• Geophysics and Geophysical Exploration
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• v.8 no.1
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• pp.1-6
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• 2005

Analogue physical modelling using granular materials (i.e., sandbox experiments) has been applied with great success to a number of geological problems at various scales. Such physical experiments can also be simulated numerically with the Discrete Element Method (DEM). In this study, we apply the DEM simulation to the collision between the Indian subcontinent and the Eurasian Plate, one of the most significant current tectonic processes in the Earth. DEM simulation has been applied to various kinds of dynamic modelling, not only in structural geology but also in soil mechanics, rock mechanics, and the like. As the target of the investigation is assumed to be an assembly of many tiny particles, DEM simulation makes it possible to treat an object with large and discontinuous deformations. However, in DEM simulations, we often encounter difficulties when we examine the validity of the input parameters, since little is known about the relationship between the input parameters for each particle and the properties of the whole assembly. Therefore, in our previous studies (Yamada et al.,2002a,2002b,2002c), we were obliged to tune the input parameters by trial and error. To overcome these difficulties, we introduce a numerical biaxial test with the DEM simulation. Using the results of this numerical test, we examine the validity of the input parameters used in the collision model. The resulting collision model is quite similar to the real deformation observed in eastern Asia, and compares well with GPS data and in-situ stress data in eastern Asia.

• Journal of the Korean Geotechnical Society
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• v.39 no.12
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• pp.93-102
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• 2023

Despite recent modifications to building structural standards emphasizing the seismic stability of building foundations, the current design focus remains solely on vertical support, resulting in insufficient consideration of horizontal loads during earthquakes. In this study, we evaluated the dynamic behavior of inclined tripod micropiles (ITMP), which provide additional seismic resistance against horizontal and vertical loads during earthquakes. A comparison of the dynamic characteristics, such as acceleration, displacement, bending moment, and axial force, of ITMP with a 15° installation angle and normal vertical micropiles with a 0° installation angle was performed using dynamic centrifuge model tests. Results show that under moderate seismic loads, the proposed ITMP exhibited lower acceleration responses than the vertical micropiles. However, when subjected to a long-period strong seismic excitation, such as sine (2 Hz), ITMP showed greater responses than the vertical micropiles in terms of acceleration and settlement. These results indicate that the use of ITMP reduces the amplif ication of short-period (high-f requency) contents compared with the use of vertical micropiles. Therefore, ITMP can be used to enhance seismic performance of structures.

• Journal of Global Scholars of Marketing Science
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• v.17 no.2
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• pp.1-29
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• 2007

The flow theory becomes one of the most important frameworks in the internet research arena. Hoffman and Novak proposed a hierarchical flow model showing the antecedents and outcomes of flow and the relationship among these variables in the hyper-media computer circumstances (Hoffman and Novak 1996). This model was further tested after their initial research (Novak, Hoffman, and Yung 2000). At their paper, Hoffman and Novak explained that the balance of challenge and skill leads to flow which means the positive optimal state of mind (Hoffman and Novak 1996). An imbalance between challenge and skill, leads to negative states of mind like anxiety, boredom, apathy (Csikszentmihalyi and Csikszentmihalyi 1988). Almost all research on the flow 4-channel model have been focusingon flow, the positive state of mind (Ellis, Voelkl, and Morris 1994 Mathwick and Rigdon 2004). However, it also needs to examine the formation of the negative states of minds and their outcomes. Flow researchers explain play or playfulness as antecedents or the early state of flow. However, play has been regarded as a distinct concept from flow in the flow literatures (Hoffman and Novak 1996; Novak, Hoffman, and Yung 2000). Mathwick and Rigdon discovered the influences of challenge and skill on play; they also observed the influence of play on web-loyalty and brand loyalty (Mathwick and Rigdon 2004). Unfortunately, they did not go so far as to test the influences of play on state of mind. This study focuses on the relationships between state of mind in the flow 4-channel model and play. Early research has attempted to hypothetically explain state of mind in flow theory, but has not been tested except flow until now. Also the importance of play has been emphasized in the flow theory, but has not been tested in the flow 4-channel model context. This researcher attempts to analyze the relationships among state of mind, skill of play, challenge, state of mind and web loyalty. For this objective, I developed a measure for state of mind and defined the concept of play as a trait. Then, the influences of challenge and skill on the state of mind and play under on-line shopping conditions were tested. Also the influences of play on state of mind were tested and those of flow and play on web loyalty were highlighted. 294 undergraduate students participated in this research survey. They were asked to respond about their perceptions of challenge, skill, state of mind, play, and web-loyalty to on-line shopping mall. Respondents were restricted to students who bought products on-line in a month. In case of buying products at two or more on-line shopping malls, they asked to respond about the shopping mall where they bought the most important one. Construct validity, discriminant validity, and convergent validity were used to check the measurement validations. Also, Cronbach's alpha was used to check scale reliability. A series of exploratory factor analyses was conducted. This researcher conducted confirmatory factor analyses to assess the validity of measurements. All items loaded significantly on their respective constructs. Also, all reliabilities were greater than.70. Chi-square difference tests and goodness of fit tests supported discriminant and convergent validity. The results of clustering and ANOVA showed that high challenge and high skill leaded to flow, low challenge and high skill leaded to boredom, and low challenge and low skill leaded to apathy. But, it was different from my expectation that high challenge and low skill didnot lead to anxiety but leaded to apathy. The results also showed that high challenge and high skill, and high challenge and low skill leaded to the highest play. Low challenge leaded to low play. 4 Structural Equation Models were built by flow, anxiety, boredom, apathy for analyzing not only the impact of play on state of mind and web-loyalty, but also that of state of mind on web-loyalty. According the analyses results of these models, play impacted flow and web-loyalty positively, but impacted anxiety, boredom, and apathy negatively. Results also showed that flow impacted web-loyalty positively, but anxiety, boredom, and apathy impacted web-loyalty negatively. The interpretations and implications of the test results of the hypotheses are as follows. First, respondents belonging to different clusters based on challenge and skill level experienced different states of mind such as flow, anxiety, boredom, apathy. The low challenge and low skill group felt the highest anxiety and apathy. It could be interpreted that this group feeling high anxiety or fear, then avoided attempts to shop on-line. Second, it was found that higher challenge leads to higher levels of play. Test results show that the play level of the high challenge and low skill group (anxiety group) was higher than that of the high challenge and high skill group (flow group). However, this was not significant. Third, play positively impacted flow and negatively impacted boredom. The negative impacts on anxiety and apathy were not significant. This means that the combination of challenge and skill creates different results. Forth, play and flow positively impacted web-loyalty, but anxiety, boredom, apathy had negative impacts. The effect of play on web-loyalty was stronger in case of anxiety, boredom, apathy group than fl ow group. These results show that challenge and skill influences state of mind and play. Results also demonstrate how play and flow influence web-loyalty. It implies that state of mind and play should be the core marketing variables in internet marketing. The flow theory has been focusing on flow and on the positive outcomes of flow experiences. But, this research shows that lots of consumers experience the negative state of mind rather than flow state in the internet shopping circumstance. Results show that the negative state of mind leads to low or negative web-loyalty. Play can have an important role with the web-loyalty when consumers have the negative state of mind. Results of structural equation model analyses show that play influences web-loyalty positively, even though consumers may be in the negative state of mind. This research found the impacts of challenge and skill on state of mind in the flow 4-channel model, not only flow but also anxiety, boredom, apathy. Also, it highlighted the role of play in the flow 4-channel model context and impacts on web-loyalty. However, tests show a few different results from hypothetical expectations such as the highest anxiety level of apathy group and insignificant impacts of play on anxiety and apathy. Further research needs to replicate this research and/or to compare 3-channel model with 4-channel model.

• Korea Journal of Hospital Management
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• v.8 no.3
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• pp.72-91
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• 2003

The purpose of this study is to investigate the recognition of health information managers, and to analyze the level of job satisfaction and organizational commitment of medical record technicians. The data for this study were collected through a self-administered survey with a structured questionnaire to 172 subjects from medical record technicians working in hospitals in Seoul and Gyeonggi Province as well as the faculty of medical schools across South Korea. In this analysis frequency, t-test, ANOVA, factor analysis and structural equation model were used. The main findings of this study are as follows: 1. As for recognition of the seven dimensions in the role of health information managers, the role as clinical data specialist received the most positive feedback, followed by document & repository managers, patient information coordinators, health information managers, data quality managers, security officers and research & decision support analyst. 2. The level of job satisfaction among medical information handlers and managers averaged 3.14. In terms of the factors in the work environment concerned with job satisfaction, being able to work independently and as team players reached the top among 6 factors with the average of 3.39, followed by professional position, salary & rewards, expectations for job performance and administration. 3. The average rate of organizational commitment stood at 3.09. Respondents tend to be focused on present tasks rather than future-oriented tasks. 4. The result of the analysis based on the relationship between recognition as health information managers, job satisfaction and organizational commitment found that all analysis are statistically meaningful. The more the respondents were aware of their roles as health information managers, the more they tended to be committed to their work and satisfied with their work. The more the respondents were committed to their work, the more satisfaction was seen. The effects of recognition as health information managers on organizational commitment measured 0.27 and for job satisfaction it was 0.17. The effects of organizational commitment on job satisfaction stood at 0.71. The feasibility of the model meets the standard at Chi-square value of 66.755 and the P value of 0.057. The Normed Fit Index (NFI) of 0.930 was in compliance with the standard for model feasibility and the squared multiple correlation coefficient of this model was 8% in organizational commitment and 60% in job satisfaction.

• The Journal of the Korea Contents Association
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• v.11 no.4
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• pp.361-377
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• 2011

This study has three primary purposes, firstly to identify how leader's personal characters influence to his/her transformational leadership, secondly to find how transformational leadership influences to innovative behavior, finally to explore how organizational cultures moderate between transformational leadership and innovative behavior. The first part of the study, based on literature study on transformational leadership, provides insight into what are antecedents, moderators and dependent variable in transformational leadership. Firstly, leader's personal characters are selected as antecedent variables such as extroversion and self-efficacy. Secondly, innovative behavior is introduced as a dependent variable. Thirdly, two types of organizational culture are considered as moderators between leader's personal character and leadership In this study, a comprehensive research model and hypothesis were empirically tested based on data from three types of questionnaires involving 663 employees in Korean organizations. In order to test the hypotheses, we have used Structural Equations Model (SEM) from AMOS7.0. In this analysis, we have employed raw data as it is instead of correlation matrix or covariance matrix. We have tested hypotheses by examining the significance of each path of the model, and gone through the process of testing the goodness of fit of the model itself. The results of statistical analysis show the following. Firstly, one of leader's personalities, self-efficacy has positive effect on his/her transformational leadership, but extroversion does not have positive effect. Secondly, transformational leadership has positive effect on innovative behavior. Finally, there was not any cultural moderating effects between transformational leadership and innovative behavior.

• Culinary science and hospitality research
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• v.18 no.3
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• pp.32-45
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• 2012

The purposes of this study is to understand the influence of culinary employees' stress coping styles in the deluxe hotel industry on counterproductive work behaviors and turnover intention. Based on total 345 culinary employees obtained from empirical research, this study reviewed the reliability and fitness of the research model and verified a total of 2 hypotheses using the AMOS program. The hypothesized relationships in the model test simultaneously by using a structural equation model(SEM). The proposed model provided an adequate fit to the data, ${\chi}^2$=736.474(p<0.001), df=233, GFI=.853, NFI=.901, CFI=.930, RMSEA=.079. Hypothesis $1^a$, which hypothesized a positive relationship between employees coping styles(avoid coping, ${\beta}$=.325; emotion coping, ${\beta}$=.261; job coping, ${\beta}$=-.203) and person-counterproductive work behavior was supported. As predicted by, Hypothesis $1^b$, employees' coping styles(job coping, ${\beta}$=-.307; avoid coping, ${\beta}$=.262; emotion coping, ${\beta}$=.146) had significant positive effects on organization-counterproductive work behavior. Also, employees' person-counterproductive work behavior(${\beta}$=.431) had significant positive effects on turnover intention(Hypothesis 2 was partially supported). Limitations and future research directions are also discussed.

• Management & Information Systems Review
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• v.37 no.2
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• pp.209-233
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• 2018

This study investigates the question of how political and economic factors may affect the export of renewable energy technologies. The relationships are tested using panel data for 19 OECD member countries over the period 1992-2012. Before establishing the empirical model, the current study checks the characteristics of the panel data, which includes various panel framework analyses, such as tests for the presence of normality, structural breaks, first-order autocorrelation, heteroscedasticity, cross-sectional dependence, panel unit-root. From the panel framework analyses, a dynamic panel model is established to test the relationship between the variables examined in this study. In order to reduce the bias of the estimation of the dynamic panel model and obtain efficient parameters, this study uses the bias-corrected least square dummy variable(LSDVC) estimator to estimate the empirical model. The results of this study show that governmental policies expressed as coercive pressure and market size positively affect the export growth of renewable energy technologies. However, public pressure and traditional energy industry have no significant effects on export performance. Policy implications are presented based on the results of this study.

• Journal of Distribution Science
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• v.13 no.3
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• pp.41-49
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• 2015

Purpose - Universities are placing a greater emphasis on relationship management as a source of competitive advantage due to increasingly competitive environments and social changes. The purpose of this study is to analyze the relationships among education service quality, relationship quality, and relationship performance from the perspective of service distribution. In other words, this study is focused on the role of education service quality with regard to relationship management. In this study, education service quality is divided into lecture, job assistance, student-faculty interaction, student-student interaction, facility welfare, and scholarship welfare quality components; relationship quality is composed of satisfaction and commitment; and relationship performance is divided into recommendation and defection intentions. Research design, data, and methodology - This study aims to identify how the various elements of education service quality affect satisfaction. Further, it aims to test the relationships among satisfaction, commitment, recommendation intentions, and defection intentions. Distribution and marketing students were randomly selected for the experiment. Out of the 380 administered questionnaires, a total of 361 respondents provided complete and usable data. The sample consisted of 232 males (64.3%) and 129 females (35.7%). The variables of the proposed model were measured through assessments that were measured on a 5-point Likert scale. Using Lisrel 8.7, a structural model was analyzed and the path coefficients were estimated. Results - The overall fit of the model was acceptable (χ2=1121.8 (df=603, P=0.00), GFI=0.967, NFI=0.974, CFI=0.981, RMR=0.021). The results generally supported the hypothesized relationships of the proposed model, except for Hypothesis 1. First, lecture, job assistance, student-faculty interaction, student-student interaction, and facility welfare quality were revealed to have positive effects on satisfaction. In particular, lecture and facility welfare quality had the strongest effects on satisfaction. However, scholarship welfare quality did not significantly affect satisfaction; this means that Hypothesis 3-2 was not supported. Second, satisfaction was positively related to commitment and recommendation intentions but it was negatively related to defection intentions. Third, commitment was positively related to recommendation intentions but it was negatively related to defection intentions. Conclusions - This study emphasizes the influence of education service quality on satisfaction in the long-term. In addition, this research has the following implications for university relationship management. First, the findings suggest that the various dimensions of education service quality have differing effects on satisfaction. In particular, lecture and facility welfare quality are found to be the most important factors in increasing the level of satisfaction. Therefore, university managers need to prioritize enhancing lecture quality and upgrading educational facilities. Second, satisfaction also improves through job assistance systems and opportunities for social interactions. Therefore, university managers should reinforce their job skills programs and should provide opportunities for social relationships to develop. Finally, it is important for university managers to take a relationship approach to maximizing relationship performance. Therefore, university managers should work to increase student recommendations and prevent their defections based on satisfaction and commitment.

• Tunnel and Underground Space
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• v.8 no.4
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• pp.307-320
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• 1998

Tunnel lining is the final support of a tunnel and reflects the results of the interaction between ground and support system. Recently it is very difficult to support and manage the tunnel because the cracks on tunnel lining cause many problems in supporting and managing tunnels. Therefore the analysis of the cracks is quite strongly required. In this study, mechanical behaviour of a tunnel lining was examined by model tests and by numerical analyses. Especially the model test was examined for double linings including shotcrete and concrete lining. The model tests were carried out under various conditions taking different loading shapes, horizontal stresses, thicknesses of linings and double lining, vault opening behind the concrete lining and rock-like medium surrounding the lining. Due to horizontal stress, compressive stress prevailed on the lining. Thus the bearing capacity of the lining increased. The existence of a vault opening behind the concrete lining reduced the bearing capacity by the similar amount of reduction of concrete lining thickness. Rock-like medium cast around the side wall of the lining restrained the deflection of the lining, and the bearing capacity for cracking and failure increased vary much. In numerical analyses a algorithm which can analysis the double lining by introduction of interface element was developed. And the results of the numerical analyses were compared with the results of the model tests.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1367-1377
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• 2020

The purpose of this study is to assess the seismic vulnerability of buildings in Gyeongju city starting with the earthquake that occurred in the city on September 12, 2016, and produce a seismic vulnerability map. 11 influence factors related to geotechnical, physical, and structural indicators were selected to assess the seismic vulnerability, and these were applied as independent variables. For a dependent variable, location data of the buildings that were actually damaged in the 9.12 Gyeongju Earthquake was used. The assessment model was constructed based on random forest (RF) as a mechanic study method and support vector machine (SVM), and the training and test dataset were randomly selected with a ratio of 70:30. For accuracy verification, the receiver operating characteristic (ROC) curve was used to select an optimum model, and the accuracy of each model appeared to be 1.000 for RF and 0.998 for SVM, respectively. In addition, the prediction accuracy was shown as 0.947 and 0.926 for RF and SVM, respectively. The prediction values of the entire buildings in Gyeongju were derived on the basis of the RF model, and these were graded and used to produce the seismic vulnerability map. As a result of reviewing the distribution of building classes as an administrative unit, Hwangnam, Wolseong, Seondo, and Naenam turned out to be highly vulnerable regions, and Yangbuk, Gangdong, Yangnam, and Gampo turned out to be relatively safer regions.