• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.397-404
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• 2021

The web-based crowdfunding platform provides small-cap companies the opportunity to reduce financial risks and to reliably produce new products through pre-orders. Meanwhile, crowdfunding projects are also helping companies as a channel to test new products before mass production. Despite these advantages, from the point of view of businesses and consumers, it is true that web-based crowdfunding platforms have limitations in the retail environment. For example, the limited social elements of a web-based platform are somewhat in conflict with the basic characteristics of crowdfunding projects - which inevitably demand high social influences for the success. As such, understanding the mechanisms of social factors of crowdfunding platforms from the consumers' perspective is important. Therefore, in this study, we empirically tested the effect of social factors of crowdfunding platform on consumer participation and evaluation. Based on the Social Influence Theory and Social Presence Theory, we developed a conceptual framework where the social group size and social presence of other backers were the independent variables and the purchaser's intention to participate as the dependent variable. In the results, the size of the social group size and the perceived social presence have a significant positive effect on purchaser's participation intent. In addition, the social presence had a greater influence on the purchaser's intention to participate than the size of the sponsor's social group. We believe that our findings contribute to the extant literature by empirically demonstrating the valid effect of social factors of crowdfunding platforms on consumer evaluations.

• Journal of the Korean Society of Clothing and Textiles
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• v.45 no.5
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• pp.892-906
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• 2021

This study explores the effects of providing information on the price fairness perception and intention of continuous use in an online fashion platform, given a price difference due to AI algorithm pricing. We investigated the moderating roles of price inequality (loss vs. gain) and technology insecurity. The experiments used four stimuli based on price inequality (loss vs. gain) and information provision (provided or not) on price inequality. We developed a mock website and offered a scenario on the product presentation based on an AI algorithm pricing. Participants in their 20s and 30s were randomly allocated to one of the stimuli. To test the hypotheses, a total of 257 responses were analyzed using Process Macro 3.4. According to the results, price fairness perception mediated between information provision and continuous use intention when consumers saw the price inequality as a gain. When the consumers perceived high technology insecurity, information provision affected the intention of continuous use mediated by price fairness perception.

• Journal of the Korea Society of Computer and Information
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• v.28 no.8
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• pp.39-48
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• 2023

This study was conducted to provide a solution to the problem of sizing errors occurring in online purchases due to discrepancies and non-standardization in clothing sizes. This paper discusses an implementation approach for a machine learning-based recommender system capable of providing personalized sizes to online consumers. We trained multiple validated collaborative filtering algorithms including Non-Negative Matrix Factorization (NMF), Singular Value Decomposition (SVD), k-Nearest Neighbors (KNN), and Co-Clustering using purchasing data derived from online commerce and compared their performance. As a result of the study, we were able to confirm that the NMF algorithm showed superior performance compared to other algorithms. Despite the characteristic of purchase data that includes multiple buyers using the same account, the proposed model demonstrated sufficient accuracy. The findings of this study are expected to contribute to reducing the return rate due to sizing errors and improving the customer experience on e-commerce platforms.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.325-345
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• 2023

In the rapidly evolving domain of e-commerce, our study presents a cohesive approach to enhance customer satisfaction prediction from online reviews, aligning methodological innovation with practical insights. We integrate the RFE-SHAP feature selection with LDA topic modeling to streamline predictive analytics in e-commerce. This integration facilitates the identification of key features-specifically, narrowing down from an initial set of 28 to an optimal subset of 14 features for the Random Forest algorithm. Our approach strategically mitigates the common issue of overfitting in models with an excess of features, leading to an improved accuracy rate of 84% in our Random Forest model. Central to our analysis is the understanding that certain aspects in review content, such as quality, fit, and durability, play a pivotal role in influencing customer satisfaction, especially in the clothing sector. We delve into explaining how each of these selected features impacts customer satisfaction, providing a comprehensive view of the elements most appreciated by customers. Our research makes significant contributions in two key areas. First, it enhances predictive modeling within the realm of e-commerce analytics by introducing a streamlined, feature-centric approach. This refinement in methodology not only bolsters the accuracy of customer satisfaction predictions but also sets a new standard for handling feature selection in predictive models. Second, the study provides actionable insights for e-commerce platforms, especially those in the clothing sector. By highlighting which aspects of customer reviews-like quality, fit, and durability-most influence satisfaction, we offer a strategic direction for businesses to tailor their products and services.

• Journal of the Korea Society of Computer and Information
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• v.25 no.8
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• pp.189-196
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• 2020

In this paper, we propose a study on the purchasing intent of the new e-commerce consumer, the coronavirus may once again drive the structural change of China's economy, and the new online marketing model will be noticed during the epidemic. Through 438 questionnaires collected on the Internet, frequency analysis, element analysis, reliability analysis and structural equation analysis were performed using SPSS V22.0 and AMOS V22.0 methods. Study the validation of hypotheses in the model to reveal the reasons why consumers in the new e-business are exposed. The results show that e-commerce features of Internet celebrities and individual characteristics of Internet celebrities can only enhance consumers' satisfaction. Quasi social relationships only increase consumer satisfaction without generating the will to purchase directly. Consumer satisfaction is the core foundation that dominates long-term consumption. E-commerce should focus on the ability of online celebrities to sell their expertise and the adaptability of value and product characteristics when conducting online celebrity marketing.

• Journal of the Korea Convergence Society
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• v.12 no.10
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• pp.19-25
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• 2021

This study contains the results obtained after two and a half years of developing a knitting customization website using a knitting machine. Recently in the fashion world, various services using customization are being provided, and devices that users can design directly using knitting machines are being developed. However the existing website for knitting machine does not provide a certain usability or layout, so it is difficult for users to use open source and custom design. Therefore, this study was conducted for the purpose of developing a website that provides ease of use to users who will use the knitting customizing service using a knitting machine. As a research method, the first usability evaluation was conducted by synthesizing the studies conducted for the knit customization website development work. As a result of the study, found the problems of the initial custom screen and the initial output screen were found, and convenience, intuition, and readability were improved. Secondary usability evaluation was conducted on the modified website and it was confirmed that the problem was corrected. Through the website finally derived from this study, it is expected that the new platform in the domestic knit market will be popularized and the usability of the custom website will be improved.