• Journal of Information Technology Applications and Management
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• v.22 no.2
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• pp.171-199
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• 2015

This study proposes the practical information security measures that help IT personnel of banks comply the information security policy. The research model of the study is composed of independent variables (clarity and comprehensiveness of policy, penalty, dedicated security organization, audit, training and education program, and top management support), a dependent variable (information security policy compliance intention), and moderating variables (age and gender). Analyses results show that the information security measures except 'clarity of policy' and 'training and education program' are proven to affect the 'information security policy compliance intention.' In case of moderating variables, age moderated the relationship between top management support and compliance intention, but gender does not show any moderating effect at all. This study analyzes information security measures based solely on the perception of the respondents. Future study may introduce more objective measurement methods such as systematically analyzing the contents of the information security measures instead of asking the respondents' perception. In addition, this study analyzes intention of employees rather than the actual behavior. Future research may analyze the relationship between intention and actual behavior and the factors affecting the relationship.

• Journal of Information Science Theory and Practice
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• v.8 no.2
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• pp.6-17
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• 2020

Word similarity is often measured to enhance system performance in the information retrieval field and other related areas. This paper reports on an experimental comparison of values for word similarity measures that were computed based on 50 intentionally selected words from a Reuters corpus. There were three targets, including (1) co-occurrence-based similarity measures (for which a co-occurrence frequency is counted as the number of documents or sentences), (2) context-based distributional similarity measures obtained from a latent Dirichlet allocation (LDA), nonnegative matrix factorization (NMF), and Word2Vec algorithm, and (3) similarity measures computed from the tf-idf weights of each word according to a vector space model (VSM). Here, a Pearson correlation coefficient for a pair of VSM-based similarity measures and co-occurrence-based similarity measures according to the number of documents was highest. Group-average agglomerative hierarchical clustering was also applied to similarity matrices computed by individual measures. An evaluation of the cluster sets according to an answer set revealed that VSM- and LDA-based similarity measures performed best.

• Journal of Information Technology Services
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• v.12 no.3
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• pp.273-287
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• 2013

The objective of this study is to empirically develop performance evaluation measures for LIS (logistics information systems) based upon BSC (balanced scorecard) model and determine the relative importance among four perspectives of BSC using AHP (analytic hierarchy process) methodology. Above all, forty nine probable measures for evaluating LIS performance were identified through reviewing the previous research related with SCM (supply chain management), logistics management, and information systems evaluation. And then, these probable measures were examined by means of coincidence analyses using three mutually exclusive criteria(validity of content, ease of measurement and reliability of measurement). Data for conducting the coincidence analyses were collected from LIS users and LIS development personnel. As the results of the coincidence analyses, it was found that 31 ones among 49 probable performance evaluation measures theoretically derived could be qualified for LIS performance evaluation. And AHP analysis showed that the weight of each perspective was respectively as follows : 46.8% for financial perspective, 31.3% for customer perspective, 14.8% for internal business process perspective, and 7.1% for learning and growth perspective. The academic contribution of this study is that performance evaluation measures for LIS could be systematically and empirically developed on the basis of BSC. Also, the results of this study are expected to be used as a practice guideline of evaluating and improving LIS.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.8
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• pp.4142-4159
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• 2019

We have developed composite measures of supercomputer technology, reflecting various factors of supercomputers using Martino's scoring model. CPUs, accelerators, memory, interconnection networks, and power consumption are chosen as factors of the model. The weight values of the factors are derived based on a survey of 129 domestic and international experts. The measured values are then standardized to integrate measurement units of the factors in the model. This model has been applied to 50 supercomputers, and rank correlation analysis was performed using representative measures. As a consequence, the ranking drastically changes except for the 1st and 2nd supercomputers on the TOP500. In addition, the characteristics of memory and interconnection networks influence the ranking, and the results demonstrate that the proposed model has low correlations with HPL and HPCG but a high correlation with Green500. This indicates that power consumption is an important factor that has a significant effect on the measures of supercomputer technology. In addition, it is determined that the differences between the HPL ranking and the proposed model ranking are influenced by power consumption, CPU theoretical peak performance, and main memory bandwidth in order of significance. In conclusion, the composite measures proposed in this study are more suitable for comprehensively describing supercomputer technology than existing performance measures. The findings of this study are expected to support decision making related to management and policy in the procurement and operation of supercomputers.

• Journal of the Korean Data and Information Science Society
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• v.18 no.1
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• pp.229-235
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• 2007

Measures of leverage in nonlinear regression models are discussed by extending the leverage in linear regression models. The connection between measures of leverage and nonlinearity of the models are explored. Illustrative example based on real data is presented.

• Journal of applied mathematics & informatics
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• v.34 no.3_4
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• pp.295-308
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• 2016

Depending upon the nature of the problem, different divergence measures are suitable. So it is always desirable to develop a new divergence measure. In the present work, new information divergence measure, which is exponential in nature, is introduced and characterized. Bounds of this new measure are obtained in terms of various symmetric and non- symmetric measures together with numerical verification by using two discrete distributions: Binomial and Poisson. Fuzzy information measure and Useful information measure corresponding to new exponential divergence measure are also introduced.

• IE interfaces
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• v.11 no.3
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• pp.41-53
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• 1998

Several performance measurement systems have been proposed and are currently being used in many organizations. However, no performance measurement system has presented a mechanism for integrating all of the information of performance measures in a way that considers the relationships between them. This paper proposes the performance information integration method (PIIM) which synthesizes all useful information of performance measures with consideration of the relationships and generates a single, global, organizational performance score. The PIIM showed good performance in the implementation in one long-term care facility. This paper provides performance measurement systems with an integration mechanism for multiple performance measures.

• Korean Management Science Review
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• v.16 no.2
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• pp.109-123
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• 1999

We have recognized that an organization should be viewed from a multifaceted perspective necessitating a sophisticated analytical and systematic approach to monitor and improve organizational performance. Although some performance measurement systems have been proposed and are currently being used in many organizations, no performance measurement system has presented a mechanism for integrating all of the information of performance measures in a way that considers relationships between them. This paper introduces the implementation of the performance information integration method(PIIM) which synthesizes all useful information of performance measures with consideration of the relationship and generates a single, global, organizational performance score. The PIIM was empirically validated by implementing in one of missouri Veterans Homes.

• Journal of the Korea Society of Computer and Information
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• v.20 no.12
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• pp.169-174
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• 2015

Permutation p-values are provided for the agreement measures for multivariate interval data among many raters. Three agreement measures, Berry and Mielke's measure, Janson and Olsson's measure, and Um's measure are described and compared. Exact and resampling permutation methods are utilized to compute p-values and empirical quantile limits for three measures. Comparisons of p-values demonstrate that resampling permutation methods provide close approximations to exact p-values, and Berry and Mielke's measure and Um's measure show similar performance in terms of measuring agreement.

• Journal of the Korean Data and Information Science Society
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• v.19 no.4
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• pp.1269-1279
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• 2008

Data mining is the technique to find useful information in huge databases. One of the well-studied problems in data mining is exploration for association rules. An association rule technique finds the relation among each items in massive volume databases by several interestingness measures. An important and useful classification scheme of interestingness measures may be based on user-involvement. This results in two categories - objective and subjective measures. This paper present some relative interestingess measures to compare with degrees of association for two groups. A comparative study with some relative interestingness measures is shown by numerical example. The results show that the relative net confidence is the best relative interestingness measure.