• Title/Summary/Keyword: Technology Diffusion

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Extraction of Landmarks Using Building Attribute Data for Pedestrian Navigation Service (보행자 내비게이션 서비스를 위한 건물 속성정보를 이용한 랜드마크 추출)

  • Kim, Jinhyeong;Kim, Jiyoung
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.37 no.1
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    • pp.203-215
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    • 2017
  • Recently, interest in Pedestrian Navigation Service (PNS) is being increased due to the diffusion of smart phone and the improvement of location determination technology and it is efficient to use landmarks in route guidance for pedestrians due to the characteristics of pedestrians' movement and success rate of path finding. Accordingly, researches on extracting landmarks have been progressed. However, preceding researches have a limit that they only considered the difference between buildings and did not consider visual attention of maps in display of PNS. This study improves this problem by defining building attributes as local variable and global variable. Local variables reflect the saliency of buildings by representing the difference between buildings and global variables reflects the visual attention by representing the inherent characteristics of buildings. Also, this study considers the connectivity of network and solves the overlapping problem of landmark candidate groups by network voronoi diagram. To extract landmarks, we defined building attribute data based on preceding researches. Next, we selected a choice point for pedestrians in pedestrian network data, and determined landmark candidate groups at each choice point. Building attribute data were calculated in the extracted landmark candidate groups and finally landmarks were extracted by principal component analysis. We applied the proposed method to a part of Gwanak-gu, Seoul and this study evaluated the extracted landmarks by making a comparison with labels and landmarks used by portal sites such as the NAVER and the DAUM. In conclusion, 132 landmarks (60.3%) among 219 landmarks of the NAVER and the DAUM were extracted by the proposed method and we confirmed that 228 landmarks which there are not labels or landmarks in the NAVER and the DAUM were helpful to determine a change of direction in path finding of local level.

Debris flow characteristics and sabo dam function in urban steep slopes (도심지 급경사지에서 토석류 범람 특성 및 사방댐 기능)

  • Kim, Yeonjoong;Kim, Taewoo;Kim, Dongkyum;Yoon, Jongsung
    • Journal of Korea Water Resources Association
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    • v.53 no.8
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    • pp.627-636
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    • 2020
  • Debris flow disasters primarily occur in mountainous terrains far from cities. As such, they have been underestimated to cause relatively less damage compared with other natural disasters. However, owing to urbanization, several residential areas and major facilities have been built in mountainous regions, and the frequency of debris flow disasters is steadily increasing owing to the increase in rainfall with environmental and climate changes. Thus, the risk of debris flow is on the rise. However, only a few studies have explored the characteristics of flooding and reduction measures for debris flow in areas designated as steep slopes. In this regard, it is necessary to conduct research on securing independent disaster prevention technology, suitable for the environment in South Korea and reflective of the topographical characteristics thereof, and update and improve disaster prevention information. Accordingly, this study aimed to calculate the amount of debris flow, depending on disaster prevention performance targets for regions designated as steep slopes in South Korea, and develop an independent model to not only evaluate the impact of debris flow but also identify debris barriers that are optimal for mitigating damage. To validate the reliability of the two-dimensional debris flow model developed for the evaluation of debris barriers, the model's performance was compared with that of the hydraulic model. Furthermore, a 2-D debris model was constructed in consideration of the regional characteristics around the steep slopes to analyze the flow characteristics of the debris that directly reaches the damaged area. The flow characteristics of the debris delivered downstream were further analyzed, depending on the specifications (height) and installation locations of the debris barriers employed to reduce the damage. The experimental results showed that the reliability of the developed model is satisfactory; further, this study confirmed significant performance degradation of debris barriers in areas where the barriers were installed at a slope of 20° or more, which is the slope at which debris flows occur.

Process Governance Meta Model and Framework (프로세스 거버넌스 메타모델과 프레임워크)

  • Lee, JungGyu;Jeong, Seung Ryul
    • Journal of Internet Computing and Services
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    • v.20 no.4
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    • pp.63-72
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    • 2019
  • As a sub-concept of corporate or organization governance, business governance and IT governance have become major research topics in academia. However, despite the importance of process as a construct for mediating the domain between business and information technology, research on process governance is relatively inadequate. Process Governance focuses on activities that link business strategy with IT system implementation and explains the creation of corporate core values. The researcher studied the basic conceptual governance models of political science, sociology, public administration, and classified governance styles into six categories. The researcher focused on the series of metamodels. For examples, the traditional Strategy Alignment Model(SAM) by Henderson and Venkatraman which is replaced by the neo-SAM model, organizational governance network model, sequential organization governance model, organization governance meta model, process governance CUBE model, COSO and process governance CUBE comparison model, and finally Process Governance Framework and etc. The Major difference between SAM and neo-SAM model is Process Governance domain inserted between Business Governance and IT Governance. Among several metamodels, Process Governance framework, the core conceptual model consists of four activity dimensions: strategic aligning, human empowering, competency enhancing, and autonomous organizing. The researcher designed five variables for each activity dimensions, totally twenty variables. Besides four activity dimensions, there are six driving forces for Process Governance cycle: De-normalizing power, micro-power, vitalizing power, self-organizing power, normalizing power and sense-making. With four activity dimensions and six driving powers, an organization can maintain the flexibility of process governance cycle to cope with internal and external environmental changes. This study aims to propose the Process Governance competency model and Process Governance variables. The situation of the industry is changing from the function-oriented organization management to the process-oriented perspective. Process Governance framework proposed by the researcher will be the contextual reference models for the further diffusion of the research on Process Governance domain and the operational definition for the development of Process Governance measurement tools in detail.

An Exploration of MIS Quarterly Research Trends: Applying Topic Modeling and Keyword Network Analysis (MIS Quarterly 연구동향 탐색: 토픽모델링 및 키워드 네트워크 분석 활용)

  • Kang, Eunkyung;Jung, Yeonsik;Yang, Seonuk;Kwon, Jiyoon;Yang, Sung-Byung
    • Journal of Intelligence and Information Systems
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    • v.28 no.2
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    • pp.207-235
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    • 2022
  • In a knowledge-based society where knowledge and information industries are the main pillars of the economy, knowledge sharing and diffusion and its systematic management are recognized as essential strategies for improving national competitiveness and sustainable social development. In the field of Information Systems (IS) research, where the convergence of information technology and management takes place in various ways, the evolution of knowledge occurs only when researchers cooperate in turning old knowledge into new knowledge from the perspective of the scientific knowledge network. In particular, it is possible to derive new insights by identifying topics of interest in the relevant research field, applied methodologies, and research trends through network-based interdisciplinary graftings such as citations, co-authorships, and keywords. In previous studies, various attempts have been made to understand the structure of the knowledge system and the research trends of the relevant community by revealing the relationship between research topics, methodologies, and co-authors. However, most studies have compared two or more journals and been limited to a certain period; hence, there is a lack of research that looked at research trends covering the entire history of IS research. Therefore, this study was conducted in the following order for all the papers (from its first issue in 1977 to the first quarter of 2022) published in the MIS Quarterly (MISQ) Journal, which plays a leading role in revealing knowledge in the IS research field: (1) After extracting keywords, (2) classifying the extracted keywords into research topics, methodologies, and theories, and (3) using topic modeling and keyword network analysis in order to identify the changes from the beginning to the present of the IS research in a chronological manner. Through this study, it is expected that by examining the changes in IS research published in MISQ, the developing patterns of IS research can be revealed, and a new research direction can be presented to IS researchers, nurturing the sustainability of future research.

Simultaneous determinations of anthracycline antibiotics by high performance liquid chromatography coupled with radial-flow electrochemical cell (고성능 액체 크로마토그래피/방사흐름 전기화학전지를 이용한 안트라사이클린계 항생제의 동시 정량)

  • Cho, Yonghee;Hahn, Younghee
    • Analytical Science and Technology
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    • v.20 no.4
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    • pp.308-314
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    • 2007
  • The analytical method of HPLC with the radial-flow electrochemical cell (RFEC) has been developed to determine doxorubicin, epirubicin, nogalamycin, daunorubicin and idarubicin simultaneously by employing a reversed-phase chromatography. Anthracyclines were detected at -0.74 V vs. a Ag/AgCl (0.01 M NaCl) reference electrode, a potential of diffusion current plateau in the mobile phase. At a $V_f$ of 1.0 mL/min doxorubicin, epirubicin, daunorubicin and idarubicin appeared at a retention time ($t_r$) of 6.4 min, 7.4 min, 12.7 min and 18.4 min, respectively, while at a $V_f$ of 0.6 mL/min, doxorubicin, epirubicin, nogalamycin, daunorubicin and idarubicin appeared at a $t_r$ of 9.9 min, 11.5 min, 13.5 min, 19.6 min and 28.7 min, respectively. The linearity between each anthracycline injected ($2.40{\times}10^{-7}M{\sim}1.42{\times}10^{-5}M$) and peak area (charge) was excellent with the square of the correlation coefficient ($R^2$) higher than 0.999. The detection limits were $1.0{\times}10^{-8}M{\sim}1.5{\times}10^{-7}M$ for the five anthracyclines. Within-day precision for the five anthracyclines were in reasonable relative standard deviations less than 3 % ($1.00{\times}10^{-6}M{\sim}1.42{\times}10^{-5}M$) except the lower concentrations less than $0.7{\mu}M$. Solid phase extractions of $1.00{\times}10^{-5}M$ epirubicin, $0.48{\times}10^{-5}M$ nogalamycin and $1.52{\times}10^{-5}M$ daunorubicin from human serum with a $C_{18}$ cartridge resulted in 97 %, 100 % and 90 % of recoveries, respectively.

An Empirical Study on the Determinants of Supply Chain Management Systems Success from Vendor's Perspective (참여자관점에서 공급사슬관리 시스템의 성공에 영향을 미치는 요인에 관한 실증연구)

  • Kang, Sung-Bae;Moon, Tae-Soo;Chung, Yoon
    • Asia pacific journal of information systems
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    • v.20 no.3
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    • pp.139-166
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    • 2010
  • The supply chain management (SCM) systems have emerged as strong managerial tools for manufacturing firms in enhancing competitive strength. Despite of large investments in the SCM systems, many companies are not fully realizing the promised benefits from the systems. A review of literature on adoption, implementation and success factor of IOS (inter-organization systems), EDI (electronic data interchange) systems, shows that this issue has been examined from multiple theoretic perspectives. And many researchers have attempted to identify the factors which influence the success of system implementation. However, the existing studies have two drawbacks in revealing the determinants of systems implementation success. First, previous researches raise questions as to the appropriateness of research subjects selected. Most SCM systems are operating in the form of private industrial networks, where the participants of the systems consist of two distinct groups: focus companies and vendors. The focus companies are the primary actors in developing and operating the systems, while vendors are passive participants which are connected to the system in order to supply raw materials and parts to the focus companies. Under the circumstance, there are three ways in selecting the research subjects; focus companies only, vendors only, or two parties grouped together. It is hard to find researches that use the focus companies exclusively as the subjects probably due to the insufficient sample size for statistic analysis. Most researches have been conducted using the data collected from both groups. We argue that the SCM success factors cannot be correctly indentified in this case. The focus companies and the vendors are in different positions in many areas regarding the system implementation: firm size, managerial resources, bargaining power, organizational maturity, and etc. There are no obvious reasons to believe that the success factors of the two groups are identical. Grouping the two groups also raises questions on measuring the system success. The benefits from utilizing the systems may not be commonly distributed to the two groups. One group's benefits might be realized at the expenses of the other group considering the situation where vendors participating in SCM systems are under continuous pressures from the focus companies with respect to prices, quality, and delivery time. Therefore, by combining the system outcomes of both groups we cannot measure the system benefits obtained by each group correctly. Second, the measures of system success adopted in the previous researches have shortcoming in measuring the SCM success. User satisfaction, system utilization, and user attitudes toward the systems are most commonly used success measures in the existing studies. These measures have been developed as proxy variables in the studies of decision support systems (DSS) where the contribution of the systems to the organization performance is very difficult to measure. Unlike the DSS, the SCM systems have more specific goals, such as cost saving, inventory reduction, quality improvement, rapid time, and higher customer service. We maintain that more specific measures can be developed instead of proxy variables in order to measure the system benefits correctly. The purpose of this study is to find the determinants of SCM systems success in the perspective of vendor companies. In developing the research model, we have focused on selecting the success factors appropriate for the vendors through reviewing past researches and on developing more accurate success measures. The variables can be classified into following: technological, organizational, and environmental factors on the basis of TOE (Technology-Organization-Environment) framework. The model consists of three independent variables (competition intensity, top management support, and information system maturity), one mediating variable (collaboration), one moderating variable (government support), and a dependent variable (system success). The systems success measures have been developed to reflect the operational benefits of the SCM systems; improvement in planning and analysis capabilities, faster throughput, cost reduction, task integration, and improved product and customer service. The model has been validated using the survey data collected from 122 vendors participating in the SCM systems in Korea. To test for mediation, one should estimate the hierarchical regression analysis on the collaboration. And moderating effect analysis should estimate the moderated multiple regression, examines the effect of the government support. The result shows that information system maturity and top management support are the most important determinants of SCM system success. Supply chain technologies that standardize data formats and enhance information sharing may be adopted by supply chain leader organization because of the influence of focal company in the private industrial networks in order to streamline transactions and improve inter-organization communication. Specially, the need to develop and sustain an information system maturity will provide the focus and purpose to successfully overcome information system obstacles and resistance to innovation diffusion within the supply chain network organization. The support of top management will help focus efforts toward the realization of inter-organizational benefits and lend credibility to functional managers responsible for its implementation. The active involvement, vision, and direction of high level executives provide the impetus needed to sustain the implementation of SCM. The quality of collaboration relationships also is positively related to outcome variable. Collaboration variable is found to have a mediation effect between on influencing factors and implementation success. Higher levels of inter-organizational collaboration behaviors such as shared planning and flexibility in coordinating activities were found to be strongly linked to the vendors trust in the supply chain network. Government support moderates the effect of the IS maturity, competitive intensity, top management support on collaboration and implementation success of SCM. In general, the vendor companies face substantially greater risks in SCM implementation than the larger companies do because of severe constraints on financial and human resources and limited education on SCM systems. Besides resources, Vendors generally lack computer experience and do not have sufficient internal SCM expertise. For these reasons, government supports may establish requirements for firms doing business with the government or provide incentives to adopt, implementation SCM or practices. Government support provides significant improvements in implementation success of SCM when IS maturity, competitive intensity, top management support and collaboration are low. The environmental characteristic of competition intensity has no direct effect on vendor perspective of SCM system success. But, vendors facing above average competition intensity will have a greater need for changing technology. This suggests that companies trying to implement SCM systems should set up compatible supply chain networks and a high-quality collaboration relationship for implementation and performance.

Origin of Organic Matter and Geochemical Variation of Upper Quaternary Sediments from the Ulleung Basin (울릉분지 상부 제4기 퇴적물의 유기물 기원 및 지화학적 분포)

  • Kim, Ji-Hoon;Park, Myong-Ho;Ryu, Byong-Jae;Lee, Young-Joo;Oh, Jae-Ho;Cheong, Tae-Jin;Chang, Ho-Wan
    • Economic and Environmental Geology
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    • v.40 no.5
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    • pp.605-622
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    • 2007
  • Elemental, Rock-Eval pyrolysis and isotopic analysis of the core sediments from the northwestern and eastern Ulleung Basin of the East were carried out to identify their geochemical characteristics, spatial and vertical variation and origin of organic matter in Upper Quaternary sediments from the northwestern and eastern Ulleung Basin of the East Sea. TOC, m and TS did not show spatial variation between the sampling locations whereas they showed systematic vertical variation associated with MIS stages related to the sea-level change of the East Sea. It is suggested that these past changes of sea-level influenced the sedimentary depositional environments and/or diagenesis which resulted the patterns observed in this study. Based on the results of TOC/N, TS/TOC, ${\delta}^{13}C_{org}\;and\;{\delta}^{15}N_{org}$ analysis, organic matters in the study area appears to be predominantly originated from the marine algae rather than land plant and deposited under normal marine oxic condition during MIS I and MIS III period, and under euxinic/anoxic condition during MIS II period. TOC/N, ${\delta}^{13}C_{org}\;and\;{\delta}^{15}N_{org}$ have a relatively constant value irrespective of MIS stages, implying that the organic matter source does not change by the sea-level fluctuations. However, the results of Rock-Eval pyrolysis indicates that the organic matter is in immature stage and originated from land-plant (Type III), locating in the immature stage land plant (Type III). Similar differences were reported from other areas such as the Atlantic Ocean, Iberia Abyssal Plain, Mediterranean Sea, suggesting that Rock-Eval method does not exactly reflect the characteristic of immature organic matters. Accordingly, the application of Rock-Eval pyrolysis for delineating the source of immature organic matters should be approached with caution and all other geochemical proxies should be considered altogether at the same time.

Electronic Word-of-Mouth in B2C Virtual Communities: An Empirical Study from CTrip.com (B2C허의사구중적전자구비(B2C虚拟社区中的电子口碑): 관우휴정려유망적실증연구(关于携程旅游网的实证研究))

  • Li, Guoxin;Elliot, Statia;Choi, Chris
    • Journal of Global Scholars of Marketing Science
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    • v.20 no.3
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    • pp.262-268
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    • 2010
  • Virtual communities (VCs) have developed rapidly, with more and more people participating in them to exchange information and opinions. A virtual community is a group of people who may or may not meet one another face to face, and who exchange words and ideas through the mediation of computer bulletin boards and networks. A business-to-consumer virtual community (B2CVC) is a commercial group that creates a trustworthy environment intended to motivate consumers to be more willing to buy from an online store. B2CVCs create a social atmosphere through information contribution such as recommendations, reviews, and ratings of buyers and sellers. Although the importance of B2CVCs has been recognized, few studies have been conducted to examine members' word-of-mouth behavior within these communities. This study proposes a model of involvement, statistics, trust, "stickiness," and word-of-mouth in a B2CVC and explores the relationships among these elements based on empirical data. The objectives are threefold: (i) to empirically test a B2CVC model that integrates measures of beliefs, attitudes, and behaviors; (ii) to better understand the nature of these relationships, specifically through word-of-mouth as a measure of revenue generation; and (iii) to better understand the role of stickiness of B2CVC in CRM marketing. The model incorporates three key elements concerning community members: (i) their beliefs, measured in terms of their involvement assessment; (ii) their attitudes, measured in terms of their satisfaction and trust; and, (iii) their behavior, measured in terms of site stickiness and their word-of-mouth. Involvement is considered the motivation for consumers to participate in a virtual community. For B2CVC members, information searching and posting have been proposed as the main purpose for their involvement. Satisfaction has been reviewed as an important indicator of a member's overall community evaluation, and conceptualized by different levels of member interactions with their VC. The formation and expansion of a VC depends on the willingness of members to share information and services. Researchers have found that trust is a core component facilitating the anonymous interaction in VCs and e-commerce, and therefore trust-building in VCs has been a common research topic. It is clear that the success of a B2CVC depends on the stickiness of its members to enhance purchasing potential. Opinions communicated and information exchanged between members may represent a type of written word-of-mouth. Therefore, word-of-mouth is one of the primary factors driving the diffusion of B2CVCs across the Internet. Figure 1 presents the research model and hypotheses. The model was tested through the implementation of an online survey of CTrip Travel VC members. A total of 243 collected questionnaires was reduced to 204 usable questionnaires through an empirical process of data cleaning. The study's hypotheses examined the extent to which involvement, satisfaction, and trust influence B2CVC stickiness and members' word-of-mouth. Structural Equation Modeling tested the hypotheses in the analysis, and the structural model fit indices were within accepted thresholds: ${\chi}^2^$/df was 2.76, NFI was .904, IFI was .931, CFI was .930, and RMSEA was .017. Results indicated that involvement has a significant influence on satisfaction (p<0.001, ${\beta}$=0.809). The proportion of variance in satisfaction explained by members' involvement was over half (adjusted $R^2$=0.654), reflecting a strong association. The effect of involvement on trust was also statistically significant (p<0.001, ${\beta}$=0.751), with 57 percent of the variance in trust explained by involvement (adjusted $R^2$=0.563). When the construct "stickiness" was treated as a dependent variable, the proportion of variance explained by the variables of trust and satisfaction was relatively low (adjusted $R^2$=0.331). Satisfaction did have a significant influence on stickiness, with ${\beta}$=0.514. However, unexpectedly, the influence of trust was not even significant (p=0.231, t=1.197), rejecting that proposed hypothesis. The importance of stickiness in the model was more significant because of its effect on e-WOM with ${\beta}$=0.920 (p<0.001). Here, the measures of Stickiness explain over eighty of the variance in e-WOM (Adjusted $R^2$=0.846). Overall, the results of the study supported the hypothesized relationships between members' involvement in a B2CVC and their satisfaction with and trust of it. However, trust, as a traditional measure in behavioral models, has no significant influence on stickiness in the B2CVC environment. This study contributes to the growing body of literature on B2CVCs, specifically addressing gaps in the academic research by integrating measures of beliefs, attitudes, and behaviors in one model. The results provide additional insights to behavioral factors in a B2CVC environment, helping to sort out relationships between traditional measures and relatively new measures. For practitioners, the identification of factors, such as member involvement, that strongly influence B2CVC member satisfaction can help focus technological resources in key areas. Global e-marketers can develop marketing strategies directly targeting B2CVC members. In the global tourism business, they can target Chinese members of a B2CVC by providing special discounts for active community members or developing early adopter programs to encourage stickiness in the community. Future studies are called for, and more sophisticated modeling, to expand the measurement of B2CVC member behavior and to conduct experiments across industries, communities, and cultures.

Animal Infectious Diseases Prevention through Big Data and Deep Learning (빅데이터와 딥러닝을 활용한 동물 감염병 확산 차단)

  • Kim, Sung Hyun;Choi, Joon Ki;Kim, Jae Seok;Jang, Ah Reum;Lee, Jae Ho;Cha, Kyung Jin;Lee, Sang Won
    • Journal of Intelligence and Information Systems
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    • v.24 no.4
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    • pp.137-154
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    • 2018
  • Animal infectious diseases, such as avian influenza and foot and mouth disease, occur almost every year and cause huge economic and social damage to the country. In order to prevent this, the anti-quarantine authorities have tried various human and material endeavors, but the infectious diseases have continued to occur. Avian influenza is known to be developed in 1878 and it rose as a national issue due to its high lethality. Food and mouth disease is considered as most critical animal infectious disease internationally. In a nation where this disease has not been spread, food and mouth disease is recognized as economic disease or political disease because it restricts international trade by making it complex to import processed and non-processed live stock, and also quarantine is costly. In a society where whole nation is connected by zone of life, there is no way to prevent the spread of infectious disease fully. Hence, there is a need to be aware of occurrence of the disease and to take action before it is distributed. Epidemiological investigation on definite diagnosis target is implemented and measures are taken to prevent the spread of disease according to the investigation results, simultaneously with the confirmation of both human infectious disease and animal infectious disease. The foundation of epidemiological investigation is figuring out to where one has been, and whom he or she has met. In a data perspective, this can be defined as an action taken to predict the cause of disease outbreak, outbreak location, and future infection, by collecting and analyzing geographic data and relation data. Recently, an attempt has been made to develop a prediction model of infectious disease by using Big Data and deep learning technology, but there is no active research on model building studies and case reports. KT and the Ministry of Science and ICT have been carrying out big data projects since 2014 as part of national R &D projects to analyze and predict the route of livestock related vehicles. To prevent animal infectious diseases, the researchers first developed a prediction model based on a regression analysis using vehicle movement data. After that, more accurate prediction model was constructed using machine learning algorithms such as Logistic Regression, Lasso, Support Vector Machine and Random Forest. In particular, the prediction model for 2017 added the risk of diffusion to the facilities, and the performance of the model was improved by considering the hyper-parameters of the modeling in various ways. Confusion Matrix and ROC Curve show that the model constructed in 2017 is superior to the machine learning model. The difference between the2016 model and the 2017 model is that visiting information on facilities such as feed factory and slaughter house, and information on bird livestock, which was limited to chicken and duck but now expanded to goose and quail, has been used for analysis in the later model. In addition, an explanation of the results was added to help the authorities in making decisions and to establish a basis for persuading stakeholders in 2017. This study reports an animal infectious disease prevention system which is constructed on the basis of hazardous vehicle movement, farm and environment Big Data. The significance of this study is that it describes the evolution process of the prediction model using Big Data which is used in the field and the model is expected to be more complete if the form of viruses is put into consideration. This will contribute to data utilization and analysis model development in related field. In addition, we expect that the system constructed in this study will provide more preventive and effective prevention.

Consumer's Negative Brand Rumor Acceptance and Rumor Diffusion (소비자의 부정적 브랜드 루머의 수용과 확산)

  • Lee, Won-jun;Lee, Han-Suk
    • Asia Marketing Journal
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    • v.14 no.2
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    • pp.65-96
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    • 2012
  • Brand has received much attention from considerable marketing research. When consumers consume product or services, they are exposed to a lot of brand related stimuli. These contain brand personality, brand experience, brand identity, brand communications and so on. A special kind of new crisis occasionally confronting companies' brand management today is the brand related rumor. An important influence on consumers' purchase decision making is the word-of-mouth spread by other consumers and most decisions are influenced by other's recommendations. In light of this influence, firms have reasonable reason to study and understand consumer-to-consumer communication such as brand rumor. The importance of brand rumor to marketers is increasing as the number of internet user and SNS(social network service) site grows. Due to the development of internet technology, people can spread rumors without the limitation of time, space and place. However relatively few studies have been published in marketing journals and little is known about brand rumors in the marketplace. The study of rumor has a long history in all major social science. But very few studies have dealt with the antecedents and consequences of any kind of brand rumor. Rumor has been generally described as a story or statement in general circulation without proper confirmation or certainty as to fact. And it also can be defined as an unconfirmed proposition, passed along from people to people. Rosnow(1991) claimed that rumors were transmitted because people needed to explain ambiguous and uncertain events and talking about them reduced associated anxiety. Especially negative rumors are believed to have the potential to devastate a company's reputation and relations with customers. From the perspective of marketer, negative rumors are considered harmful and extremely difficult to control in general. It is becoming a threat to a company's sustainability and sometimes leads to negative brand image and loss of customers. Thus there is a growing concern that these negative rumors can damage brands' reputations and lead them to financial disaster too. In this study we aimed to distinguish antecedents of brand rumor transmission and investigate the effects of brand rumor characteristics on rumor spread intention. We also found key components in personal acceptance of brand rumor. In contextualist perspective, we tried to unify the traditional psychological and sociological views. In this unified research approach we defined brand rumor's characteristics based on five major variables that had been found to influence the process of rumor spread intention. The five factors of usefulness, source credibility, message credibility, worry, and vividness, encompass multi level elements of brand rumor. We also selected product involvement as a control variable. To perform the empirical research, imaginary Korean 'Kimch' brand and related contamination rumor was created and proposed. Questionnaires were collected from 178 Korean samples. Data were collected from college students who have been experienced the focal product. College students were regarded as good subjects because they have a tendency to express their opinions in detail. PLS(partial least square) method was adopted to analyze the relations between variables in the equation model. The most widely adopted causal modeling method is LISREL. However it is poorly suited to deal with relatively small data samples and can yield not proper solutions in some cases. PLS has been developed to avoid some of these limitations and provide more reliable results. To test the reliability using SPSS 16 s/w, Cronbach alpha was examined and all the values were appropriate showing alpha values between .802 and .953. Subsequently, confirmatory factor analysis was conducted successfully. And structural equation modeling has been used to analyze the research model using smartPLS(ver. 2.0) s/w. Overall, R2 of adoption of rumor is .476 and R2 of intention of rumor transmission is .218. The overall model showed a satisfactory fit. The empirical results can be summarized as follows. According to the results, the variables of brand rumor characteristic such as source credibility, message credibility, worry, and vividness affect argument strength of rumor. And argument strength of rumor also affects rumor intention. On the other hand, the relationship between perceived usefulness and argument strength of rumor is not significant. The moderating effect of product involvement on the relations between argument strength of rumor and rumor W.O.M intention is not supported neither. Consequently this study suggests some managerial and academic implications. We consider some implications for corporate crisis management planning, PR and brand management. This results show marketers that rumor is a critical factor for managing strong brand assets. Also for researchers, brand rumor should become an important thesis of their interests to understand the relationship between consumer and brand. Recently many brand managers and marketers have focused on the short-term view. They just focused on strengthen the positive brand image. According to this study we suggested that effective brand management requires managing negative brand rumors with a long-term view of marketing decisions.

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