• Korean Journal of Human Ecology
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• v.15 no.3
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• pp.491-499
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• 2006

The purpose of this study is to measure the pizza purchasing behavioral characteristics of respondents and importances of factors affecting pizza purchase, to estimate the effects of attributes on choice of pizza restaurant, and to predict probability of selecting a particular pizza restaurant. The questionnaire consisted of two parts: The paired experimental profiles, purchasing behavior and importances of factors affecting pizza purchase. This study generated profiles of 16 hypothetical pizza restaurants based on seven attributes. The profiles comprised 16 discrete sets of variables, each of which had two levels. For this study, researcher randomly selected 150 university students as respondents. Twenty one students did not complete the survey instrument, resulting in a final sample size of 129. All estimations were carried out using frequencies, $X^2$, independent samples t-test, phreg procedure of SAS package. The results were as followed: Some purchasing behavioral characteristics and importances of factors affecting pizza purchase were significantly different by purchase frequency. Based on the estimated models developed for the two purchase frequency groups, the Chi-square statistics were significant at p<0.001. The parameter estimate for late delivery time with frequently purchase frequency group was highest, and the parameter estimate for price with frequently purchase frequency group was highest. The pizza restaurants that charged 20,000 won, offered 100% discount on eleventh pizza, promised to deliver pizza in 20 min, usually delivered the pizza as promised, offered 2 or more types of pizza crust, delivered steaming hot pizza, and did not offer a money-back guarantee which was favored by each of the two purchase frequency groups. The results from this study suggested that there was an opportunity to increase market share and profit by improving operations so that customers can receive discount and money-back guarantee simultaneously, and by reducing price, delivery time.

• Korean Journal of Construction Engineering and Management
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• v.11 no.1
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• pp.113-121
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• 2010

Since the cut-down of the purchasing price of the feed in tariff(FIT) in 2008, the numbers of photovoltaic projects get decreased, contrary to investment expansion policy of government on renewable energy. The root cause of the decrease is the irrationality of the current purchasing price structure of FIT as well as the adversity of fund raising due to the global financial crisis. This study proposes the FIT calculating model (Cost & Benefit Risk Based Purchase Price Process : CBRP3) reflecting the fluctuation of cost and benefit risks. The first step is to establish the photovoltaic generation alternatives, and to calculate each distribution data of the investment and the power generation quantity. The FIT for each alternative is, then, assessed through simulations. Finally the proposed FIT scheme is compared to the present FIT scheme and future study subjects are derived.

• Journal of the Korean Society of Food Culture
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• v.21 no.1
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• pp.57-64
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• 2006

The purpose of this study was to measure the pizza purchasing behavioral characteristics of respondents and importances of factors affecting pizza purchase, to estimate the effects of attributes on pizza restaurant choice, and to predict probability of selecting a particular pizza restaurant. The questionnaire consisted of two parts: The paired experimental profiles, purchasing behavior and importances of factors affecting pizza purchase. This study generated profiles of 16 hypothetical pizza restaurant based on the seven attributes. The profiles comprised 16 discrete sets of variables, each of which had two levels. For this study, researcher randomly selected 150 students of university as respondents. Twenty students did not complete the survey instrument, resulting in a final sample size of 129. All estimations were carried out using frequencies, $X^2$, independent samples t-test, phreg procedure of SAS package. The results are as follows. Some purchasing behavioral characteristics and importances of factors affecting pizza purchase were significantly different by gender. Based on the estimated models developed for male student group and female student group, the Chi-square statistics were significant at p<0.001. The parameter estimate for late delivery time with male student group was highest, and the parameter estimate for price with female student group was highest. The pizza restaurant that charged \20,000, offered 100% discount on eleventh pizza, promised to deliver pizza in 40 mins, usually delivered the pizza as promised time, offered only 1 type of pizza crust, delivered warm pizza, offered the money-back guarantee was favored by each of male student group and female student group. The results from this study suggested that there was an opportunity to increase market share and profit by improving operations so that customers receive discount and money-back guarantee simultaneously, and by reducing price, delivery time.

• The Journal of Industrial Distribution & Business
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• v.10 no.6
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• pp.39-50
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• 2019

Purpose - Since the local liquor industry uses the agricultural products produced in the region as the main raw material, cultivation of the industry can be a way to expand the demand for domestic agricultural products and can contribute to the income increase of the farmers. In addition, the local liquor industry can be developed into a region-specific industry differentiated from other regions by linking with the region's tourism resources. Therefore, in order to achieve various derivative effects through promotion of the local liquor industry, it is necessary to precisely understand the factors related to the purchase and consumption of local liquor which then will lead to an increase in consumption. This study analyzes the current status and problems of local liquor industries and examines the determinants of consumers' purchasing decisions of regional specialties through questionnaires. We will then propose a strategy to promote consumption of locally produced alcoholic beverages. Research design, data, and methodology - An online Domestic Consumer Survey was conducted to identify the actual purchases and uses of local liquors for 500 consumers nationwide. Based on the questionnaire results, the analysis uses an ordered probit model. Results - As a result of analyzing the effect of consumer characteristics on the purchase of local liquors, it was found that the average cost of drinking, income, local specialty, brewery experience, and health concerns have a significant effect on gender, drinking frequency. All the variables except the participation in the training of the special provincial manufacturing method were found to be statistically significant. The statistical significance was at a 1% significance level for the remaining factors excluding the bottle design. This shows that the higher taste, quality, price, and harmony with food, the higher the probability of purchasing local liquors. Conclusions - In the analysis of factors influencing the purchase intention of local liquors, it was found that factors such as taste, quality, price, and harmony with food had a significant effect. Given the diversity of purchasing factors, the importance of diversification strategies is emphasized again. In particular, it will be important to secure wide publicity for local liquors through various PR strategies.

• Journal of Distribution Science
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• v.14 no.4
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• pp.117-125
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• 2016

Purpose - As consumers' needs for purchasing fresh and safe food have been bigger in Korea, their interest in local food is also growing recently. So, the number of local food stores has been increased from 3 in 2012 to 103 in 2015. Local food stores should operate a business responding consumers' needs in order that local food stores are not to be a one-time fad. Therefore, the purpose of this study is to analyze the characteristics of consumers who use a local food store and provide helpful implications to design a strategy for sustainable growth of local food store. Research design, data, and methodology - In this study, Probit model was used for empirical analysis in order to examine the effect of purchase choice attributes of agricultural products, consumer's satisfaction, and their demographic factors upon the intention to use a local food store. After estimating coefficients of the probit model, marginal effects were calculated as a standard normal, and cumulative distribution is differentiated with respect to explanatory variables. To collect the data, questionnaire survey was carried out with the consumers using the local food store (Youngjin Nonghyup near to Jeonju city located in Jeollabuk-do). Result - The data analysis found that the more consumers are satisfied with local food store, the higher intention they have to use the local food store. In addition, it was known that the factors related to quality of agricultural products and shopping convenience among the purchase choice attributes have a considerable impact on the purchase intention of a local food store. In demographic factors, income was turned out to be an important factor affecting purchase intention of local food. Such a result supports the hypothesis that high income consumers are likely to purchase local food, which is based on the inference that consumers who have a high income tend to pursue wellbeing life. Futhermore, information delivery, through a reputable media source among general factors, was known to play an important role in forming an intention to purchase local food. According to the analysis of marginal effects, probability of purchase intention of a local food store is increased by 11.4%, if a monthly average income of a household is above 4.5 million Won(Korean currency). If purchasing satisfaction with local food stores is high, the probability of purchase intention would be increased by 24.1%. Likewise, such a probability goes up by 8.7%, 5.8%, respectively as an increasing one unit of quality of agricultural products and shopping convenience of local food stores, respectively. Conclusion - For attaining sustainable growth in a local food store, it is considered necessarily to establish a proper store operation system to meet consumers' needs, especially for quality and shopping convenience of local food. Moreover, as it was found that appropriate communication through media source has a positive effect on the intention to use local food store, PR activity seems to be necessary to expand the consumers' demands for local foods.

• Journal of Distribution Science
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• v.10 no.3
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• pp.7-13
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• 2012

Recently, with the success of Groupon in the USA using the new business model referred to as social commerce, which is a commercial transaction involving group purchases on social network service (SNS), social commerce business receives much attention. Social commerce is capable of effectively promoting additional purchasing by customers through unprecedented price discounts and limiting the number of purchasers and time allotted for purchases, and is able to achieve promotional effects over and above those of simple product promotion due to customers' voluntary word of mouth. Although social commerce is effective for short-term increase in the sales of products, there are numerous dissenting opinions on whether it can promote repurchasing by customers. In particular, social commerce in Korea focuses only on unprecedented discounted prices and does not have the marketing effect that SNS can produce over and above the sales promotion. The objective of this study is to find the factors that influence the repurchase intention on social commerce and to analyze factors that contribute the social commerce product. For this, this study extracts repurchase intention factors and computes a repurchase probability to assess the influence of factors other than price discount on social commerce customers at the time of repurchasing. In addition, the importance of factors toward sales revenue for each of the social commerce products (e.g., restaurant/café, beauty, tour/leisure, show/exhibition, and fashion/clothes) is estimated by using the computed repurchase probabilities. The repurchase probability through the analysis can be used for development of social commerce business in Korea.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.1
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• pp.10-16
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• 2015

In this study, we suggest a method to predict probability distribution of a new customer's degree of loyalty using C-CRF that reflects the RFM score and similarity to the neighbors of the customer. An RFM score prediction model is introduced to construct the first feature function of C-CRF. Integrating demographical similarity, purchasing characteristic similarity and purchase history similarity, we make a unified similarity variable to configure the second feature function of C-CRF. Then parameters of each feature function are estimated and we train our C-CRF model by training data set and suggest a probabilistic distribution to estimate a new customer's degree of loyalty. An example is provided to illustrate our model.

• Journal of Families and Better Life
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• v.15 no.3
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• pp.139-152
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• 1997

The purpose of this study was to (1) identify sociodemograghic, economic, psychological and use of credit variables that influence the late payment behavior of three types of consumer credit which are service credit, credit card, installment purchasing credit, (2) compare the levels of the credit counselling between the normal payment behavior group and the late payment behavior group about both of the counselling experiences and needs. Data were collected from questionnaires with 337 adults who were residents of Seoul. The major findings are as follows ; (1) There are independently significant probability differences for measure of the sociodemographic, economic, psychological and use of credit variables on dichotomous Logit analysis (2) Both the experience and need levels of credit counselling were concentrated on the family.

• Management Science and Financial Engineering
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• v.12 no.2
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• pp.71-85
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• 2006

Collaborative filtering, among other recommender systems, has been known as the most successful recommendation technique. However, it requires the user-item rating data, which may not be easily available. As an alternative, some collaborative filtering algorithms have been developed recently by utilizing the market basket data in the form of the binary user-item matrix. Viewing the recommendation scheme as a two-class classification problem, we proposed a new collaborative filtering scheme using a regularized discriminant analysis applied to the binary user-item data. The proposed discriminant model was built in terms of the major principal components and was used for predicting the probability of purchasing a particular item by an active user. The proposed scheme was illustrated with two modified real data sets and its performance was compared with the existing user-based approach in terms of the recommendation precision.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1659-1673
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• 2019

Android platform provides In-app Billing service for purchasing valuable items inside mobile applications. However, it has become a major target for attackers to achieve valuable items without actual payment. Especially, application developers suffer from automated attacks targeting all the applications in the device, not a specific application. In this paper, we propose a novel scheme detecting automated attacks with probabilistic tests. The scheme tests the signature verification method in a non-deterministic way, and if the method was replaced by the automated attack, the scheme detects it with very high probability. Both the analysis and the experiment result show that the developers can prevent their applications from automated attacks securely and efficiently by using of the proposed scheme.