• Title/Summary/Keyword: 서비스소비자

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A study about the effects of online commerce on the local retail commercial area (온라인 거래의 증가가 지역 소매 상권에 미치는 영향에 관한 연구)

  • Lee, Kangbae
    • Economic Analysis
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    • v.25 no.2
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    • pp.54-95
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    • 2019
  • The purpose of this study is to analyze quantitatively and qualitatively the effects of the increase in online shopping and its effects on real-world commercial outlets. The empirical analysis of this study is based on the results of "Census on Establishments" and "Online Shopping Survey" that cover 15 years, from 2002 to 2016. According to the results of this study, the increase in the number of online transactions affects the decrease in the number of stores in the real-world retail sector. However, non-specialized large stores and chain convenience stores showed an increase in the number of stores. In addition, the number of F&B stores increased the most in line with the increase in online transactions. This is because the increase in online transactions and in internet users led to the use of more delivery applications and the introduction of popular places on blogs or through social media. Street-level rents for medium and large-sized locations increased. In other words, it is seen that the demand for differentiated real-world stores that provide a good user experience increases, even though online transactions also increase. These results suggest that real-world stores should provide good user experiences in their physical locations with a certain size and assortment of goods.

A study on the aspect-based sentiment analysis of multilingual customer reviews (다국어 사용자 후기에 대한 속성기반 감성분석 연구)

  • Sungyoung Ji;Siyoon Lee;Daewoo Choi;Kee-Hoon Kang
    • The Korean Journal of Applied Statistics
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    • v.36 no.6
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    • pp.515-528
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    • 2023
  • With the growth of the e-commerce market, consumers increasingly rely on user reviews to make purchasing decisions. Consequently, researchers are actively conducting studies to effectively analyze these reviews. Among the various methods of sentiment analysis, the aspect-based sentiment analysis approach, which examines user reviews from multiple angles rather than solely relying on simple positive or negative sentiments, is gaining widespread attention. Among the various methodologies for aspect-based sentiment analysis, there is an analysis method using a transformer-based model, which is the latest natural language processing technology. In this paper, we conduct an aspect-based sentiment analysis on multilingual user reviews using two real datasets from the latest natural language processing technology model. Specifically, we use restaurant data from the SemEval 2016 public dataset and multilingual user review data from the cosmetic domain. We compare the performance of transformer-based models for aspect-based sentiment analysis and apply various methodologies to improve their performance. Models using multilingual data are expected to be highly useful in that they can analyze multiple languages in one model without building separate models for each language.

Factors Affecting Satisfaction and Continuous Use Intention of Subscription Economy (구독경제 이용 만족도 및 지속 이용 의도에 영향을 미치는 요인)

  • Chung, Byoung-gyu
    • Journal of Venture Innovation
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    • v.6 no.1
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    • pp.1-16
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    • 2023
  • Due to the progress of the 4th industrial revolution and the COVID-19 pandemic, the subscription economy was rapidly expanding. In particular, the subscription economy was expected to expand further as the servicing of products(servitization) rapidly progresses. In this study, we tried to empirically analyze the factors that promote and hinder the spread of the subscription economy from the consumer's point of view. To this end, based on the Service Profit Chain (SPC) model, which identified mechanisms leading from quality to satisfaction, loyalty, and performance, a research model was established by combining the framework of the Value-based Adoption Model (VAM), which covers both benefit and sacrifice factors. Usefulness and convenience were derived as benefit factors, and perceived risks and perceived costs were derived as sacrifice factors. The effects of these factors on satisfaction and continuous use intention were analyzed. For empirical analysis, a survey was conducted targeting people who have experience in subscription economy, and 300 effective samples were analyzed. The analysis was performed as a structural equation model using AMOS 24. As a result of the empirical study, it was found that convenience had a significant positive (+) effect on satisfaction. Perceived risk and perceived cost were analyzed to have a negative (-) effect on satisfaction. On the other hand, usefulness was found to have no significant effect on satisfaction. The influences affecting satisfaction were in the order of perceived cost, convenience, and perceived risk. Satisfaction was found to have a significant positive (+) effect on continuous use intention. The results of this study were considered meaningful in that they broadened the horizons of research by combining existing validated models at the academic level and testing their validity, and found that perceived cost was still an important factor at the practical level.

Study on the feasibility of using AI image generation tool for fashion design development -Focused on the use of Midjourney (패션디자인 개발을 위한 AI 이미지 생성 도구의 활용 가능성 연구 -미드저니(Midjourney)의 활용을 중심으로)

  • Park, Keunsoo
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.6
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    • pp.237-244
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    • 2023
  • Today, AI is being applied to various industrial fields, leading to a paradigm shift in the overall industry. In the fashion industry, AI is also used to predict trends and provide various services for consumers, and in particular, AI image creation tools have the potential as a tool for fashion design development. This study investigated the possibilities and limitations of using Midjourny for fashion design development by creating images using Midjourney among AI image creation tools and identifying its characteristics. The characteristics of images created in Midjourney are as follows. First, it has the intuitiveness to create images by intuitively applying or combining images corresponding to commands. Second, there is randomness in which different images are generated when the same command is entered at different times. Third, when using existing images and commands together, the image created in Midjourney is more dependent on the existing image than the command. In conclusion, Midjourny's various image creation functions and the ability to change images according to commands can be helpful in developing original fashion designs. However, it is important to note that fashion designs that cannot be worn or made are sometimes presented. It is expected that the results of this study will serve as basic data for the use of AI image creation tools for fashion design development.

Automated Story Generation with Image Captions and Recursiva Calls (이미지 캡션 및 재귀호출을 통한 스토리 생성 방법)

  • Isle Jeon;Dongha Jo;Mikyeong Moon
    • Journal of the Institute of Convergence Signal Processing
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    • v.24 no.1
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    • pp.42-50
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    • 2023
  • The development of technology has achieved digital innovation throughout the media industry, including production techniques and editing technologies, and has brought diversity in the form of consumer viewing through the OTT service and streaming era. The convergence of big data and deep learning networks automatically generated text in format such as news articles, novels, and scripts, but there were insufficient studies that reflected the author's intention and generated story with contextually smooth. In this paper, we describe the flow of pictures in the storyboard with image caption generation techniques, and the automatic generation of story-tailored scenarios through language models. Image caption using CNN and Attention Mechanism, we generate sentences describing pictures on the storyboard, and input the generated sentences into the artificial intelligence natural language processing model KoGPT-2 in order to automatically generate scenarios that meet the planning intention. Through this paper, the author's intention and story customized scenarios are created in large quantities to alleviate the pain of content creation, and artificial intelligence participates in the overall process of digital content production to activate media intelligence.

Impact of customer experience characteristics on perceived value and revisit intention: Focusing on offline home appliance stores (고객체험특성이 지각된 가치와 재방문 의도에 미치는 영향: 가전 오프라인 매장을 중심으로)

  • Hosun Jeong;Jungmin Park;Hyoung-Yong Lee
    • Journal of Intelligence and Information Systems
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    • v.29 no.4
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    • pp.395-413
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    • 2023
  • This research studied the effect of customer experience characteristics in offline home appliance stores on perceived value and revisit intention. Among the offline distribution of home appliances with more than 100 stores nationwide, two home appliance retailers (HiMart, E-Land), three hypermarkets (E-Mart, Homeplus, Lotte Hi-Mart), and two home appliance stores (LG Best Shop, Samsung Digital Plaza) were selected, and a survey was conducted on men and women in their 20s or older in Seoul, Gyeonggi, and Incheon who had visited and purchased the home appliance store within the last 6 months. As a result of the survey, a statistical analysis was conducted on a total of 330 samples using the PLS (Partial Least Squares) structural equation model and SPSS statistical package. Through this study, the following research results can be obtained. First, educational experience, deviant experience, and aesthetic experience had a positive (+) effect on the functional value. However, entertainment experience did not affect functional value. Second, educational experience, deviant experience, and aesthetic experience all had a positive (+) effect on emotional value. Third, both functional and sensory values had a positive (+) effect on the revisit intention. Fourth, it was confirmed that brand loyalty had no moderating effect between functional value and sensory value revisit intention. The results of this study show the structural relationship between customer experience characteristics, perceived value (functional value, sensory value), and revisit intention. This result provides guidelines on what activities home appliance offline stores should do at a time when online channels threaten the survival of offline channels.

Prediction of Customer Satisfaction Using RFE-SHAP Feature Selection Method (RFE-SHAP을 활용한 온라인 리뷰를 통한 고객 만족도 예측)

  • Olga Chernyaeva;Taeho Hong
    • 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.

Development of Hybrid Recommender System Using Review Data Mining: Kindle Store Data Analysis Case (리뷰 데이터 마이닝을 이용한 하이브리드 추천시스템 개발: Amazon Kindle Store 데이터 분석사례)

  • Yihua Zhang;Qinglong Li;Ilyoung Choi;Jaekyeong Kim
    • Information Systems Review
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    • v.23 no.1
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    • pp.155-172
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    • 2021
  • With the recent increase in online product purchases, a recommender system that recommends products considering users' preferences has still been studied. The recommender system provides personalized product recommendation services to users. Collaborative Filtering (CF) using user ratings on products is one of the most widely used recommendation algorithms. During CF, the item-based method identifies the user's product by using ratings left on the product purchased by the user and obtains the similarity between the purchased product and the unpurchased product. CF takes a lot of time to calculate the similarity between products. In particular, it takes more time when using text-based big data such as review data of Amazon store. This paper suggests a hybrid recommendation system using a 2-phase methodology and text data mining to calculate the similarity between products easily and quickly. To this end, we collected about 980,000 online consumer ratings and review data from the online commerce store, Amazon Kinder Store. As a result of several experiments, it was confirmed that the suggested hybrid recommendation system reflecting the user's rating and review data has resulted in similar recommendation time, but higher accuracy compared to the CF-based benchmark recommender systems. Therefore, the suggested system is expected to increase the user's satisfaction and increase its sales.

A Study on the Activation of Pet Plant Kit Industry - Catering to the Demands of Industry Professionals - (반려식물 키트 산업의 활성화 방안에 관한 연구 - 산업 종사자의 수요를 중심으로 -)

  • Roh, Hoi-Eun;Lim, Chae-Jun;Lee, Min-Ji;Jo, Jang-Hwan
    • Journal of the Korean Institute of Landscape Architecture
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    • v.52 no.3
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    • pp.46-58
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    • 2024
  • The purpose of this study is to understand the current status of the pet plant kit industry and determine the priorities for support policies to revitalize the industry. SWOT analysis assessed the industry's current state, and the Analytic Hierarchy Process (AHP) was used with industry professionals to prioritize support policies. The SWOT analysis results indicated that SO strategies involve leveraging government support policies to enhance marketing and developing eco-friendly DIY products. WO strategies include launching advertising campaigns to increase market recognition and establishing strategic partnerships to expand distribution. ST strategies focus on strengthening price competitiveness and proposing unique values, while WT strategies involve improving production processes and enhancing product quality based on consumer feedback. The AHP analysis identified 3 top-level and 12 sub-level evaluation items, with data collected from 17 expert surveys. The results showed the 'entry phase' (0.482), 'activation phase' (0.397), and 'advanced phase' (0.121) were prioritized, with 'organizing seminars' (0.181) as the most crucial subcategory and 'support for kit development' (0.020) as the least. The pet plant kit industry is in its early stages, and appropriate policy incubation can help activate the garden industry. This study provides foundational information on the industry's needs for activation.

The Impact of the Mobile Application on Off-Line Market: Case in Call Taxi and Kakao Taxi (모바일 어플리케이션이 오프라인 시장에 미치는 영향: 콜택시와 카카오택시를 중심으로)

  • Kyeongjin Lee;Jaehong Park
    • Information Systems Review
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    • v.18 no.4
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    • pp.141-154
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    • 2016
  • Mobile application is growing explosively with the advent of a new technology: smartphones. Mobile application is a new marketing channel and performs as a start-up platform. This study examines the effect of mobile application on the off-line market. Despite the continuous declining demand for taxi service, paradoxically, the supply of taxi service has increased. The taxi industry can be categorized into general taxi and call taxi. General taxi is accidental and inefficient because it has to search for its own passenger. As call taxi takes the request of a passenger, it is more efficient than general taxi. However, the current defective passenger-taxi driver matching system and insufficient taxi driver management hinder the development of the call taxi market. Differences in differences (DID) is an econometrical methodology that examines whether or not an event has meaningful influence. This research uses DID to investigate the effect of the Kakao taxi application on the call taxi industry. Furthermore, it examines the effect of major companies' reckless diversification, which is considered unethical behavior. The passengers of call taxi data from August 2014 to July 2015 and those of designated driving service data of the same period were collected as the control group.