• Journal of Distribution Research
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• v.15 no.4
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• pp.1-19
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• 2010

As having the movement of developing private brand (PB) goods, domestic big retailers are facing up with new problems. Thus, it is required studies of PB products, and how consumers recognize PB products as a consideration commodity set. Also, it is worthy in order that it gives us the important meaning on the marketing strategy with focusing on evaluating the differences between customers buying PB grocery goods with respect to demographic characteristics and purchasing behaviors. PB has some advantages for customers and retailers. However, according to AC Nielson's report (2005), Asian and emerging market has 1/5 sales relatively to Western countries. But we can assume that the emerging market has the most potential growth through this result. As a result from several other studies, it becomes necessary to not only increase the rate of selling composition of PB product temporarily, but also analyze the characteristics of customers using big retailers and segmenting customer groups to make PB product as a consideration commodity set for them. In addition, it is needed to have a variety of acts of marketing. From studies related to PB, there is a prejudice - cheap products have low quality - but, evaluation by customers who have used those products shows neutral stand, and there is a study representing that it is the most important to accumulate the belief between the retailers selling PB products and consumers using those for the accurate evaluation and intention on purchasing. Also, by the result from analyzing the characteristics of customers buying PB products, we could assume that higher income and higher education level, more preference on PB products. Especially, according to TNS's research, the primary targets of PB product are 30's who seeks value for money and planned spending habits, and 40's who have teenager children, and are interested in encouraging themselves. This paper used Probit model to analyze the characteristics of consumers. This model helps us to analyze with the variables representing the demographic characteristics of consumers (gender, age, educational level, occupation, income level, living area), and variables related to purchasing behavior (visiting frequency on big retailers, the average amount that they pay for goods in there, and check-up which brand made those goods). The method we used in this study is by man to man interview and survey on-line with the rate of 89% and 11% in Seoul and Gyunggi Province, respectively, for about one month from the beginning of February, 2008. As a result of this, under the assumption that people buy PB products more as long as they go shopping more, it was not meaningful for target groups which we pointed out as frequently visiting customers to be. Although, we have expected women buy more PB products than men do, gender doesn't mean anything for the result. And, it has inferred that married people buy more PB goods than singles do. It was also meaningless with variables related to occupation. Because housewives are often exposed to any kind of supermarket than workers are, we could not get any relatives. Moreover, we couldn't proof that younger generation prefer big retailers more than older people who 50~60's. Education levels doesn't affect on the purchase of PB product as well. Related to living area, the result is statistically not similar as we expected whether living in Seoul or not. It shows there is no relationship with the preference on retail brands and PB products, and it is similar with the study researched by TNS(2008) that customers tend to buy PB product impulsively no matter which brand it is and where they are even though their shopping place is the big market where customers are often using. Variables on which we had meaningful results are income level and living place. That is, customers who have 3,000,000~6,000,000 WON every month on average are more willing to buy PB products than other customers whose income is over 6,000,000 WON, and residents not living in Seoul prefer PB goods than those who are living in Seoul. To explain more about what we got, if there is only one condition about customer's visiting frequency on big retails, we could come up with this result that more exposed to PB products, more purchasing frequency. Consequently, it brings the important insight that large retailers have to prepare something to make customers visit them often to increase selling rate of PB products. To demonstrate the result of analyzing more, what is more efficient variables are demographically including marital status, income level, and residential area to buy items that affect the PB products and could include the frequency of visiting large markets by the purchase habits. Specifically, then, married couples rather than singles, middle-income customers than high-income customers, and local residents not living in Seoul than customers in Seoul are more likely to purchase PB goods. In addition, as long as a customer visits two times more, then the purchasing rate of PB products is to increase over 5.3%. Therefore, it seems that retailers are better to make a shopping place as fun and comfortable places. With overwhelming the idea that PB products are just cheap, one-time purchase goods, it is needed to increase the loyalty on those goods like NB products, try to make PB products as a consideration products set, and occur to sustainable sales. Especially, as suggested by this paper, it seems like it strongly needs to identify the characteristics of customers who prefer PB, to segment those customers, and to select the main target, and to do positioning with well-planned marketing strategies. Then, it is able to give us a meaningful point on marketing strategy by developing the field of PB study, identifying the difference of life style and shopping habits of customers.

• Journal of the Korean Geographical Society
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• v.47 no.4
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• pp.522-540
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• 2012

The main aim of the paper is to identify the position or status of Korean economic geography in changing global economic geography by reviewing papers published in Korean geographical journals since the mid-1950s. Since the late 20th century as economic geography has developed significantly with the introduction of new research issues, methodologies, and theory and concepts, economic geography in Korea also has gone through rapid development in terms of both quantitative and qualitative perspectives. The paper attempts to analyze trends in Korean economic geography by reviewing agricultural, industrial, commercial geographies, and others since the mid-1950s. The review of economic geography in Korea would be based on four periods classified by research issues and approaches; foundation (~1950s), positioning (1960s and 1970s), jump and rush (1980s and mid-1990s), and transitional period (late 1990s~). Agricultural geography in Korea has decreased due to increases of the interests in industrial geography since the 1980s. In particular, since the late 1990s industrial geography has undergone a significant transition in accordance with the emergence of new theories of institutional perspectives, centering around issues on value chains, innovative cluster, cooperative and competitive networks, foreign direct investment, flexible specialization and venture ecology. Along with this, there has been changes in the interest of commercial geography in Korea from researches on periodical markets, the structure of store formats, and distributions by commodity, to researches on producer services and retailer's locational behaviors and commercial supremacy according to the emergence of new store formats. Since the late 1990s, many researches and discussions associated with the new economic geography began to emerge in Korea. Various research issues are focused on analyzing changes of local, regional and global economic spaces and their processes in relation to institutional perspectives, knowledge and innovation, production chain and innovative networks, industrial clusters and RIS, and geographies of service. Although economic geography in Korea has developed significantly both in quantitative and qualitative perspectives, we pointed out that it has still limited in some specific scope and issues. Therefore, it is likely to imply that its scope and issues should be diversified with new perspectives and approaches.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.139-161
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• 2019

The utilization of the e-commerce market has become a common life style in today. It has become important part to know where and how to make reasonable purchases of good quality products for customers. This change in purchase psychology tends to make it difficult for customers to make purchasing decisions in vast amounts of information. In this case, the recommendation system has the effect of reducing the cost of information retrieval and improving the satisfaction by analyzing the purchasing behavior of the customer. Amazon and Netflix are considered to be the well-known examples of sales marketing using the recommendation system. In the case of Amazon, 60% of the recommendation is made by purchasing goods, and 35% of the sales increase was achieved. Netflix, on the other hand, found that 75% of movie recommendations were made using services. This personalization technique is considered to be one of the key strategies for one-to-one marketing that can be useful in online markets where salespeople do not exist. Recommendation techniques that are mainly used in recommendation systems today include collaborative filtering and content-based filtering. Furthermore, hybrid techniques and association rules that use these techniques in combination are also being used in various fields. Of these, collaborative filtering recommendation techniques are the most popular today. Collaborative filtering is a method of recommending products preferred by neighbors who have similar preferences or purchasing behavior, based on the assumption that users who have exhibited similar tendencies in purchasing or evaluating products in the past will have a similar tendency to other products. However, most of the existed systems are recommended only within the same category of products such as books and movies. This is because the recommendation system estimates the purchase satisfaction about new item which have never been bought yet using customer's purchase rating points of a similar commodity based on the transaction data. In addition, there is a problem about the reliability of purchase ratings used in the recommendation system. Reliability of customer purchase ratings is causing serious problems. In particular, 'Compensatory Review' refers to the intentional manipulation of a customer purchase rating by a company intervention. In fact, Amazon has been hard-pressed for these "compassionate reviews" since 2016 and has worked hard to reduce false information and increase credibility. The survey showed that the average rating for products with 'Compensated Review' was higher than those without 'Compensation Review'. And it turns out that 'Compensatory Review' is about 12 times less likely to give the lowest rating, and about 4 times less likely to leave a critical opinion. As such, customer purchase ratings are full of various noises. This problem is directly related to the performance of recommendation systems aimed at maximizing profits by attracting highly satisfied customers in most e-commerce transactions. In this study, we propose the possibility of using new indicators that can objectively substitute existing customer 's purchase ratings by using RFM multi-dimensional analysis technique to solve a series of problems. RFM multi-dimensional analysis technique is the most widely used analytical method in customer relationship management marketing(CRM), and is a data analysis method for selecting customers who are likely to purchase goods. As a result of verifying the actual purchase history data using the relevant index, the accuracy was as high as about 55%. This is a result of recommending a total of 4,386 different types of products that have never been bought before, thus the verification result means relatively high accuracy and utilization value. And this study suggests the possibility of general recommendation system that can be applied to various offline product data. If additional data is acquired in the future, the accuracy of the proposed recommendation system can be improved.