• Journal of KIISE:Software and Applications
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• v.32 no.9
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• pp.920-926
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• 2005

Nearest neighbor algorithms classify an unseen input instance by selecting similar cases and use the discovered membership to make predictions about the unknown features of the input instance. The usefulness of the nearest neighbor algorithms have been demonstrated sufficiently in many real-world domains. In nearest neighbor algorithms, it is an important issue to assign proper weights to the attributes. Therefore, in this paper, we propose a new method which can automatically assigns to each attribute a weight of its importance with respect to the target attribute. The method has been implemented as a computer program and its effectiveness has been tested on a number of machine learning databases publicly available.

• The Journal of the Korea Contents Association
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• v.9 no.6
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• pp.417-425
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• 2009

Jeju Special Self-governing Province continues to try to attract tourists on the basis of an active investment in the tourist industry. But most of the researches and studies on Jeju Tourism were made on a viewpoint of hardware. Therefore, the researches and studies which are related to 'the inclination of tourists who visit Jeju Island', 'the tourist satisfaction by a selection of tourist destination' and 'tourists' activities after the visit to Jeju Island' are insufficient. Accordingly, this study will support a basic datum needed for formulating a policy of Jeju tourism by closely examining the related influences among the Jeju tourists' inclination, their satisfaction and their activities after a tour of Jeju.

• The Korean Journal of Food & Health Convergence
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• v.7 no.1
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• pp.7-15
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• 2021

This study aims to empirically analyze the differences between groups of customers who prefer delivery food, which is rapidly growing amid the COVID-19 pandemic, and those who prefer the traditional practice of visiting offline restaurants. Based on the eating out lifestyle, participants were divided into three groups: participants who prefer food delivery, those who prefer to visit restaurants, and those who favor both. The comparison of differences between the groups was analyzed. A total of 215 questionnaires were distributed, and reliability and validity were verified with a sample of 201 copies, excluding 14 unreliable respondents. Then, a multivariate analysis of variance was used to compare the groups. The results showed that regarding offline restaurants, the group of customers who prefer to visit restaurants valued their atmosphere, while the customers who prefer delivery food valued the reputation of the restaurant. Regarding delivery-specialized restaurants, the group of customers who prefer delivery placed greater value on coupon events and payment convenience than other groups. The results revealed that the difference between the customers who prefer to visit restaurants and those who prefer delivery food was identified through empirical analysis, which provides strategic implications for catering companies and restaurant industries during COVID-19 in Korea.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.395-405
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• 2021

The sophistication of technology information has led to a series of innovative activities in the economy, particularly in buying and selling products and services both conventionally and online. Currently online activities provide opportunities for customers to get the desired needs. The purpose of this research is to examine the effect of website quality, hedonic shopping motivation, and impulse buying on customers' satisfaction of online shopping in Indonesia. Eight online marketplaces are the focus of this research. This study uses a quantitative approach. This is a structural equation research with data obtained from 177 students through an online questionnaire using a five-point Likert scale; the selection criteria is having shopped online from various universities in Indonesia. The statistical testing tool used is SPSS 26.0, with the effect between variables determined using Partial Least Square (SmartPLS 3.0). The findings of this study indicate that the nine proposed hypotheses are accepted, positively and significantly, directly or indirectly, which are supported by previous research to reinforce the findings that have been found. The interesting attributes associated with this study are hedonic shopping motivation and impulse buying that mediate the relationship between website quality and customer satisfaction of online shopping in Indonesia's marketplace.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.465-473
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• 2021

The main aim of this research paper is to identify the factors that influence smartphone purchase intention in the Nepalese market. The study identifies how the brand personality, attribute factors, and the price factor influence the purchase intention of a smartphone. The paper puts the emphasis on how the consumer preference functions in the selection of the smartphone and which factor plays the more significant role in smartphone purchase intention. This research paper has used primary data and a 7-point Likert scale survey questionnaire. The primary data has been collected through a structured survey questionnaire by using convenient sampling technique from 294 smartphone users in the Kathmandu Valley. Descriptive statistics, Correlation Analysis and Structural Equation Modeling (SEM) have been carried out to analyze the primary data using the SPSS AMOS 24. Brand personality, attribute factor, and product price were taken as independent variables to identify the impact on purchase intention. The result of the regression path analysis showed that brand personality has no significant effect on purchase intention in the purchasing of smartphone. It is also found that the product attributes and product price have a significant influence on consumer purchase intention of a smartphone in Nepal.

• Advances in concrete construction
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• v.13 no.6
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• pp.471-479
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• 2022

In this paper, vibrational attributes of double-walled carbon nanotubes (CNTs) has been studied based upon nonlocal elastic shell theory. The implication of small scale is being perceived by establishing nonlocal Love shell model. The wave propagation approach has been operated to frame the governing equations as eigen value system. The comparison of local and nonlocal model has been overtly explored by means of scaling parameter. An appropriate selection of material properties and nonlocal parameter has been considered. The influence of changing mechanical parameter Young's modulus has been studied in detail. The dominance of end condition via nonlocal parameter is explained graphically. The results generated furnish the evidence regarding applicability of nonlocal shell model and also verified by earlier published literature.

• The Korean Journal of Food & Health Convergence
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• v.8 no.1
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• pp.9-16
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• 2022

Recently, the use of serving robots has been increasing due to the increase in preference for non-face-to-face services and the rise in the minimum wage due to the coronavirus. When analyzing previous studies related to serving robots, it was confirmed that most of the studies on the functions and technologies of serving robots were conducted. Therefore, this study analyzed the factors affecting the attitude and customer satisfaction of restaurant consumers toward serving robots by adding performance expectations, effort expectations, and speed factors among the UTAUT2 models. The survey period was conducted from July 28, 2021 to September 9, 2021, and 306 out of a total of 310 surveys were used for analysis, excluding 4 unfaithful surveys. For the analysis, exploratory factor analysis, reliability analysis, confirmatory factor analysis, and hypothesis test were performed using SPSS 20.0 and AMOS 20.0, and the research results are as follows. First, it was found that performance expectation, effort expectation, and speed had a significant positive (+) effect on attitudes. Second, it was found that attitude had a significant positive (+) effect on customer satisfaction. This study researched customer selection attributes of robot service restaurants using the UTAUT2 model, and also provided academic and practical implications.

• The Journal of Industrial Distribution & Business
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• v.14 no.1
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• pp.21-28
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• 2023

Purpose: This study aims to analysis the difference by Michelin rating in customer satisfaction of restaurant listed in the Korea Michelin Guide. There are opinions that the Michelin Guide's rating system and evaluation criteria are somewhat ambiguous. Research design, data, and methodology: This study collected 145 actual online reviews published on TripAdvisor to examine how the effect of the content attributes of reviews on consumer satisfaction varies according to the Michelin grade. Based on this, two studies were conducted. Study 1 examined the effect of strong and weak positive reviews on consumer satisfaction according to the rating. Study 2 examined the effect of image information on consumer satisfaction. Results: The results revealed that the lower the Michelin rating, the more positive review had a significant effect on consumer satisfaction. The higher the rating, the more image information had an effect on consumer satisfaction. Expectations for Michelin three-star restaurants are higher than those of two-star restaurants, so customers are more likely to be used negatively when writing reviews. Conclusions: Accurate information on Michelin selection criteria should be delivered so as not to form high expectations and not to disappoint. For consumers to be satisfied with the name Michelin, the standards should be stricter.

• Journal of Global Scholars of Marketing Science
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• v.18 no.1
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• pp.141-156
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• 2008

Market structure analysis is a very useful tool to analyze the competition boundary of the brand or the company. But most of the studies in market structure analysis, the concern lies in nondurable goods such as candies, soft drink and etc. because of the their availability of the data. In the field of durable goods, the limitation of the data availability and the repurchase time period constrain the study. In the analysis of the automobile market, those of views might be more persuasive. The purpose of this study is to analyze the structure of automobile market based on some idea suggested by prior studies. Usually the buyers of the automobile tend to buy upper tier when they buy in the next time. That kind of behavior make it impossible to analyze the structure of automobile market under the level of automobile model. For that reason I tried to analyze the market structure in the brand or company level. In this study, consideration data was used for market structure analysis. The reasons why we used the consideration data are summarized as following. Firstly, as the repurchase time cycle is too long, brand switching data which is used for the market analysis of nondurable good is not avaliable. Secondly, as we mentioned, the buyers of the automobile tend to buy upper tier when they buy in the next time. We used survey data collected in the U.S.A. market in the year of 2005 through questionaire. The sample size was 8,291. The number of brand analyzed in this study was 9 among 37 which was being sold in U.S.A. market. Their market share was around 50%. The brands considered were BMW, Chevrolet, Chrysler, Dodge, Ford, Honda, Mercedes, and Toyota. �� ratio was derived from frequency of the consideration set. Actually the frequency is different from the brand switch concept. In this study to compute the �� ratio, the frequency of the consideration set was used like a frequency of brand switch for convenience. The study can be divided into 2 steps. The first step is to build hypothetical market structures. The second step is to choose the best structure based on the hypothetical market structures, Usually logit analysis is used for the choice best structure. In this study we built 3 hypothetical market structure. They are type-cost, cost-type, and unstructured. We classified the automobile into 5 types, sedan, SUV(Sport Utility Vehicle), Pickup, Mini Van, and Full-size Van. As for purchasing cost, we classified it 2 groups based on the median value. The median value was $28,800. To decide best structure among them, maximum likelihood test was used. Resulting from market structure analysis, we find that the automobile market of USA is hierarchically structured in the form of 'automobile type - purchasing cost'. That is, result showed that automobile buyers considered function or usage first and purchasing cost next. This study has some limitations in the analysis level and variable selection. First, in this study only type of the automobile and purchasing cost were as attributes considered for purchase. Considering other attributes is very needful. Because of the attributes considered, only 3 hypothetical structure could be analyzed. Second, due to the data, brand level analysis was tried. But model level analysis would be better because automobile buyers consider model not brand. To conduct model level study more cases should be obtained. That is for acquiring the better practical meaning, brand level analysis should be conducted when we consider the actual competition which occurred in the real market. Third, the variable selection for building nested logit model was very limited to some avaliable data. In spite of those limitations, the importance of this study lies in the trial of market structure analysis of durable good.

• Journal of the Korea Society for Simulation
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• v.29 no.1
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• pp.11-21
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• 2020

Cardio-cerebrovascular diseases (CCD) account for 24% of the causes of death to Koreans and its proportion is the highest except cancer. Currently, the risk of the cardiovascular disease for domestic patients is based on the Framingham risk score (FRS), but accuracy tends to decrease because it is a foreign guideline. Also, it can't score the risk of cerebrovascular disease. CCD is hard to predict, because it is difficult to analyze the features of early symptoms for prevention. Therefore, proper prediction method for Koreans is needed. The purpose of this paper is validating IG-MLP (Information Gain - Multilayer Perceptron) evaluation based feature selection method using CCD data with simulation. The proposed method uses the raw data of the 4^th ~ 7^th of The Korea National Health and Nutrition Examination Survey (KNHANES). To select the important feature of CCD, analysis on the attributes using IG-MLP are processed, finally CCD prediction ANN model using optimize feature set is provided. Proposed method can find important features of CCD prediction of Koreans, and ANN model could predict more accurate CCD for Koreans.