Purpose Corporate technology leakage is not only monetary loss, but also has a negative impact on the corporate image and further deteriorates sustainable growth. In particular, since SMEs are highly dependent on core technologies compared to large corporations, loss of technology leakage threatens corporate survival. Therefore, it is important for SMEs to "prevent and protect technology leakage". With the recent development of data analysis technology and the opening of public data, it has become possible to discover and proactively detect companies with a high probability of technology leakage based on actual company data. In this study, we try to construct profiles of enterprises with and without technology leakage experience through profiling analysis using data mining techniques. Furthermore, based on this, we propose a classification model that distinguishes companies that are likely to leak technology. Design/methodology/approach This study tries to develop the empirical model for prevention and protection of technology leakage through profiling method which analyzes each SME from the viewpoint of individual. Based on the previous research, we tried to classify many characteristics of SMEs into six categories and to identify the factors influencing the technology leakage of SMEs from the enterprise point of view. Specifically, we divided the 29 SME characteristics into the following six categories: 'firm characteristics', 'organizational characteristics', 'technical characteristics', 'relational characteristics', 'financial characteristics', and 'enterprise core competencies'. Each characteristic was extracted from the questionnaire data of 'Survey of Small and Medium Enterprises Technology' carried out annually by the Government of the Republic of Korea. Since the number of SMEs with experience of technology leakage in questionnaire data was significantly smaller than the other, we made a 1: 1 correspondence with each sample through mixed sampling. We conducted profiling of companies with and without technology leakage experience using decision-tree technique for research data, and derived meaningful variables that can distinguish the two. Then, empirical model for prevention and protection of technology leakage was developed through discriminant analysis and logistic regression analysis. Findings Profiling analysis shows that technology novelty, enterprise technology group, number of intellectual property registrations, product life cycle, technology development infrastructure level(absence of dedicated organization), enterprise core competency(design) and enterprise core competency(process design) help us find SME's technology leakage. We developed the two empirical model for prevention and protection of technology leakage in SMEs using discriminant analysis and logistic regression analysis, and each hit ratio is 65%(discriminant analysis) and 67%(logistic regression analysis).
This study analyzes the effects of the Smart Water City (SWC) project that was introduced from 2014 to 2016 in Paju City, Gyeonggi Province, Korea, focusing on the achievement of the business goals. The SWC is referred to as a city that embraces a healthy water supply system based on Smart Water Management (SWM) that promotes the efficiency of water management by combining Information and Communication Technologies (ICTs) with water and sewerage facilities. In order to evaluate the effectiveness of the SWC project, this study deploys evaluation criteria corresponding to the project objectives, and analyzes the outputs before and after the project. The results show that the SWC has contributed to enhancing water supply services and the reliability and drinking rate of tap water. Specific improvement areas include the rise of average water flow rate and water leakage reduction, the diffusion of water quality monitoring system, and the reduction of floating particle concentration and turbidity in drainage pipes was achieved. These were possible because of specific implementation plans for clear goal setting and achievement and active services for citizens. The data related to water quantity and quality showed improved performance compared to before the introduction of SWMS, which is a positive effect. However, a quantitative analysis of the outputs has limitations in identifying other external factors that have led to the changes. In the future, guidelines for spreading SWC and more comprehensive and specific evaluation indicators for SWC should be prepared, and SWMS should be developed in consideration of the needs of users.
The purpose of this paper is to analyze the efficiency of on-off-line integrated operations of listed retailers, propose ways to identify and improve the problems of inefficient enterprises, and accelerate the integration of on-off-line. The 28 listed retail companies selected total capital, management expenses, number of employees and wage rates as input factors as of 2018 and total operating income and operating profit were selected as output indicators to analyze efficiency using DEA. The results show that the integrated enterprise has a higher overall level of operational efficiency, but it is still in a state of stagnation. The pure technical efficiency of the integrated enterprise is generally higher, and the scale efficiency is the main reason that the overall efficiency of the enterprise is not improved. This study can help retail companies adjust their development strategies of online and offline integration according to their own degree of online and offline integration. This study has limitations in explaining the change in efficiency of retailers by conducting a cross-sectional analysis using data limited to 2018. It is necessary to utilize data over the next several years to conduct a longitudinal analysis.
Journal of the Korea Academia-Industrial cooperation Society
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v.18
no.4
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pp.191-200
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2017
Smart work is an alternative form to enable seamless business collaboration without time and space limitations using ICT. However, smart work implementation has not produced tangible achievements and sometimes has resulted in failure. This study examined users' resistance against smart work, which is regarded as one of the most important elements for the successful implementation of smart work. The study classified elements which cause users' resistance into the work's innovative characteristics and the user characteristics based on the model of innovation resistance. It also set the degree of freedom in spatial and temporal dimension as moderating factors. This empirical research results showed that low work efficiency, unfavorable evaluation methods, and high degree of satisfaction in the way of working affected smart work users' resistance. In addition, temporal freedom had a moderating effect on the relationship between users' characteristics and their resistance. On the contrary, spatial freedom affected the relationship between their works' innovative characteristics and their resistance. The study results suggest that organizations need to set up business processes and evaluation methods first to adopt Smart work successfully.
The purpose of this study is to increase the competitiveness of big data in the maritime port organization, by understanding the expected performance and the intention to accept and use big data. In the empirical analysis of factors affecting the intention to use the big data technology for maritime port organizations, the variables employed are based on the Technology Organization Environment(TOE) and Diffusion of Innovations(DOI) theories, which are related to the acceptance of information and communication technologies. To achieve the objective of this study, an empirical analysis was conducted; this analysis targeted the personnel involved in the department of strategic planning and information technology in the related field. We set up eight hypotheses to examine the relevance between variables having three characteristics-technology, organization, and environmental characteristics. The empirical results are summarized as follows. First, it was seen that the technology characteristic, including relative advantage, complexity, and compatibility, has a significant effect on the expected performance. Second, the top management support of the organization characteristic has a significant effect, but the firm size of this characteristic has no significant effect on the expected performance. Third, the competitive pressure of the environment characteristic has a positive effect on the expected performance, while the regulatory support has no significant effect. Finally, the expected performance has a significant effect on the intention to use big data.
Journal of The Korean Society of Agricultural Engineers
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v.64
no.6
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pp.87-99
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2022
The meat consumption per person has continuously increased in recent years. However, the labor force in the domestic livestock industry has decreased due to the declining and ageing population. In order to increase productivity, the government have developed and distributed design standard of livestock houses. Presently, report showed that the adaptation rate of the developed livestock house design standard on the real farm was still low. Thus, this paper aimed to find ways to improve the utilization of the design standard through surveys. The survey was conducted on 650 farms across the country. Analysis of the result showed that in the poultry house, the unawareness of farmers to the design standard was found to be the biggest reason for not using the design standards. On the other hand, in the swine house, the previously built swine houses do not fit with the design standard. From these result, the following recommendations were suggested: 1) promotion and education are needed to enhance usage of design standard; 2) since it is impossible to make a design standard considering all the farm sites, it is important to consider the conditions of various farm site prior to enhancement of the design standard; 3) improvement factors such as reinforcing the ventilation design, reflecting animal welfare, preventing livestock diseases, and enhancing ICT devices can also be promoted.
Journal of the Korean Society of Fisheries and Ocean Technology
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v.59
no.3
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pp.206-214
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2023
Fish school monitoring technology is utilized for various purposes, such as boat fishing and resource surveys. With advancements in information and communication technology, this technology has expanded its application to remote areas. Its significance has grown in fishing sites, particularly for improving the efficiency and cost-effectiveness of set-net fishing. Set-net fishing gears are not limited to coastal areas, but are also installed in inland and remote sea regions. Consequently, fishermen require technology that allows them to quickly transmit information about approaching fish schools and enables them to perform long-term monitoring. The development of remote monitoring technology for set-net fish schools must consider crucial design factors such as communication range, transmission speed, power consumption of information modules, and operational expenses. In this study, we developed a low-power remote monitoring module for set-net fish school based on WCDMA. The module was specifically designed to minimize power consumption, allowing for communication over long distances and extended operation times in set-net fishing applications. Furthermore, we developed a web server software application that enables remote access to fish schools and provides real-time weather information. The performance of the developed module was evaluated through set-net fishing site application and experiments with moving ships on the sea. The experimental results demonstrated that the remote monitoring system, consisting of the developed low-power remote monitoring module for set-net fish school based on WCDMA and a fish finder, had an average power consumption of 4.6 W, a maximum communication range of 22.84 km, and a data transmission and reception rate of 98.79%. The maximum fish school information transmission and reception rate was 97.26%
Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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v.8
no.10
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pp.63-70
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2018
Biomedical signal measurement technology using images has been developed, and researches on respiration signal measurement technology for maintaining life have been continuously carried out. The existing technology measured respiratory signals through a thermal imaging camera that measures heat emitted from a person's body. In addition, research was conducted to measure respiration rate by analyzing human chest movement in real time. However, the image processing using the infrared thermal image may be difficult to detect the respiratory organ due to the external environmental factors (temperature change, noise, etc.), and thus the accuracy of the measurement of the respiration rate is low.In this study, the images were acquired using visible light and infrared thermal camera to enhance the area of the respiratory tract. Then, based on the two images, features of the respiratory tract region are extracted through processes such as face recognition and image matching. The pattern of the respiratory signal is classified through the k-nearest neighbor classifier, which is one of the statistical classification methods. The respiration rate was calculated according to the characteristics of the classified patterns and the possibility of breathing rate measurement was verified by analyzing the measured respiration rate with the actual respiration rate.
The number of CCTV installed in Korea is over 1.3 million, increasing by more than 15% annually. However, due to the limited budget compared to the installation demand, the infrastructure is composed of 500,000 pixel low-quality CCTV, and there is a limits on identification of objects in the video. Public CCTV has high utility in various fields such as crime prevention, traffic information collection (control), facility management, and fire prevention. Especially, since installed in high height, it works as its role in solving diverse crime and is in increasing trend. However, the current public CCTV field is operated with potential problems such as inability to identify due to environmental factors such as fog, snow, and rain, and the low-quality of collected images due to the installation of low-quality CCTV. Therefore, in this study, in order to remove the typical low-quality elements of public CCTV, the method of attenuating scattered light in the image caused by dust, water droplets, fog, etc and algorithm application method which uses deep-learning algorithm to improve input video into videos over quality over 4K are suggested.
Hyeonjeong Kim;Soohyun Kwon;Jeongu Choi;Beomsoo Kim
Knowledge Management Research
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v.25
no.2
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pp.219-243
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2024
This study investigates the impact of privacy concerns, perceived utility, and awareness of the right to personal data self-determination on the effective use and expansion of MyData services, which are critical to the data economy. Integrating the value-based adoption model with privacy calculus theory, the research examines how perceived utility, privacy concerns, trust, and personal innovativeness influence perceived value, perceived privacy, and the intention to provide personal information. Data collected from an online survey of 442 MyData service users and prospective users were analyzed using PLS-SEM and Bootstrapping methods via SmartPLS 4. The results indicate that perceived utility positively affects the intention to provide personal information, while privacy concerns have a negative impact. Trust and personal innovativeness positively influence the intention to adopt MyData services, and the awareness of personal data self-determination rights moderates these intentions. The findings underscore the importance of developing beneficial services that mitigate users' privacy concerns and build trust for the successful implementation of MyData services. Additionally, the study highlights the need for education and awareness campaigns to enhance understanding of the right to personal data self-determination.
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