• Information Systems Review
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• v.7 no.1
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• pp.97-113
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• 2005

This paper designed and implemented(programmed) a comparative shopping agent that helps consumers to shop at on-line shopping malls over Internet. At offline stores, as consumers usually tell a sales clerk about a manufacturer, functions and price range of an item they want to purchase, the sales clerk will show the products or relevant catalogues. Then the consumer will compare functions, design and prices of the product and buy it with the lowest price. PriceMeter, a comparative shopping agent, introduced in this paper, is designed best geared to this consumers' buying behavior. Basically, as consumers enter a manufacturer's name, price, features and etc. at a search window, PriceMeter will search the web and provide a list of product informations such as features and prices that meet the search conditions. Consumers can see the information in either a form of catalogue or a printing format. As consumers click specific items to examine closely, it will show prices and information about shopping malls that sell the requested items. Clicking a 'Buy' icon, the consumers will be transferred to the right web page at the linked shopping mall. The emergence of the comparative shopping agent will expedite a consumer-centered retailing economy in the age of e-commerce. As consumers are provided with a better set of product and shopping mall information, they can make better purchasing decisions and gain more bargaining power shifted from manufacturers(sellers). The presentation of this comparative shopping agent is intended to promote the consumer-centered B2C e-commerce.

• Asia Marketing Journal
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• v.10 no.1
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• pp.25-64
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• 2008

Third-Party awards are growing in popularity. They are the hit product of the year chosen by The Korea Economic Daily, the best 10 products of the year chosen by Sports paper, the best hit product chosen by consulting firm and the best venture company of the year chosen by Information and Communication Ministry. Then these questions may be followed. Why industry likes this type of advertisement? Does this type of advertisement influences consumers' purchase intention? And if it does, how? Many researchers have been interested in external cue of product quality by focusing research effort on brand, price, producer, warranty etc. However, important but under-explored area is the role of third-party reference for signaling product quality. This paper comes from the idea that the third-party reference may signal consumers like manufacturer brand, product brand, product price, and shop brand. We develop a related theories to address research questions and drive some research hypotheses based on the previous studies probing source credibility, attribution, and signal theory. We put more emphasis on source credibility. We conducted the research based on 3x2x2x2 between group factorial design to explore causal relationship between the third party award winning advertising(real, fictional, no) and the purchase intention of consumers exposed to other information simultaneously such as product type(experience, search), distribution channel(direct, indirect) and perceived price(high, low). Since subjects are divided into 2 groups based on the means of response without extra experimental stimulus in case of perceived price. 12 different advertisements are used for conducting this study. The results are followings. First, the source credibility of the third party goes up, consumers' purchase intention would go up. It seems that consumers think the credibility of the third-party most when they are exposed to the third party award winning advertisement. Second, the product type does moderate the relationship between the third-party award winning advertisement and purchase intention. And the type of the distribution channel also moderates this relationship. The consumers' purchase intention goes up higher when they buy experience good and there is significant difference of purchase intention when consumers are exposed to direct channel treatment condition. But, perceived price has nothing to do with the third-party winning advertisement context for raising consumer intention to buy advertised product.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.1-15
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• 2021

If it is difficult for us to make decisions, we ask for advice from friends or people around us. When we decide to buy products online, we read anonymous reviews and buy them. With the advent of the Data-driven era, IT technology's development is spilling out many data from individuals to objects. Companies or individuals have accumulated, processed, and analyzed such a large amount of data that they can now make decisions or execute directly using data that used to depend on experts. Nowadays, the recommender system plays a vital role in determining the user's preferences to purchase goods and uses a recommender system to induce clicks on web services (Facebook, Amazon, Netflix, Youtube). For example, Youtube's recommender system, which is used by 1 billion people worldwide every month, includes videos that users like, "like" and videos they watched. Recommended system research is deeply linked to practical business. Therefore, many researchers are interested in building better solutions. Recommender systems use the information obtained from their users to generate recommendations because the development of the provided recommender systems requires information on items that are likely to be preferred by the user. We began to trust patterns and rules derived from data rather than empirical intuition through the recommender systems. The capacity and development of data have led machine learning to develop deep learning. However, such recommender systems are not all solutions. Proceeding with the recommender systems, there should be no scarcity in all data and a sufficient amount. Also, it requires detailed information about the individual. The recommender systems work correctly when these conditions operate. The recommender systems become a complex problem for both consumers and sellers when the interaction log is insufficient. Because the seller's perspective needs to make recommendations at a personal level to the consumer and receive appropriate recommendations with reliable data from the consumer's perspective. In this paper, to improve the accuracy problem for "appropriate recommendation" to consumers, the recommender systems are proposed in combination with context-based deep learning. This research is to combine user-based data to create hybrid Recommender Systems. The hybrid approach developed is not a collaborative type of Recommender Systems, but a collaborative extension that integrates user data with deep learning. Customer review data were used for the data set. Consumers buy products in online shopping malls and then evaluate product reviews. Rating reviews are based on reviews from buyers who have already purchased, giving users confidence before purchasing the product. However, the recommendation system mainly uses scores or ratings rather than reviews to suggest items purchased by many users. In fact, consumer reviews include product opinions and user sentiment that will be spent on evaluation. By incorporating these parts into the study, this paper aims to improve the recommendation system. This study is an algorithm used when individuals have difficulty in selecting an item. Consumer reviews and record patterns made it possible to rely on recommendations appropriately. The algorithm implements a recommendation system through collaborative filtering. This study's predictive accuracy is measured by Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). Netflix is strategically using the referral system in its programs through competitions that reduce RMSE every year, making fair use of predictive accuracy. Research on hybrid recommender systems combining the NLP approach for personalization recommender systems, deep learning base, etc. has been increasing. Among NLP studies, sentiment analysis began to take shape in the mid-2000s as user review data increased. Sentiment analysis is a text classification task based on machine learning. The machine learning-based sentiment analysis has a disadvantage in that it is difficult to identify the review's information expression because it is challenging to consider the text's characteristics. In this study, we propose a deep learning recommender system that utilizes BERT's sentiment analysis by minimizing the disadvantages of machine learning. This study offers a deep learning recommender system that uses BERT's sentiment analysis by reducing the disadvantages of machine learning. The comparison model was performed through a recommender system based on Naive-CF(collaborative filtering), SVD(singular value decomposition)-CF, MF(matrix factorization)-CF, BPR-MF(Bayesian personalized ranking matrix factorization)-CF, LSTM, CNN-LSTM, GRU(Gated Recurrent Units). As a result of the experiment, the recommender system based on BERT was the best.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.65-82
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• 2021

Stock market investors are generally split into foreign investors, institutional investors, and individual investors. Compared to individual investor groups, professional investor groups such as foreign investors have an advantage in information and financial power and, as a result, foreign investors are known to show good investment performance among market participants. The purpose of this study is to propose an investment strategy that combines investor-specific transaction information and machine learning, and to analyze the portfolio investment performance of the proposed model using actual stock price and investor-specific transaction data. The Korea Exchange offers daily information on the volume of purchase and sale of each investor to securities firms. We developed a data collection program in C# programming language using an API provided by Daishin Securities Cybosplus, and collected 151 out of 200 KOSPI stocks with daily opening price, closing price and investor-specific net purchase data from January 2, 2007 to July 31, 2017. The self-organizing map model is an artificial neural network that performs clustering by unsupervised learning and has been introduced by Teuvo Kohonen since 1984. We implement competition among intra-surface artificial neurons, and all connections are non-recursive artificial neural networks that go from bottom to top. It can also be expanded to multiple layers, although many fault layers are commonly used. Linear functions are used by active functions of artificial nerve cells, and learning rules use Instar rules as well as general competitive learning. The core of the backpropagation model is the model that performs classification by supervised learning as an artificial neural network. We grouped and transformed investor-specific transaction volume data to learn backpropagation models through the self-organizing map model of artificial neural networks. As a result of the estimation of verification data through training, the portfolios were rebalanced monthly. For performance analysis, a passive portfolio was designated and the KOSPI 200 and KOSPI index returns for proxies on market returns were also obtained. Performance analysis was conducted using the equally-weighted portfolio return, compound interest rate, annual return, Maximum Draw Down, standard deviation, and Sharpe Ratio. Buy and hold returns of the top 10 market capitalization stocks are designated as a benchmark. Buy and hold strategy is the best strategy under the efficient market hypothesis. The prediction rate of learning data using backpropagation model was significantly high at 96.61%, while the prediction rate of verification data was also relatively high in the results of the 57.1% verification data. The performance evaluation of self-organizing map grouping can be determined as a result of a backpropagation model. This is because if the grouping results of the self-organizing map model had been poor, the learning results of the backpropagation model would have been poor. In this way, the performance assessment of machine learning is judged to be better learned than previous studies. Our portfolio doubled the return on the benchmark and performed better than the market returns on the KOSPI and KOSPI 200 indexes. In contrast to the benchmark, the MDD and standard deviation for portfolio risk indicators also showed better results. The Sharpe Ratio performed higher than benchmarks and stock market indexes. Through this, we presented the direction of portfolio composition program using machine learning and investor-specific transaction information and showed that it can be used to develop programs for real stock investment. The return is the result of monthly portfolio composition and asset rebalancing to the same proportion. Better outcomes are predicted when forming a monthly portfolio if the system is enforced by rebalancing the suggested stocks continuously without selling and re-buying it. Therefore, real transactions appear to be relevant.

• International Commerce and Information Review
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• v.11 no.4
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• pp.395-418
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• 2009

Appeared in the 1970s he started the global warming problem of carbon reduction, unlike the expected withdrawal of the United States was anticipated to be nominal stripping. However, EU mainly carbon market, buy and sell rights to be disposed of evolution was born. In fact, the current reduction of the Kyoto Protocol, and Korea will be designated as the bureau had been scheduled. However, due to economic recession in Korea's status as exempt countries have enjoyed a considerable period. Global warming is a problem in earnest, however, the United States to participate in one or more such discussions since 2013, clearly this will begin the international order. And international order that is more stringent than expected, and is expected to be strong. Then, however, an interesting thing to justify protection of the environment in some countries to protect domestic industry, the movement is visible is the side. In fact the WTO since the conclusion of all non-tariff trade barriers were abolished. However, recently, New Round of the delay based on reciprocity and fair trade in the framework of environmental protection to justify the movement to protect the domestic industry has been captured. These trends are not friendly, never in Korea. The rationale is that these regulations are enforced, many of our countries and countries with significant trade transactions and the enforcement points. And South Korea's automotive, semiconductors, ships, etc. The main products are much discussed in the international regulations are being referred to as the target point is due. Korean government to actively participate in the international situation and efforts to explore new markets, said yesterday, and 'Low Carbon, Green Growth' was declared. And the Intergovernmental Panel on Climate Change(IPCC) recommendations of the best 30% reduction target was present. This is nothing different about this objection is true. A more fundamental solution to faithfully perform the reduction targets, while the development of environmentally friendly products and the incidence of international standards through the development and expansion of new growth engines, Indeed we are expected to be a fundamental methodology.

• Journal of the Korea Organic Resources Recycling Association
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• v.13 no.1
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• pp.90-99
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• 2005

This study was conducted to survey the attitude of Chuncheon citizens on food waste generation. About 50% of the citizens were generating $5{\sim}10{\ell}$ of MSW (municipal solid wastes) a week. These answers were almost from below 35 years old. And the citizens answered that the ratio of FW (food waste) to MSW were 10-30%. They were generating FW enveloped in a standardized vinyl bag after dewatering. About 10% of the answers were generating FW with MSW without any dewatering. The reason for FW generation in large quantities was to cook and buy much more food materials than needed. They thought that malodor and harmful insect were the most severe problems from FW storage. The systematic management was the most needed in individual restaurants. They answered that an individual citizen should make an effort to reduce FW generation. However, in fact, they did not do their best to try to reduce FW generation. They agreed that an individual citizen should try to reform 'present food culture' and to think FW as resources.

• Korean Journal of Organic Agriculture
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• v.9 no.1
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• pp.1-16
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• 2001

With increasing global concern that intensively synthetic-chemical based farming systems accelerated the decline in environmental quality, the sustainability of modem agriculture became the subject of great concern. It is well known that the movement of Community Supported Agriculture(CSA) has been contributed significantly to the development of organic agriculture in USA and Japan. It was supposed that CSA could be one of the best way to promote the movement of organic agriculture since there is little reliability on the organically grown food by consumer. In this paper it was focussed to study the movement of CSA in USA and Europe in order to provide an idea for establishment and movement of CSA in Korea to support the organic agriculture. In a CSA system, the farmer grows food for a group of shareholders who pledge to buy a portion of the farm's crop that season. This arrangement gives growers up-front cash to finance their operation and higher prices for produce, since the middleman has been eliminated. For most shareholder for CSA saving money is a secondary consideration, but fresh safe products and environmentally sound farming system. People become shareholder of CSA since they expect an organic farming which can ; \circled1protect the environment, minimize pollution, promote health, \circled2replenish and maintain long-term soil fertility by providing optimal conditions for soil biological activity, \circled3maintain diversity within the farming system and its surroundings and protect plant and wildlife habit, \circled4recycle materials and resources to the greatest extent possible within the farm and its surrounding community, \circled5maintain the integrity of organic food and processed products through each step of the process from planting to consumption, \circled6develop and adopt new technologies with consideration for their long range social and ecological impact. In all CSAs, the farmer develops a crop plan and a budget, which details costs for a growing season, including fair wages for the farmers. Experienced Information on increasing shareholder retention, the future of CSA, and getting started such as ideas for ongoing marketing, printed materials that set realistic expectations, working members, production, pick-up and delivery, setting prices, and receiving feedback were also briefly introduced.

• Korean Journal of Community Nutrition
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• v.2 no.3
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• pp.388-395
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• 1997

A survey was conducted to investigate housewives' perception and consumption of Korean fermented foods marketed in Taejon. Most subjects know how to prepare Kimchi(seasoned and fermented vegetables), 65-67% can make Kochujang(fermented red pepper soybean paste), Toenjang(Korean style soysauce) and Jang-atchies(pickled basic side dishes), 56% can make Kuk-ganjang(Korean style coysauce), 45% can make Chonggukjang (fermented soybean) and 34% can make Jot-kals(salt-fermented fish products). With decreasing age(p<0.0001), not many other subjects could make other fermented foods besides Kimchi. The percentages of subjects buying fermented foods were 71.5% for Chin-ganjang(Japanese style soysauce), 51.7% Jot-kals, 27.1%Kochujang, 25.7% Chonggukjang, 20.1% Jang-atchies, 10.4% Toenjang, 5.9% Kuk-ganjang, and 3.8% Kimchi. the uounger in age, the higher the tendency to buy marketed Kimchies(p<0.05) and Kochujang(p<0.01). The resons for purchasing fermented foods were convenience (52.9%), lack of preparation knowledge(17.5%), lack of time for preparation(12.5%), and lack of space for food storage(8.2%). Subjects indicated that their reasons for mot buying were as follows : use of additives or unreliability with regard to manufacturing dates(45%), bad taste(21%), unsanitary treatment(16%) and to keep their indigenous taste(14%). They cosidered expiration dates, taste, crpteria and safety as the important standard in selecting marketed foods. Younger subjects insisted on the improvement of sanitary condition and partial change of taste to increase the consumption of fermented foods. However, older subjects thought it best to keep the taste original for more utilization of fermented foods.

• Journal of the East Asian Society of Dietary Life
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• v.12 no.4
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• pp.280-288
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• 2002

The purpose of this study is finding a solution to increase the consumption of Korean cookies by investigating and analyzing the actual consumption patterns, suggestions fur improvement and preferences for Korean cookies. The data fer this study was collected from 358 housewives living in Daegu province. Results show that 77.4% of housewives in this locale eat Korean cookies on a special day such as memorial service day of ancestors, festive day or party. The frequency of having Korean cookies were significantly different due to the income (p<.05): the higher the income, the more often people had Korean cookies. They usually purchase Korean cookies on the market rather than making them by themselves. The percentile of housewives who have never made Korean cookies before was up to 51.7% Only the housewives over fifty had some experience making the Korean cookies. The number of people who teamed the method fur making Korean cookies from their family elders increased according to their age. The reasons why they buy Korean cookies on the market are as follows: the most frequent answer (45.5%) was the price. 34.5% of the responder리s did not know how to make them. 32.1% replied that the process is too complex and troublesome. The most frequent requests for the market was expanding the diversity and improving the quality. In response to why they want the Korean cookies to be inherited. 68.8% of respondents answered that it is traditional culture. 4.01% of respondents replied that `ssalyeatgangung' is their favorite Korean cookie. 3.90% of them like 'sanja' the best and 3.91% of the housewives preferred yakwa to other Korean cookies. This study shows that the most preferred Korean cookies are yeatganjung, yakwa and sanja

• The Journal of the Korea Contents Association
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• v.11 no.8
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• pp.177-186
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• 2011

VMD should be shifted from the store for the exhibition to the top selling store, the store that has something people want to buy, the store where people want to visit and the store that is convenient for shopping. To become the top selling store by using VMD to the information design, the primary research has been conducted on the females in Gwangju Metropolitan City by the questionnaire on the propensity to consume and purchase type. The secondary research has been conducted on the females in university who are fashion conscious. The tertiary research, by the questionnaire, has been conducted on the apparel store at the department store in Gwangju Metropolitan City. As a result of the research, it can be said that the best effect of VMD has been shown in the department store, and as the overall problem, it has become obvious that the standardized design was followed without taking advantage of the characteristics of each store.