• International Journal of Internet, Broadcasting and Communication
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• v.9 no.3
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• pp.44-58
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• 2017

The purpose of this study is to prove the Korean Internet company, Kakao's resilience capacity. For it, this paper reviews the previous literatures regarding Kakao's business models and discusses 'resilience' theory. Then, it organizes the research questions based on the theoretical background and explains the research methodology. It investigates the case of Kakao's business and organization. The case analysis shows that five levers of resilience are a good indicator for a successful platform business evolution. The five levers are composed of coordination, cooperation, clout, capability, and connection: First lever, coordination that makes the company to restructure its silo governance in order to respond to actual business flow starting from the basic asset like game and music content; second lever, cooperation where the firm provides creative people with playground for startups such as KakaoPage; third lever, clout where the company shares its data by opening its API of AI and chatbot to $3^{rd}$ party developers; fourth lever, capability where the firm establishes AI R&D center, KakaoBrain as the function of multi-domain generalist for developing diverse platforms tackling customer needs; and the last fifth lever, connection where the firm continues to expand its platform business to the peripheries, O2O businesses such as KakaoTaxi, KakaoOrder, KakaoPay, and KakaoBank. In conclusion, this study proposes Internet companies to be a resilient platform utilizing those five levers of resilience in order to form successful platform. This study contributes to the agile innovation of Internet platform with ecological sense.

• The Journal of Economics, Marketing and Management
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• v.6 no.1
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• pp.1-8
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• 2018

Purpose - Local social commerce market has grown up remarkably. And, Coupang has shown new delivery strategy of rocket delivery. Making new paradigm at local market, Coupang has expanded market scale. This study investigated state of local social commerce market, weight and promotion strategy of Coupang market to find out competitiveness edge of Coupang. Research design, data, and methodology - The study investigated state and concept of social commerce to find out state, problems and competitiveness of social commerce. New distribution service was short of precedent studies. Statistical analysis and experimental analysis were not used, and interview was done to investigate three of social commerce businesses. Results - CRM construction is insufficient to have poor system, Local delivery system could not be made enough at overnight delivery and customers were dissatisfied with ties with another company. Promotion shall be done by delivery system for increase of profitability, funding for more investment, chatbot to build new customer control system, and new delivery system to produce profit. Conclusions - Coupang and others have grown up rapidly to worsen profit and to jeopardize survival. Excessive initial investment has threatened the businesses, for instance, low sales of Amazon, excessive expenses, bench marking of logistics system, and others.

• The Journal of Information Systems
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• v.31 no.1
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• pp.175-195
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• 2022

Purpose The purpose of this study is to examine news articles and analyze trends and key agendas related to artificial intelligence(AI). In particular, this study tried to compare the reporting behaviors of Korea and the United States, which is considered to be a leader in the field of AI. Design/methodology/approach This study analyzed news articles using a big data method. Specifically, main agendas of the two countries were derived and compared through the keyword frequency analysis, topic modeling, and language network analysis. Findings As a result of the keyword analysis, the introduction of AI and related services were reported importantly in Korea. In the US, the war of hegemony led by giant IT companies were widely covered in the media. The main topics in Korean media were 'Strategy in the 4th Industrial Revolution Era', 'Building a Digital Platform', 'Cultivating Future human resources', 'Building AI applications', 'Introduction of Chatbot Services', 'Launching AI Speaker', and 'Alphago Match'. The main topics of US media coverage were 'The Bright and Dark Sides of Future Technology', 'The War of Technology Hegemony', 'The Future of Mobility', 'AI and Daily Life', 'Social Media and Fake News', and 'The Emergence of Robots and the Future of Jobs'. The keywords with high centrality in Korea were 'release', 'service', 'base', 'robot', 'era', and 'Baduk or Go'. In the US, they were 'Google', 'Amazon', 'Facebook', 'China', 'Car', and 'Robot'.

• Information Systems Review
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• v.25 no.2
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• pp.125-144
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• 2023

Generative Artificial Intelligence (AI) technology is gaining global attention as it can automatically generate sentences, images, and voices that humans previously generated. In particular, ChatGPT, a representative generative AI service, shows proactivity and accuracy differentiated from existing chatbot services, and the number of users is rapidly increasing in a short period of time. Despite this growing interest in generative AI services, most preceding studies are still in their infancy. Therefore, this study utilized LDA topic modeling and keyword network diagrams to derive success factors for generative AI services and to propose successful business strategies based on them. In addition, using ChatGPT, a new research methodology that complements the existing text-mining method, was presented. This study overcomes the limitations of previous research that relied on qualitative methods and makes academic and practical contributions to the future development of generative AI services.

• The Journal of Industrial Distribution & Business
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• v.11 no.2
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• pp.41-48
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• 2020

Purpose: This study is to examine the intention of the elderly who live alone in the customized AI speaker for the elderly living alone to improve the quality of life service for the elderly living alone in the smart city environment. Based on the quality of life model of the elderly, this study is applied to the technology acceptance model to investigate the relationship between perceived usefulness and ease of use on the sustained use intention. Research design, data and methodology: Residents in Suwon, Gyeonggi-do, selected as candidate local governments for the Smart City Challenge Project of the Ministry of Land, Infrastructure and Transport in June 2019 to measure the perceived technology acceptance of potential users for the AI technology for the elderly living alone as part of the smart city technology. In order to evaluate the intention of using AI speaker, which is the target system of this study, a video of a chatbot using experience of elderly people living alone was produced. Results: First of all, in order for the elderly living alone to have an attitude to use AI-based speakers, there should be a perceived usefulness of the quality of life of the elderly. However, ease of use did not show any significant causal relationship to attitude toward use. In addition, the attitude toward use weakly influenced the intention to use. In other words, elderly people living alone were not likely to have a significant effect on their attitude toward use. However, feeling that AI speakers are easy to use will help to improve the quality of life, which in turn led to the attitude toward using AI speakers, which could lead to indirect effects. Finally, the perceived usefulness of quality of life was found to have a weak effect on direct use intentions. Conclusions: This study conducted a study on the technology acceptance of service environment to improve the quality of life for the specific user group who live alone in the smart seat environment. In this study, we examined the effects of AI speaker on the elderly living alone to improve the quality of life for the elderly living alone.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.10
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• pp.455-460
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• 2023

Text augmentation is a methodology that creates new augmented texts by transforming or generating original texts for the purpose of improving the performance of NLP models. However existing text augmentation techniques have limitations such as lack of expressive diversity semantic distortion and limited number of augmented texts. Recently text augmentation using large language models and few-shot learning can overcome these limitations but there is also a risk of noise generation due to incorrect generation. In this paper, we propose a text augmentation method called TAGS that generates multiple candidate texts and selects the appropriate text as the augmented text. TAGS generates various expressions using few-shot learning while effectively selecting suitable data even with a small amount of original text by using contrastive learning and similarity comparison. We applied this method to task-oriented chatbot data and achieved more than sixty times quantitative improvement. We also analyzed the generated texts to confirm that they produced semantically and expressively diverse texts compared to the original texts. Moreover, we trained and evaluated a classification model using the augmented texts and showed that it improved the performance by more than 0.1915, confirming that it helps to improve the actual model performance.