Geun-Wan Park;Hyun-Ji Park;Sung-Hoon Mo;Cheol-Hyun Lim;Hee-Seok Choi;Seok-Hyoung Lee;Hye-Jin Lee;Seung-June Hwang;Chang-Hee Han
Information Systems Review
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v.21
no.4
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pp.1-29
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2019
The knowledge resources take a role in promoting the sustainable growth of organization. Therefore, it is important for the members of organization to acquire knowledge consistently so that the company can continue to grow. Knowledge service is the field that provides information and infrastructure which enable the members of organization to acquire new knowledge. As we recognized the importance of knowledge services, we analyzed the level of knowledge service management and development through the impact of knowledge quality on user capabilities. First, the matrix of knowledge patterns was presented based on the type of information and the level of customer interaction. According to patterns, the knowledge service was classified into three types of information providing, information analysis, and infrastructure, and then the results of structural model analysis were presented for each type. It found that the impact of knowledge service quality on user competence was different according to the type of service. The results suggested new indicators for measuring the performance of knowledge services, and provided information for reconstructing services based on the user considering the integrated operation of knowledge service and organizational designing knowledge service.
The Electronic Shelf Label (ESL) is an alternative to the paper price label attached to merchandise shelves and is attracting attention as a retail IoT infrastructure that will lead the innovation of offline retail outlets. In general, when introducing a substitute product, the company tends to consider the financial factors such as the efficiency of the investment cost compared to the existing product or the reduction of the operating cost. However, considering only financial factors in the decision-making process, it may not properly reflect the various values associated with corporate strategy and the requirements of stakeholders. In this study, 8 evaluation items (Investment Cost, Operating Cost, Quality Level, Customer Management, Job Efficiency, Maintenance, Functional Expandability, and Store Image) based on BSC's 4 perspectives (Financial, Customer, Internal Business Process, Learning & Growth), and using AHP (Analytic Hierarchy Process) to measure the priorities of evaluation items for domestic small supermarket employees. As a result of the research, priority was given in order of Customer, Learning & Growth, Internal Business Process, and Financial aspects among the evaluation items for adopting the price label, and the electronic price label was supported with higher importance than the paper price label. In contrast to the priorities of the financial aspects of most prior studies, the items of Learning & growth and customer perspectives have relatively high priorities. In particular, respondents classified by job group, The priorities of the 8 evaluation items were different among the groups. These results are expected to provide implications for both companies (retail outlets) and ESL providers (manufacturers and service providers) who are considering the introduction of ESL.
It is an important task to give adequate nutritions to infants and to wean properly for rapid growth. This study was conducted to survey on doing the weaning activities of the first-time mother. This study was to provide basic data of health teaching and nursing intervention for the promotion of ideal weaning activities. Survey was done from January to February in 2001. Total 444 mothers who have first-time baby under twelve month old were interviewed in five community health center around contry (Seoul, Choung-ju, Asan, Cheon-an, Jeju). The results are summarized as follows; Starting time of weaning was common in four month old(40.4%). Most common daily weaning times by age showed once(under 3 months), twice(4 to 7 months), three times(8 to 12 months). The younger, the more commercial weaning products(p<0.01). Education level showed relatively positive relation with home-made weaning food(p<0.05). Items showed low scores in 4 to 7 months group were starting new food item, waiting at least one week interval to new food, feeding by milk bottle, allowing grasping spoon, consulting pediatrician for problems after weaning, starting from morning, regular schedule. Items showed low scores in 8 to 12 months group were feeding whole egg rather than yolk only up to 12 months, keeping weaning interval were increased, feeding by milk bottle, trying various cooking method, not giving commerical cooking and instant food and unproper raw milk feeding. In weaning activities by general factors, mother age, health status, marriage duration, monthly income were statistically significant (p<0.05). To improve good weening activities, targetting on low maternal age and poor health status, and low income group, developing teaching materials and training program for items showed low scores and proper weaning time, type of easy home-made food and easy cooking method should be provided. Further study on effect of nursing intervention to improve weaning activities are needed.
Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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2016.10a
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pp.485-488
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2016
The level of domestic greenhouse complex environmental control technology is a hardware-oriented automation steps that mechanically control the environments of greenhouse, such as temperature, humidity and $CO_2$ through the technology of cultivation and consulting experts. This automation brings simple effects such as labor saving. However, in order to substantially improve the output and quality of agricultural products, it is essential to track the growth and physiological condition of the plant and accordingly control the environments of greenhouse through a software-based complex environmental control technology for controlling the optimum environment in real time. Therefore, this paper is a part of general methods on the greenhouse complex environmental control technology. and presents a horticulture production forecasting methods using artificial neural networks through the analysis of big data systems of smart farm performed in our country and artificial neural network technology trends.
We investigated the work-life balance of clinical professors in charge of patient care, research, and education at medical schools and the demand for work-life balance support according to position (professor, associate professor, or assistant professor). In total, 163 clinical professors completed the consent form and participated in the study. They filled out an online survey consisting of questions about essential characteristics, a work-life balance test, stress, burnout, work-life satisfaction, and work-life balance support needs. We analyzed the results by analysis of variance and cross-tabulation using IBM SPSS ver. 23.0. Differences were found in work-life balance, stress, burnout, and satisfaction with life and work by position. The requirements for support for work-life balance also varied by professional status. Professors had a higher balance between life and work than associate professors or assistant professors. The specific requirements for work-life balance support were also slightly different for each position. Overall, there was a high demand for work process simplification and efficiency for work support, flexible working hours and sabbatical years for family and leisure, and career management consulting and training support for growth. Assistant professors and associate professors had a lower level of work-life balance than professors, as well as higher levels of stress and burnout. Professors' job satisfaction was also higher than that of the other groups. Based on the results of this study, we hope that a healthy work environment can be established through work-life balance support suitable for clinical professors' positions.
Journal of the Korea Academia-Industrial cooperation Society
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v.19
no.10
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pp.183-193
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2018
The purpose of this study was to assess the implications for Daejeon's business management by analyzing the impact on the management performance of human solidarity among CEOs of small and medium venture companies in Daejeon. From 20th March to 20th May 2018, 212 questionnaires were collected from CEOs of small and medium-sized venture companies in Daejeon for this study and verified using the SPSS statistics Analysis Program. As a result, the study confirmed that the "work" and "school" connection factors have positive effects on securing government projects, improving business management, acquiring the necessary information for business growth, and securing competitiveness in 4th industrial revolution era. On the other hand, the "Region or Kin-group" connection factor does not affect the management performance. The following implications were derived fromthese studies on sustainable growth and development of business in Daejeon. First, it requires a higher level of the CEO solidarity. Second, efforts aimed at building mutual trust among CEOs in Daejeon are needed to develop close relationships and strong connections. Third, each operating association established in Daejeon needs to develop various programs for building relationships among CEOs and operate programs to increase the chances of contact.
This study is based on workplace learning, which has revealed its significant influence in the previous enterprise case studies. Why do small business owners have the opportunity to participate in workplace learning based on authenticity? It was intended to clarify whether it was necessary and to increase the growth and development potential of small business owners based on its contents. Moreover, this study is focused on identifying the influence of workplace learning on management performance through this series of processes. In order to investigate the influence of small enterprise workplace learning on management performance, research hypotheses were set based on a review of previous studies, and empirical analysis was carried out. A total of 203 questionnaires were empirically analyzed using SPSS 18.0 program. As a result, first, workplace learning had partially significant positive influence on job satisfaction. Second, workplace learning had significant positive influence on management performance. Third, job satisfaction had significant positive influence on management performance. Fourth, job satisfaction had partial mediating effect in the relationship between workplace learning and management performance. The analysis result showed that among sub-factors of workplace learning, only formal learning did not affect job satisfaction and that job satisfaction did not have mediating effect in the relationship between formal learning and management performance. According to analysis, this was because in poor small enterprise environments, opportunities to participate in formal learning like external training or in-house training were not kept. In other words, poor small enterprise environments were plainly revealed from the managerial, economic and social standpoint. Therefore, there is a need to establish the foundation of growth for them to solve problems and develop win-win development capabilities and an institutional system that can make a contribution to policy and education, and management, by helping small enterprises keep opportunities to participate in workplace learning. In spite of these significant study results, there can be a limitation. For improving this limitation, further research will need to target diverse fields focusing on samples, which can explain relations of many different variables. Also, working-level relation research connected to studies that can highly enhance management performance will be required.
Do, Van Quang;Nguyen, Xuan Ba;Doyle, Peter T.;Dau, Van Hai;Lane, Peter A.;Malau-Aduli, Aduli EO;Nguyen, Huu Van;Parsons, David
Journal of Animal Science and Technology
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v.57
no.9
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pp.35.1-35.8
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2015
Background: An experiment was conducted in Vietnam to test the hypothesis that total dry matter (DM) intake and liveweight (LW) gain would increase in a curvilinear manner with increasing amounts of concentrate offered. Method: There were five treatments: a basal diet of Guinea grass fed at 1 % of LW and rice straw fed ad libitum (T0), or this diet supplemented with concentrate at 0.6 (T1), 1.2 (T2), 1.8 (T3), or 2.4 % of LW (T4). The concentrate comprised locally available ingredients, namely cassava chips, rice bran, crushed rice grain, fishmeal, salt, and urea, mixed manually. Results: Concentrate intake increased from T0 to T3, but there was no difference in concentrate intake between T3 and T4. Total feed intake increased in a curvilinear manner from 4.0 to 6.4 kg DM/d as the quantity of concentrate consumed increased. The substitution of concentrate for grass and rice straw increased with increasing consumption of concentrate and was as high as 0.49 kg DM reduction per kg of concentrate consumed. LW gain increased curvilinearly, with significant differences between T0 (0.092 kg/d), T1 (0.58 kg/d) and T2 (0.79 kg/d); but there were no significant differences in LW gain between T2, T3 (0.83 kg/d) and T4 (0.94 kg/d).With increasing amount of concentrate in the diet, the digestibilities of dry matter, organic matter, crude protein, and crude fat increased, but NDF digestibility decreased. Conclusion: Based on these results, young Vietnamese Brahman-cross growing cattle will respond to a locally-sourced concentrate mix offered at a level of up to 1.2 % of LW.
Asia-Pacific Journal of Business Venturing and Entrepreneurship
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v.13
no.4
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pp.117-128
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2018
Various government support policies are being promoted in order to stimulate growth of SMEs. The government is striving to provide effective support through direct methods of tax, finance and indirect methods through support programs. However, the view on the government's startup policy is still tense. We are sympathetic with the need for support, but discussions continue to be made on the effectiveness of support projects and support projects. Therefore, this study evaluates the importance and satisfaction of the government start-up support project. For this purpose, we conducted questionnaires on ICT start-ups who have experienced government start-up support projects. Of these, 128 were analyzed for GAP analysis and ISA. As a result of the GAP analysis of the government start - up support project, the degree of satisfaction (4.408) was lower than the degree of importance (5.221), confirming that the beneficiary's evaluation on the start-up support project was negative. As a result of the importance-satisfaction analysis, 'R&D' and 'commercialization' are located in the maintenance area, and 'government funding', 'marketing, overseas advancement' projects are included in the concentrated area. In the low-ranking areas, there are 'entrepreneur events and networks' items. Finally, there are 'facilities and spaces', 'mentoring and consulting', and 'entrepreneurship education' in the surplus areas. As a result of multiple regression analysis, it was found that 'R&D', 'entrepreneurial education', and 'government funding' influenced satisfaction. Based on the results of this study, it is expected that it will contribute to improving the quality level of the government start-up support project by establishing the support policy for the ICT start-up enterprises and improving the system.
With the rapid development of artificial intelligence technology, various techniques have been developed to extract meaningful information from unstructured text data which constitutes a large portion of big data. Over the past decades, text mining technologies have been utilized in various industries for practical applications. In the field of business intelligence, it has been employed to discover new market and/or technology opportunities and support rational decision making of business participants. The market information such as market size, market growth rate, and market share is essential for setting companies' business strategies. There has been a continuous demand in various fields for specific product level-market information. However, the information has been generally provided at industry level or broad categories based on classification standards, making it difficult to obtain specific and proper information. In this regard, we propose a new methodology that can estimate the market sizes of product groups at more detailed levels than that of previously offered. We applied Word2Vec algorithm, a neural network based semantic word embedding model, to enable automatic market size estimation from individual companies' product information in a bottom-up manner. The overall process is as follows: First, the data related to product information is collected, refined, and restructured into suitable form for applying Word2Vec model. Next, the preprocessed data is embedded into vector space by Word2Vec and then the product groups are derived by extracting similar products names based on cosine similarity calculation. Finally, the sales data on the extracted products is summated to estimate the market size of the product groups. As an experimental data, text data of product names from Statistics Korea's microdata (345,103 cases) were mapped in multidimensional vector space by Word2Vec training. We performed parameters optimization for training and then applied vector dimension of 300 and window size of 15 as optimized parameters for further experiments. We employed index words of Korean Standard Industry Classification (KSIC) as a product name dataset to more efficiently cluster product groups. The product names which are similar to KSIC indexes were extracted based on cosine similarity. The market size of extracted products as one product category was calculated from individual companies' sales data. The market sizes of 11,654 specific product lines were automatically estimated by the proposed model. For the performance verification, the results were compared with actual market size of some items. The Pearson's correlation coefficient was 0.513. Our approach has several advantages differing from the previous studies. First, text mining and machine learning techniques were applied for the first time on market size estimation, overcoming the limitations of traditional sampling based- or multiple assumption required-methods. In addition, the level of market category can be easily and efficiently adjusted according to the purpose of information use by changing cosine similarity threshold. Furthermore, it has a high potential of practical applications since it can resolve unmet needs for detailed market size information in public and private sectors. Specifically, it can be utilized in technology evaluation and technology commercialization support program conducted by governmental institutions, as well as business strategies consulting and market analysis report publishing by private firms. The limitation of our study is that the presented model needs to be improved in terms of accuracy and reliability. The semantic-based word embedding module can be advanced by giving a proper order in the preprocessed dataset or by combining another algorithm such as Jaccard similarity with Word2Vec. Also, the methods of product group clustering can be changed to other types of unsupervised machine learning algorithm. Our group is currently working on subsequent studies and we expect that it can further improve the performance of the conceptually proposed basic model in this study.
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