• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.1
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• pp.85-106
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• 2023

This study reviewed and derived the success factors of overseas agricultural startups and studied their integrated research model. Agricultural startups and general startups have in common that poor resources and infrastructure exist from a resource-based perspective after startup, but a differentiated approach from general startups is required due to the nature of the primary industry of agriculture. In this study, we approach the company internal factors (human resources/vision/distribution network capacity/capital capacity/cultivated crops/physical resources/farming technology, etc.) and external factors (agricultural infrastructure/laws/regulations/relationship with surrounding society, etc.) We tried to build a research model that can be integrated by focusing on various existing research models, success factors, and entrepreneurship. Through this, it is intended to present an integrated model that is practically helpful to business performance to entrepreneurs, business-related persons, and researchers who need an integrated understanding of agricultural startups at home and abroad. made for purpose In this paper, a standard model was established through three types (existing agricultural startup, small and medium-sized business startup, multinational company, and comprehensive approach) according to size and characteristics for modeling agricultural startup success factors. Through this, a total of 9 success factors (agricultural management, external environment, manager/founder characteristics, corporate identity, business management, organizational culture, infrastructure, commercialization capability, and sustainable growth) were derived. The implication of this study is that the success factors of agricultural startups were comprehensively presented based on 'entrepreneurship' for various domestic and foreign agricultural startup cases. By confirming the systematic categorization, a standard model for future agricultural startup success factors was presented, and as a result, a foundation was presented for systematic research and practical effectiveness of related research in the future.

• Journal of Wetlands Research
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• v.26 no.1
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• pp.41-50
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• 2024

Plant Microbial Fuel Cells (P-MFCs) are biomass-based energy technologies that generate electricity from plant and root microbial communities and are suitable for natural fundamental solutions considering sustainable environments. In order to develop P-MFC technology suitable for domestic waterfront space, it is necessary to analyze international research trends first. Therefore, in this study, 700 P-MFC-related research papers were investigated in Web of Science, and the core keywords were derived using VOSviewer, a word analysis program, and the research trends were analyzed. First, P-MFC-related research has been on the rise since 1998, especially since the mid to late 2010s. The number of papers submitted by each country was "China," "U.S." and "India." Since the 2010s, interest in P-MFCs has increased, and the number of publications in the Philippines, Ukraine, and Mexico, which have abundant waterfront space and wetland environments, is increasing. Secondly, from the perspective of research trends in different periods, 1998-2015 mainly carried out microbial fuel cell performance verification research in different environments. The 2016-2020 period focuses on the specific conditions of microbial fuel cell use, the structure of P-MFC and how it develops. From 2021 to 2023, specific research on constraints and efficiency improvement in the development of P-MFC was carried out. The P-MFC-related international research trends identified through this study can be used as useful data for developing technologies suitable for domestic waterfront space in the future. In addition to this study, further research is needed on research trends and levels in subsectors, and in order to develop and revitalize P-MFC technologies in Korea, research on field applicability should be expanded and policies and systems improved.

• Therapeutic Science for Rehabilitation
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• v.13 no.1
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• pp.9-21
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• 2024

Objective : The purpose of this study was to confirm the characteristics and quality of a single-subject research that conducted interventions to improve activities of daily living (ADL) in stroke patients. Methods : 'Stroke,' 'activities of daily living,' and 'single-subject studies' were searched as keywords among papers published in the last 15 years between 2009 and 2023 among Research Information Sharing Service, DBpia, and e-articles. A total of nine papers were examined for the characteristics and quality before analysis. Results : The independent variables applied to improve ADL included constraint-induced therapy, mental practice for performing functional activities, virtual reality-based task training, subjective postural vertical training without visual feedback, bilateral upper limb movement, core stability training program, traditional occupational therapy and neurocognitive rehabilitation, smooth pursuit eye movement, neck muscle vibration, and occupation-based community rehabilitation. Assessment of Motor and Process Skills was the most common evaluation tool for measuring dependent variables, with four articles, and Modified Barthel Index and Canadian Occupational Performance Measure were two articles each. As a result of confirming the qualitative level of the analyzed papers, out of a total of nine studies, seven studies were at a high level, two at a moderate level, and none were at a low level. Conclusion : Various types of rehabilitation treatments have been actively applied as intervention methods to improve the daily life activities of stroke patients; the quality level of single-subject studies applying ADL interventions was reliable.

• Food Science and Preservation
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• v.30 no.1
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• pp.109-121
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• 2023

This study was conducted to evaluate vitamin D intake of Koreans in a total diet study (TDS) and to determine the effect of irradiation on vitamin D synthesis in mushrooms. For analysis, sample were saponified and extracted with hexane, and vitamin D was quantified by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Based on the validation results, the recovery of the National Institute of Standards and Technology (NIST) standard reference sample (SRM) 1849a was 96.7% and the z-score of -1.6 was obtained by the Food Analysis Performance Assessment Scheme (FAPAS) proficiency test (PT) 21115. Vitamin D₂ was not detected in any samples, and the highest level of vitamin D₃ was detected in mackerel and anchovies ranging from 24.2 to 120.2 ㎍/kg. The mean daily intake of vitamin D was 0.99 ㎍/day, as estimated from the vitamin D contents of the analyzed foods and their corresponding intake. The adequate intake (AI) of vitamin D based on the Dietary reference intakes for Koreans provided by the Ministry of Health and Welfare is 5-15 ㎍/day for Koreans aged 6 to 75 years. Compared with this AI, vitamin D intake of Koreans estimated in this study was inadequate. For that, the increased vitamin D content in ultraviolet (UV)/sun light irradiated mushrooms warrants further research to increase vitamin D intake of Koreans through diet.

• 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.

• Journal of Korea Water Resources Association
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• v.57 no.3
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• pp.181-193
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• 2024

The increasing atmospheric imbalance caused by climate change leads to an elevation in precipitation, resulting in a heightened frequency of flooding. Consequently, there is a growing need for technology to detect and monitor these occurrences, especially as the frequency of flooding events rises. To minimize flood damage, continuous monitoring is essential, and flood areas can be detected by the Synthetic Aperture Radar (SAR) imagery, which is not affected by climate conditions. The observed data undergoes a preprocessing step, utilizing a median filter to reduce noise. Classification techniques were employed to classify water bodies and non-water bodies, with the aim of evaluating the effectiveness of each method in flood detection. In this study, the Otsu method and Support Vector Machine (SVM) technique were utilized for the classification of water bodies and non-water bodies. The overall performance of the models was assessed using a Confusion Matrix. The suitability of flood detection was evaluated by comparing the Otsu method, an optimal threshold-based classifier, with SVM, a machine learning technique that minimizes misclassifications through training. The Otsu method demonstrated suitability in delineating boundaries between water and non-water bodies but exhibited a higher rate of misclassifications due to the influence of mixed substances. Conversely, the use of SVM resulted in a lower false positive rate and proved less sensitive to mixed substances. Consequently, SVM exhibited higher accuracy under conditions excluding flooding. While the Otsu method showed slightly higher accuracy in flood conditions compared to SVM, the difference in accuracy was less than 5% (Otsu: 0.93, SVM: 0.90). However, in pre-flooding and post-flooding conditions, the accuracy difference was more than 15%, indicating that SVM is more suitable for water body and flood detection (Otsu: 0.77, SVM: 0.92). Based on the findings of this study, it is anticipated that more accurate detection of water bodies and floods could contribute to minimizing flood-related damages and losses.

• Journal of the Korean Society of Radiology
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• v.84 no.5
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• pp.1094-1109
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• 2023

Purpose To investigate whether CT-based tumor regression grade (ctTRG) can be used to predict the response to neoadjuvant chemotherapy (NAC) in colon cancer. Materials and Methods A total of 53 patients were enrolled. Two radiologists independently assessed the ctTRG using the length, thickness, layer pattern, and luminal and extraluminal appearance of the tumor. Changes in tumor volume were also analyzed using the 3D Slicer software. We evaluated the association between pathologic TRG (pTRG) and ctTRG. Patients with Rödel's TRG of 2, 3, or 4 were classified as responders. In terms of predicting responder and pathologic complete remission (pCR), receiver operating characteristic was compared between ctTRG and tumor volume change. Results There was a moderate correlation between ctTRG and pTRG (ρ = -0.540, p < 0.001), and the interobserver agreement was substantial (weighted κ = 0.672). In the prediction of responder, there was no significant difference between ctTRG and volumetry (Az = 0.749, criterion: ctTRG ≤ 3 for ctTRG, Az = 0.794, criterion: ≤ -27.1% for volume, p = 0.53). Moreover, there was no significant difference between the two methods in predicting pCR (p = 0.447). Conclusion ctTRG might predict the response to NAC in colon cancer. The diagnostic performance of ctTRG was comparable to that of CT volumetry.

• Journal of Distribution Research
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• v.17 no.2
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• pp.29-62
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• 2012

As distribution environment is changing rapidly and competition is more intensive in the channel of distribution, the importance of retailer image and retailer equity is increasing as a different competitive advantages. Also, consumers are not functionally oriented and that their behavior is significantly affected by the symbols such as retailer image which identify retailer in the market place. That is, consumers do not choose products or retailers for their material utilities but consume the symbolic meaning of those products or retailers as expressed in their self images. The concept of self-image congruence has been utilized by marketers and researchers as an aid in better understanding how consumers identify themselves with the brands they buy and the retailer they patronize. Although self-image congruity theory has been tested across many product categories, the theory has not been tested extensively in the retailing. Therefore, this study attempts to investigate the impact of self image congruence between retailer image and self image of consumer on retailer equity such as retailer awareness, retailer association, perceived retailer quality, and retailer loyalty. The purpose of this study is to find out whether retailer-self image congruence can be a new antecedent of retailer equity. In addition, this study tries to examine how four-dimensional retailer equity constructs (retailer awareness, retailer association, perceived retailer quality, and retailer loyalty) affect customers' repatronage intention. For this study, data were gathered by survey and analyzed by structural equation modeling. The sample size in the present study was 254. The reliability of the all seven dimensions was estimated with Cronbach's alpha, composite reliability values and average variance extracted values. We determined whether the measurement model supports the convergent validity and discriminant validity by Exploratory factor analysis and Confirmatory Factor Analysis. For each pair of constructs, the square root of the average variance extracted values exceeded their correlations, thus supporting the discriminant validity of the constructs. Hypotheses were tested using the AMOS 18.0. As expected, the image congruence hypotheses were supported. The greater the degree of congruence between retailer image and self-image, the more favorable were consumers' retailer evaluations. The all two retailer-self image congruence (actual self-image congruence and ideal self-image congruence) affected customer based retailer equity. This result means that retailer-self image congruence is important cue for customers to estimate retailer equity. In other words, consumers are often more likely to prefer products and retail stores that have images similar to their own self-image. Especially, it appeared that effect for the ideal self-image congruence was consistently larger than the actual self-image congruence on the retailer equity. The results mean that consumers prefer or search for stores that have images compatible with consumer's perception of ideal-self. In addition, this study revealed that customers' estimations toward customer based retailer equity affected the repatronage intention. The results showed that all four dimensions (retailer awareness, retailer association, perceived retailer quality, and retailer loyalty) had positive effect on the repatronage intention. That is, management and investment to improve image congruence between retailer and consumers' self make customers' positive evaluation of retailer equity, and then the positive customer based retailer equity can enhance the repatonage intention. And to conclude, retailer's image management is an important part of successful retailer performance management, and the retailer-self image congruence is an important antecedent of retailer equity. Therefore, it is more important to develop and improve retailer's image similar to consumers' image. Given the pressure to provide increased image congruence, it is not surprising that retailers have made significant investments in enhancing the fit between retailer image and self image of consumer. The enhancing such self-image congruence may allow marketers to target customers who may be influenced by image appeals in advertising.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.117-127
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• 2012

Due to the recent expansion of the Web 2.0 -based services, along with the widespread of smartphones, online social network services are being popularized among users. Online social network services are the online community services which enable users to communicate each other, share information and expand human relationships. In the social network services, each relation between users is represented by a graph consisting of nodes and links. As the users of online social network services are increasing rapidly, the SNS are actively utilized in enterprise marketing, analysis of social phenomenon and so on. Social Network Analysis (SNA) is the systematic way to analyze social relationships among the members of the social network using the network theory. In general social network theory consists of nodes and arcs, and it is often depicted in a social network diagram. In a social network diagram, nodes represent individual actors within the network and arcs represent relationships between the nodes. With SNA, we can measure relationships among the people such as degree of intimacy, intensity of connection and classification of the groups. Ever since Social Networking Services (SNS) have drawn increasing attention from millions of users, numerous researches have made to analyze their user relationships and messages. There are typical representative SNA methods: degree centrality, betweenness centrality and closeness centrality. In the degree of centrality analysis, the shortest path between nodes is not considered. However, it is used as a crucial factor in betweenness centrality, closeness centrality and other SNA methods. In previous researches in SNA, the computation time was not too expensive since the size of social network was small. Unfortunately, most SNA methods require significant time to process relevant data, and it makes difficult to apply the ever increasing SNS data in social network studies. For instance, if the number of nodes in online social network is n, the maximum number of link in social network is n(n-1)/2. It means that it is too expensive to analyze the social network, for example, if the number of nodes is 10,000 the number of links is 49,995,000. Therefore, we propose a heuristic-based method for finding the shortest path among users in the SNS user graph. Through the shortest path finding method, we will show how efficient our proposed approach may be by conducting betweenness centrality analysis and closeness centrality analysis, both of which are widely used in social network studies. Moreover, we devised an enhanced method with addition of best-first-search method and preprocessing step for the reduction of computation time and rapid search of the shortest paths in a huge size of online social network. Best-first-search method finds the shortest path heuristically, which generalizes human experiences. As large number of links is shared by only a few nodes in online social networks, most nods have relatively few connections. As a result, a node with multiple connections functions as a hub node. When searching for a particular node, looking for users with numerous links instead of searching all users indiscriminately has a better chance of finding the desired node more quickly. In this paper, we employ the degree of user node vn as heuristic evaluation function in a graph G = (N, E), where N is a set of vertices, and E is a set of links between two different nodes. As the heuristic evaluation function is used, the worst case could happen when the target node is situated in the bottom of skewed tree. In order to remove such a target node, the preprocessing step is conducted. Next, we find the shortest path between two nodes in social network efficiently and then analyze the social network. For the verification of the proposed method, we crawled 160,000 people from online and then constructed social network. Then we compared with previous methods, which are best-first-search and breath-first-search, in time for searching and analyzing. The suggested method takes 240 seconds to search nodes where breath-first-search based method takes 1,781 seconds (7.4 times faster). Moreover, for social network analysis, the suggested method is 6.8 times and 1.8 times faster than betweenness centrality analysis and closeness centrality analysis, respectively. The proposed method in this paper shows the possibility to analyze a large size of social network with the better performance in time. As a result, our method would improve the efficiency of social network analysis, making it particularly useful in studying social trends or phenomena.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.169-196
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• 2017

The fourth industrial revolution represents a revolutionary change in the business environment and its ecosystem, which is a fusion of Information Technology (IT) and other industries. In line with these recent changes, the Ministry of Employment and Labor of South Korea announced 'the Fourth Industrial Revolution Leader Training Program,' which includes five key support areas such as (1) smart manufacturing, (2) Internet of Things (IoT), (3) big data including Artificial Intelligence (AI), (4) information security, and (5) bio innovation. Based on this program, we can get a glimpse of the South Korean government's efforts and willingness to emit leading human resource with advanced IT knowledge in various fusion technology-related and newly emerging industries. On the other hand, in order to nurture excellent IT manpower in preparation for the fourth industrial revolution, the role of educational institutions capable of providing high quality IT education services is most of importance. However, these days, most IT educational institutions have had difficulties in providing customized IT education services that meet the needs of consumers (i.e., learners), without breaking away from the traditional framework of providing supplier-oriented education services. From previous studies, it has been found that the provision of customized education services centered on learners leads to high satisfaction of learners, and that higher satisfaction increases not only task performance and the possibility of business application but also learners' recommendation intention. However, since research has not yet been conducted in a comprehensive way that consider both antecedent and consequent factors of the learner's satisfaction, more empirical research on this is highly desirable. With the advent of the fourth industrial revolution, a rising interest in various convergence technologies utilizing information technology (IT) has brought with the growing realization of the important role played by IT-related education services. However, research on the role of IT education service quality in the context of IT education is relatively scarce in spite of the fact that research on general education service quality and satisfaction has been actively conducted in various contexts. In this study, therefore, the five dimensions of IT education service quality (i.e., tangibles, reliability, responsiveness, assurance, and empathy) are derived from the context of IT education, based on the SERVPERF model and related previous studies. In addition, the effects of these detailed IT education service quality factors on learners' educational satisfaction and their work application/recommendation intentions are examined. Furthermore, the moderating roles of learner position (i.e., practitioner group vs. manager group) and participation motivation (i.e., voluntary participation vs. involuntary participation) in relationships between IT education service quality factors and learners' educational satisfaction, work application intention, and recommendation intention are also investigated. In an analysis using the structural equation model (SEM) technique based on a questionnaire given to 203 participants of IT education programs in an 'M' IT educational institution in Seoul, South Korea, tangibles, reliability, and assurance were found to have a significant effect on educational satisfaction. This educational satisfaction was found to have a significant effect on both work application intention and recommendation intention. Moreover, it was discovered that learner position and participation motivation have a partial moderating impact on the relationship between IT education service quality factors and educational satisfaction. This study holds academic implications in that it is one of the first studies to apply the SERVPERF model (rather than the SERVQUAL model, which has been widely adopted by prior studies) is to demonstrate the influence of IT education service quality on learners' educational satisfaction, work application intention, and recommendation intention in an IT education environment. The results of this study are expected to provide practical guidance for IT education service providers who wish to enhance learners' educational satisfaction and service management efficiency.