• Journal of Distribution Science
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• v.10 no.4
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• pp.47-53
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• 2012

Businesses make use of advertising strategy using models to give consumers efficient product information. Modern advertisements often make use of models for greater reminiscence to create messages and remind viewers of the product. The purpose of this study was to examine the characteristics of each type of model. The subjects were 230 college students in their twenties or older, and the material was collected from October 20, 2011 to November 5, 2011 to examine the effects of model characteristics on buying intention as well as attitude toward a brand. A questionnaire survey was used; investigators gave one copy to each interviewee. The study investigated the characteristics of each model using a questionnaire of each 40 copies with five kinds of photographs. The characteristics of models had great influence on buying intention and attitude toward the brand: First, factor 2 (being honest and virtuous and having good credit and a good press assessment) and factor 3 (being interesting and a good communicator and creating good memories) had great influence on buying intention. Factor 2 was explained by reliability, and factor 3 by the efficiency of the model in creating a feeling. Second, factors 1 (being attractive, smart, unique, friendly, loved by others, and popular), 2, and 3 influenced attitude toward brand. Factor 1 encapsulated the outgoing characteristics of a model, factor 2 was based on reliability, and factor 3 was based on the efficiency of the model in creating a feeling. The model's positive effects on buying intention and attitudes toward brand shall be examined. For their positive influence on buying intention, reliability and efficiency shall be given attention. For their positive influence on attitude toward brand, creating a good impression, having outgoing characteristics, being reliable, and efficiency shall be given attention. The findings were as follows: Model characteristics influencing buying intention were similar to those influencing attitude toward brand. The differences were as follows. First, reliability and efficiency influenced buying intention. When customers were asked to consider the influence on buying intention of an advertisement, regardless of the strength of the buying intention, they considered these two characteristics. Customers decided to buy based not only on the credibility of the product as presented in the advertisement but also the transmission of the contents of the advertisement. Second, outgoing characteristics, reliability, and efficiency influenced attitude toward a brand. The attitude toward a brand was said to be the attitude toward the business. The attitude is produced even after buying, so businesses view it as very important. The attitude might vary depending upon the model used rather than the brand. Therefore, a model with outgoing characteristics was thought to be important. Therefore, attitude toward a brand whose model influenced buying intention as well as attitude toward brand had outgoing characteristics. The result is that an image the model was related to attitude toward the brand. As such, customers would buy the goods advertised. However, an outgoing image of a model was also important to create a positive attitude toward a business brand. For instance, talent Park Gyeong-Rim's photo was used to promote cosmetics about 10 years ago. When she worked as a model of cosmetics products, she had to make compensation for losses and damages because she made a mistake on a talk show program. At that time, customers who had bought the cosmetics product asked for refunds of several billion won. As such, models who are said to be the face of the businesses they represent can play an important role. To advertise in the most attractive and effective way, the current image of a model should be investigated by examining current activities and news articles after selecting the model, and the model's efficiency and attitude toward the brand should be examined. Factors that stimulate customers' buying decisions can be used to plan advertisement that have positive influence on a brand. This study had the limitation of investigating mainly college students and there were insufficient copies of the questionnaire. The investigation was not done widely but in detail so that a concrete investigation could not be done. Further studies shall supplement these shortcomings and discuss new directions.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.1-23
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• 2018

From the 21st century, various high-quality services have come up with the growth of the internet or 'Information and Communication Technologies'. Especially, the scale of E-commerce industry in which Amazon and E-bay are standing out is exploding in a large way. As E-commerce grows, Customers could get what they want to buy easily while comparing various products because more products have been registered at online shopping malls. However, a problem has arisen with the growth of E-commerce. As too many products have been registered, it has become difficult for customers to search what they really need in the flood of products. When customers search for desired products with a generalized keyword, too many products have come out as a result. On the contrary, few products have been searched if customers type in details of products because concrete product-attributes have been registered rarely. In this situation, recognizing texts in images automatically with a machine can be a solution. Because bulk of product details are written in catalogs as image format, most of product information are not searched with text inputs in the current text-based searching system. It means if information in images can be converted to text format, customers can search products with product-details, which make them shop more conveniently. There are various existing OCR(Optical Character Recognition) programs which can recognize texts in images. But existing OCR programs are hard to be applied to catalog because they have problems in recognizing texts in certain circumstances, like texts are not big enough or fonts are not consistent. Therefore, this research suggests the way to recognize keywords in catalog with the Deep Learning algorithm which is state of the art in image-recognition area from 2010s. Single Shot Multibox Detector(SSD), which is a credited model for object-detection performance, can be used with structures re-designed to take into account the difference of text from object. But there is an issue that SSD model needs a lot of labeled-train data to be trained, because of the characteristic of deep learning algorithms, that it should be trained by supervised-learning. To collect data, we can try labelling location and classification information to texts in catalog manually. But if data are collected manually, many problems would come up. Some keywords would be missed because human can make mistakes while labelling train data. And it becomes too time-consuming to collect train data considering the scale of data needed or costly if a lot of workers are hired to shorten the time. Furthermore, if some specific keywords are needed to be trained, searching images that have the words would be difficult, as well. To solve the data issue, this research developed a program which create train data automatically. This program can make images which have various keywords and pictures like catalog and save location-information of keywords at the same time. With this program, not only data can be collected efficiently, but also the performance of SSD model becomes better. The SSD model recorded 81.99% of recognition rate with 20,000 data created by the program. Moreover, this research had an efficiency test of SSD model according to data differences to analyze what feature of data exert influence upon the performance of recognizing texts in images. As a result, it is figured out that the number of labeled keywords, the addition of overlapped keyword label, the existence of keywords that is not labeled, the spaces among keywords and the differences of background images are related to the performance of SSD model. This test can lead performance improvement of SSD model or other text-recognizing machine based on deep learning algorithm with high-quality data. SSD model which is re-designed to recognize texts in images and the program developed for creating train data are expected to contribute to improvement of searching system in E-commerce. Suppliers can put less time to register keywords for products and customers can search products with product-details which is written on the catalog.

• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.23-38
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• 2012

There is a large difference between purchasing patterns in an online shopping mall and in an offline market. This difference may be caused mainly by the difference in accessibility of online and offline markets. It means that an interval between the initial purchasing decision and its realization appears to be relatively short in an online shopping mall, because a customer can make an order immediately. Because of the short interval between a purchasing decision and its realization, an online shopping mall transaction usually contains fewer items than that of an offline market. In an offline market, customers usually keep some items in mind and buy them all at once a few days after deciding to buy them, instead of buying each item individually and immediately. On the contrary, more than 70% of online shopping mall transactions contain only one item. This statistic implies that traditional data mining techniques cannot be directly applied to online market analysis, because hardly any association rules can survive with an acceptable level of Support because of too many Null Transactions. Most market basket analyses on online shopping mall transactions, therefore, have been performed by expanding the co-occurrence criteria of traditional association rule mining. While the traditional co-occurrence criteria defines items purchased in one transaction as concurrently purchased items, the expanded co-occurrence criteria regards items purchased by a customer during some predefined period (e.g., a day) as concurrently purchased items. In studies using expanded co-occurrence criteria, however, the criteria has been defined arbitrarily by researchers without any theoretical grounds or agreement. The lack of clear grounds of adopting a certain co-occurrence criteria degrades the reliability of the analytical results. Moreover, it is hard to derive new meaningful findings by combining the outcomes of previous individual studies. In this paper, we attempt to compare expanded co-occurrence criteria and propose a guideline for selecting an appropriate one. First of all, we compare the accuracy of association rules discovered according to various co-occurrence criteria. By doing this experiment we expect that we can provide a guideline for selecting appropriate co-occurrence criteria that corresponds to the purpose of the analysis. Additionally, we will perform similar experiments with several groups of customers that are segmented by each customer's average duration between orders. By this experiment, we attempt to discover the relationship between the optimal co-occurrence criteria and the customer's average duration between orders. Finally, by a series of experiments, we expect that we can provide basic guidelines for developing customized recommendation systems. Our experiments use a real dataset acquired from one of the largest internet shopping malls in Korea. We use 66,278 transactions of 3,847 customers conducted during the last two years. Overall results show that the accuracy of association rules of frequent shoppers (whose average duration between orders is relatively short) is higher than that of causal shoppers. In addition we discover that with frequent shoppers, the accuracy of association rules appears very high when the co-occurrence criteria of the training set corresponds to the validation set (i.e., target set). It implies that the co-occurrence criteria of frequent shoppers should be set according to the application purpose period. For example, an analyzer should use a day as a co-occurrence criterion if he/she wants to offer a coupon valid only for a day to potential customers who will use the coupon. On the contrary, an analyzer should use a month as a co-occurrence criterion if he/she wants to publish a coupon book that can be used for a month. In the case of causal shoppers, the accuracy of association rules appears to not be affected by the period of the application purposes. The accuracy of the causal shoppers' association rules becomes higher when the longer co-occurrence criterion has been adopted. It implies that an analyzer has to set the co-occurrence criterion for as long as possible, regardless of the application purpose period.

• Journal of Food Hygiene and Safety
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• v.33 no.4
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• pp.259-265
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• 2018

Since Korean housewives are responsible for the dietary practices of family at home, it is important to know what information will make them to buy safe food. This study was designed to determine the role of perceived threats, behavioral assessments, and self-efficacy factors known to promote healthy behavior in health belief models (HBM) based on food safety awareness and behavior of housewives. This study involved 191 housewives, based on key variables such as perceived severity, perceived susceptibility, perceived benefits, perceived barriers, self-efficacy, and purchase behavior. The results showed that higher levels of education and urbanization increased the threat perception and the likelihood of buying safe food. The correlation analysis showed that increased awareness and knowledge of safe foods and interest in health contributed to higher relative benefit or self-efficiency of food, and thus, ensured food safety. The conceptual model of food safety behavior based on the HBM was verified via structural equation analysis. The findings suggest that a suitable model showcasing knowledge levels and relative benefits resulted in a greater impact on purchasing behavior than perceived threats. This study suggests that it is more effective for housewives to provide more preventive information than risk information to purchase safe food.

• The Korean Journal of Financial Management
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• v.24 no.1
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• pp.1-27
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• 2007

In this study, we investigated the market long-term performance of stock splits by using the Korean Stock Market data from 1998 through 2002. We measured the performance by the event-time portfolio approach with the buy-and-hold abnormal return(BHAR) and the cumulative average abnormal return(CAAR). Also, the calendar-time portfolio approach with one-factor and three factor model were used for avoiding the misspecification model problem. The first of main results in this study was that the stock splits had significantly positive abnormal returns around the month of the stock splits announcements. However, the period BHAR and CAAR after the announcement month were significantly negative. This negative long-term abnormal returns were confirmed by the calendar-time portfolio approach. The results suggested that the abnormal return followed by the stock splits seemed to be positive in the short-term period. Second, there was no the difference of the long term performance between the high and the low split ratios. The operating income performance in the periods followed by the stock splits announcements grew worse. Therefore, the signalling effects, the managers of the firm under considering the stock splits would make use of splits as a form of signals for the upward changes in the cash flow or profits, could not be found. Finally, in contrast to Fama, Fisher, Jensen and Roll(1969), the significant negative abnormal returns following the stock splits were still found irrespective of the change of dividend payout ratio.

• Archives of design research
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• v.18 no.2 s.60
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• pp.27-36
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• 2005

Illustrations in advertisement uses various social and cultural codes to stimulate the desire to buy in consumers in the first place, since this is an economic phenomenon orchestrated to sell a product. Hence, factors outside the product per se, such as tradition, social issues and class consciousness are introduced. Especially, in modern advertisement a strategy is adopted to differentiate standard products produced by mass production. In order to do so, such factors as mentioned above become as important as physical characteristics of the product per se and its usage value. As a result, phrases or images used for advertisement can have independent influences on the society irrespective of the sales effects on the product. In this respect, it is fair to state that advertisement reflects the phases and consciousness of a given period as a cultural phenomenon. Therefore, based on the premise of characteristics and roles attributed to the advertisement, this thesis proposes to make a comparative study on the images of women in commercial advertisement in Korea during Japanese Imperialism and China during Cultural Colonial period dating from 1900 to 1945. The starting point of this research will cover the period of foreign trade and Japanese Imperialism in Korea and interference of Western Power in China. It will also investigate on the birth of Korean advertisement by Japanese Imperialists and Chinese modern advertisement along with the modernization of Shanghai. Then, I propose to present the illustrations of women in advertisements based on comparative study of their characteristics and expressions as observed in several case studies both in Korea and China. Connotative meanings in such advertisement will be investigated in the context of political, economic and cultural dominance.

• Journal of the Ergonomics Society of Korea
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• v.34 no.3
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• pp.199-215
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• 2015

Objective: The purpose of this study is to find the level of physical relaxation of individual subject by monitoring psychophysiological biofeedback to different types of mattresses. And, the study also aims to find a protocol to make a selection of the best mattress based on the measured information. Background: In Korea, there are an increasing number of people using western style bed. However, they are often fastidious in choosing the right mattress for them. In fact, people use their past experience with their old mattress as well as the spontaneous experience they encounter in a show room to finally decide to buy a bed. Method: Total five mattresses were tested in this study. After measuring the elasticity of the mattresses, they were sorted into five different classes. Physiological and psychological variables including Electromyography (EMG), heart rates (HR), oxygen saturations (SaO2) were used. In addition, the peak body pressure concentration rate was used to find uncomfortably pressured body part. Finally, the personal factors and subjective satisfaction were also examined. A protocol was made to select the best mattress for individual subject. The selection rule for the protocol considered all the variables tested in this study. Results: The result revealing psychological comfort range of 0.68 to 0.95, dermal comfort range of 3.15 to 6.07, back muscle relaxation range of 0.25 to 1.64 and personal habit range of 2.0 to 3.4 was drawn in this study. Also a regression model was developed to predict biofeedback with the minimal use of biofeedback devices. Moreover results from the proposed protocol with the regression equation and subjective satisfaction were compared with each other for validation. Ten out of twenty subjects recorded the same level of relaxation, and eight subjects showed one-level difference while two subjects showed two-levels difference. Conclusion: The psychophysiological variables and suitability selection process used in this study seem to be used for selecting and assessing ergonomic products mechanically or emotionally. Application: This regression model can be applied to the mattress industry to estimate back muscle relaxation using dermal, psychophysiology and personal habit values.

• Journal of Digital Convergence
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• v.12 no.2
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• pp.151-162
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• 2014

One of the largest changes in retail business in Korea since the distribution market was opened in the mid 1990s is the appearance of foreign discount stores and the rapid growth of department stores. Discount stores and department stores have changed the structure of distribution business which has been primarily made up of traditional markets and supermarkets that have been the main retail markets in Korea. The retail business is changing from just a product purchasing place to a space where various values such as pleasure, happiness, etc. are provided. Therefore the purpose of this research is to grasp the effects that the shopping experience values at department stores have on the department brands, images, and awareness by means of theoretical and empirical research. Especially I classified the shopping experience values, an independent variable, into aesthetics, pleasures, consumers' interests, and services' excellence, and I verified whether they have a meaningful effects on the brand recognition and image, an endogenous variable, and the store royalty, a final various. A total of 235 questionnaires were used for analysis to test the research hypotheses. The positive analysis was done with SPSS 17.0K and AMOS 17.0 covariance structure analysis was performed. As a result, variables of the shopping experience values except consumers' interests seemed to have not only right influences on recognition and image, but also right influences on store royalty. Therefore this research shows that department store customers not only make use of department stores to buy products, but also visit department stores to get the values of pleasure and happiness, and that these aspects have a greater influence on the department store's image, recognition, or royalty in a sense.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.3
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• pp.49-55
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• 2015

Nanotechnology has been growing constantly and it is becoming the leading technology in scientific research and development. Although nanotechnology has important applications in broad variety of fields without boundary of any particular industrial area, the study of nanotechnology related to its commercialization has been conducted in a few ways. To put that figure in context, this study investigates public and expert perceptions about negative potentials of nanotechnology. Through a series of surveys with public (N = 541) and experts (N = 62), we analyzed about public willingness to pay for nano-applied products. Survey results showed that public and experts preferred nano-applied products in the order of electronics, cosmetics, and food and medicine. Experts express high payment intention to electronics rather than public intention. In addition, the survey results showed the purchasing intention of both public and expert group was affected by the attributes of nano-applied products in the order of risk fatality, risk chance, certification, and labeling. But experts put more importance in risk fatality than risk chance comparing to public. Through the case analysis of the effects of labeling and certification, we revealed either labeling or certification can induce both public and experts to buy the nano-applied products with high risk chance and low risk fatality. However, for the nano-applied product with high risk fatality and low risk chance, both labeling and certification are simultaneously required to make customers have positive purchasing intention. The result of this study could be utilized for the nanotechnology-based company to get the consumer behavior information about nano-based product and to establish their marketing strategy.

• Journal of Digital Contents Society
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• v.10 no.2
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• pp.199-207
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• 2009

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