• Journal of Global Scholars of Marketing Science
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• v.18 no.2
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• pp.19-45
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• 2008

This study is to empirically examine the primary dimensions of visual merchandising (VMD) of internet shopping mall, namely store design, merchandise, and merchandising cues, to be a attractive virtual store to the shoppers. The authors reviewed the literature related to the major components of VMD from the perspective of the AIDA model, which has been mainly applied to the offline store settings. The major purposes of the study are as follows; first, tries to derive the variables related with the components of visual merchandising through reviewing the existing literatures, establish the hypotheses, and test it empirically. Second, examines the relationships between the components of VMD and the attitude toward the VMD, however, putting more emphasis on finding out the component structure of the VMD. VMD needs to be examined with the perspective that an online shopping mall is a virtual self-service or clerkless store, which could reduce the number of employees, help the shoppers search, evaluate and purchase for themselves, and to be explored in terms of the in-store persuasion processes of customers. This study reviewed the literatures related to store design, merchandise, and merchandising cues which might be relevant to the store, product, and promotion respectively. VMD is a total communication tool, and AIDA model could explain the in-store consumer behavior of online shopping. Store design has to do with triggering a consumer attention to the online mall, merchandise with a product related interest, and merchandising cues with promotions such as recommendation and links that induce the desire to pruchase. These three steps might be seen as the processes for purchase actions. The theoretical rationale for the relationship between VMD and AIDA could be found in Tyagi(2005) that the three steps of consumer-oriented merchandising are a store, a product assortment, and placement, in Omar(1999) that three types of interior display are a architectural design display, commodity display, and point-of-sales(POS) display, and in Davies and Ward(2005) that the retail store interior image is related to an atmosphere, merchandise, and in-store promotion. Lee et al(2000) suggested as the web merchandising components a merchandising cues, a shopping metaphor which is an assistant tool for search, a store design, a layout(web design), and a product assortment. The store design which includes differentiation, simplicity and navigation is supposed to be related to the attention to the virtual store. Second, the merchandise dimensions comprising product assortments, visual information and product reputation have to do with the interest in the product offerings. Finally, the merchandising cues that refer to merchandiser(MD)'s recommendation of products and providing the hyperlinks to relevant goods for the shopper is concerned with attempt to induce the desire to purchase. The questionnaire survey was carried out to collect the data about the consumers who would shop at internet shopping malls frequently. To select the subject malls, the mall ranking data announced by a mall rating agency was used to differentiate the most popular and least popular five mall each. The subjects was instructed to answer the questions after navigating the designated mall for five minutes. The 300 questionnaire was distributed to the consumers, 166 samples were used in the final analysis. The empirical testing focused on identifying and confirming the dimensionality of VMD and its subdimensions using a structural equation modeling method. The confirmatory factor analysis for the endogeneous and exogeneous variables was carried out in four parts. The second-order factor analysis was done for a store design, a merchandise, and a merchandising cues, and first-order confirmatory factor analysis for the attitude toward the VMD. The model test results shows that the chi-square value of structural equation is 144.39(d.f 49), significant at 0.01 level which means the proposed model was rejected. But, judging from the ratio of chi-square value vs. degree of freedom, the ratio was 2.94 which smaller than an acceptable level of 3.0, RMR is 0.087 which is higher than a generally acceptable level of 0.08. GFI and AGFI is turned out to be 0.90 and 0.84 respectively. Both NFI and NNFI is 0.94, and CFI 0.95. The major test results are as follows; first, the second-order factor analysis and structural equational modeling reveals that the differentiation, simplicity and ease of identifying current status of the transaction are confirmed to be subdimensions of store design and to be a significant predictors of the dependent variable. This result implies that when designing an online shopping mall, it is necessary to differentiate visually from other malls to improve the effectiveness of the communications of store design. That is, the differentiated store design raise the contrast stimulus to sensory organs to promote the memory of the store and to have a favorable attitude toward the VMD of a store. The results that navigation which means the easiness of identifying current status of shopping affects the attitude to VMD could be interpreted that the navigating processes via the hyperlinks which is characteristics of an internet shopping is a complex and cognitive process and shoppers are likely to lack the sense of overall structure of the store. Consequently, shoppers are likely to be alost amid shopping not knowing where to go. The orientation tool enhance the accessibility of information to raise the perceptive power about the store environment.(Titus & Everett 1995) Second, the primary dimension of merchandise and its subdimensions was confirmed to be unidimensional respectively, have a construct validity, and nomological validity which the VMD dimensions supposed to have a positive correlation with the dependent variable. The subdimensions of product assortment, brand fame and information provision proved to have a positive effect on the attitude toward the VMD. It could be interpreted that the more plentiful the product and brand assortment of the mall is, the more likely the shoppers to favor it. Brand fame and information provision as well affect the VMD attitude, which means that the more famous the brand, the more likely the shoppers would trust and feel familiar with the mall, and the plentifully and visually presented information could have the shopper have a favorable attitude toward the store VMD. Third, it turned out to be that merchandising cue of product recommendation and hyperlinks affect the VMD attitude. This could be interpreted that recommended products could reduce the uncertainty related with the purchase decision, and the hyperlinks to relevant products would help the shopper save the cognitive effort exerted into the information search and gathering, which could lead to a favorable attitude to the VMD. This study tried to sheds some new light on the VMD of online store by reviewing the variables mentioned to be relevant with offline VMD in the existing literatures, and tried to link the VMD components from the perspective of AIDA model. The effect size of the VMD dimensions on the attitude was in the order of the merchandise, the store design and the merchandising cues.It is said that an internet has an unlimited place for display, however, the virtual store is not unlimited since the consumer has a limited amount of cognitive ability to process the external information and internal memory. Particularly, the shoppers are likely to face some difficulties in decision making on account of too many alternative and information overloads. Therefore, the internet shopping mall manager should take into consideration the cost of information search on the part of the consumer, to establish the optimal product placements and search routes. An efficient store composition would be possible by reducing the psychological burdens and cognitive efforts exerted to information search and alternatives evaluation. The store image is in most part determined by the product category and its brand it deals in. The results of this study support this proposition that the merchandise is most important to the VMD attitude than other components, the manager is required to take a strategic approach to VMD. The internet users are getting more accustomed and more knowledgeable about the internet media and more likely to accept the internet as a shopping channel as the period of time during which they use the internet to shop become longer. The web merchandiser should be aware that the product introduction using a moving pictures and a bulletin board become more important in order to present the interactive product information visually and communicate with customers more actively, therefore leading to making the quantity and quality of product information more rich.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.89-105
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• 2014

After emergence of Internet, social media with highly interactive Web 2.0 applications has provided very user friendly means for consumers and companies to communicate with each other. Users have routinely published contents involving their opinions and interests in social media such as blogs, forums, chatting rooms, and discussion boards, and the contents are released real-time in the Internet. For that reason, many researchers and marketers regard social media contents as the source of information for business analytics to develop business insights, and many studies have reported results on mining business intelligence from Social media content. In particular, opinion mining and sentiment analysis, as a technique to extract, classify, understand, and assess the opinions implicit in text contents, are frequently applied into social media content analysis because it emphasizes determining sentiment polarity and extracting authors' opinions. A number of frameworks, methods, techniques and tools have been presented by these researchers. However, we have found some weaknesses from their methods which are often technically complicated and are not sufficiently user-friendly for helping business decisions and planning. In this study, we attempted to formulate a more comprehensive and practical approach to conduct opinion mining with visual deliverables. First, we described the entire cycle of practical opinion mining using Social media content from the initial data gathering stage to the final presentation session. Our proposed approach to opinion mining consists of four phases: collecting, qualifying, analyzing, and visualizing. In the first phase, analysts have to choose target social media. Each target media requires different ways for analysts to gain access. There are open-API, searching tools, DB2DB interface, purchasing contents, and so son. Second phase is pre-processing to generate useful materials for meaningful analysis. If we do not remove garbage data, results of social media analysis will not provide meaningful and useful business insights. To clean social media data, natural language processing techniques should be applied. The next step is the opinion mining phase where the cleansed social media content set is to be analyzed. The qualified data set includes not only user-generated contents but also content identification information such as creation date, author name, user id, content id, hit counts, review or reply, favorite, etc. Depending on the purpose of the analysis, researchers or data analysts can select a suitable mining tool. Topic extraction and buzz analysis are usually related to market trends analysis, while sentiment analysis is utilized to conduct reputation analysis. There are also various applications, such as stock prediction, product recommendation, sales forecasting, and so on. The last phase is visualization and presentation of analysis results. The major focus and purpose of this phase are to explain results of analysis and help users to comprehend its meaning. Therefore, to the extent possible, deliverables from this phase should be made simple, clear and easy to understand, rather than complex and flashy. To illustrate our approach, we conducted a case study on a leading Korean instant noodle company. We targeted the leading company, NS Food, with 66.5% of market share; the firm has kept No. 1 position in the Korean "Ramen" business for several decades. We collected a total of 11,869 pieces of contents including blogs, forum contents and news articles. After collecting social media content data, we generated instant noodle business specific language resources for data manipulation and analysis using natural language processing. In addition, we tried to classify contents in more detail categories such as marketing features, environment, reputation, etc. In those phase, we used free ware software programs such as TM, KoNLP, ggplot2 and plyr packages in R project. As the result, we presented several useful visualization outputs like domain specific lexicons, volume and sentiment graphs, topic word cloud, heat maps, valence tree map, and other visualized images to provide vivid, full-colored examples using open library software packages of the R project. Business actors can quickly detect areas by a swift glance that are weak, strong, positive, negative, quiet or loud. Heat map is able to explain movement of sentiment or volume in categories and time matrix which shows density of color on time periods. Valence tree map, one of the most comprehensive and holistic visualization models, should be very helpful for analysts and decision makers to quickly understand the "big picture" business situation with a hierarchical structure since tree-map can present buzz volume and sentiment with a visualized result in a certain period. This case study offers real-world business insights from market sensing which would demonstrate to practical-minded business users how they can use these types of results for timely decision making in response to on-going changes in the market. We believe our approach can provide practical and reliable guide to opinion mining with visualized results that are immediately useful, not just in food industry but in other industries as well.

• Journal of Korean Home Economics Education Association
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• v.18 no.1 s.39
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• pp.77-93
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• 2006

As our current society is increasingly demanding a Home Economics Education curriculum that projects the recent changes around us, in this study we hope to present which fundamental materials would be needed in Home Economics Education to satisfy the needs of learners in schools and to Provide actual practice and information crucial to live in the future society. A reform of the present Home Economics regime is needed, and as a result of critical analysis on the subject we found that it did not portray the plurality of family relations and cultures owing to the sudden changes in society, nor did it present an active curriculum that could be applied to the changes in social environments. This was partly because of the matter of establishing a proper academic identity of Home Economics Education, the matter of specializing curriculums and general methods of applying them, the academic conservatism in the field of Home Economics, and ineffectiveness of teacher reeducation as well as a lack of leadership on the part of administrative departments. The objective and content structure of Home Economics Education should be reformed to adjust to the current society by taking an approach focused on family and the consumer. In the family part, curriculums should include the formations of various family structures and home cultures to portray a more open concept of family, which should promote gender equality in matters of child upbringing and housework. From a humanitive perspective, Home Education should he dealing with the mediation and decision-making of individuals caught between social advancement and household functions. their communication skills in choosing and deciding, and furthermore their participation in their living communities which may present more material basis of critical scientific philosophies to be discussed in class. Additional themes such as sustainable consumption for earth environment and resource preservation and ways of application to rebuild our diminishing society must also be included in the education curriculum. We should look to find a more integrated approach to Home Economics Education rather than the present field based and specialized regime.

• Journal of the Korean Geographical Society
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• v.30 no.2
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• pp.146-168
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• 1995

problems involved in defining and identifying it. However, data on ownership of business establishments may be useful and one of the best alternatives for this empirical research because of use of limited information about control This study examines the spatial patterns of external control in the Korean manufacturing activities between 1986 and 1992. Using the data on ownership iinkages of multilocational firms between 15 administrative areas, it was possible to construct a matrix of organizational control in terms of the number of establishments. The control matrix was disaggregated by three types of manufacturing industries according to the capital and labor requirements of production processes used in. On the basis of the disaggregated control matrix, a series of measures were calculated for investigating the magnitude and direction of control as well as the external dependency. In the past decades Korean industrialization development has risen at a rapid pace, deepening integration into the world economy, together with the continuing growth of the large industrial firms. The expanded scale of large firms led to a spatial separation of production from control, Increasing branch plants in the nation. But recent important changes have occurred in the spatial organization of production by technological development, increasing international competition, and changing local labor markets. These changes have forced firms to reorganize their production structures, resulting in changes of the organizational structures in certain industries and regions. In this context the empirical analysis revealed the following principal trends. In general term, the geography of corporate control in Korea is marked by a twofold pattern of concentration and dispersion. The dominance of Seoul as a major command and control center has been evident over the period, though its overall share of allexternally controlled establishments has decreased from 88% to 79%. And the substantial amount of external control from Seoul has concentrated to the Kyongki and Southeast regions which are well-developed industrial areas. But Seoul's corporate ownership links tend to streteh across the country to the less-developed regions, most of which have shown a significant increase of external dependency during the period 1986-1992. At the same time, a geographic dispersion of corporate control is taking place as Kyongki province and Pusan are developing as new increasingly important command and control reaions. Though these two resions contain a number of branch plants controlled from other locations, they may be increasingly attractive as a headquarters location with increasing locally owned establishments. The geographical patterns of external control observable in each of three types of manufacturing industries were examined in order to distinguish the changing spatial structures of organizational control with respect to the characteristics of the production processes. Labor intensive manufacturing with unskilled iabor experienced the strongest external pressure from foreign competition and a lack of low cost labor. The high pressure expected not only to disinte-grate the production process but also led to location of production facilities in areas of cheap labor. The linkages of control between Seoul and the less-developed regions have slightly increased, while the external dependency of the industrialized regions might be reduced from the tendency of organizational disintegration. Capita1 intensive manufacturing operates under high entry and exit barriers due to capital intensity. The need to increase scale economies ied to an even stronger economic and spatial oncentration of control. The strong geographical oncentration of control might be influenced by orporate and organizational scale economies rather than by locational advantages. Other sectors experience with respect to branch plants of multilocational firms. The policy implications of the increase of external dependency in less-developed regions may be negative because of the very share of unskilled workers and lack of autonomy in decision making. The strong growth of the national economy and a scarcity of labor in core areas have been important factors in this regional decentralization of industries to less-developed regions. But the rather gloomy prospects of the economic growth in the near future could prevent the further industrialization of less-developed areas. A major rethinking of regional policy would have to take place towards a need for a regional policy actively favoring indigenous establishments.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.1-23
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• 2014

Market forecasting aims to estimate the sales volume of a product or service that is sold to consumers for a specific selling period. From the perspective of the enterprise, accurate market forecasting assists in determining the timing of new product introduction, product design, and establishing production plans and marketing strategies that enable a more efficient decision-making process. Moreover, accurate market forecasting enables governments to efficiently establish a national budget organization. This study aims to generate a market growth curve for ICT (information and communication technology) goods using past time series data; categorize products showing similar growth patterns; understand markets in the industry; and forecast the future outlook of such products. This study suggests the useful and meaningful process (or methodology) to identify the market growth pattern with quantitative growth model and data mining algorithm. The study employs the following methodology. At the first stage, past time series data are collected based on the target products or services of categorized industry. The data, such as the volume of sales and domestic consumption for a specific product or service, are collected from the relevant government ministry, the National Statistical Office, and other relevant government organizations. For collected data that may not be analyzed due to the lack of past data and the alteration of code names, data pre-processing work should be performed. At the second stage of this process, an optimal model for market forecasting should be selected. This model can be varied on the basis of the characteristics of each categorized industry. As this study is focused on the ICT industry, which has more frequent new technology appearances resulting in changes of the market structure, Logistic model, Gompertz model, and Bass model are selected. A hybrid model that combines different models can also be considered. The hybrid model considered for use in this study analyzes the size of the market potential through the Logistic and Gompertz models, and then the figures are used for the Bass model. The third stage of this process is to evaluate which model most accurately explains the data. In order to do this, the parameter should be estimated on the basis of the collected past time series data to generate the models' predictive value and calculate the root-mean squared error (RMSE). The model that shows the lowest average RMSE value for every product type is considered as the best model. At the fourth stage of this process, based on the estimated parameter value generated by the best model, a market growth pattern map is constructed with self-organizing map algorithm. A self-organizing map is learning with market pattern parameters for all products or services as input data, and the products or services are organized into an $N{\times}N$ map. The number of clusters increase from 2 to M, depending on the characteristics of the nodes on the map. The clusters are divided into zones, and the clusters with the ability to provide the most meaningful explanation are selected. Based on the final selection of clusters, the boundaries between the nodes are selected and, ultimately, the market growth pattern map is completed. The last step is to determine the final characteristics of the clusters as well as the market growth curve. The average of the market growth pattern parameters in the clusters is taken to be a representative figure. Using this figure, a growth curve is drawn for each cluster, and their characteristics are analyzed. Also, taking into consideration the product types in each cluster, their characteristics can be qualitatively generated. We expect that the process and system that this paper suggests can be used as a tool for forecasting demand in the ICT and other industries.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.53-74
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• 2018

Since South Korea has an economic structure that has a characteristic which market-dependent on overseas, the tourism industry is considered as a very important industry for the national economy, such as improving the country's balance of payments or providing income and employment increases. Accordingly, the necessity of more accurate forecasting on the demand in the tourism industry has been raised to promote its industry. In the related research, economic variables such as exchange rate and income have been used as variables influencing tourism demand. As information technology has been widely used, some researchers have also analyzed the effect of media on tourism demand. It has shown that the media has a considerable influence on traveler's decision making, such as choosing an outbound destination. Furthermore, with the recent availability of online information searches to obtain the latest information and two-way communication in social media, it is possible to obtain up-to-date information on travel more quickly than before. The information in online media such as blogs can naturally create the Word-of-Mouth effect by sharing useful information, which is called eWOM. Like all other service industries, the tourism industry is characterized by difficulty in evaluating its values before it is experienced directly. And furthermore, most of the travelers tend to search for more information in advance from various sources to reduce the perceived risk to the destination, so they can also be influenced by online media such as online news. In this study, we suggested that the number of online media posting, which causes the effects of Word-of-Mouth, may have an effect on the number of outbound travelers. We divided online media into public media and private media according to their characteristics and selected online news as public media and blog as private media, one of the most popular social media in tourist information. Based on the previous studies about the eWOM effects on online news and blog, we analyzed a relationship between the volume of eWOM and the outbound tourism demand through the panel model. To this end, we collected data on the number of national outbound travelers from 2007 to 2015 provided by the Korea Tourism Organization. According to statistics, the highest number of outbound tourism demand in Korea are China, Japan, Thailand, Hong Kong and the Philippines, which are selected as a dependent variable in this study. In order to measure the volume of eWOM, we collected online news and blog postings for the same period as the number of outbound travelers in Naver, which is the largest portal site in South Korea. In this study, a panel model was established to analyze the effect of online media on the demand of Korean outbound travelers and to identify that there was a significant difference in the influence of online media by each time and countries. The results of this study can be summarized as follows. First, the impact of the online news and blog eWOM on the number of outbound travelers was significant. We found that the number of online news and blog posting have an influence on the number of outbound travelers, especially the experimental result suggests that both the month that includes the departure date and the three months before the departure were found to have an effect. It is shown that online news and blog are online media that have a significant influence on outbound tourism demand. Next, we found that the increased volume of eWOM in online news has a negative effect on departure, while the increase in a blog has a positive effect. The result with the country-specific models would be the same. This paper shows that online media can be used as a new variable in tourism demand by examining the influence of the eWOM effect of the online media. Also, we found that both social media and news media have an important role in predicting and managing the Korean tourism demand and that the influence of those two media appears different depending on the country.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.23-45
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• 2020

Big data is creating in a wide variety of fields such as medical care, manufacturing, logistics, sales site, SNS, and the dataset characteristics are also diverse. In order to secure the competitiveness of companies, it is necessary to improve decision-making capacity using a classification algorithm. However, most of them do not have sufficient knowledge on what kind of classification algorithm is appropriate for a specific problem area. In other words, determining which classification algorithm is appropriate depending on the characteristics of the dataset was has been a task that required expertise and effort. This is because the relationship between the characteristics of datasets (called meta-features) and the performance of classification algorithms has not been fully understood. Moreover, there has been little research on meta-features reflecting the characteristics of multi-class. Therefore, the purpose of this study is to empirically analyze whether meta-features of multi-class datasets have a significant effect on the performance of classification algorithms. In this study, meta-features of multi-class datasets were identified into two factors, (the data structure and the data complexity,) and seven representative meta-features were selected. Among those, we included the Herfindahl-Hirschman Index (HHI), originally a market concentration measurement index, in the meta-features to replace IR(Imbalanced Ratio). Also, we developed a new index called Reverse ReLU Silhouette Score into the meta-feature set. Among the UCI Machine Learning Repository data, six representative datasets (Balance Scale, PageBlocks, Car Evaluation, User Knowledge-Modeling, Wine Quality(red), Contraceptive Method Choice) were selected. The class of each dataset was classified by using the classification algorithms (KNN, Logistic Regression, Nave Bayes, Random Forest, and SVM) selected in the study. For each dataset, we applied 10-fold cross validation method. 10% to 100% oversampling method is applied for each fold and meta-features of the dataset is measured. The meta-features selected are HHI, Number of Classes, Number of Features, Entropy, Reverse ReLU Silhouette Score, Nonlinearity of Linear Classifier, Hub Score. F1-score was selected as the dependent variable. As a result, the results of this study showed that the six meta-features including Reverse ReLU Silhouette Score and HHI proposed in this study have a significant effect on the classification performance. (1) The meta-features HHI proposed in this study was significant in the classification performance. (2) The number of variables has a significant effect on the classification performance, unlike the number of classes, but it has a positive effect. (3) The number of classes has a negative effect on the performance of classification. (4) Entropy has a significant effect on the performance of classification. (5) The Reverse ReLU Silhouette Score also significantly affects the classification performance at a significant level of 0.01. (6) The nonlinearity of linear classifiers has a significant negative effect on classification performance. In addition, the results of the analysis by the classification algorithms were also consistent. In the regression analysis by classification algorithm, Naïve Bayes algorithm does not have a significant effect on the number of variables unlike other classification algorithms. This study has two theoretical contributions: (1) two new meta-features (HHI, Reverse ReLU Silhouette score) was proved to be significant. (2) The effects of data characteristics on the performance of classification were investigated using meta-features. The practical contribution points (1) can be utilized in the development of classification algorithm recommendation system according to the characteristics of datasets. (2) Many data scientists are often testing by adjusting the parameters of the algorithm to find the optimal algorithm for the situation because the characteristics of the data are different. In this process, excessive waste of resources occurs due to hardware, cost, time, and manpower. This study is expected to be useful for machine learning, data mining researchers, practitioners, and machine learning-based system developers. The composition of this study consists of introduction, related research, research model, experiment, conclusion and discussion.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.11
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• pp.66-79
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• 2016

A discussion has recently emerged over the increase of approvals of K-REITs, which is concluded on the basis of how to raise funds for business activity, fulfill the expected rate of return and maximize the management of managing investment funds. In addition, corporations need to acknowledge the necessity of the capital structure reflected in the current economic environment and decision-making processes. This research analyzed the characteristics by investment types and influence factors about the debt ratio of K-REITs. The data were collected from general management about business state, investment, and finance from 2002 to 2015 in K-REITs (except for the GFC period of 2007~2009). The results of the research demonstrated the high ratios of the largest shareholder characteristics, which are corporation, pension funds, mutual funds, banks, securities, insurance, and, recently, the increasing ratio of the largest shareholder and major stockholder. The investment of K-REITs is increasing the role of institutional investors that take a leading development of K-REITs. The behaviors of simultaneous investment of institutional investors were analyzed to show that they received higher interest rates than other financial institutions and ran in parallel with attraction and compensation. The results of the multiple regressions analysis, utilizing variables about debt ratio were as follows. The debt ratio showed a negative (-) relation that profitability is increasing, which matches the pecking order theory and trade off theory. On the other hand, investment opportunities (growth potential) showed a negative (-) relation and assets scale that indicated a positive (+) relation. The research results are reflected as follows. K-REITs focused on private equity REITs more than public offering REITs, and in the case of financing the capital of others, loan capital is operated under the guarantee of tangible assets (most of real estate) more than financing of the stock market. Further, after the GFC, the capital of others was actively utilized in K-REITs business, and the debt ratio showed that the determinant factors by the ratio and characteristics of the largest shareholder and investment products.

• Journal of Distribution Science
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• v.9 no.1
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• pp.29-38
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• 2011

Since a distribution market was opened in 1993 after the conclusion of the Uruguay Round (UR), various new businesses emerged in the Korean retail industry, such as convenience shops, supermarkets, specialty stores, non-store marketing methods, and cyber shopping malls, in addition to traditional markets and department stores. Competition among these retail businesses has intensified. According to the National Statistical Office (NSO), the growth rate of the total retail industry has shown a 32% increase in the past 5 years. While department stores, supermarkets, specialty stores, and other non-store retailing venues have shown signs of stagnation at a growth rate of 20-30%, which is similar to the growth rate of the entire retail industry, convenience shops and non-store marketing have shown 60-70% growth over the same period. By comparison, the growth rate of cyber shopping malls has nearly tripled. When applying development aspects of retail businesses through the competition to the retail life cycle, mom-and-pop stores and traditional markets have already entered the decline phase as specialty stores reach their maturity phase and demonstrate their limit of growth. Department stores are now in the latter part of the growth phase, which is still considered to have some growth potential. Big super markets are still in the early part of their growth stage although they were introduced 20 years ago. Meanwhile, retail businesses such as convenience stores, supermarkets, mail order houses, and warehouse stores are entering the middle growth phase and are expected to continue with their quantitative growth. At a time when most retail businesses in Korea are in a state of development or in the full growth stage, what kind of new innovative retailing will appear and develop? Moreover, what growth engine will drive it? This study analyzes the appearance of innovative retailing and its development process by establishing a discussable consumer's choice model through the interlocking mutual behavior of differentiated competitiveness and consumers' choice based on an awareness of this issue. The analysis of the results of this study can be summarized as follows. First, if a new vacuum zone emerges at the retail market level, innovative retailing such as low price/low service or high price/high service will emerge simultaneously. Second, if the number of new businesses in the vacuum zone increases, this will create competitiveness among the businesses, and each retailer will develop raising of level. Third, if a new business that raises the level develops, competition between the new and the existing retailer will occur, and an assimilation process between the existing retailing and the new retailing will be unfolded. Fourth, each retailing will promote distribution innovations in order to break the frontier of the existing distribution technology, and other retailing will follow the innovator. On the basis of an analysis of the abovementioned results, this study presents the following three suggestions. First, responding to the consumer's decision-making process on the attributes of retail shops that promote differentiation in strategies, this study established a consumer's choice model that can be discussed in relation to changes in market share. Second, this study provided an analysis of the emerging and developmental processes of innovative retail businesses using a more precise logical structure on the basis of the consumer's choice model described in this study. Third, the development process of retail businesses discussed in this study presented retailing solutions regarding management aspects on how to compose a strong retail mix that can help retail businesses gain competitive advantages in the market.

• Land and Housing Review
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• v.3 no.4
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• pp.369-378
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• 2012

In France, there are many forms of organizations based on the intercommunal solidarity for city development and management. The purpose of the collaboration among Communes is to achieve high quality and well-equipped service-delivery system through co-operation of public services needed grand finances : water supply and sewage system and waste disposal system etc. The cooperation among French Communes and its effects, even though these were owing to the existing French local administration system, continued throughout regional co-management and social co-development process. This study suggested some characteristics and implications of the collaborative-style French new-town development and management organizations focused on the EPA, SAN and CA. First, the role of developmental corporation like EPA and its collaborative structure of decision-making are meaningful, because in these ways many related Communes could share a goal of new town development. Second, the way of new town corporation (SAN) is important in the sense of enabling the Communes to collaborate with each others while maintaining autonomy, so those are not simply state-directed objects, which was very difficult in the former French local administration system. Finally, transforming to CA (Communautes d'agglomeration:city community), EPA as an intercommunal corporation is possible to extend its purpose to the domain of regional planning including new town and periphery areas and change its position to a subject which can practice Commune's sustainable development according to stages of city's development and maturity. The most important implication of this study on urban development in Korea is that administrative consultative council or association among local governments and related authorities need to be established and effectively operate because multi-stakeholders could share a goal of urban development and management through that.