• 한국경영과학회지
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• 제42권1호
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• pp.53-63
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• 2017

Managing the quantitative measurement of the data control activities in enterprise wide is important to secure management of data governance. However, research on data governance is limited to concept definitions and components, and data governance research on evaluation models is lacking. In this study, we developed a model of quantitative assessment for data governance including the assessment area, evaluation index and evaluation matrix. We also, proposed a method of developing the model of quantitative assessment for data governance. For this purpose, we used previous studies and expert opinion analysis such as the Delphi technique, KJ method in this paper. This study contributes to literature by developing a quantitative evaluation model for data governance at the early stage of the study. This paper can be used for the base line data in objective evidence of performance in the companies and agencies of operating data governance.

• 정보기술과데이타베이스저널
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• 제3권2호
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• pp.97-118
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• 1996

Information systems quality engineering is one of the most problematic areas in practice and research, and needs cooperative efforts between practice and theory [Glass, 1996]. A model for evaluating the quality of system development process and ensuing success is proposed based on information processing theory of project unit design. A nomological net among a set of quality variables is identified from prior research in the areas of organization science, software engineering, and management information systems. More specifically, system development success was modelled as a function of project complexity, system development modelling environment, user participation, project unit structure, resource availability, and the level of iterative nature of development methodology. Based on the model developed from the information processing theory of project unit design in organization science. appropriate quality metrics for each variable in the proposed model are matched. In this way, a framework of relevant systems development and success quality metrics for controlling systems development processes and ensuing success is proposed. The causal relationships among the constructs in the proposed model are proposed as future empirical research for academicians and as managerial tools for quality managers. The framework and propositions help quality manager to select more parsimonious quality metrics for controlling information systems development processes and project success in an integrated way. Also this model can be utilized for evaluating software quality assurance programmes, which are developed and marketed by many vendors.

• 한국물환경학회지
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• 제31권6호
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• pp.653-664
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• 2015

TPLMS (Total water pollutant load management system) that is the most powerful water-quality protection program have been implemented since 2004. In the implementation of TPLMS, target water-quality and permissible discharged load from each unit watershed can be decided by water-quality modeling. And NPS (Non-point sources) discharge coefficients associated with certain (standard) flow are used on estimation of input data for model. National Institute of Environmental Research (NIER) recommend NPS discharge coefficients as 0.15 (Q₂₇₅) and 0.50 (Q₁₈₅) in common for whole watershed in Korea. But, uniform coefficient is difficult to reflect various NPS characteristics of individual watershed. Monthly NPS discharge coefficients were predicted and estimated using surface flow and water-quality from HSPF watershed model in this study. Those coefficients were plotted in flow duration curve of study area (Palger stream and Geumho C watershed) with monthly average flow. Linear regression analysis was performed about NPS discharge coefficients of BOD, T-N and T-P associated with flow, and R² of regression were distributed in 0.893~0.930 (Palger stream) and 0.939~0.959 (Geumho C). NPS Discharge coefficient through regression can be estimated flexibly according to flow, and be considered characteristics of watershed with watershed model.

• Water Engineering Research
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• 제3권2호
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• pp.143-153
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• 2002

As the natural flows in rivers dramatically decrease during drought season in Korea, a deterioration of river water quality is accelerated. Thus, consideration of downstream water quality responding to changes in reservoir release is essential for an integrated watershed management with regards to water quantity and quality. In this study, water quality models based on artificial neural networks (ANNs) method were developed using historical downstream water quality (rm $\NH_3$-N) data obtained from a water treatment plant in Geum river and reservoir release data from Daechung dam. A nonlinear multiple regression model was developed and compared with the ANN models. In the models, the rm NH$_3$-N concentration for next time step is dependent on dam outflow, river water quality data such as pH, alkalinity, temperature, and rm $\NH_3$-N of previous time step. The model parameters were estimated using monthly data from Jan. 1993 to Dec. 1998, then another set of monthly data between Jan. 1999 and Dec. 2000 were used for verification. The predictive performance of the models was evaluated by comparing the statistical characteristics of predicted data with those of observed data. According to the results, the ANN models showed a better performance than the regression model in the applied cases.

• 지식경영연구
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• 제3권1호
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• pp.1-18
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• 2002

Many organizations implement knowledge management initiates by developing knowledge management systems. This study aims at investigating knowledge sharing behaviors in a knowledge management system and identifying factors affecting such behaviors. To do this, we defined knowledge sharing behaviors in a knowledge management system as registration and view of knowledge at a system. Based on this definition, we established a research model by identifying seven factors affecting both behaviors as independent variables: Learning orientation, Pressure to share knowledge, Top management support, Reward for knowledge sharing, Level of experience in IT, System quality, and Knowledge quality. The 14 hypotheses derived from a research model were tested by a correlation analysis and a multiple regression analysis with data from 165 respondents of the 21 organizations which implemented knowledge management initiatives. As results, both of knowledge registration and knowledge review were strongly affected by the learning-orientedness of an organization. Finally, we discussed results and limitations of this study.

• 한국경영과학회지
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• 제42권1호
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• pp.65-77
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• 2017

The purpose of this paper is to develop a model of level evaluation for data governance that can diagnose and verify level of insufficient part of operating data governance. We expanded the previous study related on attribute indices of data governance and developed a level model of evaluation and items. The model of level evaluation for data governance is the level of evaluation and has items of 400 components. We used previous studies and expert opinion analysis such as the Delphi technique, KJ method in this paper. This study contributes to literature by developing a level evaluation model for data governance at the early phase. This paper will be used for the base line data in objective evidence of performance in the companies and agencies of operating data governance.

• 품질경영학회지
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• 제29권1호
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• pp.140-159
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• 2001

The purpose of this study is to analyse the effectiveness of Quality Leadership on the Business Performance through Quality System for Manufacturing Companies in the North-east China, and research into the model of Quality Leadership is related with the Business Performance. A new questionnaire of QM based on Conti's Quality System thesis, was developed and tested. A statistical analysis of data was collected from Manufacturing Firms in the North-east China. As a result, Quality Leadership is the important drivers of Total Quality Management, and is related with the Quality System. Then, the Quality System is directly related with process, and process is also related with the Product Quality and the Business Performance. Of course, the Product Quality is directly related with the Business Performance in the end.

• 융합경영연구
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• 제11권2호
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• pp.1-11
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• 2023

Purpose: With the rapid development of e-commerce, logistics services, as an important part of e-commerce shopping, have gradually attracted people's attention. Customer engagement behavior is a new topic in marketing, and its connotation is still being explored. The purpose of this paper is to study the relationship between logistics service quality and customer engagement behavior. Research design, data and methodology: This study employed the method of online questionnaire survey, with Chinese e-commerce platform users as the survey objects, 248 valid survey sample data were collected, and the method of factor analysis and structural equation model analysis was used to verify the research hypothesis model constructed in this paper. Results: The four dimensions of e-commerce logistics service quality have different influences on customer satisfaction, and the influence of availability on customer satisfaction is not significant. Convenience, assurance, and security have a significant positive impact on customer satisfaction; Customer satisfaction has a significant positive impact on the three dimensions of customer engagement behavior: customer repeat purchase behavior, online word-of-mouth, and customer referrals. Conclusion: The results of this study will provide useful reference for the managers of e-commerce companies to improve customer engagement behavior by improving the logistics service quality.

• 경영과학
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• 제12권2호
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• pp.129-146
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• 1995

As society's relience on computerized information systems to support a wide range of activities proliferates, the long recognized importance for adequate data quality becomes imperative. Furthermore, current trends in information systems such as dispersal of the data resource together with its management have increased the difficulty of maintaining suitable levels of data integrity. Especially, the importance of adequate accounting (transaction) data quality has been long recognized and many procedures (extensive and often elaborate checks and controls) to prevent errors in accounting systems have been introduced and developed. Nevertheless, over time, even in the best maintained systems, deficiencies in stored data will develop. In order to maintain the accuracy and reliability of accounting data at certain level, periodic internal checks and error corrections (internal audits) are required as a part of internal control system. In this paper we develop a general data quality degradation (error accumulation ) and cost model for an account in which we have both error occurrences and error amounts and provide a closed form of optimal audit timing in terms of the number of transactions that should occur before an internal audit should be initiated. This paper also considers the cost- effectiveness of various audit types and different error prevention efforts and suggests how to select the most economical audit type and error prevention method.

• 지식경영연구
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• 제13권1호
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• pp.25-39
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• 2012

According to knowledge-based view, knowledge is an essential strategic resource for a firm to retain sustainable competitive advantage. As knowledge is created and disseminated throughout the firm, the firm can enhance its capability to respond to new and unusual situations. Thus, a lot of companies actively manage their knowledge and intellectual capital. Especially, knowledge management (KM) activities in R&D organizations play a critical role in enhancing R&D performances such as innovation capability. In this regard, this study develops a theoretical model to examine the effects of R&D KM activities on R&D performance. The research model posits KM participation, knowledge management system (KMS) use, and community of practice (CoP) as the main activities of R&D KM. This study proposes that R&D shared knowledge quality and R&D KM satisfaction play a mediating role between R&D KM activities and its performance. The proposed research model was tested by using survey data collected from 248 employees in an R&D department. PLS (partial least squares) was employed for the analysis of the data. The findings of this study showed that R&D KM activities play a significant role in enhancing R&D performance. The findings revealed that R&D shared knowledge quality is not significantly related to R&D performance, while R&D KM satisfaction significantly influences R&D performance. The theoretical and practical implications of the findings were described.