• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.311-328
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• 2022

Because of the spread of smartphones due to the development of information and communication technology, online shopping mall services can be used on computers and mobile devices. As a result, the number of users using the online shopping mall service increases rapidly, and the types of products traded are also growing. Therefore, to maximize profits, companies need to provide information that may interest users. To this end, the recommendation system presents necessary information or products to the user based on the user's past behavioral data or behavioral purchase records. Representative overseas companies that currently provide recommendation services include Netflix, Amazon, and YouTube. These companies support users' purchase decisions by recommending products to users using ratings, purchase records, and clickstream data that users give to the items. In addition, users refer to the ratings left by other users about the product before buying a product. Most users tend to provide ratings only to products they are satisfied with, and the higher the rating, the higher the purchase intention. And recently, e-commerce sites have provided users with the ability to vote on whether product reviews are helpful. Through this, the user makes a purchase decision by referring to reviews and ratings of products judged to be beneficial. Therefore, in this study, the correlation between the product rating and the helpful information of the review is identified. The valuable data of the evaluation is reflected in the recommendation system to check the recommendation performance. In addition, we want to compare the results of skipping all the ratings in the traditional collaborative filtering technique with the recommended performance results that reflect only the 4 and 5 ratings. For this purpose, electronic product data collected from Amazon was used in this study, and the experimental results confirmed a correlation between ratings and review usefulness information. In addition, as a result of comparing the recommendation performance by reflecting all the ratings and only the 4 and 5 points in the recommendation system, the recommendation performance of remembering only the 4 and 5 points in the recommendation system was higher. In addition, as a result of reflecting review usefulness information in the recommendation system, it was confirmed that the more valuable the review, the higher the recommendation performance. Therefore, these experimental results are expected to improve the performance of personalized recommendation services in the future and provide implications for e-commerce sites.

• Journal of Global Scholars of Marketing Science
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• v.18 no.4
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• pp.157-194
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• 2008

The popularity of communities on the internet has captured the attention of marketing scholars and practitioners. By adapting to the culture of the internet, however, and providing consumer with the ability to interact with one another in addition to the company, businesses can build new and deeper relationships with customers. The economic potential of online communities has been discussed with much hope in the many popular papers. In contrast to this enthusiastic prognostications, empirical and practical evidence regarding the economic potential of the online community has shown a little different conclusion. To date, even communities with high levels of membership and vibrant social arenas have failed to build financial viability. In this perspective, this study investigates the role of various kinds of influencing factors to online community loyalty and basically suggests the framework that explains the process of building purchase loyalty. Even though the importance of building loyalty in an online environment has been emphasized from the marketing theorists and practitioners, there is no sufficient research conclusion about what is the process of building purchase loyalty and the most powerful factors that influence to it. In this study, the process of building purchase loyalty is divided into three levels; characteristics of community site such as content superiority, site vividness, navigation easiness, and customerization, the mediating variables such as self congruency, consumer experience, and consumer to consumer interactivity, and finally various factors about online community loyalty such as visit loyalty, affect, trust, and purchase loyalty are those things. And the findings of this research are as follows. First, consumer-to-consumer interactivity is an important factor to online community purchase loyalty and other loyalty factors. This means, in order to interact with other people more actively, many participants in online community have the willingness to buy some kinds of products such as music, content, avatar, and etc. From this perspective, marketers of online community have to create some online environments in order that consumers can easily interact with other consumers and make some site environments in order that consumer can feel experience in this site is interesting and self congruency is higher than at other community sites. It has been argued that giving consumers a good experience is vital in cyber space, and websites create an active (rather than passive) customer by their nature. Some researchers have tried to pin down the positive experience, with limited success and less empirical support. Web sites can provide a cognitively stimulating experience for the user. We define the online community experience as playfulness based on the past studies. Playfulness is created by the excitement generated through a website's content and measured using three descriptors Marketers can promote using and visiting online communities, which deliver a superior web experience, to influence their customers' attitudes and actions, encouraging high involvement with those communities. Specially, we suggest that transcendent customer experiences(TCEs) which have aspects of flow and/or peak experience, can generate lasting shifts in beliefs and attitudes including subjective self-transformation and facilitate strong consumer's ties to a online community. And we find that website success is closely related to positive website experiences: consumers will spend more time on the site, interacting with other users. As we can see figure 2, visit loyalty and consumer affect toward the online community site didn't directly influence to purchase loyalty. This implies that there may be a little different situations here in online community site compared to online shopping mall studies that shows close relations between revisit intention and purchase intention. There are so many alternative sites on web, consumers do not want to spend money to buy content and etc. In this sense, marketers of community websites must know consumers' affect toward online community site is not a last goal and important factor to influnece consumers' purchase. Third, building good content environment can be a really important marketing tool to create a competitive advantage in cyberspace. For example, Cyworld, Korea's number one community site shows distinctive superiority in the consumer evaluations of content characteristics such as content superiority, site vividness, and customerization. Particularly, comsumer evaluation about customerization was remarkably higher than the other sites. In this point, we can conclude that providing comsumers with good, unique and highly customized content will be urgent and important task directly and indirectly impacting to self congruency, consumer experience, c-to-c interactivity, and various loyalty factors of online community. By creating enjoyable, useful, and unique online community environments, online community portals such as Daum, Naver, and Cyworld are able to build customer loyalty to a degree that many of today's online marketer can only dream of these loyalty, in turn, generates strong economic returns. Another way to build good online community site is to provide consumers with an interactive, fun, experience-oriented or experiential Web site. Elements that can make a dot.com's Web site experiential include graphics, 3-D images, animation, video and audio capabilities. In addition, chat rooms and real-time customer service applications (which link site visitors directly to other visitors, or with company support personnel, respectively) are also being used to make web sites more interactive. Researchers note that online communities are increasingly incorporating such applications in their Web sites, in order to make consumers' online shopping experience more similar to that of an offline store. That is, if consumers are able to experience sensory stimulation (e.g. via 3-D images and audio sound), interact with other consumers (e.g., via chat rooms), and interact with sales or support people (e.g. via a real-time chat interface or e-mail), then they are likely to have a more positive dot.com experience, and develop a more positive image toward the online company itself). Analysts caution, however, that, while high quality graphics, animation and the like may create a fun experience for consumers, when heavily used, they can slow site navigation, resulting in frustrated consumers, who may never return to a site. Consequently, some analysts suggest that, at least with current technology, the rule-of-thumb is that less is more. That is, while graphics etc. can draw consumers to a site, they should be kept to a minimum, so as not to impact negatively on consumers' overall site experience.

• Journal of Distribution Science
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• v.9 no.3
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• pp.47-54
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• 2011

This paper presents exploratory research on consumer awareness and attitudesabout organic food, for which consumer demand continues to increase the paper also assesses consumers' organic food distribution channel preferences. By conducting a literature review, a case study has been carried out in order to glean customer behavior, market condition and typesof distribution channels, and development of specialty stores for organic foods. The early research indicates that consumer awareness and customer attitudes toward organic food are mostly positive however, organic food's high price, as well as a lack of organic food stores, cause a negative effect on consumers' purchase intention. Secondly, the U.S. organic food retail channel consists of such mainstream supermarket/grocery stores and leading natural and organic food supermarket chains as Whole Foods, Trader Joe's, and Sunflower Farmers Market. For the current retail distribution of organic food in Korea, off-line stores are composed of direct management stores and franchise chains. Most of the organic food retail distribution operates through the Internet shopping mall, and are commonly located at retail distribution centers as multi-channel, shop-in-shop stores. Moreover, unlike in the U.S., association and consumers' cooperatives (Co-Ops), and such other member-direct retail stores as Hansallim, iCOOP, Nature Dream,and online shopping malls, are all active in Korea. Thirdly, as a result of an analysis of the present state of the organic food retail channel, as well as building a case for organic food specialty stores, the distinctive featuresand rapid growth of such unique organic food stores as Whole Foods Market, or Trader Joe's successful downsizing strategies, as well as Sunflower Farmers Market low-price approach, show steady industry growth. Moreover, as a result of a case studyof such domestic representative organic food specialty stores as "Olga" and "Chorokmaeul," a similar management style to the United States' "Whole Foods Market" and "Trader Joe's," respectively, can be seen. Similar to the U.S. market, Korean organic food markets should also implement active retail distribution opportunities, allowing consumers to select from various diverse and differentiated choices. In order to accomplish this goal, it is necessary to prepare such measures as sustaining reasonable prices, securing various suppliers for unique products,and improving consumer trust through advertisement strategies that are suitable for each company's branding processes.

• Journal of Food Hygiene and Safety
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• v.37 no.1
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• pp.1-8
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• 2022

In this study, the pesticide residues in 106 commercial cereal grains were monitored from February to July 2021. For the investigation, 40 domestic and 66 imported products from large, small-to-medium sized offline and online distribution channels, were collected and analyzed by using the multiresidue method for 341 pesticides on GC/ECD, GC/NPD, GC/MSMS, UPLC/PDA, HPLC/FLD, LC/MSMS. Pesticides were detected in total of 8 samples (7.5%), of which one was from big box retailers, two from small and medium-sized distribution stores, and five from online shopping mall. Five (4.7%) samples were found to have pesticide residues greater than the maximum residue limits (MRLs). The detected pesticides in kidney beans (1 case), mung beans (6 cases), and sorghum (1 case), were MGK-264, chlorpyrifos, thiamethoxam, malathion, piperonyl butoxide, and pirimiphos-methyl. Specifically, an excessive amount of thiamethoxam was found from the imported mung bean (5 cases).

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.27-42
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• 2020

Traditional companies with offline stores were unable to secure large display space due to the problems of cost. This limitation inevitably allowed limited kinds of products to be displayed on the shelves, which resulted in consumers being deprived of the opportunity to experience various items. Taking advantage of the virtual space called the Internet, online shopping goes beyond the limits of limitations in physical space of offline shopping and is now able to display numerous products on web pages that can satisfy consumers with a variety of needs. Paradoxically, however, this can also cause consumers to experience the difficulty of comparing and evaluating too many alternatives in their purchase decision-making process. As an effort to address this side effect, various kinds of consumer's purchase decision support systems have been studied, such as keyword-based item search service and recommender systems. These systems can reduce search time for items, prevent consumer from leaving while browsing, and contribute to the seller's increased sales. Among those systems, recommender systems based on association rule mining techniques can effectively detect interrelated products from transaction data such as orders. The association between products obtained by statistical analysis provides clues to predicting how interested consumers will be in another product. However, since its algorithm is based on the number of transactions, products not sold enough so far in the early days of launch may not be included in the list of recommendations even though they are highly likely to be sold. Such missing items may not have sufficient opportunities to be exposed to consumers to record sufficient sales, and then fall into a vicious cycle of a vicious cycle of declining sales and omission in the recommendation list. This situation is an inevitable outcome in situations in which recommendations are made based on past transaction histories, rather than on determining potential future sales possibilities. This study started with the idea that reflecting the means by which this potential possibility can be identified indirectly would help to select highly recommended products. In the light of the fact that the attributes of a product affect the consumer's purchasing decisions, this study was conducted to reflect them in the recommender systems. In other words, consumers who visit a product page have shown interest in the attributes of the product and would be also interested in other products with the same attributes. On such assumption, based on these attributes, the recommender system can select recommended products that can show a higher acceptance rate. Given that a category is one of the main attributes of a product, it can be a good indicator of not only direct associations between two items but also potential associations that have yet to be revealed. Based on this idea, the study devised a recommender system that reflects not only associations between products but also categories. Through regression analysis, two kinds of associations were combined to form a model that could predict the hit rate of recommendation. To evaluate the performance of the proposed model, another regression model was also developed based only on associations between products. Comparative experiments were designed to be similar to the environment in which products are actually recommended in online shopping malls. First, the association rules for all possible combinations of antecedent and consequent items were generated from the order data. Then, hit rates for each of the associated rules were predicted from the support and confidence that are calculated by each of the models. The comparative experiments using order data collected from an online shopping mall show that the recommendation accuracy can be improved by further reflecting not only the association between products but also categories in the recommendation of related products. The proposed model showed a 2 to 3 percent improvement in hit rates compared to the existing model. From a practical point of view, it is expected to have a positive effect on improving consumers' purchasing satisfaction and increasing sellers' sales.

• Archives of design research
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• v.19 no.2 s.64
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• pp.53-62
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• 2006

E-mail has indeed developed from 'a means of instant communication' to an indispensable part of online marketing. Therefore, companies need to implement consistent customer management. Communication with customers and marketing through e-mail is a powerful way of communication and adapting one-to-one marketing strategies to customer trends, habits and taste preferences. Since setting accurate targets is especially important in the fashion industry, e-mail marketing is the most effective way to communicate with customers and one-to-one marketing constitutes a very important strategy. In this study, I will analyze this powerful one-on-one marketing tool, particularly actual e-mail messages sent by an Internet Shopping Mall from June 12 to July 30, 2005, examine the effect of these messages on sales growth and analyze actual feedback received. Regarding e-mail read rates broken down by age and gender, 1 found that females in their late twenties recorded the highest rate at 21.66% and their contribution to sales growth was recorded at 3.5% From actual sales records, found that 28.10% of total sales were attributable to people in their late twenties, showing that the age group that reads e-mails the most also buys the most. Regarding feedback by e-mail title, e-mails from the 'Casual' category seemed to be the most effective, in that most of these e-mails were read. Also, messages sent on Tuesdays were read the most, according to the feedback analysis by weekday. Section e-mails were read more often than regular e-mails. Regarding the view rate according to the time e-mails were sent, messages sent to females in their late twenties at two o'clock in the afternoon were read by 20.93% of recipients, recording the highest read rate. By offering informative content and practical tips, visitors will be attracted to the site and generate site traffic. Therefore, we can conclude that sending e-mail messages can greatly contribute to sales growth and e-mail marketing is very effective. Also, in order to make e-mail campaigns more effective and improve marketing results, we need to analyze actual results and apply our findings in future e-mail campaigns. With this, we get successful marketing results.

• The Journal of the Korea Contents Association
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• v.20 no.4
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• pp.124-137
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• 2020

The need for customized products has also been increasing as more active consumers consume according to their values in recent years. Accordingly, fashion customizing web is becoming popular, but because custom freedom is low, we want to increase custom freedom by applying knitwear. To this end, a theoretical review was conducted through prior research and literature research on customization, knit design, and GUI, and based on this, a case analysis was conducted focusing on knit-making programs and fashion customizing web. Knit designs have more considerations than other fashion design process, resulting in more UIs, so users should use visual elements that are easily recognizable. Therefore, a draft assessment item was derived based on the preceding survey and three Delphi surveys were conducted on experts based on the draft. Each item was modified and deleted during the Delphi research process to produce the Custom Knitware Web GUI Design Guide. Through this study, we were able to identify the need for intuitive understanding and application of knit custom functions in GUI design of custom knitwear web. Through this research, it is expected that this data will be used to improve the usability of custom knitwear websites and to refer to knit design fields that utilize knit machines.

• Journal of Korean society of Dental Hygiene
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• v.10 no.2
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• pp.311-322
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• 2010

Objectives : Since the program about sodium lauryl sulfate that might cause oral dryness and taste change including oral tissue allergy was on the air, the ingredients of D.I.Y dentifrices without sodium lauryl sulfate have been sold in online shopping mall and ordinary people can make the dentifrices easily. But there have not been any reports about the effect of dental plaque removal and preference about D.I.Y dentifrices. Therefore, this study was designed as a pilot study which aimed to investigate the effect of dental plaque removal and prefernece about D.I.Y dentifrices. Methods : 6 subjects were collected to test the effect of dental plaque removal with D.I.Y dentifrices with written consent. They didn't brushed the teeth during 12 hours until the check-up time on the next day. The O'leary index was calculated in baseline, 1 minute, 2 minute, 3 minute after brusing with D.I.Y dentifrices and market dentifrices. The preference about D.I.Y dentifrices through self-administered questionnaire was surveyed in 51 subjects after using D.I.Y dentifrices. Results : 1. The market dentifrices could remove larger amount of dental plaque than D.I.Y dentifrices, but, it wasn't significant. 2. In feeling refreshment, the market dentifrices had more positive answers significantly. 3. In feeling taste change, the market dentifries had more duration of taste change significantly. 4. In feeling oral dryness, the market dentifrices had more duration of oral dryness after toothbrushing. but, it wasn't significant. 5. As a result about reviewing the dental journals about ingredients of D.I.Y dentirices, green tea, sodium carbonate, bamboo salt, propolis had each evidence. But, We could not find out the evidences of calculus adhesion by corn starch, preservative by napri, disinfectant of peppermint. Conclusions : Although we cannot find the difference of the effect of dental plaque removal between D.I.Y dentifrices and market dentifrices, and D.I.Y dentifrices have the merits of decrease of oral dryness and taste change, it was suggested to have another test about stability and safety of D.I.Y dentifrices for safety of the user of D.I.Y dentifrices.

• The Journal of Society for e-Business Studies
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• v.22 no.1
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• pp.65-87
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• 2017

We propose a method to analyze the user reviews and ratings of the products in the online shopping mall and automatically extracts the features of the products to determine the characteristics of a product. By judging whether a rating is given by a specific feature of a product, our method distributes the score to each feature. Conventional methods force users to wastes time reading overflowing number of reviews and ratings to decide whether to buy the product or not. Moreover, it is difficult to grasp the merits and demerits of the product, because of the way reviews and ratings are provided. It is structured in a way that it is impossible to decide which rating is given to the which characteristics of the product. Therefore, in this paper, to resolve this problem, we propose a method to automatically extract the feature of the product from the user review and distribute the score to appropriate characteristics of the product by calculating the rating of each feature from the overall rating. proposed method collects product reviews and ratings, conducts morphological analysis, and extracts features and emotional words of the products. In addition, a method for determining the polarity of a sentence in which the feature appears is given a weight value for each feature. results of the experiment and the questionnaires comparing the existing methods show the usefulness of the proposed method. We also validates the results by comparing the analysis conducted by the product review experts.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.8
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• pp.535-542
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• 2013

Since case-based reasoning(CBR) has many advantages, it has been used for supporting decision making in various areas including medical checkup, production planning, customer classification, and so on. However, there are several factors to be set by heuristics when designing effective CBR systems. Among these factors, this study addresses the issue of selecting appropriate neighbors in case retrieval step. As the criterion for selecting appropriate neighbors, conventional studies have used the preset number of neighbors to combine(i.e. k of k-nearest neighbor), or the relative portion of the maximum similarity. However, this study proposes to use the absolute similarity threshold varying from 0 to 1, as the criterion for selecting appropriate neighbors to combine. In this case, too small similarity threshold value may make the model rarely produce the solution. To avoid this, we propose to adopt the coverage, which implies the ratio of the cases in which solutions are produced over the total number of the training cases, and to set it as the constraint when optimizing the similarity threshold. To validate the usefulness of the proposed model, we applied it to a real-world target marketing case of an online shopping mall in Korea. As a result, we found that the proposed model might significantly improve the performance of CBR.