• Restorative Dentistry and Endodontics
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• v.19 no.1
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• pp.124-134
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• 1994

The shade of restorative materials is very important for successful restoration esthetically harmonized with the natural tooth. The purpose of this study was to evaluate the color stability and the opacity change of conventional chemical setting and visible light curing glass-ionomer cements for restorative esthetic filling. Specimens of each brand (GC Fuji II and Fuji II LC) were uniformly prepared and divided into three groups: In group l(control group), the specimens received no surface treatment; in group 2, the specimens were coated with varnish and the excess gently blown off; and in group 3. the specimens were coated with light-cured bonding resin and irradiated by a visible light curing unit for 20 seconds on both sides. All specimens were stored in distilled water at $37^{\circ}C$ and checked after for 24 hours. 2 months. 4 months, 6 months. and 8 months. The color characteristics($L^*,\;a^*,\;b^*$) and the opacity(Y%) of all the samples were measured by a spectrocolorimeter and the total color differences(${\Delta}E^*$) and opacity changes(${\Delta}Y%$) were computed. The following results were obtained : 1. The total tolor differences in all groups increased with time. 2. The total color differences of the LC groups after immersion for 8 months in distilled water at $37^{\circ}C$ were lower than those of GC groups(p<0.01), and the total color differences of the varnish or the light-cured bonding resin coated groups were lower than those of the control group with glass-ionomer cements which had no surface treatment(p<0.01). 3. In all groups the translucency decreased with time. 4. In the control group and the varnish coating group. the opacity changes of the GC groups were lower than those of the LC groups(p<0.01) and in the light-cured bonding resin coated group, there was no significant difference between the GC group and the LC group. 5. The opacity changes of the varnish or the light-cured bonding resin coated groups were lower than those of the control group(p<0.01). These results suggest that color change and opacity of conventional chemical setting and light cured glass-ionomer cement were increased with time, and the color changes and the opacity changes of a control group after immersion for 8 months in distilled water at $37^{\circ}C$ were greater than those of the varnish or the light-cured bonding resin coated groups.

• Journal of the Korean Society for Library and Information Science
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• v.56 no.4
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• pp.129-159
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• 2022

This study generated primary data for supporting the place branding as a part of the library advertising and marketing strategies to increase public library visits. The literature review enabled the use of the place branding concepts to discover the relationships among the constituent parts, factors, expected outcomes, and loyalty, then to develop the research model and the hypothesis, which were verified using the Structural Equation Model. There were 34 research hypotheses, of which 21 were adopted. The place image factors such as library reliability, library reciprocity, and library safety were found to be significant. This study derived social contribution value as new place value and place image factors as the potential brand image of public libraries. It helped select the place image factors that best fit the local library's core values (i.e., place value). This study is meaningful because it is a fundamental study to introduce place branding in public libraries as an advertising and marketing strategy. And it is expected that public libraries will grow into high-quality brands with high awareness, loyalty, and secure leadership in the local community.

• Journal of Global Scholars of Marketing Science
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• v.18 no.4
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• pp.195-215
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• 2008

The scarcity is pervasive aspect of human life and is a fundamental precondition of economic behavior of consumers. Also, the effect of scarcity message is a power social influence principle used by marketers to increase the subjective desirability of products. Because valuable objects are often scare, consumers tend to infer the scarce objects are valuable. Marketers often do base promotional appeals on the principle of scarcity to increase the subjective desirability their products among consumers. Specially, advertisers and retailers often promote their products using restrictions. These restriction act to constraint consumers' ability th take advantage of the promotion and can assume several forms. For example, some promotions are advertised as limited time offers, while others limit the quantity that can be bought at the deal price by employing the statements such as 'limit one per consumer,' 'limit 5 per customer,' 'limited products for special commemoration celebration,' Some retailers use statements extensively. A recent weekly flyer by a prominent retailer limited purchase quantities on 50% of the specials advertised on front page. When consumers saw these phrase, they often infer value from the product that has limited availability or is promoted as being scarce. But, the past researchers explored a direct relationship between the purchase quantity and time limit on deal purchase intention. They also don't explored that all restriction message are not created equal. Namely, we thought that different restrictions signal deal value in different ways or different mechanism. Consumers appear to perceive that time limits are used to attract consumers to the brand, while quantity limits are necessary to reduce stockpiling. This suggests other possible differences across restrictions. For example, quantity limits could imply product quality (i.e., this product at this price is so good that purchases must be limited). In contrast, purchase preconditions force the consumer to spend a certain amount to qualify for the deal, which suggests that inferences about the absolute quality of the promoted item would decline from purchase limits (highest quality) to time limits to purchase preconditions (lowest quality). This might be expected to be particularly true for unfamiliar brands. However, a critical but elusive issue in scarcity message research is the impacts of a inferred motives on the promoted scarcity message. The past researchers not explored possibility of inferred motives on the scarcity message context. Despite various type to the quantity limits message, they didn't separated scarcity message among the quantity limits. Therefore, we apply a stricter definition of scarcity message(i.e. quantity limits) and consider scarcity message type(general scarcity message vs. special scarcity message), scarcity depth(high vs. low). The purpose of this study is to examine the effect of the scarcity message on the consumer's purchase intension. Specifically, we investigate the effect of general versus special scarcity messages on the consumer's purchase intention using the level of the scarcity depth as moderators. In other words, we postulates that the scarcity message type and scarcity depth play an essential moderating role in the relationship between the inferred motives and purchase intention. In other worlds, different from the past studies, we examine the interplay between the perceived motives and scarcity type, and between the perceived motives and scarcity depth. Both of these constructs have been examined in isolation, but a key question is whether they interact to produce an effect in reaction to the scarcity message type or scarcity depth increase. The perceived motive Inference behind the scarcity message will have important impact on consumers' reactions to the degree of scarcity depth increase. In relation ti this general question, we investigate the following specific issues. First, does consumers' inferred motives weaken the positive relationship between the scarcity depth decrease and the consumers' purchase intention, and if so, how much does it attenuate this relationship? Second, we examine the interplay between the scarcity message type and the consumers' purchase intention in the context of the scarcity depth decrease. Third, we study whether scarcity message type and scarcity depth directly affect the consumers' purchase intention. For the answer of these questions, this research is composed of 2(intention inference: existence vs. nonexistence)${\times}2$(scarcity type: special vs. general)${\times}2$(scarcity depth: high vs. low) between subject designs. The results are summarized as follows. First, intention inference(inferred motive) is not significant on scarcity effect in case of special scarcity message. However, nonexistence of intention inference is more effective than existence of intention inference on purchase intention in case of general scarcity. Second, intention inference(inferred motive) is not significant on scarcity effect in case of low scarcity. However, nonexistence of intention inference is more effective than existence of intention inference on purchase intention in case of high scarcity. The results of this study will help managers to understand the relative importance among the type of the scarcity message and to make decisions in using their scarcity message. Finally, this article have several contribution. First, we have shown that restrictions server to activates a mental resource that is used to render a judgment regarding a promoted product. In the absence of other information, this resource appears to read to an inference of value. In the presence of other value related cue, however, either database(i.e., scarcity depth: high vs. low) or conceptual base(i.e.,, scarcity type special vs. general), the resource is used in conjunction with the other cues as a basis for judgment, leading to different effects across levels of these other value-related cues. Second, our results suggest that a restriction can affect consumer behavior through four possible routes: 1) the affective route, through making consumers feel irritated, 2) the cognitive making route, through making consumers infer motivation or attribution about promoted scarcity message, and 3) the economic route, through making the consumer lose an opportunity to stockpile at a low scarcity depth, or forcing him her to making additional purchases, lastly 4) informative route, through changing what consumer believe about the transaction. Third, as a note already, this results suggest that we should consider consumers' inferences of motives or attributions for the scarcity dept level and cognitive resources available in order to have a complete understanding the effects of quantity restriction message.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.39-70
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• 2017

Data-drive analytics techniques have been recently applied to public surveys. Instead of simply gathering survey results or expert opinions to research the preference for a recently launched product, enterprises need a way to collect and analyze various types of online data and then accurately figure out customer preferences. In the main concept of existing data-based survey methods, the sentiment lexicon for a particular domain is first constructed by domain experts who usually judge the positive, neutral, or negative meanings of the frequently used words from the collected text documents. In order to research the preference for a particular product, the existing approach collects (1) review posts, which are related to the product, from several product review web sites; (2) extracts sentences (or phrases) in the collection after the pre-processing step such as stemming and removal of stop words is performed; (3) classifies the polarity (either positive or negative sense) of each sentence (or phrase) based on the sentiment lexicon; and (4) estimates the positive and negative ratios of the product by dividing the total numbers of the positive and negative sentences (or phrases) by the total number of the sentences (or phrases) in the collection. Furthermore, the existing approach automatically finds important sentences (or phrases) including the positive and negative meaning to/against the product. As a motivated example, given a product like Sonata made by Hyundai Motors, customers often want to see the summary note including what positive points are in the 'car design' aspect as well as what negative points are in thesame aspect. They also want to gain more useful information regarding other aspects such as 'car quality', 'car performance', and 'car service.' Such an information will enable customers to make good choice when they attempt to purchase brand-new vehicles. In addition, automobile makers will be able to figure out the preference and positive/negative points for new models on market. In the near future, the weak points of the models will be improved by the sentiment analysis. For this, the existing approach computes the sentiment score of each sentence (or phrase) and then selects top-k sentences (or phrases) with the highest positive and negative scores. However, the existing approach has several shortcomings and is limited to apply to real applications. The main disadvantages of the existing approach is as follows: (1) The main aspects (e.g., car design, quality, performance, and service) to a product (e.g., Hyundai Sonata) are not considered. Through the sentiment analysis without considering aspects, as a result, the summary note including the positive and negative ratios of the product and top-k sentences (or phrases) with the highest sentiment scores in the entire corpus is just reported to customers and car makers. This approach is not enough and main aspects of the target product need to be considered in the sentiment analysis. (2) In general, since the same word has different meanings across different domains, the sentiment lexicon which is proper to each domain needs to be constructed. The efficient way to construct the sentiment lexicon per domain is required because the sentiment lexicon construction is labor intensive and time consuming. To address the above problems, in this article, we propose a novel product reputation mining algorithm that (1) extracts topics hidden in review documents written by customers; (2) mines main aspects based on the extracted topics; (3) measures the positive and negative ratios of the product using the aspects; and (4) presents the digest in which a few important sentences with the positive and negative meanings are listed in each aspect. Unlike the existing approach, using hidden topics makes experts construct the sentimental lexicon easily and quickly. Furthermore, reinforcing topic semantics, we can improve the accuracy of the product reputation mining algorithms more largely than that of the existing approach. In the experiments, we collected large review documents to the domestic vehicles such as K5, SM5, and Avante; measured the positive and negative ratios of the three cars; showed top-k positive and negative summaries per aspect; and conducted statistical analysis. Our experimental results clearly show the effectiveness of the proposed method, compared with the existing method.

• Asia Marketing Journal
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• v.13 no.3
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• pp.55-77
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• 2011

This study investigate the interaction effects of bundle price discount framing and message framing on consumer's attitude of bundle component. Although each effect of bundle price discount framing and message framing has been explored individually, few attempts have been made to invest them jointly. This study tests the interaction effects of bundle price discount framing and message framing on consumer's evaluation of bundle component. Moreover, this research focuses on consumer's evaluation of individual bundle component while the existing research on bundling primarily focused on consumer's evaluation of the bundle. Prior research suggests that consumers are sensitive to the framing of prices and discounts in the presentation of the bundle offer. For example, there is considerable evidence that partitioning or consolidating the prices of a bundle can influence the attractiveness of the bundle offer. Similarly, there is evidence that an equivalent price reduction to the overall bundle, one of the individual products in the bundle, or distributed among the individual products in the bundle can alter the perceived attractiveness of the offer (e.g. Chakravarti, Krish, Paul, and Srivastava 2002; Hamilton and Srivastava 2008; Janiszewski and Cunha 2004; Johnson, Herrmann and Bauer 1999; ; Morwitz, Greenleaf, and Johnson 1998; Yadav 1994; 1995). In line with these earlier research, this research suggests that the bundle type can influence the consumer's evaluation of bundle component. There are two types of bundle - mixed-leader bundle and mixed-joint bundle. In mixed-leader bundling, the price of one of the two products is discounted when the other product is purchased at the regular price. In mixed-joint bundling, a single price is set when the two product are purchased jointly. This study supposes that the teeth whitening product is the leader product in a mixed-leader bundle. So bundle price discount framing is manipulated such as "Buy the teeth whitening product (regular price \80,000) and get 50% discount on the functional toothpaste(regular price \40,000), special set price \100,000" or "Buy the functional toothpaste and the teeth whitening product as a set and get discount for the set, special set price \60,000". Message framing is manipulated through the product claims described in an advertising bill. The positive framing presents that "Over 95% of users achieved the expected 2-3 shades of improvement in two weeks" where as the negative framing presents "less than 5% of users did not achieve the expected 2-3 shades of improvement in two weeks". This study uses hypothetical brand name of the teeth whitening product and the functional toothpaste This study is based on a 2x2 factorial design with bundle discount framing (mixed-leader bundle vs. mixed-joint bundle) and massage framing (positive vs. negative). The dependant variables are consumer's perceived quality and attitude of the teeth whitening product The data reveals that two dependant variables are correlated, so the data is analyzed with two-way MANOVA. This research explores the significant interaction effect of bundle discount framing and message framing on consumer's perceived quality and attitude of the teeth whitening product. When the message framing is positive, consumer's perceived quality and attitude of the teeth whitening product is higher in mixed-leader bundle than mixed-joint bundle condition. However, when the message framing is negative, consumer's evaluation is higher in mixed-joint bundle than mixed-leader bundle. The author explains this result by stating that consumers are less likely to use heuristics such as price-quality association and value discounting hypothesis(Raghubir 2004) in the negative message framing condition. Additionally, consumer's perceived risk of the teeth whitening product in the negative message framing condition can be more reduced by the bundle partner(e.g. the toothpaste) in mixed-joint bundle than mixed-leader bundle. Based on the results, marketing managers are advised to use different bundle type based on message framing of their product.

• Journal of Distribution Research
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• v.15 no.1
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• pp.1-24
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• 2010

I. Introduction The industry of domestic discount store was reorganized with 2 bigs and 1 middle, and then Home Plus took over Home Ever in 2008. In present, Oct, 2008, E-Mart has 118 outlets, Home Plus 112 outlets, and Lotte Mart 60 stores. With total number of 403 outlets, they are getting closer to a saturation point. We know that the industry of discount store has been getting through the mature stage in retail life cycle. There are many efforts to maintain existing customers rather than to get new customers. These competitions in this industry lead firms to acknowledge 'store loyalty' to be the first strategic tool for their sustainable competitiveness. In other words, the strategic goal of discount store is to boost up the repurchase rate of customers throughout increasing store loyalty. If owners of retail shops can figure out main factors for store loyalty, they can easily make more efficient and effective retail strategies which bring about more sales and profits. In this practical sense, there are many papers which are focusing on the antecedents of store loyalty. Many researchers have been inspecting causal relationships between antecedents and store loyalty; store characteristics, store image, atmosphere in store, sales promotion in store, service quality, customer characteristics, crowding, switching cost, trust, satisfaction, commitment, etc., In recent times, many academic researchers and practitioners have been interested in 'dual path model for service loyalty'. There are two paths in store loyalty. First path has an emphasis on symbolic and emotional dimension of service brand, and second path focuses on quality of product and service. We will call the former an extrinsic path and call the latter an intrinsic path. This means that consumers' cognitive path for store loyalty is not single but dual. Existing studies for dual path model are as follows; First, in extrinsic path, some papers in domestic settings show that there is 'store personality-identification-loyalty' path. Second, service quality has an effect on loyalty, which is a behavioral variable, in the mediation of customer satisfaction. But, it's very difficult to find out an empirical paper applied to domestic discount store based on this mediating model. The domestic research for store loyalty concentrates on not only intrinsic path but also extrinsic path. Relatively, an attention for intrinsic path is scarce. And then, we acknowledge that there should be a need for integrating extrinsic and intrinsic path. Also, in terms of retail industry, this study is meaningful because retailers want to achieve their competitiveness by using store loyalty. And so, the purpose of this paper is to integrate and complement two existing paths into one specific model, dual path model. This model includes both intrinsic and extrinsic path for store loyalty. With this research, we would expect to understand the full process of forming customers' store loyalty which had not been clearly explained. In other words, we propose the dual path model for discount store loyalty which has been originated from store personality and service quality. This model is composed of extrinsic path, discount store personality$\rightarrow$store identification$\rightarrow$store loyalty, and intrinsic path, service quality of discount store$\rightarrow$customer satisfaction$\rightarrow$store loyalty. II. Research Model Dual path model integrates intrinsic path and extrinsic path into one specific model. Intrinsic path put an emphasis on quality characteristics and extrinsic path focuses on brand characteristics. Intrinsic path is based on information processing perspective, and extrinsic path emphasizes symbolic and emotional dimension of brand. This model is composed of extrinsic path, discount store personality$\rightarrow$store identification$\rightarrow$store loyalty, and intrinsic path, service quality of discount store$\rightarrow$customer satisfaction$\rightarrow$store loyalty. Hypotheses are as follows; Hypothesis 1: Service quality perceived by customers in discount store has an positive effect on customer satisfaction Hypothesis 2: Store personality perceived by customers in discount store has an positive effect on store identification Hypothesis 3: Customer satisfaction in discount store has an positive effect on store loyalty. Hypothesis 4: Store identification has an positive effect on store loyalty. III. Results and Implications We examined consumers who patronize discount stores for samples of this study. With the structural equation model(SEM) analysis, we empirically tested the validity and fitness of the dual path model for store loyalty in discount stores. As results, the fitness indices of this model were well fitted to data obtained. In an intrinsic path, service quality(SQ) is positively related to customer satisfaction(CS), customer satisfaction(CS) has very significantly positive effect on store loyalty(SL). Also, in an extrinsic path, the store personality(SP) is positively related to store identification(SI), it shows significant effect on store loyalty. Table 1 shows the results as follows; There are some theoretical and practical implications. First, Many studies on discount store loyalty have been executed from various perspectives. But there has been no integrative view on this issue. And so, this research was theoretically designed to integrate various and controversial arguments into one systematic model. We empirically tested dual path model forming store loyalty, and brought up a systematic and integrative framework for future studies. We want to expect creative and aggressive research activities. Second, a few established papers are focused on the relationship between antecedents and store loyalty; store characteristics, atmosphere, sales promotion in store, service quality, trust, commitment, etc., There has been some limits in understanding thoroughly the formation process of store loyalty with a singular path, intrinsic or extrinsic. Beyond these limits in single path, we could propose the new path for store loyalty. This is meaningful. Third, discount store firms make and execute marketing strategies for increasing store loyalty. This research provides real practitioners with reference framework needed for actual strategy formation. Because this paper shows integrated and systematic path for store loyalty. A special feature of this study is to represent 6 sub dimensions of service quality in intrinsic path and 4 sub dimensions of store personality in extrinsic path. Marketers can make more analytic marketing planning with concrete sub dimensions of service quality and store personality. When marketers of discount stores make strategic planning like MPR, Ads, campaign, sales promotion, they can use many items which are more competitive than competitors.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.1-19
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• 2018

Large amount of data is now available for research and business sectors to extract knowledge from it. This data can be in the form of unstructured data such as audio, text, and image data and can be analyzed by deep learning methodology. Deep learning is now widely used for various estimation, classification, and prediction problems. Especially, fashion business adopts deep learning techniques for apparel recognition, apparel search and retrieval engine, and automatic product recommendation. The core model of these applications is the image classification using Convolutional Neural Networks (CNN). CNN is made up of neurons which learn parameters such as weights while inputs come through and reach outputs. CNN has layer structure which is best suited for image classification as it is comprised of convolutional layer for generating feature maps, pooling layer for reducing the dimensionality of feature maps, and fully-connected layer for classifying the extracted features. However, most of the classification models have been trained using online product image, which is taken under controlled situation such as apparel image itself or professional model wearing apparel. This image may not be an effective way to train the classification model considering the situation when one might want to classify street fashion image or walking image, which is taken in uncontrolled situation and involves people's movement and unexpected pose. Therefore, we propose to train the model with runway apparel image dataset which captures mobility. This will allow the classification model to be trained with far more variable data and enhance the adaptation with diverse query image. To achieve both convergence and generalization of the model, we apply Transfer Learning on our training network. As Transfer Learning in CNN is composed of pre-training and fine-tuning stages, we divide the training step into two. First, we pre-train our architecture with large-scale dataset, ImageNet dataset, which consists of 1.2 million images with 1000 categories including animals, plants, activities, materials, instrumentations, scenes, and foods. We use GoogLeNet for our main architecture as it has achieved great accuracy with efficiency in ImageNet Large Scale Visual Recognition Challenge (ILSVRC). Second, we fine-tune the network with our own runway image dataset. For the runway image dataset, we could not find any previously and publicly made dataset, so we collect the dataset from Google Image Search attaining 2426 images of 32 major fashion brands including Anna Molinari, Balenciaga, Balmain, Brioni, Burberry, Celine, Chanel, Chloe, Christian Dior, Cividini, Dolce and Gabbana, Emilio Pucci, Ermenegildo, Fendi, Giuliana Teso, Gucci, Issey Miyake, Kenzo, Leonard, Louis Vuitton, Marc Jacobs, Marni, Max Mara, Missoni, Moschino, Ralph Lauren, Roberto Cavalli, Sonia Rykiel, Stella McCartney, Valentino, Versace, and Yve Saint Laurent. We perform 10-folded experiments to consider the random generation of training data, and our proposed model has achieved accuracy of 67.2% on final test. Our research suggests several advantages over previous related studies as to our best knowledge, there haven't been any previous studies which trained the network for apparel image classification based on runway image dataset. We suggest the idea of training model with image capturing all the possible postures, which is denoted as mobility, by using our own runway apparel image dataset. Moreover, by applying Transfer Learning and using checkpoint and parameters provided by Tensorflow Slim, we could save time spent on training the classification model as taking 6 minutes per experiment to train the classifier. This model can be used in many business applications where the query image can be runway image, product image, or street fashion image. To be specific, runway query image can be used for mobile application service during fashion week to facilitate brand search, street style query image can be classified during fashion editorial task to classify and label the brand or style, and website query image can be processed by e-commerce multi-complex service providing item information or recommending similar item.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.85-107
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• 2019

Online consumers browse products belonging to a particular product line or brand for purchase, or simply leave a wide range of navigation without making purchase. The research on the behavior and purchase of online consumers has been steadily progressed, and related services and applications based on behavior data of consumers have been developed in practice. In recent years, customization strategies and recommendation systems of consumers have been utilized due to the development of big data technology, and attempts are being made to optimize users' shopping experience. However, even in such an attempt, it is very unlikely that online consumers will actually be able to visit the website and switch to the purchase stage. This is because online consumers do not just visit the website to purchase products but use and browse the websites differently according to their shopping motives and purposes. Therefore, it is important to analyze various types of visits as well as visits to purchase, which is important for understanding the behaviors of online consumers. In this study, we explored the clustering analysis of session based on click stream data of e-commerce company in order to explain diversity and complexity of search behavior of online consumers and typified search behavior. For the analysis, we converted data points of more than 8 million pages units into visit units' sessions, resulting in a total of over 500,000 website visit sessions. For each visit session, 12 characteristics such as page view, duration, search diversity, and page type concentration were extracted for clustering analysis. Considering the size of the data set, we performed the analysis using the Mini-Batch K-means algorithm, which has advantages in terms of learning speed and efficiency while maintaining the clustering performance similar to that of the clustering algorithm K-means. The most optimized number of clusters was derived from four, and the differences in session unit characteristics and purchasing rates were identified for each cluster. The online consumer visits the website several times and learns about the product and decides the purchase. In order to analyze the purchasing process over several visits of the online consumer, we constructed the visiting sequence data of the consumer based on the navigation patterns in the web site derived clustering analysis. The visit sequence data includes a series of visiting sequences until one purchase is made, and the items constituting one sequence become cluster labels derived from the foregoing. We have separately established a sequence data for consumers who have made purchases and data on visits for consumers who have only explored products without making purchases during the same period of time. And then sequential pattern mining was applied to extract frequent patterns from each sequence data. The minimum support is set to 10%, and frequent patterns consist of a sequence of cluster labels. While there are common derived patterns in both sequence data, there are also frequent patterns derived only from one side of sequence data. We found that the consumers who made purchases through the comparative analysis of the extracted frequent patterns showed the visiting pattern to decide to purchase the product repeatedly while searching for the specific product. The implication of this study is that we analyze the search type of online consumers by using large - scale click stream data and analyze the patterns of them to explain the behavior of purchasing process with data-driven point. Most studies that typology of online consumers have focused on the characteristics of the type and what factors are key in distinguishing that type. In this study, we carried out an analysis to type the behavior of online consumers, and further analyzed what order the types could be organized into one another and become a series of search patterns. In addition, online retailers will be able to try to improve their purchasing conversion through marketing strategies and recommendations for various types of visit and will be able to evaluate the effect of the strategy through changes in consumers' visit patterns.

• Asia Marketing Journal
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• v.12 no.4
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• pp.137-164
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• 2011

In the past, retailers secured customer loyalty by offering convenient locations, unique assortments of goods, better services than competitors, and good credit policy. All this has changed. Goods assortments among stores have become more alike as national-brand manufacturers place their goods in more and more retail stores. Service differentiation also has eroded. Many department stores have trimmed services, and many discount stores have increased theirs. Customers have become smarter shoppers. They don't pay more for identical brands, especially when service differences have diminished. In the face of increased competition from discount storess and specialty stores, department stores are waging a comeback war. Growth of intertype competition, competition between store-based and non-store-based retailing and growing investment in technology are changing the way consumers shop and retailers sell. Different types of stores-discount stores, catalog showrooms, department stores-all compete for the same consumers by carrying the same type of merchandise. The biggest winners are retailers that have helped shoppers to be economically cautious, simplified their increasingly busy and complicated lives, and provided an emotional connection. The growth of e-retailers has forced traditional brick-and-mortar retailers to respond. Basically brick-and-mortar retailers utilize their natural advantages, such as products that shoppers can actually see, touch, and test, real-life customer service, and no delivery lag time for small-sized purchases. They also provide a shopping experience as a strong differentiator. They are adopting practices as calling each shopper a "guest". The store atmosphere should match the basic motivations of the shopper. If target consumers are more likely to be in a task-oriented and functional mindset, then a simpler, more restrained in-store environment may be better. Consistent with this reasoning, some retailers of experiential products are creating in-store entertainment to attract customers who want fun and excitement. The retail experience must deliver value to turn a one-time visitor into a loyal customer. Retailers need a tool that measures the full range of components that define experience-based value. This study uses an experiential value scale(EVS) developed by Mathwick, Malhotra and Rigdon(2001) which reflects the benefits derived from perceptions of playfulness, aesthetics, customer "return on investment" and service excellence. EVS is useful to predict differences in shopping preferences and patronage behavior of customers. EVS consists of items measuring efficiency, economic value, visual appeal, entertainment value, service excellence, escapism, and intrinsic enjoyment, which are subscales of experiencial value. Efficiency, economic value, service excellence are linked to the utilitarian shopping value. And visual appeal, entertainment value, escapism and intrinsic enjoyment are linked to hedonic shopping value. It has been found that consumers value hedonic experiences activated from escapism and attractiveness of shopping environment as much as the product quality, price, and the convenient location. As a result, many department stores, discount stores, and other retailers are introducing differential marketing strategy based on emotional/hedonic values. Many researches suggest that consumers go shopping not only for buying products but also for various shopping experiences. In other words, they seek the practical, rational value as well as social, recreational values in the shopping process(Babin et al, 1994; Bloch et al, 1994). Retailers may enhance buyer's loyalty to store by providing excellent emotional/hedonic value such as the excitement from shopping, not just the practical value of buying good products efficiently. We investigate the effect of perceived shopping values on the emotional experience and store loyalty based on the EVS(Experiential Value Scales) developed by Holbrook(1994), Mathwick, Malhotra and Rigdon(2001). This study assumes that the relative effect of shopping value dimensions on the responses of shoppers will differ according to types of stores and analyzes the moderating effect of store type(department store VS. discount store) on the causal relationship between shopping value dimensions and store loyalty. Emprical results show that utilitarian values of shopping experience and hedonic value of shipping experience give the positive effect on the emotional response of consumers and store loyalty. We also found the moderating effect of store types. The effect of utilitarian shopping values on the attitude toward discount store is higher than the effect of utilitarian shopping values on the attitude toword department store. And the effect of hedonic shopping value on the emotional response to discount store is higher than on the emotional response to department store. The empirical results reflect on the recent trend that discount stores try to fulfill the hedonic needs of consumers as well as utilitarian needs(i.e, low price) that discount stores traditionally have focused on

• Journal of the Korean Institute of Landscape Architecture
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• v.38 no.2
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• pp.109-118
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• 2010

This study aims to propose practical strategies for the new urban ideal of regeneration. A book review highlights the emergence of new trends of urbanization in knowledge-information industrial society beyond the new town Ideal of the industrial society. The meaning of ‘landscape’ in landscape urbanism represents not the visual and decorative pictures, but the dynamic process in the context of changes and evolutions. Also, knowledge-information industrial society and landscape have a meaning in the same context of flow and process with changes of velocity. Finally, these key words convey a meaning with the new urban trends of urbanization in knowledge-information industrial society in the context of value-oriented characteristics of dynamics and process. Urban regeneration is emerging as the new urban ideal in the knowledge-information industrial society, beyond the new town ideal of industrial society. It is in the same context as landscape urbanism with respect to green infrastructure buildings and designs for the transformation of urban surfaces covered with concrete and asphalt into the ecological surface, and of the ecological surfaces into the cultural surface that could be communicated with human beings. This research revealed the six strategies for urban regeneration as follows. The First, the strategies for the transformation of urban surfaces into ecological surfaces, the second, the strategies for the transformation of ecological surfaces into cultural surfaces, the third, the introduction of mixed and convergence land use, the forth, the transformation of former sites(e.g. military and factory) into urban parks, the fifth, the introduction of waterfront park zones that have the function of ecological and park-oriented mixed land use and, the sixth, the building and design of green infrastructure in the residential and commercial complex in CBD. These strategies call for the reforms of development laws and regulations to restrict building coverage ratio, building heights, and the introduction of park-oriented mixed zoning regulations. Another method for implementating the above listed strategies was the introduction of a strategic planning system instead of the traditional master plan system. This system uses a value planning approach and brand making by imagery. It is able to construct the meaning of an image and its creativeness directly.