Goh, Byeong Ki;Park, Sol Ip;Kim, Da Hye;Sung, Chang Soo
Asia-Pacific Journal of Business Venturing and Entrepreneurship
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v.17
no.5
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pp.31-47
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2022
The TIPS, a representative public-private cooperative project to revitalize the start-up ecosystem, is a government supported policy that promotes successful commercialization through various start-up support for technology-based startups. The purpose of this study is to analyze the investment decision factors of the TIPS program and to derive priorities. In order to achieve the research purpose, first, the investment decision factors were derived through literature analysis, a Delphi surveys were conducted on investors and experts participating in the evaluation of the TIPS program, and an AHP analysis was conducted on 20 VCs to empirically analyze the priority of factors on investment decisions. As a result of the analysis, the importance of critical factors was confirmed in the order of entrepreneurs(team) > market > product/service > finance > network. The importance of detailed factors was found in the order of entrepreneur's reliability and authenticity > market growth and scalability > team members' expertise and capabilities > adequacy of current market size > new market creation. This study presented the capabilities of technology-based startups preparing to participate in the TIPS program by deriving factors that influence investment decisions from an investor's perspective and comparing and analyzing the importance. It is also meaningful that basic data on determinants of private-led investment decision-making were presented to stake-holders such as venture capital, accelerator, and start-up support institutions.
The development and generalization of the Internet increased the popularity of food delivery service applications in Korea. The food delivery market based on online-to-offline service is growing rapidly. This study compares the usability of Korean food delivery service application between that of Chinese food delivery service application. This study suggests improvement points for Korean food delivery service applications. To conduct this study, we explore the status of various food delivery service applications and conduct interviews and surveys based on the honeycomb model developed by Peter Morville. This study obtained the following results. First, all restaurants participating in the Korean food delivery service must be able to accept order through the application. Second, the shopping cart function must be able to accept order of all restaurants simultaneously. Third, when users look for menu recommendation, their purchase history and shopping cart functions should appear at the first page of the website. Users should be able to perceive the improved usability of the website using those functions. Fourth, when the search window is fixed on the top of each page, users should be able to find the information they need. Fifth, the application must allow users to find the exact location of the delivery person and the estimated delivery time. Finally, the restaurants'address should be disclosed and fast delivery time should be confirmed to enhance users'trust on the application. This study contributes to academia and industry by suggesting useful insight into food delivery service applications and improving the point of food delivery service application in Korea.
Journal of the Korean BIBLIA Society for library and Information Science
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v.35
no.2
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pp.25-45
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2024
This study aims to understand the everyday information-seeking behaviors of Alpha-generation elementary school students. A survey was conducted among 4th to 6th grade students to investigate their information needs in daily life, the sources they use to fulfill these needs and the reasons for their choices, the barriers they encounter during the information search process, and their satisfaction and trust in the information obtained. The results indicate that Alpha generation elementary students most frequently use video platforms and have the highest information needs related to hobbies and leisure activities. The main reasons for choosing information sources were familiarity and convenience. Differences based on demographic characteristics and media literacy education were also analyzed. There were significant differences in information-seeking behavior based on gender. Also, students who had received media literacy education experienced fewer difficulties in the information acquisition process compared to those who had not. The findings of this study are expected to provide valuable data for developing information services and media literacy education directions for the Alpha generation in school settings.
This study aims to identify the main factors that caused the digital divide during the COVID-19 pandemic. Utilizing data from the 2020 and 2021 Digital Divide Surveys by the National Information Agency, a research model was constructed for analysis using SmartPLS 4, applying PLS-SEM and Multigroup Analysis methods. The results of the study are as follows. First, combining 2020 and 2021, mobile internet usage during COVID-19 is positively associated with digital skills, digital usage, and usage outcomes except for networking. Second, the impact of digital usage was significantly higher during the outbreak than during the beginning of COVID-19, which may be due to the increased demand for digital usage as the outbreak continued, and the corresponding increase in internet usage. Third, we discovered that demographics are not the main factor affecting changes in mobile internet use during the COVID-19 pandemic. Instead, digital literacy affects mobile usage, which is the most important one. The results show the importance of creating programs to teach people how to use technology appropriately. We propose that digital literacy should be central to training programs for people who use digital services.
With the advent of 5G, characterized by Enhanced Mobile Broadband (eMBB), Ultra-Reliable Low Latency Communications (URLLC), and Massive Machine Type Communications (mMTC), efficient network management and service provision are becoming increasingly critical. This paper proposes a novel approach to address key challenges of 5G networks, namely ultra-high speed, ultra-low latency, and ultra-reliability, while dynamically optimizing network slicing and resource allocation using machine learning (ML) and deep learning (DL) techniques. The proposed methodology utilizes prediction models for network traffic and resource allocation, and employs Federated Learning (FL) techniques to simultaneously optimize network bandwidth, latency, and enhance privacy and security. Specifically, this paper extensively covers the implementation methods of various algorithms and models such as Random Forest and LSTM, thereby presenting methodologies for the automation and intelligence of 5G network operations. Finally, the performance enhancement effects achievable by applying ML and DL to 5G networks are validated through performance evaluation and analysis, and solutions for network slicing and resource management optimization are proposed for various industrial applications.
Journal of the Korean Society for Library and Information Science
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v.58
no.2
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pp.251-268
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2024
Recently, with the implementation of the "e-Government Performance Management Guidelines," there is a growing demand for setting performance indicators for information systems. For systems that provide information services to the public, such as CODIL, it is not easy to set performance indicators. This study presented a research model that applies Monte Carlo simulation to set expected performance targets that can be achieved through CODIL based on objective evidence. Among the survey contents conducted from 2015 to 2023, the statistical characteristics of user satisfaction regarding the frequency of use of construction technology information provided by CODIL were designated as input variables. Future expected targets and confidence intervals from 2024 to 2026 were designated as outcome variables. The expected target value was measured by generating 5 simulation alternatives and 1,000 random numbers for each alternative. Next, the measured expected goals were interpreted and compared with the results of time series regression analysis measured in previous studies. Although, as in previous studies, the expected target value could not be predicted based on time series regression analysis that considers the correlation between years. However, compared to previous studies, this study can be considered a more accurate analysis result because it predicted the expected target value based on 5,000 input variables.
This paper analyzed the overall status of the domestic freight transportation business, established SWOT analysis and strategy through existing literature research and designed an AHP model to derive priorities for each strategy. The SWOT analysis analyzed the management model of the consignment borrowers belonging to a transportation company that did not handle the supplies with the lowest satisfaction with the consignment system. The AHP model was designed by establishing a SWOT strategy through SWOT analysis. As a result of the analysis of the upper class, priorities were derived in the order of WO strategy, SO strategy, ST strategy, and WT strategy. As a result of comprehensive priorities for the development strategy of the domestic freight transportation business, WO strategy's "Improvement of cooperative relations between transportation companies and consignment owners through fair consignment contracts" was first, SO strategy's "Public promotion of the necessity of consignment systems based on high economic feasibility and reliability" was second, and ST strategy's "Proposal of policies to strengthen financial performance through the introduction of freight transport platforms" was fourth, followed by WT strategy's "Improvement of satisfaction with transport services through the introduction of freight transport platforms" and SO strategy's "Expansion of safe freight systems" in sixth, respectively.
Journal of the Korean Association of Geographic Information Studies
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v.2
no.2
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pp.27-44
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1999
Digital maps produced in Korea are various in scale and include a lot of geographic and attribute data. In this study, it is argued that, to reduce the production cost and the difficulties for renewal, it is necessary to establish the already nationally drawn 1:5,000 scale digital maps as the base maps and simplify them as much as the TIGER files in the U.S. The comprehensive data included in the digital maps in Korea are mostly land use information, which are supposed to be established separately from the digital maps. The land use information system could be maintained and updated cheaply and frequently at the local government level. In response to common needs, the land use information could be imported to GIS and used for analyses. As technologies and societies changes, the Census questions and methodologies should be changed for better uses. Along with GIS, the Census would be developed and processed more reliably and efficiently. Also, it is recommended for Korean government to develop the Census Tract and Block Group system. Current Eup, Myon, Dong as basic units for Census information may not be useful or effective for micro level urban analyses and public service planning activities because of their large population and land areas. It is recommended that optimum population of a Census Tract be 5,000 and a Block Groups 1,500, and one Census Tract includes 1~9 Block Groups. It is recommend that Census Tract and Block Group boundary lines be decided flexibly in light of population, physical features, socio-economic attributes, and tradition. For urban analyses using GIS, socio-economic census data, city government's information such as parcel data and building permit data, survey data, and satellite image data could also be used. The existence of Census Tracts and Block Groups as well as GIS could help for the data and methods to be useful for urban analyses and public service provisions.
Nowadays, Internet users tend to do a variety of actions at the same time such as web browsing, social networking and multimedia consumption. While watching a video, once a user is interested in any product, the user has to do information searches to get to know more about the product. With a conventional approach, user has to search it separately with search engines like Bing or Google, which might be inconvenient and time-consuming. For this reason, a video annotation platform has been developed in order to provide users more convenient and more interactive ways with video content. In the future of smart TV environment, users can follow annotated information, for example, a link to a vendor to buy the product of interest. It is even better to enable users to search for information by directly discussing with friends. Users can effectively get useful and relevant information about the product from friends who share common interests or might have experienced it before, which is more reliable than the results from search engines. Social networking services provide an appropriate environment for people to share products so that they can show new things to their friends and to share their personal experiences on any specific product. Meanwhile, they can also absorb the most relevant information about the product that they are interested in by either comments or discussion amongst friends. However, within a very huge graph of friends, determining the most appropriate persons to ask for information about a specific product has still a limitation within the existing conventional approach. Once users want to share or discuss a product, they simply share it to all friends as new feeds. This means a newly posted article is blindly spread to all friends without considering their background interests or knowledge. In this way, the number of responses back will be huge. Users cannot easily absorb the relevant and useful responses from friends, since they are from various fields of interest and knowledge. In order to overcome this limitation, we propose a method to filter a user's friends for information search, which leverages semantic video annotation and social networking services. Our method filters and brings out who can give user useful information about a specific product. By examining the existing Facebook information regarding users and their social graph, we construct a user profile of product interest. With user's permission and authentication, user's particular activities are enriched with the domain-specific ontology such as GoodRelations and BestBuy Data sources. Besides, we assume that the object in the video is already annotated using Linked Data. Thus, the detail information of the product that user would like to ask for more information is retrieved via product URI. Our system calculates the similarities among them in order to identify the most suitable friends for seeking information about the mentioned product. The system filters a user's friends according to their score which tells the order of whom can highly likely give the user useful information about a specific product of interest. We have conducted an experiment with a group of respondents in order to verify and evaluate our system. First, the user profile accuracy evaluation is conducted to demonstrate how much our system constructed user profile of product interest represents user's interest correctly. Then, the evaluation on filtering method is made by inspecting the ranked results with human judgment. The results show that our method works effectively and efficiently in filtering. Our system fulfills user needs by supporting user to select appropriate friends for seeking useful information about a specific product that user is curious about. As a result, it helps to influence and convince user in purchase decisions.
Journal of the Korean Institute of Landscape Architecture
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v.45
no.2
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pp.40-50
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2017
Compared to the traditional format, the revised IPA is an effective method for selecting a management strategy as compared to the traditional IPA. Comparison between the traditional IPA and revised IPA with a management strategy has been, however, limited. Therefore, the difference between the traditional IPA and revised IPA was compared to select an effective management strategy in the Suncheon Bay Wetland Reserve. First of all, related papers were reviewed to select an appropriate revised IPA. It was found that Deng (2007)'s revised IPA was appropriate for quantifying service quality and a management strategy that affects the measurable satisfaction of visitors in the space. Second, the results of the traditional IPA were compared with the revised IPA in the Suncheon Bay Wetland Reserve and the management strategy of the revised IPA and the changes of management factors were discussed. It was found that some management factors deviated from the order of the quadrant "low priority for managers", "Concentrate management here", "Keep up the good work" were moved to the order of the quadrants "Concentrate management here", "low priority for managers" and "Possible overkill" in the revised IPA grid. The complexity as a management factor resulted in higher demand management than the traditional IPA, which moved from "low priority for managers" to "Concentrate management here". Management factors resulted in lower demand management than the traditional IPA moved from "Concentrate management here" to "low priority for managers"; these consisted of shade trees, exhibition exteriors, programs, and a guided tour. Also, management factors moved from "Keep up the good work" to "Possible overkill" consisted of relaxation facilities, glow of the setting sun, a hedge, and an exhibition interior. Over all, the revised IPA responded properly to changes in the measurable satisfaction of visitors to the Suncheon Bay Wetland Reserve. Therefore, a revised IPA should be provided for accurate and reliable guidelines when decision makers establish management strategies.
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