• Journal of Information Technology Applications and Management
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• v.17 no.4
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• pp.107-126
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• 2010

IT capability is one of the main research topics in MIS area. Given the finding that IT investment does not necessarily contribute to better organizational performance, the concept of IT capability was selected as an alternative antecedent variable for IT's effect on performance. A number of existing MIS papers have shown that firms with the high level of IT capability lead to a better performance. However, very little research has been done concerning the issue of how the IT capability could be enhanced. Recently, enterprise architecture effort has been emerged as an avenue to better IT management. This study aims to empirically examine the relationship between EA effort and IT capability.

• Journal of Information Technology Services
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• v.10 no.4
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• pp.191-204
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• 2011

Recently, many software companies are trying to improve the software quality and project outcome with more costs and efforts in development time. In the software convergence and integration environments, it is required efforts to gain high quality of software. In other words, it is required to utilize software engineering knowledge and technology for higher software quality and better software project productivity. The Software development productivity can be varied by software process capability according to building a framework for software development, selection and use of appropriate technology, human resource management. Software process capability will influence software project outcome which is the general opinion. This study provides empirical evidence about software engineering efforts and investment approach to lead software project performance. We measured the software engineering efforts by SW engineering level and analyzed the corelation between software engineering level and schedule deviation. And, we verified that this performance is affected by the size of software company. As a result, software process capability is important to build a infrastructure and develop systematically software project. The higher software engineering level can lead to improved software project performance.

• KIEE International Transactions on Power Engineering
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• v.5A no.3
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• pp.244-251
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• 2005

Power transfer capability has been recently highlighted as a key issue in many utilities. It is determined by the thermal stability, dynamic stability and voltage stability limits of generation and transmission systems. In particular, voltage stability affects power transfer capability to a great extent in many power systems. This paper presents a tool for determining total transfer capability from a static voltage stability viewpoint using IPLAN, which is a high level language used with the PSS/E program. The tool was developed so as to analyze static voltage stability and to determine the total transfer capability between different areas from a static voltage stability viewpoint by tracing stationary behaviors of power systems. A unified power flow controller (UPFC) is applied for enhancing total transfer capability between different areas from the viewpoint of static voltage stability. Evaluation of the total transfer capability of a practical KEPCO power system is performed from the point of view of static voltage stability, and the effect of enhancing the total transfer capability by UPFC is analyzed.

• Journal of the Korea Convergence Society
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• v.9 no.10
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• pp.285-291
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• 2018

The purpose of this study is to identify the effects of consulting participation level, consulting specialty, and consulting capability on consulting intelligibility and consulting performance for Small Medium-sized Enterprises (SMEs).This study performed statistical analysis such as AMOS 22.0 to conduct exploratory factor analysis and measurement model in order to identify interrelationship among the consulting participation level, consulting intelligibility and consulting performance. The results of our study are as follow. Firstly and secondly consulting participation level, consulting specialty and consultant capability has positive effect on consulting performance and consulting intelligibility. Thirdly, consulting intelligibility has non positive effect on consulting performance. According to this survey, it is important to make good consulting performance through consulting participation level, specialty and capability. But the consulting intelligibility is not effected on consulting performance.

• 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.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.722-727
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• 2007

As the world construction market is rearranged by the level of technological capability, recently the technological capability in construction industry is developing rapidly. The important of measuring and analyzing technological capability in construction industry is gaining more and more emphasis. It enables to grasp the past and present situation of construction industry as well as to foresee changes in the future. However the concept of technological capability cannot be identified easily, as well as it is hard to compare that capability of construction industry among different countries. Although there have been numerous studies conducted on the technological capability of construction industry, most of the studies were in formsof surveys of specialists or industry professionals which lacked objectivity and sound basis for data. This study will be focused on investigating the methodology in exploiting and measuring surface of the earth and developing indicator and process to understand technological capability in construction industry through quantitative and statistical analysis. Then it will verify them through a case study.

• Proceedings of the Technology Innovation Conference
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• 1998.06a
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• pp.57-90
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• 1998

This study attempts to explore the evolution paths of Korean SMEs'strategies and their technological teaming processes. Several different evolution paths are identified based on a dynamic strategic group analysis of 115 SMEs'strategy in the Korean electronic component industry for the period of 1990-1995. Further, inadept case analyses on technological learning processes in 5 firms are undertaken. Major findings of this study can be summarized as follows : 1) There are three dominant evolution paths in SMEs'strategy. First path indicates the evolution from a subcontractor or petty imitator group(a strategic group with the narrow product/market domain and the low level of accumulated resource/capabilities) into an innovator group(a strategic group with the narrow domain but high level of technological capability) by accumulating technological capabilities. Second, some firms move from a subcontractor group into a generalizer group(a strategic group with broad product/market domain but relatively low level of technological capability) by simply adding product lines. Third path involves firms which evolve from a subcontractor group into a production focus group(a strategic group with high level of production capability) by investing in production capabilities. 2) An in-depth case analysis shows those who succeeded in technological learning are managed by CEOs, who have technological expertise and strategic vision, and have made an effort to establish management practices to support innovation, such employee educational program, performance-based reward system, etc. The successful firms also aggressively pursue diverse external linkages with outside technology sources to learn product and process technologies. Fiendly, this study discusses several implications of the findings for the theoretical development and strategic management of small firms in Korea.

• Journal of Korean Society for Quality Management
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• v.47 no.4
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• pp.713-723
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• 2019

Purpose: The purpose of this study is to develop a statistical program for capability analysis of measuring system and measurement process based upon KS Q ISO 22514-7. Methods: R is a powerful open source functional programming language that provides high level graphics and interfaces to other languages. Therefore, in this study, we will develop the statistical program using R language. Results: The R program developed in this study consists of the following five modules. ① Measuring system capability analysis with Type 1 study data: MSCA_Type1.R ② Measuring system capability analysis with Linearity study(Type 4 study) data: MSCA_Type4.R ③ Measurement process capability analysis with Type 1 study & Gage R&R study data: MPCA_T1GRR.R ④ Measurement process capability analysis with Type 4 study & Gage R&R study data: MPCA_T4GRR.R ⑤ Attribute measurement processes capability analysis : AttributeMP.R Conclusion: KS Q ISO 22514-7 evaluates measuring systems and measurement processes on the basis of the measurement uncertainty that was determined according to the GUM(KS Q ISO/IEC Guide 98-3). KS Q ISO 22514-7 offers precise procedures, however, computations are more intensive. The R program of this study will help to evaluate the measurement process.

• The Journal of the Korea Contents Association
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• v.17 no.6
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• pp.98-105
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• 2017

The medical institution considers liability management problems as a direct factor in managerial risks, such as bankruptcy. Cash Flow provides useful information to necessary funds and predicting bankruptcy. The study for 24 general hospitals and 23 hospitals, a regression analysis was performed to determine the impact of cash flows on the debt repayment capability, a multivariate discrimination analysis was conducted to find out how to manage cash flow for the risk posed by debt. The analysis results, For general hospitals, the level of debt repayment capability was done to net income, increase of payables from operating activities and decrease of patient receivables and inventories from operating activities. If there is no dept repayment capability, it is necessary to increase the net income, increase the expenses not involving cash outflows, decrease of patient receivables and increase of payables from operating activities. For hospitals, the level of debt repayment capability was done to net income, increase of expenses not involving cash outflows and payables from operating activities, decrease of income not involving cash inflows, decrease of patient receivables and inventories from operating activities. If there is no dept repayment capability, it is necessary to increase of payables from operating activities.

• Asia pacific journal of information systems
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• v.23 no.1
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• pp.87-106
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• 2013

In the service-oriented economy, knowledge and skills are considered core resources to secure competitive advantages and service innovation. Knowledge management capability, which facilitates to produce, share, accumulate and reuse knowledge, becomes as important as knowledge itself to create service value. Along with knowledge management capability, dynamic capability and operational capability are the key capabilities related to managing service delivery processes. Previous studies indicated that these three capabilities are related to service innovation. Although separately investigate the relationship between the three capabilities. The purpose of this study is 1) to define variables that have effects on service innovation including knowledge management capability, dynamic capability and operational capability, and 2) to empirically test to identify relationship among variables. In this study, knowledge management capability is defined as the capability to manage knowledge process. Dynamic capability is regarded as the firm's ability to integrate, build, and reconfigure internal and external competences to address rapidly changing environments. Operational capability refers to a high-level routine that, together with its implementing input flows, confers upon an organization's management a set of decision options for producing significant outputs of a particular type. The proposed research model was tested against the data collected through the survey method. The survey questionnaire was distributed to the managers who participated in an educational program for management consulting. Each individual who answered the questionnaire represented a knowledge based service firm. About 212 surveys questionnaires were sent via e-mail or directly delivered to respondents. The number of useable responses was 93. Measurement items were adapted from previous studies to reflect the characteristics of the industry each informant worked in. All measurement items were in, 5 point Likert scale with anchors ranging from strongly disagree (1) to strongly agree (5). Out of 93 respondents, about 81% were male, 82% of respondents were in their 30s. In terms of jobs, managers were 39.78%, professions/technicians were 24.73%, researchers were 12.90%, and sales people were 10.75%. Most of respondents worked for medium size enterprises (47,31%) in their, less than 30 employees (46.24%) in their number of employees, and less than 10 million USD (65.59%) in terms of sales volume. To test the proposed research model, structural equation modeling (SEM) technique (SPSS 16.0 and AMOS version 5) was used. We found that the three organizational capabilities have influence on service innovation directly or indirectly. Knowledge management capability directly affects dynamic capability and service innovation but indirectly affect operational capability through dynamic capability. Dynamic capability has no direct impact on service innovation, but influence service innovation indirectly through operational capability. Operational capability was found to positively affect service innovation. In sum, three organizational capabilities (knowledge management capability, dynamic capability and operational capability) need to be strategically managed at firm level, because organizational capabilities are significantly related to service innovation. An interesting result is that dynamic capability has a positive effect on service innovation only indirectly through operational capability. This result indicates that service innovation might have a characteristics similar to process innovation rather than product orientation. The results also show that organizational capabilities are inter-correlated to influence each other. Dynamic capability enables effective resource management, arrangement, and integration. Through these dynamic capability affected activities, strategic agility and responsibility get strength. Knowledge management capability intensify dynamic capability and service innovation. Knowledge management capability is the basis of dynamic capability as well. The theoretical and practical implications are discussed further in the conclusion section.