• Title/Summary/Keyword: 인터넷 상거래

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A Study on Accounting Information and Stock Price of IoT-related Companies after COVID-19 (코로나-19 이후 IoT 관련 기업의 회계정보와 주가에 관한 연구)

  • Lee, Sangho;Cho, Kwangmoon
    • Journal of Internet of Things and Convergence
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    • v.8 no.1
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    • pp.1-10
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    • 2022
  • The purpose of this study is to establish a foundation for IoT-related industries to secure financial soundness and to dominate the global market after COVID-19. Through this study, the quantitative management status of IoT-related companies was checked. It also was attempted to preemptively prepare for corporate insolvency by examining the relationship between financial ratios in accordance with stock price fluctuations and designation of management items. This study selected 502 companies that were listed on the KOSPI and KOSDAQ in the stock market from 2019 to 2020. For statistical analysis, multiple regression analysis, difference analysis and logistic regression analysis were performed. The research results are as follows. First, it was found that the impact of IoT company accounting information on stock prices differs depending on before and after COVID-19. Second, it was found that there is a difference in the closing stock prices of IoT companies before and after COVID-19. Third, it was found that financial ratios according to stock price fluctuations exist differently after COVID-19. Fourth, it was found that the financial ratios according to the designation of management items after COVID-19 exist differently. Through these studies, some suggestions were made to secure the financial soundness of IoT companies and to lay the groundwork for leaping into the global market after COVID-19. Through the results of this study, it is expected that it will lead the growth of IoT companies and contribute to growth as a decacorn company of the future that can guarantee financial soundness in the changing financial market.

A Study on Management Strategies and Management Performance According to Organizational Culture Types in the Digital Economy Era (디지털 경제 시대의 조직문화 유형에 따른 경영전략 및 경영성과에 관한 연구)

  • Lee, Sangho;Cho, Kwangmoon
    • Journal of Internet of Things and Convergence
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    • v.8 no.4
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    • pp.85-96
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    • 2022
  • The purpose of this study was to investigate how the management strategies and organizational culture required in the digital economy have an effect on business performance. It provided basic data on management strategies and organizational culture necessary to approach as a digital leading country. For data collection, a survey was conducted from March 1 to May 30, 2022 for companies located in J province and engaged in industries related to the digital economy. The survey was conducted online and non-face-to-face, and a total of 225 companies participated in the survey. For statistical analysis, frequency analysis, exploratory factor analysis and reliability analysis, cluster analysis, independent sample t-test, and multiple regression analysis were performed. The research results are as follows. First, organizational culture was classified into high and low groups according to preference in innovation oriented, relationship oriented, task oriented, and hierarchical oriented. Second, the 4 types of organizational culture showed differences in prospectors strategy, analyzers strategy, defenders strategy, differentiation strategy, cost leadership strategy, financial performance, and non-financial performance according to preference. Third, management strategies affecting financial performance were found to be analyzers strategy, differentiation strategy, prospectors strategy, and cost leadership strategy. Fourth, management strategies affecting non-financial performance were found to be differentiation strategy, defenders strategy, analysis strategy, offensive strategy, cost leadership strategy, and focus strategy. Fifth, organizational culture affecting financial performance was found to be task oriented. Sixth, organizational culture affecting non-financial performance was found to be innovation oriented and relationship oriented. Through these studies, it is expected that the economy will be revitalized in the domestic market and a growth ecosystem that can take a new leap forward is created in the global market.

A Study on Corporate Blockchain Business Conditions and Financial Platform Promotion Plans (블록체인 기업실태 및 금융플랫폼 촉진 방안 연구)

  • Sangho Lee;Kwangmoon Cho
    • Journal of Internet of Things and Convergence
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    • v.9 no.3
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    • pp.99-111
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    • 2023
  • The purpose of this study is to identify the difficulties in business implementation that blockchain suppliers are experiencing, and to suggest ways to promote blockchain technology by solving them. First, industrial surveys of blockchain supply companies were collected. Next, a survey was conducted to confirm whether financial service users intend to use blockchain technology. The research results are as follows. First, in user characteristics, usefulness and innovation were found to have an effect on intention to use. In the technical characteristics, suitability and reliability were found to affect the intention to use. Second, in user characteristics, usefulness and innovativeness were found to affect the intention to use by mediating promotion conditions. In the technical characteristics, suitability and reliability were found to affect the intention to use by mediating the promotion conditions. Third, it was found that the new technology environment modulates the effect of ubiquity and innovativeness on the intention to use. The new technology environment was found to moderate the impact of security on intention to use. Fourth, it was found that the organizational environment moderates the effect of security and suitability on the intention to use. A plan to solve the difficulties of these blockchain suppliers and a plan to promote blockchain-based financial services are presented.

Resolving the 'Gray sheep' Problem Using Social Network Analysis (SNA) in Collaborative Filtering (CF) Recommender Systems (소셜 네트워크 분석 기법을 활용한 협업필터링의 특이취향 사용자(Gray Sheep) 문제 해결)

  • Kim, Minsung;Im, Il
    • Journal of Intelligence and Information Systems
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    • v.20 no.2
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    • pp.137-148
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    • 2014
  • Recommender system has become one of the most important technologies in e-commerce in these days. The ultimate reason to shop online, for many consumers, is to reduce the efforts for information search and purchase. Recommender system is a key technology to serve these needs. Many of the past studies about recommender systems have been devoted to developing and improving recommendation algorithms and collaborative filtering (CF) is known to be the most successful one. Despite its success, however, CF has several shortcomings such as cold-start, sparsity, gray sheep problems. In order to be able to generate recommendations, ordinary CF algorithms require evaluations or preference information directly from users. For new users who do not have any evaluations or preference information, therefore, CF cannot come up with recommendations (Cold-star problem). As the numbers of products and customers increase, the scale of the data increases exponentially and most of the data cells are empty. This sparse dataset makes computation for recommendation extremely hard (Sparsity problem). Since CF is based on the assumption that there are groups of users sharing common preferences or tastes, CF becomes inaccurate if there are many users with rare and unique tastes (Gray sheep problem). This study proposes a new algorithm that utilizes Social Network Analysis (SNA) techniques to resolve the gray sheep problem. We utilize 'degree centrality' in SNA to identify users with unique preferences (gray sheep). Degree centrality in SNA refers to the number of direct links to and from a node. In a network of users who are connected through common preferences or tastes, those with unique tastes have fewer links to other users (nodes) and they are isolated from other users. Therefore, gray sheep can be identified by calculating degree centrality of each node. We divide the dataset into two, gray sheep and others, based on the degree centrality of the users. Then, different similarity measures and recommendation methods are applied to these two datasets. More detail algorithm is as follows: Step 1: Convert the initial data which is a two-mode network (user to item) into an one-mode network (user to user). Step 2: Calculate degree centrality of each node and separate those nodes having degree centrality values lower than the pre-set threshold. The threshold value is determined by simulations such that the accuracy of CF for the remaining dataset is maximized. Step 3: Ordinary CF algorithm is applied to the remaining dataset. Step 4: Since the separated dataset consist of users with unique tastes, an ordinary CF algorithm cannot generate recommendations for them. A 'popular item' method is used to generate recommendations for these users. The F measures of the two datasets are weighted by the numbers of nodes and summed to be used as the final performance metric. In order to test performance improvement by this new algorithm, an empirical study was conducted using a publically available dataset - the MovieLens data by GroupLens research team. We used 100,000 evaluations by 943 users on 1,682 movies. The proposed algorithm was compared with an ordinary CF algorithm utilizing 'Best-N-neighbors' and 'Cosine' similarity method. The empirical results show that F measure was improved about 11% on average when the proposed algorithm was used

    . Past studies to improve CF performance typically used additional information other than users' evaluations such as demographic data. Some studies applied SNA techniques as a new similarity metric. This study is novel in that it used SNA to separate dataset. This study shows that performance of CF can be improved, without any additional information, when SNA techniques are used as proposed. This study has several theoretical and practical implications. This study empirically shows that the characteristics of dataset can affect the performance of CF recommender systems. This helps researchers understand factors affecting performance of CF. This study also opens a door for future studies in the area of applying SNA to CF to analyze characteristics of dataset. In practice, this study provides guidelines to improve performance of CF recommender systems with a simple modification.

  • Color-related Query Processing for Intelligent E-Commerce Search (지능형 검색엔진을 위한 색상 질의 처리 방안)

    • Hong, Jung A;Koo, Kyo Jung;Cha, Ji Won;Seo, Ah Jeong;Yeo, Un Yeong;Kim, Jong Woo
      • Journal of Intelligence and Information Systems
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      • v.25 no.1
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      • pp.109-125
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      • 2019
    • As interest on intelligent search engines increases, various studies have been conducted to extract and utilize the features related to products intelligencely. In particular, when users search for goods in e-commerce search engines, the 'color' of a product is an important feature that describes the product. Therefore, it is necessary to deal with the synonyms of color terms in order to produce accurate results to user's color-related queries. Previous studies have suggested dictionary-based approach to process synonyms for color features. However, the dictionary-based approach has a limitation that it cannot handle unregistered color-related terms in user queries. In order to overcome the limitation of the conventional methods, this research proposes a model which extracts RGB values from an internet search engine in real time, and outputs similar color names based on designated color information. At first, a color term dictionary was constructed which includes color names and R, G, B values of each color from Korean color standard digital palette program and the Wikipedia color list for the basic color search. The dictionary has been made more robust by adding 138 color names converted from English color names to foreign words in Korean, and with corresponding RGB values. Therefore, the fininal color dictionary includes a total of 671 color names and corresponding RGB values. The method proposed in this research starts by searching for a specific color which a user searched for. Then, the presence of the searched color in the built-in color dictionary is checked. If there exists the color in the dictionary, the RGB values of the color in the dictioanry are used as reference values of the retrieved color. If the searched color does not exist in the dictionary, the top-5 Google image search results of the searched color are crawled and average RGB values are extracted in certain middle area of each image. To extract the RGB values in images, a variety of different ways was attempted since there are limits to simply obtain the average of the RGB values of the center area of images. As a result, clustering RGB values in image's certain area and making average value of the cluster with the highest density as the reference values showed the best performance. Based on the reference RGB values of the searched color, the RGB values of all the colors in the color dictionary constructed aforetime are compared. Then a color list is created with colors within the range of ${\pm}50$ for each R value, G value, and B value. Finally, using the Euclidean distance between the above results and the reference RGB values of the searched color, the color with the highest similarity from up to five colors becomes the final outcome. In order to evaluate the usefulness of the proposed method, we performed an experiment. In the experiment, 300 color names and corresponding color RGB values by the questionnaires were obtained. They are used to compare the RGB values obtained from four different methods including the proposed method. The average euclidean distance of CIE-Lab using our method was about 13.85, which showed a relatively low distance compared to 3088 for the case using synonym dictionary only and 30.38 for the case using the dictionary with Korean synonym website WordNet. The case which didn't use clustering method of the proposed method showed 13.88 of average euclidean distance, which implies the DBSCAN clustering of the proposed method can reduce the Euclidean distance. This research suggests a new color synonym processing method based on RGB values that combines the dictionary method with the real time synonym processing method for new color names. This method enables to get rid of the limit of the dictionary-based approach which is a conventional synonym processing method. This research can contribute to improve the intelligence of e-commerce search systems especially on the color searching feature.

    Designing an Intelligent Advertising Business Model in Seoul's Metro Network (서울지하철의 지능형 광고 비즈니스모델 설계)

    • Musyoka, Kavoya Job;Lim, Gyoo Gun
      • Journal of Intelligence and Information Systems
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      • v.23 no.4
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      • pp.1-31
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      • 2017
    • Modern businesses are adopting new technologies to serve their markets better as well as to improve efficiency and productivity. The advertising industry has continuously experienced disruptions from the traditional channels (radio, television and print media) to new complex ones including internet, social media and mobile-based advertising. This case study focuses on proposing intelligent advertising business model in Seoul's metro network. Seoul has one of the world's busiest metro network and transports a huge number of travelers on a daily basis. The high number of travelers coupled with a well-planned metro network creates a platform where marketers can initiate engagement and interact with both customers and potential customers. In the current advertising model, advertising is on illuminated and framed posters in the stations and in-car, non-illuminated posters, and digital screens that show scheduled arrivals and departures of metros. Some stations have digital screens that show adverts but they do not have location capability. Most of the current advertising media have one key limitation: space. For posters whether illuminated or not, one space can host only one advert at a time. Empirical literatures show that there is room for improving this advertising model and eliminate the space limitation by replacing the poster adverts with digital advertising platform. This new model will not only be digital, but will also provide intelligent advertising platform that is driven by data. The digital platform will incorporate location sensing, e-commerce, and mobile platform to create new value to all stakeholders. Travel cards used in the metro will be registered and the card scanners will have a capability to capture traveler's data when travelers tap their cards. This data once analyzed will make it possible to identify different customer groups. Advertisers and marketers will then be able to target specific customer groups, customize adverts based on the targeted consumer group, and offer a wide variety of advertising formats. Format includes video, cinemagraphs, moving pictures, and animation. Different advert formats create different emotions in the customer's mind and the goal should be to use format or combination of formats that arouse the expected emotion and lead to an engagement. Combination of different formats will be more effective and this can only work in a digital platform. Adverts will be location based, ensuring that adverts will show more frequently when the metro is near the premises of an advertiser. The advertising platform will automatically detect the next station and screens inside the metro will prioritize adverts in the station where the metro will be stopping. In the mobile platform, customers who opt to receive notifications will receive them when they approach the business premises of advertiser. The mobile platform will have indoor navigation for the underground shopping malls that will allow customers to search for facilities within the mall, products they may want to buy as well as deals going on in the underground mall. To create an end-to-end solution, the mobile solution will have a capability to allow customers purchase products through their phones, get coupons for deals, and review products and shops where they have bought a product. The indoor navigation will host intelligent mobile-based advertisement and a recommendation system. The indoor navigation will have adverts such that when a customer is searching for information, the recommendation system shows adverts that are near the place traveler is searching or in the direction that the traveler is moving. These adverts will be linked to the e-commerce platform such that if a customer clicks on an advert, it leads them to the product description page. The whole system will have multi-language as well as text-to-speech capability such that both locals and tourists have no language barrier. The implications of implementing this model are varied including support for small and medium businesses operating in the underground malls, improved customer experience, new job opportunities, additional revenue to business model operator, and flexibility in advertising. The new value created will benefit all the stakeholders.

    Effects of e-CRM Activities and Trust on Loyalty & Mediating Effects of Trust (e-CRM활동, 신뢰도, 충성도 간의 영향 관계 및 신뢰도 매개효과 연구)

    • Hwang, Soo-Young
      • The Journal of the Korea Contents Association
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      • v.20 no.4
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      • pp.487-497
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      • 2020
    • This study is to examine the effects of e-CRM activities(e-Sales activities, e-Service activities and e-System activities) and trust on loyalty. Particularly, it focuses on the mediating effects of trust on the relationships between e-CRM activities and loyalty. The data is collected from 336 university students over two and half month periods. The results are as follows: Firstly, e-Sales activities, e-Service activities and e-System activities effect exert a significant influence on the trust, but e-Sales activities, e-Service activities and e-System activities do not directly influence on the loyalty. Secondly, trust impacts significantly on loyalty. Finally, in summary, findings confirm the mediating effects of trust on the relationship between e-Sales activities, e-Service activities and e-System activities and loyalty. These results show that if e-commerce firms implement e-CRM activities(e-Sales activities, e-Service activities and e-System activities), their customers will more recognize additional service attributes and the customers' relationships, trust and loyalty with their firms will improve.

    Study on E-commerce Evaluation Model : Focused on "Internet Business Model" (전자상거래 평가모형에 관한 연구 : 인터넷 비즈니스모델을 중심으로)

    • Lee, Young-Min
      • Journal of Distribution Science
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      • v.14 no.1
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      • pp.85-91
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      • 2016
    • Purpose - Recently, the importance of rapid change in business models is more and more increasing as the change of information technology environment. Therefore, a variety of business models have emerged. On the other hand, there is no company that can generate revenue. Many enterprises are still maintained while they are changing only their appearance of the business model. Business model is important in e-commerce. However, a lot of researches are targeted only in Web sites. Thus, e-commerce companies do not have the infrastructure for measuring and business models. The purpose of paper is to evaluate factors which are related with the structuring of the e-commerce success. And it proposed a financial items and non-financial items. From the perspectives of administrators and managers, the paper researches the possibility for E-Commerce Evaluation Model as a valuable criteria in measuring business model. Research design, data and methodology - The methods are taken by the classification for the type of business-to-business transactions, transactions subject, and the degree of integration and innovation capabilities. Financial and Non-financial value is used to build E-Commerce Evaluation Model. Evaluation items in Administration's perspective are composed with enhance the effectiveness of the mission, improving efficiency of the administration, and control of costs. Evaluation items in the customer's perspective were measured by customer participation and cooperation with customer Satisfaction. In the case of researching the information system's perspective, three criteria are used such as adequacy of the development process, improvement of the quality of service, and maintenance of standardized information technology. In researching for the ICT competence's perspective, evaluation items were composed of enhanced user capabilities, utilizing new technologies, and empowerment of information workers. Results - In this paper, E-Commerce Evaluation Model with financial and non-financial perspectives shows the possibility to be criteria in the case of measuring business model. Moreover, it gives the positive expectation to be successful criteria. But the research may have ambiguity in its essential concept because it cannot avoid the limitation in selecting evaluation tools from merely the model. It is impossible to exclude the possibility in omitting specific properties which may take place in actual case study. Therefore, In hereafter research, it is necessary to include actual case study research in selecting evaluation tools in order to improve the limit point. Actual measurement items which are derived from actual case study should be subdivided, and it would be more effective to complete the research. Conclusions - In rapid change in business models, there are various kinds of business models. But it is general situation that companies which adopted business models have not brought in revenue. For this reason, E-Commerce Evaluation Model is needed as an important factor for the structuring of the e-commerce success. Although it has the limitation in selecting evaluation tools from model, E-Commerce Evaluation Model proposes the implication for measuring business models as a valuable criteria.

    Analysis on the Trend in Customers' Consciousness as Appeared in Wellbeing Trend, LOHAS -Mainly in Food, Clothing, and Shelter Based Websites- (웰빙 트렌드 로하스(LOHAS)에 나타난 소비자 의식 변화에 따른 웹 디자인 발전방향 분석 - 의, 식, 주 웹 사이트를 중심으로 -)

    • Kim, Min-Seo;Chun, Yang-Deok
      • Archives of design research
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      • v.20 no.3 s.71
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      • pp.49-60
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      • 2007
    • As the world is in the age of globalization and information, we observe diverse changes in the market environment. Since wide-spread internet services and global networks made ubiquitous learning and business possible, equalizing consumers' ideology and preference, new trend and life style could be introduced easily. This study stipulates on the theoretical concept of the wellbeing consumer and LOHAS consumer. Consumers of LOHAS could be sampled out through pre-questionnaire targeting at selected food, clothing, and shelter based on companies of both wellbeing and general brands. Through this it is attempted to measure wellbeing emotion, recognition quotient of emotion and reason, affirmation and negation, mental emotion quotient, and preference in order to find out their value and to ultimately come up with what web design should be aiming at. Conclusions are as follows: Firstly, consumers easily recognize emotional identification from the web pages of wellbeing brand, rather than that of general brands. Secondly, what web pages of wellbeing brand recognize is reason, not emotion. Thirdly, the design of wellbeing brands scored higher than those of general brands in terms of positive aspects such as hospitality and familiarity, and high mental emotion quotient could not affect the consumers' preference toward web design. Fourthly, wellbeing brands win more preference than general brands do, and preference becomes higher after customers' visit to web pages basically. Lastly, sampled emotional adjectives toward the web designs of wellbeing brands marked a aesthetic graph figure, without leaning toward an active or stable one. It is expected that this study can serve as a groundwork to create proper strategies to actively involve consumers in industrial sphere.

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    The Effect of an Emotional Factor on User Experience with Smartphone Unlocking Process (스마트 폰 잠금 해제 과정에서의 감성적 UX 요소가 전반적 기기 사용 경험과 향후 사용 의도에 미치는 영향)

    • Lee, Sunhwa;Shin, Youngsoo;Im, Chaerin;Beak, Hannah;Lee, Sungho;Kim, Jinwoo
      • Science of Emotion and Sensibility
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      • v.17 no.4
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      • pp.79-88
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      • 2014
    • Smart-phones have become a vital part of our lives, paying a bill online, shopping using applications, using email and office applications. Therefore, the risk of the leakage of personal informations and the misuse of them becomes high, for the cost of loosing smart-phone. Many types of smart-phone security features such as password, slide-lock, and pattern lock have been introduced. However, those security locks make users not to easily access and use a smart-phone. There is tradeoff between security on one hand, and usability and cost on the other. This paper propose Self-Concealment to solve the tradeoff problem and demonstrate the effect through the experiment. In sum, Self-Concealment lowers smart-phone experience; however increases smart-phone use intension. This paper has implication for proposing new User Experience (UX) construct to resolve the trade-off between security and usability.


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