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1. Research Purpose Consumers rely on various clues to evaluate their decision to patronize a retail store, and store brand is one of them (Dodds 1991; Grewal et al. 1998). As consumers find ever increasing variety of contact points connecting them to specific store, the value of experiential shopping as a means of increasing store's brand equity warrants greater attention from scholars of retail management. Retail shopping values are credited for creating not only cognitive experiences like brand knowledge but also emotional experiences such as shopping pleasure and pride (Schmitt 1999). This may be because today's consumers place emphasis on emotional values associated with shopping pleasure, lifestyle brought to life, brand relationship, and store atmosphere more than utilitarian values such as product quality and price. Many previous literature found this to be true (Ahn and Lee 2011; Mathwick et al. 2001). This brings forth important research issues and questions regarding the roles of shopping experiential values and brand equity with regard to consumer's retail patronage choice. However, despite this importance, research on this area remains quite inadequate (Hwang 2010). For this reason, this study aims to verify the relationships among experiential shopping values, retail store brand equity and tries to link that with customer loyalty by surveying large-scale discount store shoppers in Korea and China. 2. Research Contents In order to carry out the research objective, this study conducted comprehensive literature survey on previous literature by discussing major findings and implications with regard to shopping values and retail brand equity and store loyalty. For data collection, researcher employed survey-based research method where data were collected in two major cities of Korea (Seoul) and China (Bejing) and sampling frame was based on patrons of large discount stores in both countries. Specific research questions raised in this study are as follows; RQ1: How do Korean and Chinese consumers differently perceive of shopping values regarding shopping at large-sclae discount stores? RQ2: Are there differences in consumers' emotional consumption propensities? RQ3: Do Korean and Chinese consumers display different perceptions of brand equity towards large-scale discount stores? RQ4: Are there differences in relationships between shopping values and brand equity for Korean and Chinese consumers? For statistical analysis, SPSS17.0, AMOS17.0 and SmartPLS were employed. 3. Research Results The data collected through face-to-face survey conducted in Seoul and Bejing revealed appropriate data validity and reliability as a result of exploratory/confirmatory factor analysis and reliability tests, andh SEM model yielding satisfactory model fitness. The result of the study may be summarized by three main points. First, as a result of testing differences in consumption dispositions, Chinese consumers showed higher scores in aesthetic and symbolic dispositions, whereas Korean consumers scored higher in hedonic disposition. Second, testing on perceptions toward brand equity of large discount stores showed that Korean consumers exhibited more positive perceptions of brand awareness and brand image than Chinese counterparts. Third, the result of exploratory factor analysis on the experiential shopping values revealed different factors for each country. On Korean side, consumer interest value, aesthetic value, and hedonic value were prominent, whereas on Chinese side, hedonic value, aesthetic value, consumer interest value, and service excellence value were found salient. 4. Research Implications While many previous studies on inter-country differences in retailing area mainly focused on cultural dispositions or orientations to explain the differences, this study sets itself apart by specifically targeting individual consumer's shopping values from an experiential viewpoint. The study result provides important theoretical as well as practical implications for large-scale discount store, especially the impotance of fully exploring the linkage between shopping values and brand equity, which has significant influence on loyalty. Therefore, the specific implications deriving from the result shed some important insights upon the consumption values based on shopping experiences and brand equity. The differences found in store shoppers between the two countries may also provide useful insights for Korean and Chinese retailers who plan to expand their operations globally. Related strategic implications derived from this study is the importance of localizing retail strategy which is based on the differences found in experiential shopping values between the two country groups. Especially the finding that Chinese consumers value consumer interest and service excellence, whereas Koreans place importance on hedonic or aesthetic values indicates the need to differentiate the consumer's psychographical profiles when it comes to expanding retail operations globally. Particularly important will be to pursue price-orienated strategy in China in consideration of the high emphasis on consumer interests and service excellence, but to emphasize the symbolic aspects of brand equity in Korea by maximizing the brand equity associated with aesthetic values and hedonic orientations. 5. Recommendations This study focused on generic retail branded discount stores in both countries, thus making it difficult to tease out store-specific strategies based on specific retail brands. Future studies may benefit fro employing actual brand names in survey questionnaire to verify relationship between shopping values and brand-based store strategy. As with other studies of this nature, this study needs to strengthen the result's generalizability by selecting respondents from a wider spectrum of respondents.
Recently, as the information communication technology develops, the discussion regarding the ubiquitous environment is occurring in diverse perspectives. Ubiquitous environment is an environment that could transfer data through networks regardless of the physical space, virtual space, time or location. In order to realize the ubiquitous environment, the Pervasive Sensing technology that enables the recognition of users' data without the border between physical and virtual space is required. In addition, the latest and diversified technologies such as Context-Awareness technology are necessary to construct the context around the user by sharing the data accessed through the Pervasive Sensing technology and linkage technology that is to prevent information loss through the wired, wireless networking and database. Especially, Pervasive Sensing technology is taken as an essential technology that enables user oriented services by recognizing the needs of the users even before the users inquire. There are lots of characteristics of ubiquitous environment through the technologies mentioned above such as ubiquity, abundance of data, mutuality, high information density, individualization and customization. Among them, information density directs the accessible amount and quality of the information and it is stored in bulk with ensured quality through Pervasive Sensing technology. Using this, in the companies, the personalized contents(or information) providing became possible for a target customer. Most of all, there are an increasing number of researches with respect to recommender systems that provide what customers need even when the customers do not explicitly ask something for their needs. Recommender systems are well renowned for its affirmative effect that enlarges the selling opportunities and reduces the searching cost of customers since it finds and provides information according to the customers' traits and preference in advance, in a commerce environment. Recommender systems have proved its usability through several methodologies and experiments conducted upon many different fields from the mid-1990s. Most of the researches related with the recommender systems until now take the products or information of internet or mobile context as its object, but there is not enough research concerned with recommending adequate store to customers in a ubiquitous environment. It is possible to track customers' behaviors in a ubiquitous environment, the same way it is implemented in an online market space even when customers are purchasing in an offline marketplace. Unlike existing internet space, in ubiquitous environment, the interest toward the stores is increasing that provides information according to the traffic line of the customers. In other words, the same product can be purchased in several different stores and the preferred store can be different from the customers by personal preference such as traffic line between stores, location, atmosphere, quality, and price. Krulwich(1997) has developed Lifestyle Finder which recommends a product and a store by using the demographical information and purchasing information generated in the internet commerce. Also, Fano(1998) has created a Shopper's Eye which is an information proving system. The information regarding the closest store from the customers' present location is shown when the customer has sent a to-buy list, Sadeh(2003) developed MyCampus that recommends appropriate information and a store in accordance with the schedule saved in a customers' mobile. Moreover, Keegan and O'Hare(2004) came up with EasiShop that provides the suitable tore information including price, after service, and accessibility after analyzing the to-buy list and the current location of customers. However, Krulwich(1997) does not indicate the characteristics of physical space based on the online commerce context and Keegan and O'Hare(2004) only provides information about store related to a product, while Fano(1998) does not fully consider the relationship between the preference toward the stores and the store itself. The most recent research by Sedah(2003), experimented on campus by suggesting recommender systems that reflect situation and preference information besides the characteristics of the physical space. Yet, there is a potential problem since the researches are based on location and preference information of customers which is connected to the invasion of privacy. The primary beginning point of controversy is an invasion of privacy and individual information in a ubiquitous environment according to researches conducted by Al-Muhtadi(2002), Beresford and Stajano(2003), and Ren(2006). Additionally, individuals want to be left anonymous to protect their own personal information, mentioned in Srivastava(2000). Therefore, in this paper, we suggest a methodology to recommend stores in U-market on the basis of ubiquitous environment not using personal information in order to protect individual information and privacy. The main idea behind our suggested methodology is based on Feature Matrices model (FM model, Shahabi and Banaei-Kashani, 2003) that uses clusters of customers' similar transaction data, which is similar to the Collaborative Filtering. However unlike Collaborative Filtering, this methodology overcomes the problems of personal information and privacy since it is not aware of the customer, exactly who they are, The methodology is compared with single trait model(vector model) such as visitor logs, while looking at the actual improvements of the recommendation when the context information is used. It is not easy to find real U-market data, so we experimented with factual data from a real department store with context information. The recommendation procedure of U-market proposed in this paper is divided into four major phases. First phase is collecting and preprocessing data for analysis of shopping patterns of customers. The traits of shopping patterns are expressed as feature matrices of N dimension. On second phase, the similar shopping patterns are grouped into clusters and the representative pattern of each cluster is derived. The distance between shopping patterns is calculated by Projected Pure Euclidean Distance (Shahabi and Banaei-Kashani, 2003). Third phase finds a representative pattern that is similar to a target customer, and at the same time, the shopping information of the customer is traced and saved dynamically. Fourth, the next store is recommended based on the physical distance between stores of representative patterns and the present location of target customer. In this research, we have evaluated the accuracy of recommendation method based on a factual data derived from a department store. There are technological difficulties of tracking on a real-time basis so we extracted purchasing related information and we added on context information on each transaction. As a result, recommendation based on FM model that applies purchasing and context information is more stable and accurate compared to that of vector model. Additionally, we could find more precise recommendation result as more shopping information is accumulated. Realistically, because of the limitation of ubiquitous environment realization, we were not able to reflect on all different kinds of context but more explicit analysis is expected to be attainable in the future after practical system is embodied.
Physical and chemical properties of the aggregate by-products including sludge and crushed dust samples collected from the 21 private companies throughout the country were analyzed to evaluate possible usage of the by-products as artificial soil materials for plantation. The pH of the materials ranged from 8.0 to 11.0. The organic matter content was