• Culinary science and hospitality research
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• v.14 no.2
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• pp.215-224
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• 2008

The objective for this research was to clarify the preference for alternative restaurants with different combinations of factor levels: local specialty food, non-local specialty food, very attentive service, moderately attentive service, not attentive service, traditional decoration, modern decoration, \10,000, \15,000, and \20,000. Total 230 copies of questionnaire were completed. Conjoint experiment method was used to develop full restaurant profiles. Ordinal probit model was used to measure the effects of factor levels on the preference. Results of the study demonstrated that the ordinal probit model analysis result for the data also indicated a good model fit. The effects of factor levels on the preference were statistically significant. As expected, the estimates of implicit price to pay were statistically significant. Moreover, the customers were more willing to pay for local specialty than other factor levels. The customers also considered the food factor as a very important factor. This research suggested that the customer's decision-making process for restaurants was best modeled as a conjoint experiment method that combines various factor levels. And it showed the results could be used as good data for understanding the relationships between the factors and preference in choosing food and restaurants in tourist areas.

• Journal of Korean Institute of Industrial Engineers
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• v.32 no.1
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• pp.18-28
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• 2006

Some issues which should be considered in an R&D project selection problem are as follows: First, quantitative analysis on the efficiencies of R&D projects is required to guarantee objective validity in the evaluation of the projects. For this reason, the methodology for selecting R&D projects should be based on mathematical models that perform quantitative analysis. Second, in general there are ordinal factors like Likert-scale in the data for evaluating R&D projects. Previous researches, however, couldn't suggest explicit methods incorporating these ordinal factors into models. Third, for the R&D project selection problems with limited resources like budget, it is necessary to decide the perfect ranking of the all projects. This paper develops a mathematical model that can be applicable to the problems of selecting R&D projects with the previous features. In this paper, we improve the original DEA model for evaluating efficiency to incorporate ordinal factors and suggest a new model which can decide the perfect ranking of all projects by merging the improved DEA model and AHP method. Furthermore a web-based R&D project selection system using the DEA/AHP model suggested in this paper is developed and illustrated.

• Journal of Korea Technology Innovation Society
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• v.11 no.3
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• pp.376-399
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• 2008

Science and technology (S&T) is one of the most important elements in a nation's competitiveness. In an effort to strengthen their national competitiveness, all countries are focusing on upgrading the level of eir S&T. With these factors in mind, Korea has increased its support of national research and development (R&D). In recent years, this added support has resulted in an increased interest in the effectiveness of R&D. We have made continuous efforts to enhance the accountability and effectiveness of R&D by strengthening performance evaluation and considering R&D evaluation results during the budget review (appropriation) process. In order to change to a performance based system, we need to develop objective and scientific indicators to measure and evaluate the quality of the research performance of R&D programs. One of the primary research outcomes is publications. The impact factor of publications is widely used to evaluate overall journal quality and the quality of the papers published therein. However, the use of impact factors has been criticised because they can vary greatly when works from different subject areas are compared. In order to overcome this limitation, we have developed three kinds of qualitative indicators, which are functions of the impact factor. Two of these qualitative indicators, Modified Rank Normalized Impact Factor and Ordinal Rank Normalized Impact Factor, are based on order statistics (rank) for all journals from a specific specialty. The third qualitative indicator, Relative Field Impact Factor, uses the average impact factor of all journals within a subject category. We also suggest a quantitative indicator, Percentage of Contribution. In this study, we suggest 4 indicators and use them to evaluate the performance of outcomes from three R&D programs supported by the Ministry of Education, Science & Technology. We also perform a simulation study to verify the effectiveness of the proposed indicators. It can be shown that the proposed Ordinal Rank Normalized Impact Factor is the most reliable and effective indicator for comparing research performance across subject categories. However, we recommend using previous indicators in combination with the proposed indicators in this study for the research evaluation of R&D programs.

• Journal of the Korea Convergence Society
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• v.13 no.3
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• pp.33-41
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• 2022

In this article, we proposed to predict natural gas (NG) leakage levels through feature selection based on a factor analysis (FA) of the integrating the Korean Meteorological Agency data and natural gas leakage data for considering complex factors. The paper has been divided into three modules. First, we filled missing data based on the linear interpolation method on the integrated data set, and selected essential features using FA with OrdinalEncoder (OE)-based normalization. The dataset is labeled by K-means clustering. The final module uses four algorithms, K-nearest neighbors (KNN), decision tree (DT), random forest (RF), Naive Bayes (NB), to predict gas leakage levels. The proposed method is evaluated by the accuracy, area under the ROC curve (AUC), and mean standard error (MSE). The test results indicate that the OrdinalEncoder-Factor analysis (OE-F)-based classification method has improved successfully. Moreover, OE-F-based KNN (OE-F-KNN) showed the best performance by giving 95.20% accuracy, an AUC of 96.13%, and an MSE of 0.031.

• Journal of Environmental Impact Assessment
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• v.6 no.2
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• pp.123-135
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• 1997

The solid waste incineration facilities which cause environmental pollution. And those are some kind of loathing facilities for residents who do not want it. This problem could be solved by location feasibility study. The purpose of location feasibility study was to determine one site out of three candidate sites. This study which was done by the law, environmental and economic factor was considered for optimum site selection. Comparative evaluation among the candidate sites was done by ordinal scale and thus the optimum site was selected.

• Korean Journal of Agricultural Science
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• v.50 no.4
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• pp.927-940
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• 2023

Online shopping has been undergoing significant developments in the South Asian region in the last decade. Using a representative sample of Sri Lankan consumers, this study explored online food purchasing behavior in Sri Lanka, a developing nation and island in South Asia. Data were collected from 562 respondents from all nine provinces in Sri Lanka using an online survey. Consumer attitudes were evaluated using factor analysis, and factor scores were added as explanatory variables to the final model. An ordered logistic regression model was used to examine the impact of consumer demographics, economic variables, and consumer attitudes on online food purchases. Online food purchasing intensity was categorized into four groups that suited ordinal rankings: zero for never, low for rarely, medium for occasionally, and high for regularly. Results indicated that age, income, education, and living in urban areas affect the online food purchasing behavior of Sri Lankan consumers. In addition, trust, convenience, and attitudes toward price were powerful drivers of online food purchasing. The findings have a number of significant managerial ramifications for creating strategies to promote online food purchases in developing South Asian nations like Sri Lanka. Moreover, promoting online shopping could be a potential solution for traffic congestion, ultimately helping to mitigate the negative externalities associated with it, such as carbon emissions and air pollution.

• Journal of Korean Academy of Nursing
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• v.51 no.1
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• pp.5-14
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• 2021

Purpose: This study aimed to investigate sub-health status (SHS) of people living in China during the Coronavirus disease 2019 (COVID-19) COVID-19 pandemic. COVID-19 is a severe acute respiratory syndrome coronavirus (SARS-CoV) infection-induced acute infectious disease, which is featured by universal susceptibility and strong infectivity, and SHS (a status of low quality health) refers to a status of low-quality health. COVID-19 has gradually developed into a global pandemic, making the public in a high stress situation in physiological, psychological and social states in the short term. Methods: From March 6 to 11, 2020, a large-scale cross-sectional survey was conducted by convenient sampling, and SHS assessment scale was used in the questionnaire. The ordinal logistic regression analysis was used to identify the factors affecting SHS. Results: In this study, 17,078 questionnaires were delivered with 16,820 effective questionnaires collected, and 10,715 subjects (63.7%) were found with SHS, with moderate SHS primarily. Physiological sub-scale scored the highest, followed by psychological and social sub-scales. Ordinal logistic regression analysis indicated that man, only-child, workers and farmers were risk factors of SHS. Protective factors of SHS included living in rural areas and townships, laid-off retirees and education degree. Conclusion: It shows many people in China place in a poor health status during COVID-19 pandemic. It is necessary that relevant departments pay more attention to people with poor health such as men, only-child, urban people, workers and farmers, and groups with high education degree during and after pandemic stabilization.

• The Korean Journal of Applied Statistics
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• v.27 no.6
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• pp.909-922
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• 2014

This paper reviews Bayesian inference with inequality constraints. It focuses on ⅰ) comparison of models with various inequality/equality constraints on parameters, ⅱ) multiple tests on equalities of parameters when parameters are under inequality constraints, ⅲ) multiple test on equalities of score parameters in models for contingency tables with ordinal categorical variables.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.6D
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• pp.577-585
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• 2010

Traffic accidents are caused by several factors such as drivers, vehicles, and road environment. It is necessary to investigate and analyze them in advance to prevent similar and repetitive traffic accidents. Especially, the human factor is most significant element and traffic accidents by drinking-driving caused from human factor have become social problem to be paid attention to. The study analyzes traffic accidents resulting from drinking-driving and the effects of driver's attributes and environmental factors on them. The study is composed as two parts. First, the log-linear model is applied to analyze that accidents by drinking or non-drinking driving associate with road geometry, weather condition and personal characteristics. Probability is tested for drinking-driving accidents relative to non-drinking drive accidents. The study analyzes probability differences between genders, between ages, and between kinds of vehicles through odds multipliers. Second, traffic accidents related to drinking are classified into property damage, minor injury, heavy injury, and death according to their severity. Heavy injury is more serious than minor one and death is more serious than heavy injury. The ordinal regression models are established to find effecting factors on traffic accident severity.

• IE interfaces
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• v.17 no.3
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• pp.349-358
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• 2004

The organizations that adopted ISO 9000:1994 have upgraded to ISO 9001:2000 family through transition period by December, 2003. This paper focuses on the implementation of ISO 9001:2000 QMS in Busan and Kyungnam provinces where most machinery and metal manufacturing companies are located. Based on the questionnaire survey, we calculate ordinal association measures of requirements questions, perform factor analysis, and test three hypotheses to ascertain if there is any difference in implementing ISO 9001:2000 QMS. Results show that a professional manager-CEO maintains QMS general requirements(4.1), work environment(6.4), measurement analysis and improvement general(8.1), and monitoring and measurement(8.2) better than an owner-CEO. In addition, it has been found that customer focus(5.2) and improvement(8.5) are well maintained in companies by internal developmental reasons, and infrastructure(6.3) and purchasing(7.4) are well maintained by companies with long term implementation.