for the all experiments. Then we composite the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. Bagging is the abbreviation of "Bootstrap Aggregation" and it composite outputs from several machine learning techniques for raising the performance and stability of prediction or classification. This technique is special form of the averaging method. Bumping is the abbreviation of "Bootstrap Umbrella of Model Parameter," and it only considers the model which has the lowest error value. The results show that bumping outperforms bagging and the other predictors except for "Poster" product group. For the "Poster" product group, artificial neural network model performs better than the other models. In the second step, we use the market basket analysis to extract association rules for co-purchased products. We can extract thirty one association rules according to values of Lift, Support, and Confidence measure. We set the minimum transaction frequency to support associations as 5%, maximum number of items in an association as 4, and minimum confidence for rule generation as 10%. This study also excludes the extracted association rules below 1 of lift value. We finally get fifteen association rules by excluding duplicate rules. Among the fifteen association rules, eleven rules contain association between products in "Office Supplies" product group, one rules include the association between "Office Supplies" and "Fashion" product groups, and other three rules contain association between "Office Supplies" and "Home Decoration" product groups. Finally, the proposed product recommender systems provides list of recommendations to the proper customers. We test the usability of the proposed system by using prototype and real-world transaction and profile data. For this end, we construct the prototype system by using the ASP, Java Script and Microsoft Access. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The participants for the survey are 173 persons who use MSN Messenger, Daum Caf$\acute{e}$, and P2P services. We evaluate the user satisfaction using five-scale Likert measure. This study also performs "Paired Sample T-test" for the results of the survey. The results show that the proposed model outperforms the random selection model with 1% statistical significance level. It means that the users satisfied the recommended product list significantly. The results also show that the proposed system may be useful in real-world online shopping store.

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

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

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.3
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• pp.139-153
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• 2024

The importance of sustainable growth and cost reduction has increased globally, leading to the expansion of outsourcing by companies. Additionally, the spread of the platform economy has brought changes in the way we work, and the online outsourcing market, where tasks are mediated through platforms, is growing. Academically, while research on general outsourcing is actively conducted, studies on online outsourcing are relatively insufficient compared to its actual utilization. This study aims to analyze the factors and performance factors of online outsourcing utilization by startups, to identify the effects and concerns of using online outsourcing from multiple perspectives, and to suggest the roles of various stakeholders for effective utilization and industry development. For the research, a survey was conducted with 281 employees of startups who have experience in using online outsourcing, and the main findings are as follows. First, the enhancement of efficiency, profitability, and innovation through the use of online outsourcing positively affects organizational commitment and job satisfaction of startup members. Especially, the improvement of efficiency due to the use of online outsourcing has a significant effect on enhancing job satisfaction. Second, concerns about the burden of online outsourcing fees or uncertain outcomes negatively affect organizational commitment and job satisfaction. Third, there are perceptual differences in the motivations and performance regarding the utilization of online outsourcing depending on the job position. Practitioners perceive that the use of online outsourcing increases organizational commitment, whereas managers have relatively higher concerns about the uncertainty of outsourced task outcomes and information security. Through this study, the possibility that human resource shortages and employee management issues in startups can be improved through online outsourcing was confirmed. By verifying the influence of various factors of online outsourcing utilization, this study also provides meaningful implications for establishing business strategies for online outsourcing intermediary platform companies and for formulating startup support policies by government and other startup support organizations.