• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.1
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• pp.125-140
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• 2023

Careful preparation for a start-up can lower the risk of failure and create a successful business model. However, there are still challenges for middle-aged entrepreneurs, as start-up services and policies are often not readily accessible or fully utilized. Despite active research on middle-aged start-ups, previous studies have not delved deeply into the demographics of start-up preparation and various preparation behaviors. In response to this, a study was conducted to identify which start-up support services middle-aged entrepreneurs use, and how start-up preparation can be classified based on this. Data from 324 middle-aged tech start-up owners, based in Seoul and who started their businesses within the past 7 years, was collected and analyzed. The results showed that middle-aged entrepreneurs had moderate start-up preparation, with the greatest focus on the preparation period and the least focus on start-up education. Latent Profile Analysis revealed three groups of start-up preparation types among middle-aged entrepreneurs: "Overall Tribal Type," "Lack of Start-up Education Type," and "Comprehensive Preparation Type." BCH was performed on start-up satisfaction, start-up competence, fear of failure, access to start-up services, and support needs for middle-aged entrepreneurs based on the preparation type. The results showed that "Overall Tribal Type" had statistically lower start-up satisfaction, competence, and service accessibility compared to the other groups. Meanwhile, "Comprehensive Preparation Type" had a statistically lower fear of failure than the other types. "Overall Tribal Type" also had lower accessibility to middle-aged start-up services. All types had a high recognition of the need for support for specialized middle-aged start-ups. The findings highlight the need for more comprehensive support for middle-aged entrepreneurs. This could include expanding support projects to enhance their level of preparation, providing customized support based on their level of preparation, and improving the visibility and accessibility of start-up support services for middle-aged individuals. Additionally, specialized education that addresses the characteristics of middle-aged individuals should be provided.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.5
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• pp.79-96
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• 2021

Green infrastructure planning represents landscape planning measures to reduce particulate matter. This study aimed to derive factors that may be used in planning green infrastructure for particulate matter reduction using text mining techniques. A range of analyses were carried out by focusing on keywords such as 'particulate matter reduction plan' and 'green infrastructure planning elements'. The analyses included Term Frequency-Inverse Document Frequency (TF-IDF) analysis, centrality analysis, related word analysis, and topic modeling analysis. These analyses were carried out via text mining by collecting information on previous related research, policy reports, and laws. Initially, TF-IDF analysis results were used to classify major keywords relating to particulate matter and green infrastructure into three groups: (1) environmental issues (e.g., particulate matter, environment, carbon, and atmosphere), target spaces (e.g., urban, park, and local green space), and application methods (e.g., analysis, planning, evaluation, development, ecological aspect, policy management, technology, and resilience). Second, the centrality analysis results were found to be similar to those of TF-IDF; it was confirmed that the central connectors to the major keywords were 'Green New Deal' and 'Vacant land'. The results from the analysis of related words verified that planning green infrastructure for particulate matter reduction required planning forests and ventilation corridors. Additionally, moisture must be considered for microclimate control. It was also confirmed that utilizing vacant space, establishing mixed forests, introducing particulate matter reduction technology, and understanding the system may be important for the effective planning of green infrastructure. Topic analysis was used to classify the planning elements of green infrastructure based on ecological, technological, and social functions. The planning elements of ecological function were classified into morphological (e.g., urban forest, green space, wall greening) and functional aspects (e.g., climate control, carbon storage and absorption, provision of habitats, and biodiversity for wildlife). The planning elements of technical function were classified into various themes, including the disaster prevention functions of green infrastructure, buffer effects, stormwater management, water purification, and energy reduction. The planning elements of the social function were classified into themes such as community function, improving the health of users, and scenery improvement. These results suggest that green infrastructure planning for particulate matter reduction requires approaches related to key concepts, such as resilience and sustainability. In particular, there is a need to apply green infrastructure planning elements in order to reduce exposure to particulate matter.

• Cross-Cultural Studies
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• v.50
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• pp.395-424
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• 2018

The purpose of this paper is to examine the current situation and background of the Russian consumer music market, where digital music sources are making great strides in the noted recent years. In addition, music storage technology, media and change are considered together in this report. Moreover, Russia is the 12th largest music market in the world. The Russian music industry is following the recent trend of the global music industry, where the digital music market is growing rapidly on many different levels. The explosive growth of the digital sound sources in Russia's music industry is attributed to the explosive increase in available consumer downloads, streaming sound source service, and the increase in the number of digital sound sources using mobile technologies due to the development of the Internet. In particular, the sales of the available and accessible streaming sound sources are expected to grow explosively by the year 2020, which is expected to account for more than 85% of total digital music sales. In other words, the spread of smartphones and the resulting changes in the lifestyle of the Russians have created these changes for the global consumer of music. In other words, the time has come for anyone to easily access music and listen to music without a separate audio or digital player. And the fact that the Russian government's strong policy on the eradication of illegal copying of music is becoming an effective deterrent, as is also the factor that led to the increase of the share of the digital sound source to increase sales in Russia. Today, the Russian music industry is leading this change through the age and process of simply adapting to the digital age. Music is the most important element of cultural assets, and it is the beneficial content, which drives the overall growth of the digital economy. In addition, if the following five improvements(First, strengthen the consciousness of the Russian people about copyright protection; Second, utilizing the Big Data Internet resources in the digital music industry; Third, to improve the monopoly situation of digital music distributors; Fourth, distribution of fair music revenues; and Fifth, revitalization of a re-investment in the current Russian music industry) are effective and productive, Russia's role and position in the world music market is likely to expand.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.155-169
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• 2014

With the rapid advances in technologies, organizations are more likely to depend on information systems in their decision-making processes. Business Intelligence (BI) systems, in particular, have become a mainstay in dealing with complex problems in an organization, partly because a variety of advanced computational methods from statistics, machine learning, and artificial intelligence can be applied to solve business problems such as demand forecasting. In addition to the ability to analyze past and present trends, these predictive analytics capabilities provide huge value to an organization's ability to respond to change in markets, business risks, and customer trends. While the performance effects of BI system use in organization settings have been studied, it has been little discussed on the use of predictive analytics technologies embedded in BI systems for forecasting tasks. Thus, this study aims to find important factors that can help to take advantage of the benefits of advanced technologies of a BI system. More generally, a BI system can be viewed as an advisor, defined as the one that formulates judgments or recommends alternatives and communicates these to the person in the role of the judge, and the information generated by the BI system as advice that a decision maker (judge) can follow. Thus, we refer to the findings from the advice-giving and advice-taking literature, focusing on the role of explanations of the system in users' advice taking. It has been shown that advice discounting could occur when an advisor's reasoning or evidence justifying the advisor's decision is not available. However, the majority of current BI systems merely provide a number, which may influence decision makers in accepting the advice and inferring the quality of advice. We in this study explore the following key factors that can influence users' advice taking within the setting of a BI system: explanations on how the box-office grosses are predicted, types of advisor, i.e., system (data mining technique) or human-based business advice mechanisms such as prediction markets (aggregated human advice) and human advisors (individual human expert advice), users' evaluations of the provided advice, and individual differences in decision-makers. Each subject performs the following four tasks, by going through a series of display screens on the computer. First, given the information of the given movie such as director and genre, the subjects are asked to predict the opening weekend box office of the movie. Second, in light of the information generated by an advisor, the subjects are asked to adjust their original predictions, if they desire to do so. Third, they are asked to evaluate the value of the given information (e.g., perceived usefulness, trust, satisfaction). Lastly, a short survey is conducted to identify individual differences that may affect advice-taking. The results from the experiment show that subjects are more likely to follow system-generated advice than human advice when the advice is provided with an explanation. When the subjects as system users think the information provided by the system is useful, they are also more likely to take the advice. In addition, individual differences affect advice-taking. The subjects with more expertise on advisors or that tend to agree with others adjust their predictions, following the advice. On the other hand, the subjects with more knowledge on movies are less affected by the advice and their final decisions are close to their original predictions. The advances in predictive analytics of a BI system demonstrate a great potential to support increasingly complex business decisions. This study shows how the designs of a BI system can play a role in influencing users' acceptance of the system-generated advice, and the findings provide valuable insights on how to leverage the advanced predictive analytics of the BI system in an organization's forecasting practices.

• Journal of the Korean Society of Food Science and Nutrition
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• v.42 no.10
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• pp.1618-1628
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• 2013

Relationships between fatty acids and tocopherols in conventional and genetically modified peanut cultivars were studied by gas chromatography with flame ion detector and high performance liquid chromatography with fluorescence detection. Eight fatty acids and four tocopherol isomers in the sample set were identified and quantified. Oleic acid and linoleic acid are major fatty acids and the ratio of oleic and linoleic acids ranged from 1.11 to 16.26. Tocopherols contents were 6.76 to 12.24 for ${\alpha}$-tocopherol (T), 0.08 to 0.39 for ${\beta}$-T, 5.28 to 15.02 for ${\gamma}$-T, and 0.17 to 1.17 mg/100 g for ${\delta}$-T. Correlation coefficient (r) for fatty acids and tocopherols indicated a strong inverse relationship between oleic & linoleic acids (r=-0.97, P<0.05) and positive relationships between palmitic & linoleic acids (r=0.95, P<0.05) and ${\gamma}$-T & ${\delta}$-T (r=0.83, P<0.05). Principal component analysis (PCA) of fatty acids and tocopherols gave four significant principal components (PCs, with eigenvalues>1), which together account for 85.49% of the total variance in the data set with PC1 and PC2 contributing 45.27% and 21.33% of the total variability, respectively. Eigen analysis of the correlation matrix loadings of the four significant PCs revealed that PC1 was mainly contributed by palmitic, oleic, linoleic, and gondoic acids, while PC2 was by behenic acid, ${\beta}$-T, and ${\gamma}$-T. The score plot generated by PC1-PC2 identified sample clusters in the two spatial planes based on the oleic and linoleic acids. The score plot PC3-PC4 didn't separate sample groups.

• Journal of the Korean Society of Radiology
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• v.13 no.1
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• pp.111-118
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• 2019

Chest digital tomosynthesis has become a practical imaging modality because it can solve the problem of anatomy overlapping in conventional chest radiography. However, because of both limited scan angle and finite-size detector, a portion of chest cannot be represented in some or all of the projection. These bring a discontinuity in intensity across the field of view boundaries in the reconstructed slices, which we refer to as the truncation artifacts. The purpose of this study was to reduce truncation artifacts using a weighted normalization approach and to investigate the performance of this approach for our prototype chest digital tomosynthesis system. The system source-to-image distance was 1100 mm, and the center of rotation of X-ray source was located on 100 mm above the detector surface. After obtaining 41 projection views with ${\pm}20^{\circ}$ degrees, tomosynthesis slices were reconstructed with the filtered back projection algorithm. For quantitative evaluation, peak signal to noise ratio and structure similarity index values were evaluated after reconstructing reference image using simulation, and mean value of specific direction values was evaluated using real data. Simulation results showed that the peak signal to noise ratio and structure similarity index was improved respectively. In the case of the experimental results showed that the effect of artifact in the mean value of specific direction of the reconstructed image was reduced. In conclusion, the weighted normalization method improves the quality of image by reducing truncation artifacts. These results suggested that weighted normalization method could improve the image quality of chest digital tomosynthesis.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.2
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• pp.35-52
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• 2023

Recently, as the non-face-to-face environment has developed due to COVID-19 and environmental pollution, the importance of online digital healthcare is increasing, and venture start-ups and activities such as health care, telemedicine, and digital treatments are also actively underway. This study conducted the impact on the acceptability of digital healthcare smartwatches with an integrated approach of the expanded integrated technology acceptance model (UTAUT2) and the behavioral inference model (BRT). The most advanced integrated technology acceptance model for innovative technology acceptance research was used to identify major factors such as utility expectations, social effects, convenience, price barriers, lack of alternatives, and behavioral intentions. For the study, about 410 responses from ordinary people in their teens to 60s across the country were collected, and based on this, the hypothesis was verified using structural equations after testing reliability and validity of the data. SPSS 23 and AMOS 23 were used for research analysis. Studies have shown that personal innovation has a significant impact on the reasons for acceptance (use value, social impact, convenience of use), attitude, and non-use (price barriers, lack of alternatives, and barriers to use). These results are the same as the results of previous studies that confirmed the influence of the main value of innovative ICT on user acceptance intention. In addition, the reason for acceptance had a significant effect on attitude, but the effect of the reason for non-acceptance was not significant. It can be analyzed that consumers are interested in new ICT products and new services, but purchase them more carefully and selectively. This study has evolved from the acceptance analysis of general-purpose consumer innovation technology to the acceptance analysis of consumer value in smartwatch digital healthcare, which is a new and important area in the future. Industrially, it can contribute to the product's purchase and marketing. It is hoped that this study will contribute to increasing research in the digital healthcare sector, which will play an important role in our lives in the future, and that it will develop into in-depth factors that are more suitable for consumer value through integrated approach models and integrated analysis of consumer acceptance and non-acceptance.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.4
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• pp.101-118
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• 2023

During the COVID-19 pandemic, the utilization rate of neighborhood parks and green spaces increased significantly, and the outbreak served as an opportunity to highlight the values and functions of neighborhood parks and green spaces for urban residents. This study aims to empirically analyze how citizens' movement and the use of neighborhood parks and green spaces changed before and after COVID-19 and examine the social and spatial characteristics that affected these changes. As a research method, first, people's mobility around neighborhood parks and green spaces before and after the COVID-19 pandemic were compared using signal data from telecommunication carriers. Through the analysis of changes in residence time and movement volume, the movement characteristics of citizens after COVID-19 and changes in walking-based park visits were examined. Second, the factors affecting the mobility change in neighborhood parks and green spaces were analyzed. The social and spatial characteristics that affect citizens' visits to neighborhood parks and green spaces before and after COVID-19 were examined through correlation and multiple regression analysis. Subsequently, through cluster analysis, the types of living areas for the post-COVID era were classified from the perspective of the supply and management of neighborhood parks and green spaces services, and directions for improving neighborhood parks and green spaces by type were presented. Major research findings are as follows: First, since the outbreak of COVID-19, activities within 500m of the residence have increased. The amount of stay and walking movement increased in both 2020 and 2021, which means that the need to review the quantitative standards and attractions of neighborhood parks and green spaces has increased considering the changed scope of the walking and living area. Second, the overall number of visits to neighborhood parks and green spaces by walking has increased since the outbreak of COVID-19. The number of visits to neighborhood parks and green spaces centered on the house and the workplace increased significantly. The park green policy in the post-COVID era should be promoted by discovering underprivileged areas, focusing on areas where residential, commercial, and business facilities are concentrated, and improving neighborhood parks and green services in quantitative and qualitative terms. Third, it was found that the higher the level of park green service, the higher the amount of walking movement. It is necessary to use indicators that contribute to improving citizens' actual park green services, such as walking accessibility, rather than looking at the criteria for securing green areas. Fourth, as a result of cluster analysis, five types of neighborhood parks and green spaces were derived in response to the post-COVID era. This suggests that it is necessary to consider the socioeconomic status and characteristics of living areas and the level of park green services required in future park green policies. This study has academic and policy significance in that it has laid the basis for establishing neighborhood parks and green spaces policy in response to the post-COVID era by using various analysis methodologies such as carrier signal data analysis, GIS analysis, and statistical analysis.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.1
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• pp.70-79
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• 2014

Following the technology developments of traffic network and communication for the wide area, the importance of the cooperation system to vitalize the wide area economy is increasing. Therefore, in this study, DongNam Kwon industry information system is established for the industrial information sharing based on GIS in the DongNam Kwon wide area economy. The DongNam Kwon is an industrial integration area centered with the manufacturing so that the operation of effective industrial cluster and cooperation systems are required across the administrational boundaries. To establish the database of the information, the information system was established utilizing already established industrial databases in Busan, Ulsan and Gyeongnam. But, various issues caused by the discordances among the data of each local government and the insufficiency of GIS based location information have been found. According to the analysis, the standardization considering the courses of collection, distributions and utilization are required immediately to solve the issues. This study establishes an 2-way industrial information system enabling the information creation and the phased approach between the administrator and the user in the bi-directions on the web by utilizing cadastral and numerical maps. The result of this study would have a meaning in providing a fundamental frame for cooperative responses and cooperation system for DongNam Kwon's industrial promotion using industrial information sharing.

• Journal of Korea Technology Innovation Society
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• v.17 no.4
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• pp.820-844
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• 2014

Various innovation theories, such as innovation system, innovation cluster, triple helix model, are different in their focus. However they all emphasize the interaction between innovation actors in order to generate, diffuse, and appropriate technological innovations successfully. This study analyzes how the interaction of innovation actors in Daedeok Innopolis has been changed since the introduction of innovation cluster policy like the designation of Daedeok Innopolis. Based on the analysis of survey data, Innopolis statistics, and patent joint-application data, we come to the conclusions that the Daedeok Innopolis has characteristics of multi-level governance structure, in which innovation cluster, i.e. Daedeok Innopolis, regional innovation system, and national innovation system directly overlap under the framework of innovation system. In addition, from the perspectives of triple helix model, we are able to verify that the inter-domain interactions between innovation actors, such as tri-lateral network, have been constantly increased in the Daedeok Innopolis. Based on our analysis, we identify some policy suggestions in order to strengthen the competitiveness of the Daedeok Innopolis as well as other innovation clusters in Korea. First, the network activities between innovation actors within innovation cluster should be strengthened based on the geographical accessibility. Second, private intermediate organizations should be established and their roles should be extended. Third, the entrepreneurial activities of universities within innovation cluster should be strengthened. In other words, the roles of universities within the Innopolis should be activated. Finally, the government should provide relevant policy supports to activate the interactions between innovation actors within innovation cluster.