• Journal of the Korean Data and Information Science Society
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• v.18 no.1
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• pp.219-228
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• 2007

In this paper, we consider a decision-theoretic oriented, objective Bayesian inference for the ratio of two normal variances. Specifically we derive the Bayesian reference criterion as well as the intrinsic estimator and the credible region which correspond to the intrinsic discrepancy loss and the reference prior. We illustrate our results using real data analysis and simulation study.

• Culinary science and hospitality research
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• v.23 no.6
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• pp.57-69
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• 2017

In this quantitative research, it was enhanced to understand the impact of intrinsic motivation on creative process engagement by examining the significant role of psychological safety on intrinsic motivation. These relationships were examined by targeting the employees working full-time for five star deluxe hotels. Total number of 230 responses had been collected out of 250 cases requested and he number of 213 cases was used for the final analysis. The data were analyzed using structural equation modeling with SPSS 19.0 and AMOS 7 software program. The results suggested that psychological safety is significantly associated with intrinsic motivation. Furthermore, the hotel employees' problem identification, information searching & coding, and idea generation are affected by intrinsic motivation. That is, intrinsic motivation plays a significant role for each sub-factors of creative process engagement in the hotel industry. The theoretical and practical implications of these findings are established and related suggestion for formulating marketing strategy is well discussed.

• Asia pacific journal of information systems
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• v.15 no.3
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• pp.91-109
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• 2005

According to traditional theories of information systems, one of the reasons for using information technology is that users believe it to be helpful or useful for what they want to do, which is called extrinsic motivation. However, in addition to extrinsic motivation, there are other reasons for using it such as enjoying or playing with information technology itself, called intrinsic motivation, and just others around users, called social influence. The objective of this study is to provide a research model for using information technology considering intrinsic and extrinsic motivation, and social influence. For validation of this model, we survey the users of 'Minihompy' since it is one of the most popular blog services in Korea and there are relatively clear extrinsic and intrinsic motivation, and social influence respectively in using it. By analysing 549 valid samples by Partial Least Square(PLS), we show the suggested research model to be a valid one. That is, all hypotheses we suggested turn out to be statistically significant and $R^2$ of the dependent variable, the intention of use, explaining by the model to be higher than 40%. In addition to validation of the research model, it is found that intrinsic motivation may be more important than extrinsic motivation and social influence in using information technology.

• Journal of the Korean Data and Information Science Society
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• v.17 no.4
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• pp.1365-1374
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• 2006

In this paper, we consider a decision-theoretic oriented, objective Bayesian inference for the difference between two normal means with known variances. We derive the Bayesian reference criterion as well as the intrinsic estimator and the credible region which correspond to the intrinsic discrepancy loss and the reference prior. We show the similarity between derived two-sample results and the results for the one-sample case in Bernardo(1999).

• Journal of the Korean Data and Information Science Society
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• v.15 no.3
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• pp.689-694
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• 2004

We investigate the test for model adequacy in nonlinear regression. We can expect the usual likelihood ratio statistic to be unaffected by any parametric- effect curvature; only the effect of intrinsic curvature needs to be considered. Multiplicative correction factor is derived for the limiting distribution of test statistic, which is a function of the intrinsic curvature arrays.

• Management & Information Systems Review
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• v.20
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• pp.115-135
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• 2007

This study explored how intrinsic and extrinsic motivation relates to achieving creativity at project work. We were interested in differences in how motivational factors relate to creativity. Using data from the 98 engineers and researchers employed by a variety of companies, principal components factor analysis with marimax rotation was performed on the data. We examined effects of the moderate variables the intrinsic and extrinsic motivation and creativity relationship. The results indicate of positive mental involvement, the time and the resource constraints relates positively to creativity in organizations and that the relationship is a simple linear one. These outcomes are significantly related to intrinsic motivation and the creativity. In additions, extrinsic motivation is related to less the creativity. Our survey findings are also consistent with other sources of knowledge on the topic. Our results suggest that there are two different role: mental involvement, time and resources constraints, both of which predict creativity, and external control and extrinsic motivations reduce to creativity.

• Journal of the Korean Data and Information Science Society
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• v.21 no.2
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• pp.297-308
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• 2010

This article deals with the problem of testing mean when the coefficient of variation in normal distribution is known. We propose Bayesian hypothesis testing procedures for the normal mean under the noninformative prior. The noninformative prior is usually improper which yields a calibration problem that makes the Bayes factor to be defined up to a multiplicative constant. So we propose the objective Bayesian hypothesis testing procedures based on the fractional Bayes factor and the intrinsic Bayes factor under the reference prior. Specially, we develop intrinsic priors which give asymptotically same Bayes factor with the intrinsic Bayes factor under the reference prior. Simulation study and a real data example are provided.

• Journal of the Korean Data and Information Science Society
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• v.16 no.4
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• pp.1119-1128
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• 2005

The Bayes factors with improper noninformative priors are defined only up to arbitrary constants. So it is known that Bayes factors are not well defined due to this arbitrariness in Bayesian hypothesis testing and model selections. The intrinsic Bayes factor and the fractional Bayes factor have been used to overcome this problem. In this paper, we suggest a Bayesian hypothesis testing based on the intrinsic Bayes factor and the fractional Bayes factor for the comparison of two lognormal variances. Using the proposed two Bayes factors, we demonstrate our results with some examples.

• Interdisciplinary Bio Central
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• v.2 no.2
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• pp.3.1-3.4
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• 2010

In the present research, we assessed the utility of the structural information of drugs for predicting human in vivo intrinsic clearance from in vitro intrinsic clearance data obtained by human hepatic microsome experiment. To compare with the observed intrinsic clearance, human intrinsic clearance values for 51 drugs were estimated by the classical methods using in vivo-in vitro scale-up and by the new methods using the in vitro experimental data and selected molecular descriptors of drugs by the forward selection technique together. The results showed that taking consideration of molecular descriptors into prediction from in vitro experimental data could improve the prediction accuracy. The in vitro experiment is very useful when the data can estimate in vivo data accurately since it can reduce the cost of drug development. Improvement of prediction accuracy in the present approach can enhance the utility of in vitro data.

• Journal of the Korean Data and Information Science Society
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• v.14 no.3
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• pp.661-671
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• 2003

The Bayes factors with improper noninformative priors are defined only up to arbitrary constants. So, it is known that Bayes factors are not well defined due to this arbitrariness in Bayesian hypothesis testing and model selections. The intrinsic Bayes factor by Berger and Pericchi (1996) and the fractional Bayes factor by O'Hagan (1995) have been used to overcome this problems. This paper suggests intrinsic priors for testing the equality of two lognormal means, whose Bayes factors are asymptotically equivalent to the corresponding fractional Bayes factors. Using proposed intrinsic priors, we demonstrate our results with real example and a simulated dataset.