• KDI Journal of Economic Policy
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• v.32 no.4
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• pp.75-114
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• 2010

This paper examines empirically whether information and communication technology(ICT) has improved total factor productivity at industry level in Korea, considering time lag between ICT capital accumulation and improvement of productivity. To evaluate if ICT is pervasive enough to raise productivity, ICT capital stock of Korea is compared with those of advanced economies. From the perspective of aggregate economy, the ICT capital in Korea has increased fast since the mid-1990s and became comparable with advanced economies. However it is mostly attributed to rapid growth of ICT-producing industries. In other industries, ICT capital are still less accumulated than advanced economies. Growth accounting results exhibit that the productivity has risen faster since 2000 in industries using ICT intensively, but looking into specific industries, it is not likely for ICT to be the main factor of productivity improvement except in business service industry. Regression results provide some evidence that ICT is useful in raising productivity only after considerable amount of time allowed. To fully exploit the positive effect of ICT on productivity, it may be necessary for the Korean economy to create institutional environment facilitating complementary innovations as well as ICT captial accumulation.

• Spatial Information Research
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• v.9 no.2
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• pp.341-352
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• 2001

This study was carried out to developed that appraisement model of Potential Productivity Index(PPI). PPI model was used Farmland Productivity Index(FPI) and Labor Productivity Index(LPI) by GIS, and PPI model applied to farm land consolidation region which has been completed recently. FPI was determined by overlapping Poly Grid of the soil properties at the analyzed project region. LPI was estimated by addition productive wages ratio of total direct productive cost. Addition productive wages determined by GIS Network analysis GIS Network analysis of working distance between farm house to paddy and each paddy. PPI variation of each the analyzed paddy of Masu and Weoncheon region was 0.967~0.780 respectively, and could be showed relative largely PPI value. PPI will provide basic element for large scaling and gathering of farm land and a substitute lot of farm land consolidation, and will be maximize productivity of paddy.

• Journal of KIBIM
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• v.9 no.3
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• pp.30-40
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• 2019

Extraction of fabrication documents is very important because it provides information related to tasks of fabrication and construction. Therefore, in the case of a prefabricated member such as a steel structure, it is necessary to improve the productivity of fabrication documents through 3D BIM. However, research and evidence data on direct comparison analysis of 3D BIM-based documents extraction versus 2D CAD-based documents extraction are hard to find. Thus, this study focuses on productivity analysis of 3D BIM based fabrication documents extraction. In this study, the productivity data of fabrication documents extraction for module construction of EPC project was analyzed. For the productivity analysis, a case study on the fabrication documents of Module A (1,965 sheets) and Module B (1,216 sheets) was conducted. Fabrication documents for each module include general arrangement drawing, assembly drawing, single part drawing and single plate drawing. Comparison of 2D CAD based fabrication documents extraction and 3D BIM based fabrication documents extraction, the productivity for the entire work was improved from 17 hours to 16 hours for Module A and 12 hours to 7 hours for Module B. Especially, the productivity of the assembly drawings, which occupies a large part of the fabrication documents, was improved by about 48.75% from the total time required from 281 hours to 144 hours.

• Journal of the Korea Society of Computer and Information
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• v.20 no.1
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• pp.237-246
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• 2015

In this paper, Improved productivity models of container terminal are provided by utilizing a simulation considering Tandem-lift Quay Crane and transport vehicle of container's high productivity 'Alternative ship-to-yard vehicles.' Feature of this method is deriving the data of tandem-lift Quay Crane and Alternative ship-to-yard vehicles, estimating the productivity model of tandem-lift Quay Crane by using regression analysis. Tandem-lift Quay Crane is equipment of loading and unloading to increase productivity approximately by 2 time existing (single, twin) Quay Crane by dealing with four 20ft containers or two 40ft containers at the same. Alternative ship-to-yard vehicles can transfer containers(4TEU) more than existing Yard Tractor. This paper is deriving the optimal combination showing the highest productivity by using simulation considering Tandem-lift Quay Crane and Alternative ship-to-yard vehicles on container terminals and developing estimating model of productivity by using regression analysis using data of simulation.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2016.05a
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• pp.74-75
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• 2016

The success of the domestic construction project is mostly judged by process and costs. It can raise the accuracy of the process and costs through productivity measurement and management. System which can increase the productivity and efficiency is required at this moment. The purpose of this study is to introduce the case of measuring productivity system using the Digital Pen System. To utilize Digital Pen System can raise construction productivity. This system is expected to more efficient to accumulation and utilization of construction site information.

• Korean Journal of Construction Engineering and Management
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• v.9 no.5
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• pp.86-94
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• 2008

Productivity is one of key management indexes for evaluating soundness of a manufacturing organization and its efficiency. In many aspects of productivity management in the construction industry, however, intuition of an experienced field manager still plays a greater role while productivity data is not utilized efficiently for the construction management purposes, because the collection and analysis of the productivity-related information are not systematic. Lack of systematic method in collecting and analyzing the productivity data results in such problems. The existing WBS should therefore be improved to solve them. The authors developed a new WBS for productivity data collection and analysis by following the research direction that was determined by literature reviews, overseas cases, and interviews with field engineers. The new breakdown structure was then evaluated for its feasibility as a productivity analysis framework. It is expected that the productivity data collected by the WBS will be used for OLAP and mining for future productivity forecast.

• Journal of Environmental Impact Assessment
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• v.7 no.2
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• pp.37-51
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• 1998

This study was carried out to lead the scientific management of the urban forest by estimating the forest environment. Forest environmental information was constructed using IDRISI system based on survey data, soil, plant, and digital elevation data. Forest environmental information was consisted of soil depth, soil organic content, soil hardness and parent rock as a soil environmental factor, and forest community, tree age, crown density as a plant environmental factor. Plant activity and topographic environment also were analyzed by using remote sensing data and digital elevation data. Environmental function of urban forest was estimated based on results of soil conservation and forest productivity. 70% of urban forest is located in elevation of lower than 200m and 55% of forest area have the slope of lower than 15 degree. Analyzed soil conservation status and forest productivity were almost the same as the soil chemical properties of collected soil sample and the vegetation index estimated using remote sensing data, respectively. Thus, the constructed forest environmental information could be useful to give some ideas for management of urban forest ecosystem and establishment of environmental conservation planning, including forests, in Taejon. The best forest environmental function was appeared at the natural ecology preservation zone. Current natural parks and urban parks were appeared to establish the environmental conservation plan for further development. The worst forest environmental function was appeared at the forest near to the industrial area and an overall and systematic plan was required for the soil management and high forest productivity because these forest was developing a severe soil acidification and having a low forest productivity.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.927-939
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• 2020

This study aims at investigating the effects of internal control effectiveness on business survival of food businesses in Thailand through the mediators of productivity improvement and value creation. In this study, 155 food businesses in Thailand are the samples of the study. The results show that internal control effectiveness has a significant influence on productivity improvement and business survival. Productivity improvement critically affects value creation and business survival while value creation is an important determinant of business survival. However, internal control effectiveness has no relationship with value creation. Also, productivity improvement explicitly mediates the internal control effectiveness-business survival relationships. In summary, internal control effectiveness can enhance firms' sustainable competitive advantage, superior performance and long-term survival. Firms need to focus on internal control effectiveness through investing their assets and resources and utilizing their abilities, competencies and capabilities in order to continuously develop and improve their appropriate concepts and characteristics in an organization. Better internal control effectiveness definitely leads to more long-term survival. To generalize the research results, future research needs to collect data from other businesses and industries. Increased response rate of the study is important for future research to verify and confirm the research results.

• Agribusiness and Information Management
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• v.7 no.2
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• pp.12-18
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• 2015

Since 2000s, proper utilization of IoT (Internet of Things) technology is a key factor for a firm to become more competitive, and this stream is not exceptional for the food and agriculture industry. Along with this stream, Korea government organization, for example MAFRA (Ministry of Agriculture, Food and Rural Affairs), elected to adopt IoT technology, such as USN and RFID technologies, in the food and agriculture industry. Based on the IoT technology, MAFARA launched six "IoT based farm" project in 2007. IoT based farm project includes IoT based greenhouse system project, and it shows drastic efficiency in terms of cost reduction. When it comes to the productivity, however, the effect of IoT based greenhouse system is still ambiguous. In this regard, this study conducted systems analysis and design for IoT based tomato greenhouse in order to help farmers' decision making related to the productivity by establishing standardized database structure and designing output form to analyze productivity indices. Proposed systems analysis and design can be utilized as a data analysis tools by farmers. Productivity data from the proposed systems is can be used by researchers to identify the relationship among environment, plant growth and productivity. Policy makers also can refer to the data and output forms to predict the quantity of fruit during certain period and to revise production guideline more precisely.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.484-487
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• 2022

This study suggests an XAI-based machine learning method to predict the productivity of tight oil reservoirs according to the production period. The XAI algorithm refers to interpretable artificial intelligence and provides the basis for the predicted result and the validity of the derivation process. In this study, we proposed a supervised learning model that predicts productivity in the early and late stages of production after performing data preprocessing based on field data. and then based on the model results, the factors affecting the productivity prediction model were analyzed using XAI.