• Management Science and Financial Engineering
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• v.11 no.3
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• pp.19-45
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• 2005

Collaborative filtering is one of the most common methods that e-commerce sites and Internet information services use to personalize recommendations. Collaborative filtering has the advantage of being able to use even sparse evaluation data to predict preference scores for new products. To date, however, no in-depth investigation has been conducted on how the data sparsity effect in customers' evaluation data affects collaborative filtering-based recommendation performance. In this study, we analyzed the sparsity effect and used a hybrid method based on customers' evaluations and purchases collected from an online bookstore. Results indicated that recommendation performance decreased monotonically as sparsity increased, and that performance was more sensitive to sparsity in evaluation data rather than in purchase data. Results also indicated that the hybrid use of two different types of data (customers' evaluations and purchases) helped to improve the recommendation performance when evaluation data were highly sparse.

• International journal of advanced smart convergence
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• v.13 no.2
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• pp.44-47
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• 2024

With the advancement of Internet technology, online sales and purchases of products have become active. Along with this, the importance of user reviews is also being highlighted. Although user reviews are actively utilized for product sales and purchases, it is difficult to quickly and easily obtain useful information due to the abundance of user reviews. Therefore, prioritizing user reviews is a necessary service for customers that requires careful consideration. Metadata, which contains important information, can be effectively used to prioritize user reviews. However, it is crucial to select and use metadata appropriately according to the purpose. Lean Startup proposes a strategy of repeatedly correcting the problems of ideas or making early transitions to continue trying different approaches. In this paper, we propose a three-step method applying the Lean Startup process to analyze ways to prioritize user reviews using metadata: Build Priority, Measure Priority, Learn Priority.

• Knowledge Management Research
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• v.17 no.3
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• pp.45-64
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• 2016

As the digital retail environement becomes prevalent, consumers are given greater opportunities to make purchases across physical and digital boundaries. Prior research emphasizes that the attractiveness of the digital or online channel is relatively determined by spatial specifics of physical locations. The overall market trend combined with prior research suggests that understanding spatial specifics becomes a key to managing both offline and online sales performance together. In this study, we focus on geographic variation in sales performance through offline and online channels and aim to investigate the channel-level sales difference between central and subsidiary areas. To this end, we obtain sales data of skincare and makeup products from a leading cosmetic company. Next, we examine spatial autocorrelations in data and then employ the spatial error models to study the effects of spatial specifics. The empirical findings are as follows. First, there are significant differences in category-specific and channel-level sales between central and subsidiary areas. Second, Moran's I statistics demonstrate the spatial autocorrelations of each variable. Third, spatial error models outperform simple regression models with lower AIC values. Finally, spatial specifics play a greater role in understanding online sales in subsidiary areas whereas they exert greater influence on offline sales in central areas. We believe our study advances the related theory and knowledge of multi-channel retailing and also contributes practically to location-dependent multi-channel strategies and sales data analytics.

• Journal of the Korea Society of Computer and Information
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• v.24 no.3
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• pp.191-199
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• 2019

This study is about online purchases of foods that have been reluctant to deal with distribution processes and reliability issues. We find out that attributes of the online food market affects behavior intention and whether it differs according to consumption tendency. A survey was conducted on consumers who had ever purchased food online for hypothesis testing. Reliability and feasibility were reviewed for the collected data and the hypothesis was verified through structural equation model analysis. While product diversity, product information and customer service factors of the online food market significantly affect behavior intention, price is not. We identified differences in the impact of behavior intention on consumption tendencies. For the Gaseongbi group, only the product information factors have significant effect on behavior, and for the Gasimbi group, the price and customer service factors have a significant effect on behavior intention. The findings provide theoretical and practical implications for marketers to study various marketing method based on consumer tendencies.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.2
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• pp.626-642
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• 2018

Recently, a number of studies have drawn attention to purchasing online game items. Most of the studies are based on the assumption that consumers behave rationally. Accordingly, TRA- or value-based approaches have been mainly employed to understand the online purchases of game items. However, the purchasing behavior of consumers involves not only making rational decisions, but also making irrational decisions. Hence, their purchase behavior is affected by propensities for conspicuous consumption, impulsive consumption, and habitual consumption. Playing games can be highly addictive, and players often display such addictive behaviors. Our study explored both the rational and irrational factors in purchase behavior to understand how they are associated with purchasing game items. A total of 366 pieces of data were collected from Korean online game users through a survey. Regression analyses of the collected data showed that the behavior of buying game items was influenced not only by the intention to purchase which is a rational factor in consumption, but also by such irrational factors as habit, impulse, and ostentation which should be further emphasized in future studies.

• The Journal of the Korea Contents Association
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• v.22 no.4
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• pp.172-181
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• 2022

This study aims to find out the design needs of millennials for flower services amid changes in the environment in which flowers are purchased online. To this end, first, the consumption tendency of millennials and online flower purchase trends were examined. In addition, focusing on flower bouquet products, the market status of flower delivery shopping malls, which are online flower product services, and regular flower subscription services, a new trend in the flower market, were investigated. Based on this, a survey was conducted to improve online flower services. As a result of the survey, it was found that millennials trusted branded products, preferred eco-friendly products, and tended to have strong design openness in improving online flower service design. In addition, millennials prefer natural bouquet designs mixed with large and small flowers to large and colorful roses, which are currently mainly sold at flower delivery shopping malls. Therefore, we hope that this study will improve the design of online flower services that meet the needs of millennial consumers, revitalizing flower purchases, and expanding to new online flower service design research.

• Asia pacific journal of information systems
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• v.26 no.1
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• pp.66-79
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• 2016

The availability of detailed data on customers' online behaviors and advances in big data analysis techniques enable us to predict consumer behaviors. In the past, researchers have built purchase prediction models by analyzing clickstream data; however, these clickstream-based prediction models have had several limitations. In this study, we propose a new method for purchase prediction that combines information theory with machine learning techniques. Clickstreams from 5,000 panel members and data on their purchases of electronics, fashion, and cosmetics products were analyzed. Clickstreams were summarized using the 'entropy' concept from information theory, while 'random forests' method was applied to build prediction models. The results show that prediction accuracy of this new method ranges from 0.56 to 0.83, which is a significant improvement over values for clickstream-based prediction models presented in the past. The results indicate further that consumers' information search behaviors differ significantly across product categories.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.209-218
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• 2022

Today, with the development of the Internet and mobile technology, consumers' purchasing patterns have shifted from offline to online. In addition, due to the recent COVID-19, online purchases have significantly increased, and accordingly, the courier industry for logistics delivery has also grown significantly. Various logistics robots are being operated in many industrial and can reduce the labor intensity and physical and mental fatigue of workers. However, if the logistics robot does not properly recognize the people or environment around it, it can lead to a serious accident. We conducted that how logistics robots can perform safe work in a working environment such as a logistics warehouse through the application of ISO/DIS 21448 (SOTIF) to autonomous logistics transport robots. This result is expected to contribute to the operation of unmanned logistics warehouses using AGV.

• Journal of Fashion Business
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• v.27 no.4
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• pp.88-100
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• 2023

This study analyzed the compositional characteristics of fashion videos and the characteristics of fashion design spreading as trends through Subversive Basics. Literature research and case studies were conducted concurrently. Based on the literature review, an analysis method was designed, focusing on the concept of online video content, Subversive Basics, and the video content type. For the case analysis, videos were collected and classified using Subversive Basics as the keyword. The content was observed, and design features were analyzed. Based on the results, the collected videos were classified into tutorial, curation, and creative content types according to their compositional characteristics. Tutorial content emphasizes practical actions that demonstrate how to make or modify clothing, thereby promoting user-generated content for dissemination. Curation contents provide users with style ideas and information about clothing and purchases to encourage clothing purchases and influence purchase decisions that lead to dissemination through clothing consumption and wear. Creative content showcases the process of modifying and creating clothes to enhance understanding and value of creative design. The characteristics of fashion design utilized in these contents include bold designs with high visual effects as the first category, designs that can be easily and quickly modified due to intentional incompleteness as the second category, and prominently featured body-positive, individualistic designs as the third category. The results of this study can be associated with balanced development between basic design elements and personalized unique designs, catering to consumer needs.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.291-298
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• 2015

It is pretty hard to sell the kids' furniture online because of the characteristics of the consumers that they will like to make purchases after looking at the actual objects and then considering purchasing them. In this paper, we made the scheme to boost the on-line malls of the kids' furniture market by collecting the consumers' intention to buy before purchasing with questionnaire survey, comparing it with the real data of purchasing, and analyzing the differences. We analyzed the visit number of shopping mall, the page number of views, page duration time per visit, and customer's shopping path by using log data from the children's furniture online shopping mall server. In addition, we analyzed where the customer's influx route is among online advertising. We found that there are requirements for the designs, prices, brand names, and practicalities by the consumers purchasing the kids' furniture online. To strengthen competitiveness of the online kids' furniture malls, we proposed that reinforcing the on-line experiences of furniture, the differential strategies for the products, ensuring the fixed customers are needed.