• Culinary science and hospitality research
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• v.16 no.3
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• pp.14-31
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• 2010

Lifestyle has the largest influence on purchasing intention. Currently, consumers have to be adjusted to dynamic environmental change, therefore they are demanding more and more on bakery items and functional food products. It is important to understand the trend of customers' eating habits and the effect of this trend on purchasing intention as well as the development of special characteristics in purchase, viewpoints, and behaviors. Based on this fact, this study was conducted to classify the types of lifestyle according to the consumer's behavior and to examine how the variety and quality of bakery products affect consumer's purchasing pattern. The subjects of this survey were housewives in thirties and forties at the national capital region. AIO(activities, interests, opinions) analysis was used to classify lifestyle and to investigate the effect or relationship between lifestyle, variety and quality of bakery products. Lifestyle was classified into the pursuit of rationality, the pursuit of utility and the pursuit of convenience. The information was the most concerning area in the pursuit of rationality, the taste in the pursuit of utility, and convenience in the pursuit of convenience. The purchasing intention was not affected by the quality of the bakery product itself but by the satisfaction with the service of the bakery.

• Journal of the Korean Society of Costume
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• v.51 no.2
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• pp.105-120
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• 2001

The purpose of this study is to identify the relationship of self-efficacy, which is a kind of the self concept about one's own ability, to the decision-making process, which is the key part of consumer behavior. The subjects in this study were 985 male and female undergraduates of a university located in the city of Kyongsan, the north Kyongsang province. The collected data were statistically processed by MANOVA and ANOVA. For post test, Scaffle and $\chi$$^2$-test were employed. The followings are findings of this study : 1. Concerning incentive to buying, the group having the weaker general self-efficacy is stimulated more highly by the incentives of self-display, fashion pursuit and economic utility than the group having the stronger general self-efficacy does. 2. Regarding information sources. the factor of observation is frequently used by the group having the weaker general and social self-efficacies more than the group having the stronger general and social self-efficacies. 3. As to the evaluative criteria of clothes, the group having the stronger general and social self-efficacies put a higher value on functional and economical points than the group having the weaker general and social self-efficacies does. 4. As for the evaluative criteria of store the group having the stronger general self-efficacy lays stress on store atmosphere, store attributes and convenient shopping condition, while the group having the weaker general self-efficacy puts emphasis on brand and fashion. 5. In buying apparels, the group having the stronger general and social self-efficacies makes more planned purchase.

• Korean Journal of Human Ecology
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• v.15 no.4
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• pp.623-630
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• 2006

The purpose of this study is to do research hairdressers' knowledge of hairless head dummy's brand name, and to suggest and develop various hairless head dummy for the students who are learning hair styling in the colleges and the academies, for the hairdressers working in the beauty salons. Using only one and same kind of hairless head model is not appropriate for hairdressers and students being trained hair styling skill, because people have a variety of head shapes. Three hundred twenty nine persons who live in Iksan area are selected as subjects. The results of the study are as follow: by the analysis of subjects' knowledge of hairless head dummy's brand name, most of them didn't know it exactly. This study deduced that there is a significant relation between the utility of hairless head dummy and subjects' intention of purchasing the dummy. To put it in detail, in case of college students, there is little significant difference between them. But in case of academy students, there is. By the regression analysis, especially, in case of hairdressers working in beauty salons and academy students, four conditions did significantly matter in their purchasing the dummy: first, whether the respondents owns it, second, whether it is helpful to themselves, third, whether they have ever used foreign products and, finally, whether they have intention to purchase various hairless head dummys or not. In conclusion, it depended on each group position whether their knowledge of brand names of hairless head model affects their purchase of the dummy or not.

• The Journal of the Korea Contents Association
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• v.10 no.2
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• pp.320-329
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• 2010

As software producers have tried to keep their profit against illegal piracy, contents producers also want to protect their contents from unlawful sharing among users. Some researchers uncovered that the regulation on the unlicensed contents is not the best policy to maximize their profit mainly due to network effect but this issue has been still controversial. In this paper, we develop a model to investigate the effect of regulation against unlicensed contents sharing on the profit of contents producers and present the optimal condition to maximize profit of contents producers under the regulation and non-regulation of unlicensed contents. As a result, we analyzed that the firm's payoff under the regulation on unlicensed contents is not always greater than the payoff under the non-regulation because of network externality. If the additional utility from off-line purchase of type P consumers (who enjoy the additional benefit of off-line purchase) is large enough, then the firm's payoff is maximized without regulation.

• Journal of the East Asian Society of Dietary Life
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• v.24 no.6
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• pp.915-923
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• 2014

This study investigated organic coffee choice motives from a coffee shop market segmentation perspective in order to understand the potential importance they may have upon attitudes and behavioral intentions to buy organic coffee. A factor-cluster segmentation approach was used for this study. An exploratory factor analysis identified five organic coffee choice motives: 'Sensory', 'Environment', 'Trust', 'Health' and 'Price'. Based upon these five choice motives, cluster analyses classified all respondents into three homogeneous subgroups: 'Highly motivated', 'Moderately motivated' and 'Unmotivated'. Analysis of variance tests indicated that attitudes and intentions to purchase organic coffee were significantly different among the three clusters. In particular, two cluster groups representing 'Highly motivated' and 'Moderately motivated' were found to offer the most utility for further organic coffee market segmentation research. Especially, due to perceptions about high price premium of organic coffee, the 'Moderately motivated' group had higher positive attitudes, although, their intentions to buy organic coffee were not higher than those of the 'Unmotivated' cluster. Findings support previous research propositions that high price could be the strongest barrier for people to purchase organic products including the organic coffee business context. This will assist to market and promote pricing strategies for caf$\acute{e}$s and restaurants to optimize organic coffee sales revenue. Implications for all cluster groups regarding unique socio-demographic characteristics and behavioral intentions are discussed. Organic coffee marketers can apply these findings towards the development of effective target market strategies.

• The Journal of Bigdata
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• v.7 no.1
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• pp.213-224
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• 2022

In logistics and distribution, Market Basket Analysis (MBA) is used as an important means to analyze the correlation between major sales products and to increase internal operational efficiency. In particular, the results of market basket analysis are used as important reference data for decision-making processes such as product purchase prediction, product recommendation, and product display structure in stores. With the recent development of e-commerce, the number of items handled by a single distribution and logistics company has rapidly increased, And the existing analytical methods such as Apriori and FP-Growth have slowed down due to the exponential increase in the amount of calculation and applied to actual business. There is a limit to examining important association rules to overcome this limitation, In this study, at the Main-Category level, which is the highest classification system of products, the utility item set mining technique that can consider the sales volume of products together was used to first select a group of products mainly sold together. Then, at the sub-category level, the types of products sold together were identified using FP-Growth. By using this sequential layer filtering technique, it may be possible to reduce the unnecessary calculations and to find practically usable rules for enhancing the effectiveness and profitability.

• Asia-Pacific Journal of Business
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• v.12 no.1
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• pp.135-149
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• 2021

Purpose - I analyzes risk-to-performance evaluated in the market using data from sale and lease back. Specifically, I analyze from the perspective of financial institutions that purchase sale and lease back based on the cases of investment by ship investment companies and acquisition of ships. Design/methodology/approach - I use 49 sale and lease back data from 2017 to 2019 for empirical analysis. Findings - The main results of this paper are as follows. First, after sale and lease back of domestic ships, the average amount of sales by the leased shipping company is 25.1 billion won, the average amount of investment by the purchased financial institution is 14.6 billion won (60%) and the average length of the ship is nine years. In ship finance, sale and lease back is deemed to be appropriately used as a means of restructuring for a large amount of money. Second, the main risk factor for sale and lease back of domestic ships is credit risk and can be measured in VaR in practice. As a result of the empirical analysis, the average credit risk burden ratio is 9%. As a major risk factor, low creditworthiness of restructuring companies is the key. Third, as a result of measuring the profitability of financial institutions that purchase sale and lease back of domestic ships at a net current price, it has an average value of 300 million won, but the deviation by case is very large. Fourth, the risk adjusted performance of sale and lease back of domestic ships is 0.54 on average compared to the total risk capital, and 0.52 compared to the stock-risk capital, and as with profitability earlier, the deviation of each case is very large and misaligned. In order to boost the sale and lease back market for large and long-term assets, in order to overcome low profitability as a prerequisite for future participation of commercial purchased financial institutions, it is expected that purchase decisions based on expectations versus risk will be necessary. Research implications or Originality - The results of this paper are expected to broaden the understanding of sale and lease back and foster the ability to assess long-term risk and performance. Based on this, it is believed that rapid restructuring of companies through sale and lease back of large amounts of long-term assets will greatly increase the utility of the domestic financial market.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.26 no.4
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• pp.105-121
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• 2015

PDA model is new collection development method not only corresponding user's demand, but also expensing acquisition budget effectively. In the PDA model, when the trigger that indicates user's demand reaches up to treshold, e-book is automatically purchased without librarian's interrogation. This study examines concept, basic principles, and current condition of operation about PDA and finds a way that could applicate to Korean university library foreign E-book consortium. Current model of university library e-book acquisition pursuit reduction of budget and utility value, but the selected collection is not based on user's demand. Therefore, it could be considerable to apply PDA or evidence based purchase model to foreign e-book acquisition consortium.

• Journal of Agricultural Extension & Community Development
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• v.25 no.1
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• pp.31-44
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• 2018

This is a case study on "the Project for Production Facility and Technical Support of Processed Seed-Potato (2008-2010)" based on the Value Chain Analysis (VCA) used to create and plan International development cooperation projects. The project is the earliest model of Creating Shared Value (CSV) in the agricultural sector. For the case analysis, a framework was established to assess the effectiveness and impact of the CSV project based on the main factors of the VCA. As a result of the assessment, project participation by OSI was able to increase the overall utility by developing the Vietnamese potato processing industry and meeting consumer demand. Furthermore, it formed a business model to promote win-win cooperation and upgraded the value chain of the potato industry. In addition, it contributed to the improvement of incomes and the quality of life of farmers and communities by providing technical guidance and purchase of contracts, as well as labor division and cooperation with other activity supporters.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.538-561
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• 2020

Recommender Systems (RecSys) have a major role in e-commerce for recommending products, which they may like for every user and thus improve their business aspects. Although many types of RecSyss are there in the research field, the state of the art RecSys has focused on finding the user similarity based on sequence (e.g. purchase history, movie-watching history) analyzing and prediction techniques like Recurrent Neural Network in Deep learning. That is RecSys has considered as a sequence prediction problem. However, evaluation of similarities among the customers is challenging while considering temporal aspects, context and multi-component ratings of the item-records in the customer sequences. For addressing this issue, we are proposing a Deep Learning based model which learns customer similarity directly from the sequence to sequence similarity as well as item to item similarity by considering all features of the item, contexts, and rating components using Dynamic Temporal Warping(DTW) distance measure for dynamic temporal matching and 2D-GRU (Two Dimensional-Gated Recurrent Unit) architecture. This will overcome the limitation of non-linearity in the time dimension while measuring the similarity, and the find patterns more accurately and speedily from temporal and spatial contexts. Experiment on the real world movie data set LDOS-CoMoDa demonstrates the efficacy and promising utility of the proposed personalized RecSys architecture.