• Journal of Distribution Science
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• v.13 no.10
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• pp.93-99
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• 2015

Purpose - It has been argued that the regulations restricting entry and opening hours of General Super Markets and Super Super Markets have not been as effective as expected. In contrast, the win-win item scheme that appeared recently has the advantage that it could raise the effectiveness of the system in that win-win items are in principle resigned on the basis of bilateral agreements. This study analyzes the win-win item agreement made between Homeplus at Hap-jung and small traditional markets to examine the practical effectiveness of the win-win item scheme. While existing literature studying the regulatory effects have concentrated on the restrictions around store entry or opening hours of large retailers, it can be said that there have been few empirical studies on the effect of win-win items agreement with large retailers. Research design, data, and methodology - Homeplus at Hap-jung made a win-win items agreement with nearby small traditional market traders in 2013. In accordance with this voluntary agreement, Homeplus started by limiting its sales to 15 win-win items. The survey was conducted through one-on-one interviews, April 14 to May 2, 2014, by a professional public opinion research agency. The interviews were targeted at small business retailers in the nearby traditional market. We divided the traditional markets near Homeplus at Hap-jung where the win-win item agreement was achieved into two groups, win-win item agreement markets and non win-win item agreement markets, to compare the performance difference between the two groups. Results - To determine the change in sales of the 15 win-win items, we examined the performance difference between the two groups using two criteria (compared with similar items, and compared to sales volume a year ago). The results show that the individual sales of win-win items in the win-win item agreement markets are more likely to increase than in the non win-win item agreement markets. Total sales volume of individual stores in the agreement markets also showed a more significant increase compared to a year ago than those in non win-win item agreement markets. Conclusions - Contrary to the existing retail regulations that have one-sided and uniform characteristics, it can be pointed out that the win-win item scheme has the effect of increasing the success of the system itself because it is done on the basis of mutual agreement between General Super Markets and traditional markets. The empirical results of this study can be said to support this conjecture. For the successful settlement of a win-win items agreement, the following points should be reviewed. First, it requires a great effort from the selection process of win-win items in order to improve the effectiveness of the agreement. Second, the existing General Super Markets customers should be introduced to the traditional markets or small shops to increase the sales of win-win items. Therefore, voluntary effort is essentially required from the traditional markets to engage customers.

• The Journal of the Convergence on Culture Technology
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• v.8 no.2
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• pp.37-46
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• 2022

Recently, our society and environment has changed rapidly due to the pandemic caused by the COVID-19 virus. In this rapidly changing environment, companies fulfill their social responsibilities and require non-financial elements of transparent management activities. ESG has become one of the non-financial factors, and interest of ESG management is increasing worldwide. In this paper, we examine the importance of ESG concept and ESG management performance and the correlation with companies, and examine the necessity of ESG management for companies in the future. The literature reviews are conducted on CU which is currently best practicing ESG management through various secondary data. Also, we used interview articles so that reflect the rich voice of the distribution industry. In addition, after examining ESG characteristics through examples of global companies, we looked at BGF Retail's CU convenience store ESG activities, which is a leader in ESG management, in distribution industry. CU was divided into all sectors of E, S, and G, and all sectors were actively engaged in activities and flexibly coping with changing environments and social needs. In particular, it was confirmed that CU's environmental management, which focuses the most, achieved successful results due to the increase in actual consumption of customers. ESG management activities at CU convenience stores are currently ongoing and future tasks. As a leading company in ESG management in the current industry, it is meaningful to understand the process of growing into a company that shares concerns, efforts, and practical activities and fulfills social responsibility. Through this study, the changes and growth of CU and domestic companies to ESG and sustainable management are expected in the futures.

• (The)Study of the Eastern Classic
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• no.73
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• pp.153-184
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• 2018

The aim of this thesis was to examine the circumstances that led up to successful coin use across the entire nation in 1678 (the $4^{th}$ year of King Sukjong's reign), during the Joseon Dynasty. To this end, this thesis analysed the Sa-Mouk(事目, Provisions) that contained the institutional protocol for coin circulation, implemented by King Hyojong and the statesman Kim Youk(金堉) who had practical experience in these matters over the ten years of King Hyojong's reign(1649-1659). To regulate the problematic wide circulation of coarse cotton cloth as currency in the market of 1650 (the $1^{st}$ year of King Hyojong's reign), prohibition measures were implemented. Besides the superficial justification given for these measures(i.e., that the market price was disturbed by the use of coarse cotton cloth), there was another purpose to prohibiting the circulation of cotton cloth as money, following the standard ruled by the government: the state aimed to ensure momentum for the upcoming coin circulation policy, by strengthening its control of the current economy. In 1651 (the $2^{nd}$ year of King Hyojong's reign), the government fully cracked down on the use of coarse cotton cloth as currency, and simultaneously implemented its coin circulation policy in the Pyeongan(平安) region. The pretext for this policy was to raise finances to support people who were starving as a result of poor harvests and famine. People who received coins from government officials could purchase food in the market, and the coin circulation policy was judged to be successful. Subsequently, to extend coin circulation further throughout the region, the Sa-Mouk for Seoul was established. The Sa-Mouk included stipulations regarding the use of coin in transactions and for government expenditure; it aimed thereby to enhance the national policy's market credit. The hasty implementation of the policy for the expansion of coin circulation caused some problems that required its modification. In 1652 (the $3^{rd}$ year of King Hyojong's reign), coin circulation was increased to encompass the Gyeonggi(京畿) region, and some of the tax that had been paid in rice was now paid in coin. However, coins were in short supply, since there was insufficient copper, the main material used in coin production, and the policy faced a significant limitation. Therefore, in 1655(the $6^{th}$ year of King Hyojong's reign), a new Sa-Mouk for coin circulation was established. This Sa-Mouk included specifications regarding the determination of coin values based on rice and silver, and mandated the wide spread installation of stores for exchanging spot goods for coins throughout the region in which coins were circulating. This policy's objective was to secure stability for the national economy by further regulating coin circulation. The sustained implementation of the coin circulation policy for ten years by King Hyojong and the statesman Kim Youk offered the government an opportunity to accumulate experience in coin circulation in the market, and also to learn from institutional trial and error. This may have been one of the contributing factors to the nation-wide coin circulation that was established in 1678. The objective of the policy implemented during King Hyojong's reign was not to meet the market's requirements, but rather to ensure the preservation of the national economy, and this misjudgement constituted the policy's key limitation. At this time, the government urgently needed to secure finances to cope with the war against China's Qing Dynasty.

• Journal of Distribution Research
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• v.17 no.2
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• pp.29-62
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• 2012

As distribution environment is changing rapidly and competition is more intensive in the channel of distribution, the importance of retailer image and retailer equity is increasing as a different competitive advantages. Also, consumers are not functionally oriented and that their behavior is significantly affected by the symbols such as retailer image which identify retailer in the market place. That is, consumers do not choose products or retailers for their material utilities but consume the symbolic meaning of those products or retailers as expressed in their self images. The concept of self-image congruence has been utilized by marketers and researchers as an aid in better understanding how consumers identify themselves with the brands they buy and the retailer they patronize. Although self-image congruity theory has been tested across many product categories, the theory has not been tested extensively in the retailing. Therefore, this study attempts to investigate the impact of self image congruence between retailer image and self image of consumer on retailer equity such as retailer awareness, retailer association, perceived retailer quality, and retailer loyalty. The purpose of this study is to find out whether retailer-self image congruence can be a new antecedent of retailer equity. In addition, this study tries to examine how four-dimensional retailer equity constructs (retailer awareness, retailer association, perceived retailer quality, and retailer loyalty) affect customers' repatronage intention. For this study, data were gathered by survey and analyzed by structural equation modeling. The sample size in the present study was 254. The reliability of the all seven dimensions was estimated with Cronbach's alpha, composite reliability values and average variance extracted values. We determined whether the measurement model supports the convergent validity and discriminant validity by Exploratory factor analysis and Confirmatory Factor Analysis. For each pair of constructs, the square root of the average variance extracted values exceeded their correlations, thus supporting the discriminant validity of the constructs. Hypotheses were tested using the AMOS 18.0. As expected, the image congruence hypotheses were supported. The greater the degree of congruence between retailer image and self-image, the more favorable were consumers' retailer evaluations. The all two retailer-self image congruence (actual self-image congruence and ideal self-image congruence) affected customer based retailer equity. This result means that retailer-self image congruence is important cue for customers to estimate retailer equity. In other words, consumers are often more likely to prefer products and retail stores that have images similar to their own self-image. Especially, it appeared that effect for the ideal self-image congruence was consistently larger than the actual self-image congruence on the retailer equity. The results mean that consumers prefer or search for stores that have images compatible with consumer's perception of ideal-self. In addition, this study revealed that customers' estimations toward customer based retailer equity affected the repatronage intention. The results showed that all four dimensions (retailer awareness, retailer association, perceived retailer quality, and retailer loyalty) had positive effect on the repatronage intention. That is, management and investment to improve image congruence between retailer and consumers' self make customers' positive evaluation of retailer equity, and then the positive customer based retailer equity can enhance the repatonage intention. And to conclude, retailer's image management is an important part of successful retailer performance management, and the retailer-self image congruence is an important antecedent of retailer equity. Therefore, it is more important to develop and improve retailer's image similar to consumers' image. Given the pressure to provide increased image congruence, it is not surprising that retailers have made significant investments in enhancing the fit between retailer image and self image of consumer. The enhancing such self-image congruence may allow marketers to target customers who may be influenced by image appeals in advertising.

• Journal of Global Scholars of Marketing Science
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• v.18 no.1
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• pp.1-31
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• 2008

Trust is central to human relationships, at all times and places. The importance of trust is fundamental in all areas of human life, not only in the area of business administration. 2,500 years ago in China, Confucius taught that the foundation of politics was the trust of the people, more important even than military strength or the supply of food. Shakespeare's play, "Much Ado about Nothing' is about trust and deception. These days, trust and transparency in a commercial organization's business culture form the basis of the 'social capital' by which that organization increases its productivity. A successful company raises productivity by the accumulation of social capital, derived from a trust relationship between business partners, and between the company and consumers. Trust is the crucial factor. At the national level, building trust determines a nation's competitiveness. For a company, long term trust relationships with customers are essential for its survival in a business environment of rapid change. Such relationships, based on trust, are important assets to ensure a company's competitive advantage, and need to be organic to that company's business culture. Because of this importance, trust relationships have been studied in diverse areas within business administration, and especially within marketing, where they form the basis of a successful relationship between producer and consumer. However, what has been lacking is a unified definition of trust. Research has been conducted on the basis of various definitions and models. The majority of researchers have not considered the multidimensional character of the concept of trust until now. Approaches based on a one dimensional model have undermined the value of research results. Furthermore, researchers have only considered trust and trustworthiness as a single component. The majority of research has explored the consequences of perceived trust for outcomes such as loyalty or cooperation, but has neglected the effects of trustworthiness upon the mechanisms of consumer trust. This study focuses on the dimension of trust from such a perspective. It seeks to verify the effect of trust on customer intentions by breaking it down into three separate components: 1) the salesperson, 2) the product/service, and 3) the company. The purposes of this paper are as follows: Firstly, we review the multidimensional nature of trust objects: the salesperson, the product/service, and the company. Secondly, we analyze the relationship between multidimensional trust and trustworthiness. Thirdly, we analyze the connection between trust and repeat purchase intentions for the maintenance of long term relationships. For these purposes the author has developed several hypotheses as follows: H1-1: The competence of a salesperson is positively associated with the trust given by the consumer to the salesperson. H1-2: The benevolence of a salesperson is positively associated with the trust given by the consumer to the salesperson. H2-1: The competence of product/service is positively associated with the trust given by the consumer to the product/service. H2-2: The benevolence of product/service is positively associated with the trust given by the consumer to the product/service. H3-1: The reputation of a company is positively associated with the trust given by the consumer to the company. H3-2: The physical environment of a company is positively associated with the trust given by the consumer to the company. H4-1: Trust in a salesperson is positively associated with repeat purchase intentions. H4-2: Trust in a product/service is positively associated with repeat purchase intentions. H4-3: Trust in a company is positively associated with repeat purchase intentions. The data was compiled from 366 questionnaires. 500 questionnaires were collected, but some of the data was considered unsuitable and inappropriate. The subjects of the survey were male and female customers purchasing products at department stores in Seoul, Daegu and Gyeongbuk. It was carried out between Oct. 25 and 29, 2007. The data was analyzed by frequency analysis using SPSS 12.0 and structural equation modeling using LISREL 8.7. The result of the overall model analysis is as follows: Chi-Square=445.497, d.f.=185, p-value=0.0, GFI=.901, RMSEA=.0617, NNFI=.986, NFI=.981, CFI=.989, AGFI=.864, RMR=.0872. The results of the overall model analysis were coherent. It was found that trust is a multi-dimensional construct, that each of the dimensions of trust are meaningful influences on customer's repurchase intention. Trust in a company may be the most relevant, while trust in a product/service and a salesperson may be less relevant to repurchase intentions. The effective factors in determining trust in a salesperson and a company's product/service were found to be competence and benevolence. Factors in determining trust in a company were its reputation and physical environment, and the relationship of each effective trust factor has been verified in this research. As a result, it was found that competence and benevolence have a meaningful influence on trust in a salesperson and in product/service. It was also found that a company's reputation influences the overall trust in the company significantly but a company's physical environment does not have much effect.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.305-316
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• 2011

Recommender system is the system which, by using automated information filtering technology, recommends products or services to the customers who are likely to be interested in. Those systems are widely used in many different Web retailers such as Amazon.com, Netfix.com, and CDNow.com. Various recommender systems have been developed. Among them, Collaborative Filtering (CF) has been known as the most successful and commonly used approach. CF identifies customers whose tastes are similar to those of a given customer, and recommends items those customers have liked in the past. Numerous CF algorithms have been developed to increase the performance of recommender systems. However, the relative performances of CF algorithms are known to be domain and data dependent. It is very time-consuming and expensive to implement and launce a CF recommender system, and also the system unsuited for the given domain provides customers with poor quality recommendations that make them easily annoyed. Therefore, predicting in advance whether the performance of CF recommender system is acceptable or not is practically important and needed. In this study, we propose a decision making guideline which helps decide whether CF is adoptable for a given application with certain transaction data characteristics. Several previous studies reported that sparsity, gray sheep, cold-start, coverage, and serendipity could affect the performance of CF, but the theoretical and empirical justification of such factors is lacking. Recently there are many studies paying attention to Social Network Analysis (SNA) as a method to analyze social relationships among people. SNA is a method to measure and visualize the linkage structure and status focusing on interaction among objects within communication group. CF analyzes the similarity among previous ratings or purchases of each customer, finds the relationships among the customers who have similarities, and then uses the relationships for recommendations. Thus CF can be modeled as a social network in which customers are nodes and purchase relationships between customers are links. Under the assumption that SNA could facilitate an exploration of the topological properties of the network structure that are implicit in transaction data for CF recommendations, we focus on density, clustering coefficient, and centralization which are ones of the most commonly used measures to capture topological properties of the social network structure. While network density, expressed as a proportion of the maximum possible number of links, captures the density of the whole network, the clustering coefficient captures the degree to which the overall network contains localized pockets of dense connectivity. Centralization reflects the extent to which connections are concentrated in a small number of nodes rather than distributed equally among all nodes. We explore how these SNA measures affect the performance of CF performance and how they interact to each other. Our experiments used sales transaction data from H department store, one of the well?known department stores in Korea. Total 396 data set were sampled to construct various types of social networks. The dependant variable measuring process consists of three steps; analysis of customer similarities, construction of a social network, and analysis of social network patterns. We used UCINET 6.0 for SNA. The experiments conducted the 3-way ANOVA which employs three SNA measures as dependant variables, and the recommendation accuracy measured by F1-measure as an independent variable. The experiments report that 1) each of three SNA measures affects the recommendation accuracy, 2) the density's effect to the performance overrides those of clustering coefficient and centralization (i.e., CF adoption is not a good decision if the density is low), and 3) however though the density is low, the performance of CF is comparatively good when the clustering coefficient is low. We expect that these experiment results help firms decide whether CF recommender system is adoptable for their business domain with certain transaction data characteristics.

• KDI Journal of Economic Policy
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• v.13 no.2
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• pp.141-161
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• 1991

Resale price maintenance has long been employed in book distribution, perhaps longer than for any other product. Another unusual practice in the book trade that has proven to be quite durable in spite of its substantial cost in real resources is the returns policy. Publishers typically grant the right to return unsold books within a stipulated time for full credit against future orders. This paper investigates the functions and effects of resale price maintenance in the book trade, and argues that resale price maintenance and returns are substitute methods of providing the same economic function. Resale price maintenance can be used to compensate booksellers for initially stocking books with uncertain prospects and for providing a conduit through which manufacturers acquire information about consumer demand (market testing services). Permitting the return of unsold books for full credit places a floor under retail prices and transfers a considerable portion of the cost of introducing a new product line back to the publisher. Both reflect publishers' needs to have their books displayed. In the U.S. returns privileges were first proposed in 1913, roughly coincident with the Macy decision outlawing RPM. Publishers slowly granted return privileges, which become nearly universal by 1970. The decline in margins in recent years has been accompanied by an increase in returns as the return policy served to substitute for lost margins on successful titles as a methods of compensating full-line booksellers. In contrast, returns privileges are unusual in countries where price maintenance in books has been practiced. These observations are consistent with our analysis. In Korea, resale price maintenance of books is practiced under an exception to Korean antitrust law. The availability of effective price maintenance is likely to reduce the use of returns programs. Since consumers prefer to obtain books at outlets where they know the books are likely to be stocked rather than taking a chance on stores that carry a more limited line, it also provides a strong incentive for booksellers to expand. But the privilege of resale price maintenance should be confined to books which publishers want to be price maintained. Resale price maintenance and returns system differ in the transactions costs associated with inventory holding, and publishers' judgement on the comparative advantage of the two schemes should be honored. Publishers should also remain free to authorize sales at discount at any time not to impair the ability of booksellers to dispose of product variants that prove unpopular.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.159-172
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• 2010

The recommender system is one of the possible solutions to assist customers in finding the items they would like to purchase. To date, a variety of recommendation techniques have been developed. One of the most successful recommendation techniques is Collaborative Filtering (CF) that has been used in a number of different applications such as recommending Web pages, movies, music, articles and products. CF identifies customers whose tastes are similar to those of a given customer, and recommends items those customers have liked in the past. Numerous CF algorithms have been developed to increase the performance of recommender systems. Broadly, there are memory-based CF algorithms, model-based CF algorithms, and hybrid CF algorithms which combine CF with content-based techniques or other recommender systems. While many researchers have focused their efforts in improving CF performance, the theoretical justification of CF algorithms is lacking. That is, we do not know many things about how CF is done. Furthermore, the relative performances of CF algorithms are known to be domain and data dependent. It is very time-consuming and expensive to implement and launce a CF recommender system, and also the system unsuited for the given domain provides customers with poor quality recommendations that make them easily annoyed. Therefore, predicting the performances of CF algorithms in advance is practically important and needed. In this study, we propose an efficient approach to predict the performance of CF. Social Network Analysis (SNA) and Artificial Neural Network (ANN) are applied to develop our prediction model. CF can be modeled as a social network in which customers are nodes and purchase relationships between customers are links. SNA facilitates an exploration of the topological properties of the network structure that are implicit in data for CF recommendations. An ANN model is developed through an analysis of network topology, such as network density, inclusiveness, clustering coefficient, network centralization, and Krackhardt's efficiency. While network density, expressed as a proportion of the maximum possible number of links, captures the density of the whole network, the clustering coefficient captures the degree to which the overall network contains localized pockets of dense connectivity. Inclusiveness refers to the number of nodes which are included within the various connected parts of the social network. Centralization reflects the extent to which connections are concentrated in a small number of nodes rather than distributed equally among all nodes. Krackhardt's efficiency characterizes how dense the social network is beyond that barely needed to keep the social group even indirectly connected to one another. We use these social network measures as input variables of the ANN model. As an output variable, we use the recommendation accuracy measured by F1-measure. In order to evaluate the effectiveness of the ANN model, sales transaction data from H department store, one of the well-known department stores in Korea, was used. Total 396 experimental samples were gathered, and we used 40%, 40%, and 20% of them, for training, test, and validation, respectively. The 5-fold cross validation was also conducted to enhance the reliability of our experiments. The input variable measuring process consists of following three steps; analysis of customer similarities, construction of a social network, and analysis of social network patterns. We used Net Miner 3 and UCINET 6.0 for SNA, and Clementine 11.1 for ANN modeling. The experiments reported that the ANN model has 92.61% estimated accuracy and 0.0049 RMSE. Thus, we can know that our prediction model helps decide whether CF is useful for a given application with certain data characteristics.