• Journal of Mushroom
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• v.15 no.1
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• pp.45-53
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• 2017

Profitability of farmers has decreased mainly owing to low price while the gross amount of mushroom production has increased continuously in South Korea. In this regard, analyzing patterns of mushroom consumption is believed to be meaningful. We used a panel data set consisting of 667 families, from 2010 to 2015. Based on the panel data, mushroom consumption patterns of people living in city areas were examined. Multiple descriptive analysis methods and frequency analysis approaches were adopted in this study in terms of time and space dimensions, demographic properties, and purchase behaviors. The findings of this studyshow that mushroom purchase is highly dependent on seasonal events, which implies that the product consumption timing is predictable. In addition, yearly purchase amount patterns reflect that superstores have become the major mushroomtrading venues. This directly supports the need to establish supply chain capabilities for mushroom farmers so that they gain more bargaining power against enterprise-type groceries. Finally, functional features of mushroom can be linked with marketing promotion because purchase patterns demonstrate potential needs for healthcare food in mushroom categories. Based on the analyzed patterns, this paper provides insightful implications for policy makers who want to promote mushroom consumption.

• Journal of Service Research and Studies
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• v.10 no.3
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• pp.103-118
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• 2020

Chinese economic growth and Chinese adoption of foreign cultures have changed varied phenomena, consumption patterns and consumer life-styles, in particular. In order to understand behavior of Chinese consumers, it is critical to explore their lifestyles and its effects on their purchase behavior. For attaining this goal, our research classifies Chinese consumer lifestyles related to cosmetics, into four types: brand oriented, price sensitive, rational consumption, and impulse buying. The research further analyzes the effects of consumer lifestyles on perceived value, satisfaction, and purchase intention in each case of skin care cosmetics and make-up cosmetics. Significant difference are found in perceived value, satisfaction, and purchase intention of skin care cosmetics exists between brand-oriented type and rational consumption type. This is also the case between rational consumption type and impulse buying type. Purchase intention is only found to be different between rational consumption type and price sensitive type. In case of make-up cosmetics, significant differences in perceived value, satisfaction, and purchase intention in the pairs of brand-oriented type and rational consumption type, rational consumption type and impulse buying type, and rational consumption type and price sensitive type. This implies rational consumption type should be more appropriate target consumers in the Chinese cosmetics market.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.19-42
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• 2012

Consumer consumption patterns are shifting rapidly as buyers migrate from offline markets to e-commerce routes, such as shopping channels on TV and internet shopping malls. In the offline markets consumers go shopping, see the shopping items, and choose from them. Recently consumers tend towards buying at shopping sites free from time and place. However, as e-commerce markets continue to expand, customers are complaining that it is becoming a bigger hassle to shop online. In the online shopping, shoppers have very limited information on the products. The delivered products can be different from what they have wanted. This case results to purchase cancellation. Because these things happen frequently, they are likely to refer to the consumer reviews and companies should be concerned about consumer's voice. E-commerce is a very important marketing tool for suppliers. It can recommend products to customers and connect them directly with suppliers with just a click of a button. The recommender system is being studied in various ways. Some of the more prominent ones include recommendation based on best-seller and demographics, contents filtering, and collaborative filtering. However, these systems all share two weaknesses : they cannot recommend products to consumers on a personal level, and they cannot recommend products to new consumers with no buying history. To fix these problems, we can use the information which has been collected from the questionnaires about their demographics and preference ratings. But, consumers feel these questionnaires are a burden and are unlikely to provide correct information. This study investigates combining collaborative filtering with the centrality of social network analysis. This centrality measure provides the information to infer the preference of new consumers from the shopping history of existing and previous ones. While the past researches had focused on the existing consumers with similar shopping patterns, this study tried to improve the accuracy of recommendation with all shopping information, which included not only similar shopping patterns but also dissimilar ones. Data used in this study, Movie Lens' data, was made by Group Lens research Project Team at University of Minnesota to recommend movies with a collaborative filtering technique. This data was built from the questionnaires of 943 respondents which gave the information on the preference ratings on 1,684 movies. Total data of 100,000 was organized by time, with initial data of 50,000 being existing customers and the latter 50,000 being new customers. The proposed recommender system consists of three systems : [+] group recommender system, [-] group recommender system, and integrated recommender system. [+] group recommender system looks at customers with similar buying patterns as 'neighbors', whereas [-] group recommender system looks at customers with opposite buying patterns as 'contraries'. Integrated recommender system uses both of the aforementioned recommender systems to recommend movies that both recommender systems pick. The study of three systems allows us to find the most suitable recommender system that will optimize accuracy and customer satisfaction. Our analysis showed that integrated recommender system is the best solution among the three systems studied, followed by [-] group recommended system and [+] group recommender system. This result conforms to the intuition that the accuracy of recommendation can be improved using all the relevant information. We provided contour maps and graphs to easily compare the accuracy of each recommender system. Although we saw improvement on accuracy with the integrated recommender system, we must remember that this research is based on static data with no live customers. In other words, consumers did not see the movies actually recommended from the system. Also, this recommendation system may not work well with products other than movies. Thus, it is important to note that recommendation systems need particular calibration for specific product/customer types.

• Journal of the Korean Society of Clothing and Textiles
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• v.31 no.12
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• pp.1721-1732
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• 2007

This study identified types of information source, and explored a path model for consumer information search by shopping attributes in the context of online decision making. Participants completed self-administered questionnaires during regularly scheduled classes. A total of 219 usable questionnaires were obtained from respondents who enroll at universities in the southwestern region of the United States. For data analysis, factor analysis and path model estimation were used. Consumer information source was classified into three types for online clothing purchases: Online source, Offline retail source, and Mass media. Consumers were more likely to rely on offline retail source for online clothing purchases, than other sources. In consumer information search by shopping attributes, online sources were more likely to be related to transaction-related attributes(e.g., incentive service), whereas offline retail source(e.g., displays in stores, manufacturer's catalogs and pamphlets) were more likely to be related to product and market related attributes(e.g., aesthetics, price) when purchasing clothing online. Also, the path model emphasizes the effect of shopping attributes on traditional retailer search behavior, leading to online purchase intention for clothing. This study supports consumer information search by attributes, and discusses a managerial implication of multi-channel retailing for apparel.

• Korean Journal of Poultry Science
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• v.47 no.4
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• pp.247-254
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• 2020

This study examined how consumer choices (i.e., selecting food safety certified products, health-related products, and familiar brands) affect the purchase of Korean native chicken (KNC) and the demographics that influence KNC purchases using secondary consumer panel data from the Rural Development Administration of Korea. The grocery purchase data from 654 Korean households between 2017 and 2019 were used; the propensity for food safety certified products was measured by the purchasing frequency of Good Agricultural Practice (GAP) and Hazard Analysis and Critical Control Point (HACCP) products, and the propensity for health-related products was measured by the purchasing frequency of home meal replacement (HMR) and hedonic products. The propensity to purchase familiar brands was measured using a questionnaire. Logistic regression was used to examine the determinants of the KNC purchase experience, and multiple linear regression was used to determine the factors that influenced the KNC purchase frequency. The results showed that unemployed women purchased more safety certified products, health-related products, familiar brands, and KNC. These findings suggest that targeting consumers with differential marketing strategies may help promote KNC consumption. This study identified factors that influence KNC purchases, which is important for understanding consumer behavior and revitalizing the market.

• Journal of Intelligence and Information Systems
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• v.15 no.4
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• pp.159-182
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• 2009

We construct product networks from the retail transaction dataset of an off-line department store. In the product networks, nodes are products, and an edge connecting two products represents the existence of co-purchases by a customer. We measure the quantities frequently used for characterizing network structures, such as the degree centrality, the closeness centrality, the betweenness centrality and the centralization. Using the quantities, gender, age, seasonal, and regional differences of the product networks were analyzed and network characteristics of each product category containing each product node were derived. Lastly, we analyze the correlations among the three centrality quantities and draw a marketing strategy for the cross-selling.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04c
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• pp.579-581
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• 2003

본 논문은 웹사이트를 구성하는 웹컨텐츠의 합목적성 및 사용성 평가를 위하여 웹사이트 사용자들의 흔적인 웹로그 분석 데이터를 적용하여 정량적인 평가를 한 결과 에 대하여 보고 하고자 한다. 웹로그파일은 사용자가 웹사이트를 이용하면 이에 대한 기록이 로그라는 형태로 흔적이 남는다. 로그분석이란 이 데이터를 기반으로 위에서 말한 다양한 정보를 추출해 내는 것이라 할 수 있다. 로그분석은 사용자에 따라 단지 로그 정보를 분석하는 것에 한정시키기도, 로그 정보를 기반으로 한 보다 다양한 정보를 분석하는 확장된 개념으로 확대시키기도 한다. 본 논문은 웹트랜즈［로그분석 툴］를 사용하여 웹사이트내의 웹컨텐츠 분석에 웹 로그 분석 결과가 같는 정량적인 개념을 활용하여 정상적인 분석으로 일관되었던 웹사이트 분석에 새로운 결과를 도출하였다. 또한 마케팅을 수행하는 데 있어서 고객의 요구에 천저히 대응하기 위해서 고객을 철저히 파악하여야 한다. 로그파일 분석을 통해서 주요 고객층, 고객의 구매 패턴, 주 구매시간, 구매탐색 경로등의 데이터를 추출할 수 있다. 로그파일 분석 데이터를 기반으로 인터페이스 설계나 상품의 레이아웃등의 설계, 고객 서비스 강화등의 다양한 대 고객 마케팅을 펼칠 수 있다. 본 논문은 단순 수치해석의 개념이었던 로그 분석에 웹컨텐츠분석 기법을 접목하여 웹사이트내에서 사용되고 있는 컨텐츠의 사용성에 대안 연구 결과에 대해서 발표하고자 한다.

• The Journal of the Korea Contents Association
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• v.16 no.10
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• pp.645-655
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• 2016

The purpose of this study is to search shot clip' using variables influencing on the VOD purchase intention and watching intention of real-time broadcasting. This research focused on usage motivation, usage experience such as use time, time of utilization, genre, utilization pattern. Controlling demographic factors, results show that personal relation, benefit against whole broadcast, education genre, watching video, video sharing and recommendation were statistically influential to VOD purchase intention. And, results show that flexibility of use, drama/movie genre, read and write comments were statistically influential to watching intention of real-time broadcasting.

• Journal of the Korea Society of Computer and Information
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• v.11 no.1 s.39
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• pp.293-300
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• 2006

The Recommender systems help users to find and evaluate items of interest. Such systems have become powerful tools in the domains from electronic commerce to digital libraries and knowledge management. Sellers can recommend products to customers with the prediction of future buying behavior on the basis of the consumer's population statistics and past selling behavior. In this paper, we are describing the design and the development of personalization recommender system which increases satisfaction level of customers by searching products to reflect the pattern and propensity of customers properly. The suggested system supplies the real-time analysis service to predict the customers purchase situation by applying the association rule of the data mining.

• 한국신재생에너지학회:학술대회논문집
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• 2010.11a
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• pp.177.2-177.2
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• 2010

전세계 풍력발전 시장은 2009년말 160GW로 지난 5년간 연평균 36.1%로 성장하였으며, 2012년 310GW, 2020년에는 1,900GW에 이를 전망이다. 특히, 풍력산업은 조선, 중공업 등 우리나라가 강세에 있는 산업과 연관성이 높아 관련분야 대기업을 중심으로 시장진출이 활발히 진행되고 있는 추세이다. 본 연구는 지식경제부에서 지원하고 있는 신재생에너지기술개발사업 R&D지원실적을 토대로 풍력산업 및 기술혁신패턴을 분석하고, 이를 토대로 풍력산업 발전을 위한 기술혁신 지원전략을 연구하였다. 분석결과, 풍력시장이 급성장함에 따라 대기업을 중심으로 급진적 혁신 행태을 보였으며, 기술도입 및 선진기술의 모방이라는 전형적인 초기산업화 패턴을 보이고 있다. 이러한 기업전략은 기술혁신체제 관점에서 기술학습을 통한 기술축적이 부족하고, 부품소재 중심으로 공급사슬을 구성하는 중소 중견기업군이 취약하여 원가절감 등 시장 경쟁력에 장애요인으로 나타났다. 이를 개선하기 위해서는 첫째, 시스템 기업은 중소 중견기업을 중심으로 부품국산화 노력을 통한 경쟁력 있는 공급사슬 구현이 시급하다. 둘째, 정부는 부품소재 중심의 원천연구에 대한 지원을 확대하여야 하며 셋째, 경쟁력 있는 국가의 기술혁신체계 구현을 위해 정부 출연연구소 및 대학을 중심으로 기술축적을 위한 방안이 시급하다. 마지막으로 초기 풍력산업의 주요 수요자가 정부 및 공공기관인점을 감안할 때, 풍력시스템의 국산화 비율을 구매 조건의 핵심 평가요인으로 채택해야 할 것이다.