• The Journal of Asian Finance, Economics and Business
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• v.9 no.8
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• pp.135-144
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• 2022

Organizational culture has been recognized as a determinant of corporate Effectiveness. Cultural components could affect corporate Effectiveness to different extents. However, it seems that none of the previous studies have evaluated and compared these influential extents of cultural components. The current research applies analytic hierarchy processes to assess and rate the significance extents that, cultural components play in resulting in corporate Effectiveness. Then, the current work utilizes regression analyses to re-evaluate the significance extents for the robustness of analytic hierarchy processes. The findings indicate that clan culture is the most vital component in explaining corporate Effectiveness. In contrast, adhocracy culture is the least important component in affecting corporate Effectiveness. Market culture is a cultural component that is ranked the second in determining corporate Effectiveness, and next is hierarchy culture which is the third. The findings are in support of the positive influences of clan, market, and adhocracy cultures on corporate Effectiveness; whereas it found the negative impact of hierarchy culture on corporate Effectiveness.

• Journal of the Korea Society for Simulation
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• v.14 no.3
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• pp.43-54
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• 2005

For the effective design of automated distribution center composed of Automated Storage/Retrieval System, Automated Guided Vehicle System, and Conveyor System, we proposed an analysis method to determining. design and control parameters with multiple performance objectives using Compromise Programming, which can resolve the dilemma of conflicting objectives. The Evolution Strategy generates the optimal solutions for each objectives. The Analytic Hierarchy Process selects the best solution among the alternatives generated from Evolution Strategy. The Regression Analysis formulates the objective functions for each objectives. By reducing deviations between goal values and target values generated from Analytic Hierarchy Process, Compromise Programming determines design and control parameters by compromising the multiple objectives formulated using Regression Analysis. When the parameters of system are changed, this proposed analysis method has a benefit of reducing costs and time without repeating whole simulation run.

• The Journal of Information Systems
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• v.16 no.3
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• pp.109-132
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• 2007

In the paper, we builds an advanced new credit evaluation system for Micro-small sized individual firms through appropriate evaluation factors derived by logistic regression analysis for credit evaluation model using in Korean Federation of Credit Guarantee Foundations, and the weights of factors computed by analytic hierarchy process(AHP). Industry characteristics are more applied to previous credit model with the additional the financial fact-information and non-financial judgement-information. Our results show that the financial factors have become more important than three years ago. Moreover, in the non-financial factors, the fact-information factors consider more important then the judgement-information factors. A new credit evaluation system is developed based on this credit evaluation model.

• IE interfaces
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• v.23 no.1
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• pp.78-88
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• 2010

In this paper we develop a model for the performance evaluation of defense R&D test development projects based on analytic hierarchy process. First, evaluation indicators are collected through the related literature survey and a delphi inquiry method. Second, stepwise multiple linear regression is used for developing a hierarchical structure for analytic hierarchy process in the evaluation model, which can make the selected evaluation indicators of the hierarchical structure independent. Also we verify the effectiveness of proposed indicators of the performance evaluation by comparing with the existing evaluation indicators. The developed indicators for the performance evaluation is more reasonable and practical than the previous indicators on defense R&D test development projects.

• Journal of The Korean Society of Agricultural Engineers
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• v.49 no.3
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• pp.63-68
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• 2007

The LRA(Logistic Regression Analysis) conducts a quantitative analysis by collecting a lot of samples and the AHP(Analytic Hierarchy Program) makes use of expert decision influenced by subjective judgment to a certain degree. This study is to suggest a combination method in mapping landslide hazard by giving equal weight for the result of LRA and AHP. Topographic factors(slope, aspect, elevation), soil dram, soil depth and land use were adopted to classify landslide hazard areas. The three methods(LRA, AHP, the combined approach) was applied to a $520km^2$ region located in the middle of South Korea which have occurred 39 landslides during 1999 and 2003. The suggested method showed 58.9% matching rate for the real landslide sites comparing with the classified areas of high-risk landslide While LRA and AHP Showed 46.1% and 48.7% matching rates respectively. Further studies are recommended to find the optimal combining weight of LRA and AHP with more landslide data.

• Proceedings of the KSRS Conference
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• v.2
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• pp.547-550
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• 2006

This study is to suggest a methodology to produce landslide hazard map by combining LRA (Logistic Regression Analysis) and AHP (Analytic Hierarchy Program) Approach. Topographic factors (slope, aspect, elevation), soil drain, soil depth and land use were adopted to classify landslide hazard areas. The method was applied to a 520 $km^2$ region located in the middle of South Korea which have occurred 39 landslides during 1999 and 2003. The suggested method showed 58.9 % matching rate for the real landslide sites comparing with the classified areas of high-risk landslide while LRA and AHP showed 46.1 % and 48.7 % matching rates respectively.

• Journal of the Korea Convergence Society
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• v.6 no.5
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• pp.1-8
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• 2015

The data of fair value hierarchy is expected to contain different degree of measurement error, information asymmetry, and information risk by the level of hierarchy. Thus, this study examines how hierarchy of fair value discriminately influences on companies' cost of capital. Through regression analysis of corporations listed from 2011 to 2014, it turns out that the regression coefficient of level 1 and 2 of fair value variable vary their rank by cost of capital types, while level 3 contains the highest regression coefficient for every cost of capital variable. In addition, further study of how the relevance between cost of capital and the fair value hierarchy gets affected by market risk management level and audit quality finds no consistent results. However, by analyzing the effect of coincident interaction through the convergence of market risk management and audit quality, when audit quality and market risk management level are high, the effect of relieving cost of capital of Level 3 gets the highest. In conclusion, fair value hierarchy data seems to affect discriminately on cost of capital by involved information risk, and the information risk could decrease by the level of market risk management and audit quality.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.4
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• pp.118-126
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• 2022

This study attempts a comparison between AHP(Analytic Hierarchy Process) in which the importance weight is structured by individual subjective values and regression model with importance weight based on statistical theory in determining the importance weight of casual model. The casual model is designed by for students' satisfaction with university, and SERVQUAL modeling methodology is applied to derive factors affecting students' satisfaction with university. By comparison of importance weights for regression model and AHP, the following characteristics are observed. 1) the lower the degree of satisfaction of the factor, the higher the importance weight of AHP, 2) the importance weight of AHP has tendency to decrease as the standard deviation(or p-value) increases. degree of decreases. the second sampling is conducted to double-check the above observations. This study empirically checks that the importance weight of AHP has a relationship with the mean and standard deviation(or p-value) of independence variables, but can not reveal how exactly the relationship is. Further research is needed to clarify the relationship with long-term perspective.

• Journal of Korean Clinical Nursing Research
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• v.24 no.3
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• pp.313-323
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• 2018

Purpose: This cross-sectional survey study explored the moderating effect of social support between hierarchy-oriented nursing organizational culture and turnover intention in clinical nurses. Methods: Data were collected using self-report questionnaires from 240 nurses working at three general hospitals in February 2018. Hierarchy-oriented nursing organizational culture, turnover intention and social support were measured using 5, 6, and 8 items, respectively, of validated instruments. Descriptive analysis and hierachical multiple regression were conducted using SPSS/WIN 21.0. Results: Nurses rated $3.66{\pm}0.50$ for hierarchy-oriented nursing organizational culture, $3.40{\pm}0.64$ for turnover intention, and $3.77{\pm}0.56$ for social support respectively. Nurses' turnover intention was positively correlated with hierarchical organizational culture, but negatively with social support. The moderating effect of social support was not significant in the relationship between hierarchical nursing organizational culture and turnover intention. Conclusion: It is required to improve the hierarchy-oriented nursing organizational culture. Institutional preparation and education are urgently needed to strengthen the boss and peer support for clinical nurses and finally to reduce turnover intention.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.2
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• pp.17-30
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• 2015

Technology-oriented national R&D programs produce intellectual property as their final result. Patents, as typical industrial intellectual property, are therefore considered an important factor when evaluating the outcome of R&D programs. Among the main components of patent evaluation, in particular, the patent right quality is a key component constituting patent value, together with marketability and usability. Current approaches for patent right quality evaluation rely mostly on intrinsic knowledge of patent attorneys, and the recent rapid increase of national R&D patents is making expert-based evaluation costly and time-consuming. Therefore, this study defines a hierarchy of patent right quality and then proposes how to quantify the evaluation process of patent right quality by combining text mining and regression analysis. This study will contribute to understanding of the systemic view of the patent right quality evaluation, as well as be an efficient aid for evaluating patents in R&D program assessment processes.