• The Journal of the Korea Contents Association
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• v.19 no.10
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• pp.325-340
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• 2019

The purpose of this paper is to develop and suggest an integrative leadership contingency framework of leadership that will state the situational and psychological factors under which leadership effect should be maximized. Our leadership model presents that situational factors, including development, circumstances urgency and task structure, proposes which of transformational, transactional, empowering, and authentic leadership solutions. Also, our integrative leadership contingency model in turn results in a combination of the level of follower commitment, intrinsic motivation, and individual creativity based on inductive research method. This integrative leadership model suggested here has significant contributions for leadership effectiveness and future leadership research agenda. Next leadership research could experimentally examine the structural relationships between each of the leadership styles and levels of contingency and psychological factors of followers.

• Journal of the Korean Data and Information Science Society
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• v.27 no.6
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• pp.1621-1629
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• 2016

This paper studies Bayesian pooling for analysis of categorical data from small areas. Many surveys consist of categorical data collected on a contingency table in each area. Statistical inference for small areas requires considerable care because the subpopulation sample sizes are usually very small. Typically we use the hierarchical Bayesian model for pooling subpopulation data. However, the customary hierarchical Bayesian models may specify more exchangeability than warranted. We, therefore, investigate the effects of pooling in hierarchical Bayesian modeling for the contingency table from small areas. In specific, this paper focuses on the methods of direct or indirect pooling of categorical data collected on a contingency table in each area through Dirichlet priors. We compare the pooling effects of hierarchical Bayesian models by fitting the simulated data. The analysis is carried out using Markov chain Monte Carlo methods.

• Knowledge Management Research
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• v.7 no.2
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• pp.35-52
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• 2006

Increasing competitive pressure, the constantly accelerating transformation of the economy, and a stronger focus on value creation have initiated the search for sustainable sources of competitive advantage in organizations. In this context, the concept of treating organizational knowledge as a valuable strategic resource has become quite popular recently. Knowledge has become the most critical component in the struggle for sustained competitive advantage and knowledge management (KM) has also been described for its possible role in creating sustainable competitive advantage. In order to examine the contingency between KM resources, KM strategies, and KM performance of organizations, a contingency model of KM, which is based on resource-based theory as well as knowledge-based theory, is developed from the information systems and strategic management literature in order to assess the following questions: (i) What KM resources affect the organization's KM strategies? (ii) Is there a relationship between KM strategies and organizational performance enhanced by KM? A detailed exploratory analysis of survey responses from 79 Korean companies provides the following significant findings: (i) This study found support for the proposed contingency model of KM; (ii) The organization's KM strategies are determined by social resources and its capabilities; (iii) An organization with a culture-based KM strategy is more likely to enhance organizational KM performance than an organization with a technology-based KM strategy.

• Journal of Information Technology Applications and Management
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• v.23 no.3
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• pp.71-86
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• 2016

This paper proposes a new software quality model composed of a hierarchy of software quality views and three software quality characteristics models. The software view hierarchy is composed of two levels : end view and means view at the first level, contingency view and intrinsic view as sub-views of means view. Three software quality characteristics models are activity quality characteristics model, contingency quality characteristics model, and intrinsic quality characteristics model, which correspond to end view, contingency view, and intrinsic view respectively. This paper also reclassifies characteristics of ISO/IEC 25000 series SQuaRE's software product quality model according to the proposed software quality model. The results illustrate clearly the shortcomings of SQuaRE's product quality model and how to overcome them. First of all, most of SQuaRE's product characteristics should be redefined and conceptually clarified according to the views on which they are really rested. Much more characteristics should be supplemented too. After that, rigorous empirical researches will become relevant. Causal relationships between activity quality characteristics and characteristics of means view should be empirically researched.

• Communications for Statistical Applications and Methods
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• v.8 no.1
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• pp.39-49
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• 2001

When an appropriate model is fitted to explain a certain categorical data, outlying cell detection plays very important role to reduce the lack of fit. There exist many statistical methods to identify outlying cells in contingency table. In this paper, correspondence analysis is applied to identify one or two outlying cells. When corresponding relationships between categories of the row and columns are explored, we find that outlying cells could be identified via the correspondence analysis map.

• The Pure and Applied Mathematics
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• v.4 no.1
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• pp.7-18
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• 1997

Consider an $r\;\times\;c$ contingency table under the full multinomial model in which each classification is ordered. The problem is to test the null hypothesis of independence. A number of tests have been proposed for this problem. In this article we show that all of these tests can be improved on in some sense for most cases. In fact the preceding tests sometimes are inadmissible in a strict sense. Furthermore, we show by example that in some cases improved tests can yield substantially improved power functions.

• Communications for Statistical Applications and Methods
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• v.21 no.4
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• pp.275-284
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• 2014

Matched pairs are twice continuously measured data with the same categories. They can be represented as the square contingency tables. We can also consider symmetry and marginal homogeneity. Moreover, we can infer the matched pairs models; the symmetry model, the quasi-symmetry model, and the ordinal quasi-symmetry model. These inferences are involved in assumptions for special distributions. In this study, we visualize matched pairs models using modified correspondence analysis. Modified correspondence analysis can be used when square contingency tables are given; consequently, it is involved in the square and asymmetric correspondence matrix. This technique does not need assumptions for special distributions and is more helpful than the correspondence analysis to visualize matched pairs models.

• Journal of the Korean Statistical Society
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• v.33 no.1
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• pp.129-147
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• 2004

For square contingency tables with nominal categories, this paper proposes a measure to represent the degree of departure from the quasi-symmetry (QS) model and the Bradley-Terry (BT) model. The measure proposed is expressed by using the Cressie and Read (1984)'s power-divergence or Patil and Taillie (1982)'s diversity index. The measure lies between 0 and 1, and it is useful for comparing the degree of departure from QS or BT in several tables.

• Journal of the Korean Statistical Society
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• v.21 no.1
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• pp.59-69
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• 1992

A measure is proposed to represent the degree of residuals from the symmetry model for square contingency tables with nominal categories. The measure is derivedby modifying the sum of squared singular values for a skew symmetric matrix of the residuals from the symmetry model. The proposed measure would be useful for comparing the degree of residuals from the symmetry model in several tables.

• Journal of Ocean Engineering and Technology
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• v.19 no.4 s.65
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• pp.35-41
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• 2005

There has been increasing offshore oil exploration, drilling, and production activities, as well as a huge amount of petroleum being transported by tankers and pipelines through the ocean and costal environment. Assessment must be made of the potential risk of damage resulting from the exploration, development and transportation activities. This is achieved through predictive impact evaluations of the fate of hypothetical or real oil spills. VVhen an oil spill occurs, planning and execution of cleanup measures also require the capability to forecast the short-term and long-term behavior of the spilled oil. A great amount of effort has been spent by government agencies, oil industries, and researchers over the past decade to develop more realistic models for oil spills. Numerous oil spill models have been developed and applied, most of which attempt to predict the oil spill fate and behavior. For an actual contingency planning, the oil fate and behavior model should be combined with an oil spill incident model, an environmental impact and risk model and a contingency planning model. The purpose of this review study is to give an overview of existing oil spill models that deal with the physical, chemical, biological, and socia-economical aspects of the incident, fate, and environmental impact of oil spills. After reviewing the existing models, future research needs are suggested. In the study, available oil spill models are separated into oil spill incident, oil spill fate and behavior, environmental impact and risk, and contingency planning models. The processes of the oil spill fate and behavior are reviewed in detail and the characteristics of existing oil spill fate and behavior models are examined and classified so that an ideal model may be identified. Finally, future research needs are discussed.