• Asia pacific journal of information systems
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• v.23 no.3
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• pp.25-53
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• 2013

This study analyzes the effect of Computer Aided Innovation (CAI) to improve R&D Capabilities empirically. Survey was distributed by e-mail and Google Docs, targeting CTO of 235 SMEs. 142 surveys were returned back (rate of return 60.4%) from companies. Survey results from 119 companies (83.8%) which are effective samples except no-response, insincere response, estimated value, etc. were used for statistics analysis. Companies with less than 50billion KRW sales of entire researched companies occupy 76.5% in terms of sample traits. Companies with less than 300 employees occupy 83.2%. In terms of the type of company business Partners (called 'partners with big companies' hereunder) who work with big companies for business occupy 68.1%. SMEs based on their own business (called 'independent small companies') appear to occupy 31.9%. The present status of holding IT system according to traits of company business was classified into partners with big companies versus independent SMEs. The present status of ERP is 18.5% to 34.5%. QMS is 11.8% to 9.2%. And PLM (Product Life-cycle Management) is 6.7% to 2.5%. The holding of 3D CAD is 47.1% to 21%. IT system-holding and its application of independent SMEs seemed very vulnerable, compared with partner companies of big companies. This study is comprised of IT infra and IT Utilization as CAI capacity factors which are independent variables. factors of R&D capabilities which are independent variables are organization capability, process capability, HR capability, technology-accumulating capability, and internal/external collaboration capability. The highest average value of variables was 4.24 in organization capability 2. The lowest average value was 3.01 in IT infra which makes users access to data and information in other areas and use them with ease when required during new product development. It seems that the inferior environment of IT infra of general SMEs is reflected in CAI itself. In order to review the validity used to measure variables, Factors have been analyzed. 7 factors which have over 1.0 pure value of their dependent and independent variables were extracted. These factors appear to explain 71.167% in total of total variances. From the result of factor analysis about measurable variables in this study, reliability of each item was checked by Cronbach's Alpha coefficient. All measurable factors at least over 0.611 seemed to acquire reliability. Next, correlation has been done to explain certain phenomenon by correlation analysis between variables. As R&D capabilities factors which are arranged as dependent variables, organization capability, process capability, HR capability, technology-accumulating capability, and internal/external collaboration capability turned out that they acquire significant correlation at 99% reliability level in all variables of IT infra and IT Utilization which are independent variables. In addition, correlation coefficient between each factor is less than 0.8, which proves that the validity of this study judgement has been acquired. The pair with the highest coefficient had 0.628 for IT utilization and technology-accumulating capability. Regression model which can estimate independent variables was used in this study under the hypothesis that there is linear relation between independent variables and dependent variables so as to identify CAI capability's impact factors on R&D. The total explanations of IT infra among CAI capability for independent variables such as organization capability, process capability, human resources capability, technology-accumulating capability, and collaboration capability are 10.3%, 7%, 11.9%, 30.9%, and 10.5% respectively. IT Utilization exposes comprehensively low explanatory capability with 12.4%, 5.9%, 11.1%, 38.9%, and 13.4% for organization capability, process capability, human resources capability, technology-accumulating capability, and collaboration capability respectively. However, both factors of independent variables expose very high explanatory capability relatively for technology-accumulating capability among independent variable. Regression formula which is comprised of independent variables and dependent variables are all significant (P<0.005). The suitability of regression model seems high. When the results of test for dependent variables and independent variables are estimated, the hypothesis of 10 different factors appeared all significant in regression analysis model coefficient (P<0.01) which is estimated to affect in the hypothesis. As a result of liner regression analysis between two independent variables drawn by influence factor analysis for R&D capability and R&D capability. IT infra and IT Utilization which are CAI capability factors has positive correlation to organization capability, process capability, human resources capability, technology-accumulating capability, and collaboration capability with inside and outside which are dependent variables, R&D capability factors. It was identified as a significant factor which affects R&D capability. However, considering adjustable variables, a big gap is found, compared to entire company. First of all, in case of partner companies with big companies, in IT infra as CAI capability, organization capability, process capability, human resources capability, and technology capability out of R&D capacities seems to have positive correlation. However, collaboration capability appeared insignificance. IT utilization which is a CAI capability factor seemed to have positive relation to organization capability, process capability, human resources capability, and internal/external collaboration capability just as those of entire companies. Next, by analyzing independent types of SMEs as an adjustable variable, very different results were found from those of entire companies or partner companies with big companies. First of all, all factors in IT infra except technology-accumulating capability were rejected. IT utilization was rejected except technology-accumulating capability and collaboration capability. Comprehending the above adjustable variables, the following results were drawn in this study. First, in case of big companies or partner companies with big companies, IT infra and IT utilization affect improving R&D Capabilities positively. It was because most of big companies encourage innovation by using IT utilization and IT infra building over certain level to their partner companies. Second, in all companies, IT infra and IT utilization as CAI capability affect improving technology-accumulating capability positively at least as R&D capability factor. The most of factor explanation is low at around 10%. However, technology-accumulating capability is rather high around 25.6% to 38.4%. It was found that CAI capability contributes to technology-accumulating capability highly. Companies shouldn't consider IT infra and IT utilization as a simple product developing tool in R&D section. However, they have to consider to use them as a management innovating strategy tool which proceeds entire-company management innovation centered in new product development. Not only the improvement of technology-accumulating capability in department of R&D. Centered in new product development, it has to be used as original management innovative strategy which proceeds entire company management innovation. It suggests that it can be a method to improve technology-accumulating capability in R&D section and Dynamic capability to acquire sustainable competitive advantage.

• Journal of Korean Society for Quality Management
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• v.48 no.1
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• pp.149-169
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• 2020

Purpose: This study analyzes the characteristics of the Quality Management performed by SMEs in the Defense Industry in supply chains and analyzes the effect of the continuous improvement activities based on cooperation. Especially, for Military Supplies, the suitability of products is usually decided by judging their conformity to the specification, and from this structural characteristic, this study would analyze the structural relationship of systematic improvement activities with Supply Chain Quality Management(SCQM) and Business Performance(BP). Methods: Continuous improvement activities(CI) have significance as the driver force for the promotion of Quality Management. Thus, this study analyzed the causal relationships from the perspective of the process among CI, SCQM and BP. For an analysis of the structural characteristics and causal relationships among the constituents, AMOS was used, and 297 companies in the Defense Industry were utilized as samples. Results: It turned out that CI had significant impacts on Management Infra(MGT_Infra), Process Management(PM), Human Resources Management(HRM) and Communication(COMU) and had an indirect impact on the enterprises' financial performance through the parameters of HRM and Communication. Meanwhile, it turned out that between CI and non-financial performance, there was a direct effect, and there was also an indirect effect through the variables of the Management Infra and Communication. Conclusion: It turned out that CI had a positive effect on SCQM as a proactive driver and that they had significant relationships with BP(financial, Non-financial), both financial performance and non-financial performance. However, PM did not have a significant relationship of effect with BP because of the character appearing by the evaluation method of military supplies for the conformity to the specifications.

• Journal of Digital Convergence
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• v.7 no.4
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• pp.117-125
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• 2009

Information and computer technology(ICT) readiness in SME(small and medium enterprises) in globalized digital world get much attention due to its capability to reach broader customers and to personalized the products to the clients. The purpose of this study is to compare the readiness of ICT capabilities in SME between Korean firms operated in Qingdao China and Incheon, South Korea. The results of the study are presented and the implication of this comparative research is discussed. It is hoped that the finding of the research would be beneficial to academian and practitioners in China and South Korea.

• Journal of Korean Society for Quality Management
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• v.45 no.4
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• pp.867-888
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• 2017

Purpose: This study suggests a SCQM model for the national Defense field based on earlier studies on the Quality Management of supply chain and to identify critical activities factors of supply chain that makes effect on the business results. Also, this study analyzed moderating effects of performance sharing between businesses which is becoming the big issues with regard to the supply chain cooperation. Methods: A causality of qm activities factor of SCQM model affecting benefit sharing and business performance was analyzed by using structural equation model. A company used in analysis performed a survey by targeting 297 Defense SMEs(weapon-system/non-weapon system). Results: As a result of analyzing the influence relationship between key activity of SCQM on finance performance, it was identified that Management Infra(MI), Process Management(PM), Human Resource Management(HRM), Performance Sharing activity(PS) made significant effect on Financial Performance, and Human Resource Management(HRM) and Performance Sharing(PS) activity made effect on non-financial Performance. Conclusion: The four variables(MI, PM, HRM, PS) of Defense SCQM were significantly effecting Financial performance and two variables(HRM, PS) were significant effected non-Financial performance. We also proved the moderating effect of performance sharing.