• Knowledge Management Research
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• v.25 no.1
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• pp.43-66
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• 2024

In an era where digital technology reshapes brand-consumer interactions, this study examines the influence of Nike's Run Club and Adidas' Runtastic apps on loyalty and advocacy. Analyzing 3,715 English reviews from January 2020 to October 2023 through text mining, and conducting a focused sentiment analysis on 155 'recommend' mentions, we explore the nuances of 'hot loyalty'. The findings reveal Nike as a 'companion' with an emphasis on emotional engagement, versus Runtastic's 'tool' focus on reliability. This underscores the varied consumer perceptions across similar platforms, highlighting the necessity for brands to integrate user preferences and address technical flaws to foster loyalty. Demonstrating how customized technology adaptations impact loyalty, this research offers crucial insights for digital brand strategy, suggesting a proactive approach in app development and management for brand loyalty enhancement

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.2
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• pp.61-73
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• 2021

This study aimed to identify the landscape perception and landscape characteristics of users by utilizing SNS data generated by their experiences. Therefore, how to recognize the main places and scenery appearing on the island, and what are the characteristics of the main scenery were analyzed using online text data and photo data. Text data are text mining and network structural analysis, while photographic data are landscape identification models and color analysis. As a result of the study, First, as a result of frequency analysis of Bakji·Banwol-do topics, we were able to derive keywords for local landscapes such as 'Purple Bridge', 'Doori Village', and location, behavior, and landscape images by analyzing them simultaneously. Second, the network structure analysis showed that the connection between key and undrawn keywords could be more specifically analyzed, indicating that creating landscapes using colors is affecting regional activation. Third, after analyzing the landscape identification model, it was found that artificial elements would be excluded to create preferred landscapes using the main targets of "Purple Bridge" and "Doori Village", and that it would be effective to set a view point of the sea and sky. Fourth, Bakji·Banwol-do were the first islands to be created under the theme of color, and the colors used in artificial facilities were similar to the surrounding environment, and were harmonized with contrasting lighting and saturation values. This study used online data uploaded directly by visitors in the landscape field to identify users' perceptions and objects of the landscape. Furthermore, the use of both text and photographic data to identify landscape recognition and characteristics is significant in that they can specifically identify which landscape and resources they prefer and perceive. In addition, the use of quantitative big data analysis and qualitative landscape identification models in identifying visitors' perceptions of local landscapes will help them understand the landscape more specifically through discussions based on results.

• Journal of the HCI Society of Korea
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• v.12 no.2
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• pp.21-29
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• 2017

While the second and the third industrial revolutions made it possible a few standardized designs to be extracted and produced in large quantities, the recent development of the 3D printing technology allowed many individuals to reflect their unique personal characteristics on their creative works and produce them in large quantities-i.e., personally customized designs and mass production of various designs. However, for the customized designs and the mass production of various designs through the 3D printing technology, the individuals should use a 3D modeling software and the supporting features of the software can significantly affect the type and shape of a creative work. In this study, we surveyed the individuals who design the creative works using 3D printers about the type of software that they use and the type of creative works that they design using the software, to propose a possible direction of new software that supports their activities. To do this, we first surveyed sixty members of the OpenCreators, which is the largest 3D printing creator community in South Korea, about the 3D modelling Software that they use for their 3D printing creations, the best 3D modelling software for the 3D printing, and the type of frequently printing creation using the best 3D modelling software. We then analysed the response results. As a result, we found that most of 3D printing creators in South Korea use Rhino and 123D Design. More specifically, the Rhino was being widely used by the people in the 3D printing industry to print prototypes, samples, and mock-ups, while the 123D Design was being mainly used for general purposes such as educational tools, accessories, and home interior accessories. Therefore, we believe it is necessary to develop the software in two separated categories, i.e. for the business, like the Rhino, and for the beginners, and educational and personal purposes, like the 123D Design. Finally, we stressed and proposed the necessity to support individual creators by developing an industry-specific 3D modeling software.

• Journal of Korean Home Economics Education Association
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• v.32 no.3
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• pp.97-110
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• 2020

The purpose of this study is to develop milk education materials for adults based on the scientific basis of right milk consumption in the format of card news that can be easily accessed on a mobile phone or the internet and has high impact. The topics to be included in the card news were selected based on the findings from literature analysis and focus group interviews with 10 adults(32.0±6.4 years). For the eight selected topics, effective communication was made by suggesting some information that users want to know while reflecting adult eating habits, lifestyle habits, and nutrition and health interests. The card news draft was reviewed by researcher and consulting experts, and then questionnaire survey was conducted using Likert 5-point scales by 50 adults(42.7±10.2 years). Based on the results of the review, consultation and questionnaire survey, a final draft of the card news consisting of 11 cuts was completed. Card news proposal is expected to produce educational effects, since the respondents showed high satisfaction with the card news (higher than 4 on the 5-point scales) according to the questionnaire survey. Adults can easily access and use the card news developed in this study, and thus this card news is expected to increase milk consumption in adulthood and improve nutrition and health through friendly and systematic milk education.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.57-78
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• 2020

With the development of the Internet, consumers have had an opportunity to check product information easily through E-Commerce. Product reviews used in the process of purchasing goods are based on user experience, allowing consumers to engage as producers of information as well as refer to information. This can be a way to increase the efficiency of purchasing decisions from the perspective of consumers, and from the seller's point of view, it can help develop products and strengthen their competitiveness. However, it takes a lot of time and effort to understand the overall assessment and assessment dimensions of the products that I think are important in reading the vast amount of product reviews offered by E-Commerce for the products consumers want to compare. This is because product reviews are unstructured information and it is difficult to read sentiment of reviews and assessment dimension immediately. For example, consumers who want to purchase a laptop would like to check the assessment of comparative products at each dimension, such as performance, weight, delivery, speed, and design. Therefore, in this paper, we would like to propose a method to automatically generate multi-dimensional product assessment scores in product reviews that we would like to compare. The methods presented in this study consist largely of two phases. One is the pre-preparation phase and the second is the individual product scoring phase. In the pre-preparation phase, a dimensioned classification model and a sentiment analysis model are created based on a review of the large category product group review. By combining word embedding and association analysis, the dimensioned classification model complements the limitation that word embedding methods for finding relevance between dimensions and words in existing studies see only the distance of words in sentences. Sentiment analysis models generate CNN models by organizing learning data tagged with positives and negatives on a phrase unit for accurate polarity detection. Through this, the individual product scoring phase applies the models pre-prepared for the phrase unit review. Multi-dimensional assessment scores can be obtained by aggregating them by assessment dimension according to the proportion of reviews organized like this, which are grouped among those that are judged to describe a specific dimension for each phrase. In the experiment of this paper, approximately 260,000 reviews of the large category product group are collected to form a dimensioned classification model and a sentiment analysis model. In addition, reviews of the laptops of S and L companies selling at E-Commerce are collected and used as experimental data, respectively. The dimensioned classification model classified individual product reviews broken down into phrases into six assessment dimensions and combined the existing word embedding method with an association analysis indicating frequency between words and dimensions. As a result of combining word embedding and association analysis, the accuracy of the model increased by 13.7%. The sentiment analysis models could be seen to closely analyze the assessment when they were taught in a phrase unit rather than in sentences. As a result, it was confirmed that the accuracy was 29.4% higher than the sentence-based model. Through this study, both sellers and consumers can expect efficient decision making in purchasing and product development, given that they can make multi-dimensional comparisons of products. In addition, text reviews, which are unstructured data, were transformed into objective values such as frequency and morpheme, and they were analysed together using word embedding and association analysis to improve the objectivity aspects of more precise multi-dimensional analysis and research. This will be an attractive analysis model in terms of not only enabling more effective service deployment during the evolving E-Commerce market and fierce competition, but also satisfying both customers.