• Journal of Distribution Science
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• v.16 no.3
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• pp.13-21
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• 2018

Purpose - This study examined the effect of the importance of selective attribute of HMR(Home Meal Replacement) on customers' satisfaction and repurchase intention which is rapidly increasing with the changes of demographic, social and cultural trends as well as the influence of on and offline shopping channel moderating role. Research design, data, and methodology - Based on the research of previous studies, it assumed the selection attributes of HMR products were price, convenience, menu, freshness. With 231 surveyed questionnaires, this study was conducted by AMOS 21.0 and the SEM(structural equation model) was used as statistical method for examining the hypotheses in this study. Results - The analysis showed that price, convenience, and freshness had a significant effect on satisfaction, whereas menu did not affect satisfaction and the effect of satisfaction on repurchase intention was statistically significant. However, the results were different depending on the on and offline shopping channel for customers to buy HMR products. Price, menu and freshness are affected by online shopping, meanwhile convenience is more influenced by offline. Conclusions - This study analyzed the effect of selection attribute of HMR products on the satisfaction, repurchase intention, and the influence of each shopping channel, and provided practical implications.

• Culinary science and hospitality research
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• v.14 no.4
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• pp.106-118
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• 2008

Even though the number of food courts increased in recent years, there were few studies about them. Considering the effects of a food court on the sales of a mall or other shopping spots, it was necessary to analyze what kind of attribute attracts customers. For this research, conjoint analysis was used to test which attribute was the most decisive factor, and the results of this study were as follows. First, price was the first factor that customers attached great importance to. Next were time required from order to eat and menu diversity. Second, cluster analysis used by the individual value of utilities derived through the conjoint analysis showed two clusters. Third, the most preferred food court form gained 35.4% potential market share from the simulation. The information gained from this analysis provided an important starting point for marketing and determined what kind of attribution was considered in being part of the malls or buildings. Also, it could be made full use of creating and executing the most effective marketing strategies.

• Journal of the Korean Operations Research and Management Science Society
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• v.30 no.1
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• pp.161-176
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• 2005

In a situation that ordinal preferences on multiattribute weights are captured, we present two solution approaches: an exact approach and an approximate method. The former, an exact solution approach via interaction with a decision-maker, pursues the progressive reduction of a set of non-dominated alternatives by narrowing down the feasible attribute weights region. Subsequent interactive questions and responses, however, sometimes may not guarantee the best alternative or a complete rank order of a set of alternatives that the decision-maker desires to have. Approximate solution approaches, on the other hand, can be divided into three categories including surrogate weights methods, dominance value-based decision rules, and three classical decision rules. Their efficacies are evaluated in terms of choice accuracy via a simulation analysis. The simulation results indicate that a proposed hybrid approach, intended to combine an exact solution approach through interaction and a dominance value-based approach, is recommendable for aiding a decision making in a case that a final choice is seldom made at single step under attribute weights that are imprecisely specified beyond ordinal descriptions.

• Current Research on Agriculture and Life Sciences
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• v.26
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• pp.45-54
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• 2008

The purpose of this research is to develope street trees management program for more an effective street trees management. The principal point of this program is to relate spatial data and attribute data that is the main concept in GIS(Geographic Information System). To do this function, MapObjects which is ESRI's mapping and GIS components was used to process spatial data and Access which had been developed by MS was used to manipulate attribute data in this program. Visual Basic also was used to design and develop user interfaces and procedures, relate two sort of data, and lastly complete Application. Relational data model was adopted to design tables and their relation, Antenucci's GIS development model was selected to design and complete this program. The configuration of this application is composed of management data and reference data. The management data includes the location of street tree, a growth condition, a surrounding environment, the characters of tree, an equipments, a management records and etc. The reference data include general information about tree, blight and insects.

• 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.

• East Asian Journal of Business Economics (EAJBE)
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• v.8 no.4
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• pp.1-18
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• 2020

Purpose - The current study attempts to reveal the causal relationship and identify the interrelationships among individual value, product selection attribute, and re-purchase intention of consumers when purchasing kimchi. Research design, data, and methodology - The surveys were distributed and retrieved to kimchi consumers in Seoul and Gyeonggi Province who were over 20 years old and who had purchased kimchi before. The current study utilized the self-reporting survey as the research method. Result - First, as a result of hypothesis 1 test, both internal value and external value had a significant effect. Second, as a result of hypothesis 2 test, while internal value had a significant effect, external value did not have a significant effect. Third, as a result of hypothesis 3 test, while internal value had a significant effect, external value did not have a significant effect. Fourth, as a result of hypothesis 4 test, all quality, brand, and price had a significant effect. Fifth, as a result of hypothesis 5 test, while internal value had a significant effect, external value did not have a significant effect. Conclusion - The current study aims to establish marketing and service strategies to maximize profits and secure competitive advantage in the kimchi industry through changes in the management strategy of the Korean kimchi industry.

• Culinary science and hospitality research
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• v.15 no.3
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• pp.42-53
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• 2009

There has been increased interest in revealing how well-being and selection attribute affect customer satisfaction and customer loyalty. Recently, there are growing needs to pursue health and better life, and this study has proposed to explore the relations between well-being and selection attribute and customer satisfaction and customer loyalty. The results are as follows. First, well-being significantly affected customer satisfaction and customer loyalty, showing that well-being was an important variable for improving customer satisfaction and loyalty for Korean traditional pastry. Second, selection attribute had significant influence on customer satisfaction, but not customer loyalty, which are supposed to confuse the minds of customers who select traditional pastry. In this respect, it is concluded that customer satisfaction and loyalty were made according to the customer needs to be more healthier and pursue better life based on the colors and tastes of Korean traditional pastry.

• Journal of the Korea Society of Computer and Information
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• v.25 no.5
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• pp.1-9
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• 2020

In this paper, we propose a model that performs more natural facial attribute editing by utilizing mask information in the hair and hat region. STGAN, one of state-of-the-art research of facial attribute editing, has shown results of naturally editing multiple facial attributes. However, editing hair-related attributes can produce unnatural results. The key idea of the proposed method is to additionally utilize information on the face regions that was lacking in the existing model. To do this, we apply three ideas. First, hair information is supplemented by adding hair ratio attributes through masks. Second, unnecessary changes in the image are suppressed by adding cycle consistency loss. Third, a hat segmentation network is added to prevent hat region distortion. Through qualitative evaluation, the effectiveness of the proposed method is evaluated and analyzed. The method proposed in the experimental results generated hair and face regions more naturally and successfully prevented the distortion of the hat region.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.9
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• pp.3274-3297
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• 2021

Permission delegation is an important research issue in access control. It allows a user to delegate some of his permissions to others to reduce his workload, or enables others to complete some tasks on his behalf when he is unavailable to do so. As an ideal solution for controlling read access on outsourced data objects on the cloud, Ciphertext-Policy Attribute-Based Encryption (CP-ABE) has attracted much attention. Some existing CP-ABE schemes handle the read permission delegation through the delegation of the user's private key to others. Still, these schemes lack the further consideration of granularity and traceability of the permission delegation. To this end, this article proposes a flexible and fine-grained CP-ABE key delegation approach that supports white-box traceability. In this approach, the key delegator first examines the relations between the data objects, read permission thereof that he intends to delegate, and the attributes associated with the access policies of these data objects. Then he chooses a minimal attribute set from his attributes according to the principle of least privilege. He constructs the delegation key with the minimal attribute set. Thus, we can achieve the shortest delegation key and minimize the time of key delegation under the premise of guaranteeing the delegator's access control requirement. The Key Generation Center (KGC) then embeds the delegatee's identity into the key to trace the route of the delegation key. Our approach prevents the delegatee from combining his existing key with the new delegation key to access unauthorized data objects. Theoretical analysis and test results show that our approach helps the KGC transfer some of its burdensome key generation tasks to regular users (delegators) to accommodate more users.

• Korean Journal of Construction Engineering and Management
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• v.11 no.4
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• pp.22-31
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• 2010

Because the estimated cost at early stage has great influence on decisions of project owner, the importance of early cost estimation is increasing. However, it depends on experience and knowledge of the estimator mainly due to shortage of information. Those tendency developed into case-based reasoning(CBR) method which solves new problems by adapting previous solution to similar past problems. The performance of CBR model is affected by attribute weight, so that its accurate determination is necessary. Previous research utilizes mathematical method or subjective judgement of estimator. In order to improve the problem of previous research, this suggests CBR schematic cost estimation method using genetic algorithm to determine attribute weight. The cost model employs nearest neighbor retrieval for selecting past case. And it estimates the cost of new cases based on cost information of extracted cases. As the result of validation for 17 testing cases, 3.57% of error rate is calculated. This rate is superior to accuracy rate proposed by AACE and the method to determine attribute weight using multiple regression analysis and feature counting. The CBR cost estimation method improve the accuracy by introducing genetic algorithm for attribute weight. Moreover, this makes user understand the problem-solving process easier than other artificial intelligence method, and find solution within short time through case retrieval algorithm.