• Journal of Information Technology Applications and Management
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• v.16 no.1
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• pp.169-183
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• 2009

The purpose of this research, based on the Media Selection Theory, the Technology Acceptance Model, and the Social Influence Theory, is to investigate the influential factors that affect media selection in banking transactions. Analyses showed that for location sensitive bank windows and ATMs(automatic teller machines), defined as offline-based transaction channels, convenience was the variable affecting media selection. However, in the case of online media not related to location, (phone banking, internet banking, and mobile banking) reliability was the significant variable influencing use. The findings show that banking organizations may benefit from identifying traits of media affecting use, and should differentiate customer services for competitive advantage.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.235-235
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• 2022

Genome selection is a promising tool for plant and animal breeding, which uses genome-wide molecular marker data to capture large and small effect quantitative trait loci and predict the genetic value of selection candidates. Genomic selection has been shown previously to have higher prediction accuracies than conventional marker-assisted selection (MAS) for quantitative traits. In this study, the prediction accuracy of 10 agricultural traits in the wheat core group with 567 points was compared. We used a cross-validation approach to train and validate prediction accuracy to evaluate the effects of training population size and training model.As for the prediction accuracy according to the model, the prediction accuracy of 0.4 or more was evaluated except for the SVN model among the 6 models (GBLUP, LASSO, BayseA, RKHS, SVN, RF) used in most all traits. For traits such as days to heading and days to maturity, the prediction accuracy was very high, over 0.8. As for the prediction accuracy according to the training group, the prediction accuracy increased as the number of training groups increased in all traits. It was confirmed that the prediction accuracy was different in the training population according to the genetic composition regardless of the number. All training models were verified through 5-fold cross-validation. To verify the prediction ability of the training population of the wheat core collection, we compared the actual phenotype and genomic estimated breeding value using 35 breeding population. In fact, out of 10 individuals with the fastest days to heading, 5 individuals were selected through genomic selection, and 6 individuals were selected through genomic selection out of the 10 individuals with the slowest days to heading. Therefore, we confirmed the possibility of selecting individuals according to traits with only the genotype for a shorter period of time through genomic selection.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.56
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• pp.3-27
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• 2012

The purpose of this thesis is to develop a relational model which can explain consumer selection for exporting goods and analyze the effect of corporate image on the relations between country image and consumer selection under global trade environment. The specific objectives are as follows: 1) to suggest a concept of consumer selection and measurement criteria, 2) to analyze correlations among country image, corporate image and consumer selection and 3) to find out the effect of corporate image on the relations between country image and consumer selection. The SPSS program for window and LISREL program were used to analyze the data for this study. The statistical method used in this study was the covariance structure analysis estimating parameters by maximum likelihood method. Path coefficients were tested for t-tests with a statistical significance level of .05. The conclusions of this study are as follows. First, significant correlations were observed among all sub-variables proposed in this study. In addition, significant correlations were detected among country image, consumer selection and corporate image. Second, a hypothetical model proposed in this study was mostly appropriate. Country image had a positive direct effect on consumer selection and corporate image with statistical significance. In addition, it has an indirect impact on consumer selection with statistical significance with corporate image as an intervening variable. Third, corporate image had a significant moderation effect in country image-consumer selection relations. As corporate image levels increased, the effect of country image on consumer selection increased as well. In other words, it has been confirmed that if corporate image levels are high, country image could end up with consumer selection.

• The Journal of the Korea Contents Association
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• v.13 no.6
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• pp.401-411
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• 2013

Selection of profitable research and development (R&D) projects is one of the major factors affecting sustained growth of firms and countries. This paper analyze what influences the knowledge on the business model exerted on selection of a R&D project. A business model converts the technology value to the customer value, and comprehensively describes the target customers for commercializing a new technology, core values, behaviors within organizations, resources, and external partners. Thus, understanding a business model would make R&D project evaluators place the feasibility and profitability of the business above the merits of the proposed technology in evaluating the technology development. To verify this hypothesis, we had 78 R&D project evaluators acquire the knowledge on the business model and measured how their criteria for R&D project selection have changed using the AHP method. The results shows that feasibility and profitability are more important than the merit of proposed technology, especially capability of company and business development are more important than the levels of technology innovation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.3
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• pp.501-509
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• 2011

In this paper, we offer a new strategic Portfolio Model for national IT R&D project selection in Korea. A risk and return (R-R) Portfolio Model was developed using an objectively quantified index on the two axes of risk and return, in order to select a strategic project and allocate resources in compliance with a national IT R&D strategy. We strategize using the R-R Portfolio Model to solve the non-strategy and subjectivity problems of the existing national R&D project selection Model. We also use the quantified evaluation index of the IT technology road map (TRM) and the technology level Survey (TLS) for the subjectivity of project selection, and try to discover the weights using the analytic hierarchy process (AHP). In addition, we intend to maximize the chance for a successful national IT R&D project, by selecting a strategic Portfolio project and balancing the allocation of resources effectively and objectively.

• The Journal of Information Systems
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• v.14 no.1
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• pp.171-195
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• 2005

The current study investigates major factors which influence the consumer's selection of internet shopping malls. Based on the technology acceptance model(TAM)(Davis, 1989) and trust theory(McKnight & Chervany, 2001), consumer selection factors from marketing research(Burke, 1997;Dodds et al, 2001), perceived usefulness, perceived ease of use, trust, service quality, and product price were hypothesized as to affect the consumer's decision to choose one's specific internet shopping malls. The study developed a research model to explain the shopping mall selection and collected the survey responses from 312 internet shopping mall users. The results of the current research indicate that all the research variables employed in the study, perceived usefulness, perceived ease of use, trust, service quality, and product price, are found to significantly influence the consumer's shopping mall selection decision. Among the influencing factors, price, service quality, and trust showed a greater effect on the shopping mall selection than usefulness and ease of use. This result implies that purchase-related variables such as price and service quality may be more critical to attracting customers and thereby raising the sales volume of the shopping mall, than the web site's usefulness and ease of use.

• Journal of Construction Engineering and Project Management
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• v.6 no.3
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• pp.1-7
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• 2016

The purpose of this paper is to develop a model for selecting the best contractor in the Gaza Strip using the Artificial Neural Network (ANN). The contractor's selection methods and criteria were identified using a field survey. Fifty four engineers were asked to fill a questionnaire that covers factors related to the selection criteria of contractors practiced in Gaza Strip. The results shows that the dominant part of respondents (91%) confirmed that the current awarding method "the lowest bid price" is considered one of the major problems of the construction sector, "award the bid to the highest weight after combination of the technical and financial scores" represented 50% of the respondents. The criteria weights were determined based on Relative Importance Index (RII. Ninety-one tenders(13 projects) were used to train and test the ANN model after re-evaluating the contractors depend on the weights of factors to select the best contractor who achieves the highest score. Neurosolution software was used to train the models. The results of the trained models indicated that neural network reasonably succeeded in selection the best contractor with 95.96% accuracy. The performed sensitivity analysis showed that the profitability and capital of company are the most influential parameters in selection contractors. This model gives chance to the owner to be more accurate in selecting the most appropriate contractor.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.18 no.1
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• pp.59-67
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• 2009

The purpose of this study is to provide a decision support to select an appropriate layered manufacturing(LM) machine that suits the application of a part. Selection factors include concept model, form/fit/functional model, pattern model far molding, material property, build time and part cost that greatly affect the performance of LM machines. However, the selection of a LM is not an easy decision because they are uncertain and vague. For this reason, the aim of this research is to propose hybrid multiple attribute decision making approaches to effectively evaluate LM machines. In addition, because subjective considerations are relevant to selection decision, a fuzzy logic approach is adopted. The proposed selection procedure consists of several steps. First, we identify LM machines that the users consider After constructing the evaluation criteria, we calculate the weights of the criteria by applying the fuzzy Analytic Hierarchy Process(AHP) method. Finally, we construct the fuzzy Technique of Order Preference by Similarity to Ideal Solution(TOPSIS) method to achieve the ranking order of all machines providing the decision information for the selection of LM machines.

• Journal of applied mathematics & informatics
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• v.14 no.1_2
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• pp.377-386
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• 2004

A technique that provides prediction intervals based on a model called an empirical linear model is discussed. The technique, high-dimensional empirical linear prediction (HELP), involves principal component analysis, factor analysis and model selection. HELP can be viewed as a technique that provides prediction (and confidence) intervals based on a factor analysis models do not typically have justifiable theory due to nonidentifiability, we show that the intervals are justifiable asymptotically.

• Bulletin of the Korean Mathematical Society
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• v.42 no.2
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• pp.397-404
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• 2005

In this note, we characterize the limiting diffusion of a diploid model by defining the discrete generator for the resealed Markov chain. We conclude that this limiting diffusion model is with uncountable state space and mutation selection and special 'mutation or gene conversion rate'.