• International conference on construction engineering and project management
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• 2011.02a
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• pp.58-65
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• 2011

Construction Productivity is one of the most important elements in construction management. It is used in construction process scheduling and cost management, which are significant sector in construction management. It is important to make appropriate schedule and monitor how works are done within schedule. But construction project contains uncertainty and inexactitude, modifying construction schedule is being an issue to manage construction works well. Even though prediction and monitoring of productivity can be principal activity, it is hard to predict productivity with manager's experience and a standard of estimate. A large number of factors influencing productivity, such as drawing, construction method, weather, labor, material, equipment, etc. But current calculation of productivity depends on empirical probability, not consider difference of each influencing factor. In this research, the aim is to present a productivity predicting regression model of form work, which includes effectiveness of influences factors. 5 variables existed inside form work are selected by interview and site research based on literature review of existed various productivity influencing factors. The effectiveness and correlation of productivity influencing factors are analyzed by statistical approach, and it is used to make productivity regression model. The finding of this research will improves monitoring and controlling of project schedule in construction phase.

• Korean Journal of Agricultural Science
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• v.32 no.2
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• pp.151-167
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• 2005

In this study, certain factors influencing cherry tomato were estimated using system equations. In addition, the amount of influence to income from each factor was estimated from both direct and indirect effects. Based on OLS(Ordinary Least Squares) estimation, path analysis and factor analysis were employed to overcome multicollinearity problems. Data used in this study is interviewed cross sectional data of 65 cherry tomato producing farm in Chungnam-do area. Average age of the producers is 46.5. Average year of the production is 8 years. Average farm size, productivity, and income are 1,123 pyong, 7,439kg/10a, 8,112,000won/10a, respectively. The business performance of the sample farms were above average, in terms of the diagnosis by "Standard Business Diagnosis for Cherry tomato". To identify the factors influencing productivity, 15, 19, and 25 independent variables were selected for the dependent variables of yield, price(quality), and business cost, respectively. Finally, yield, quality, and business cost variables were set as independent variables to explain income as dependent variable. As a result of main factor analysis, 10, 12, 15, and 16 factors were identified as main factors for yield, quality, business cost, and income, respectively.

• Journal of Construction Engineering and Project Management
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• v.7 no.3
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• pp.39-55
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• 2017

Preeminent performance of construction industry are unattainable with poor productivity resulting in time and cost over runs. Enhancement in productivity cannot be achieved without identifying and analyzing factors that adversely affect productivity. The objective therefore is to propose a productivity analysis model to quantify the probability of effect of factors influencing productivity by using fuzzy logic incorporated with relative importance index method, for various types of construction projects. To achieve this objective, a questionnaire survey was carried out targeting respondents of Indian construction industry, from four distinct projects, namely, residential, commercial, infrastructure and industrial projects. Based on questionnaire administered, the relative importance and ranks of factors demonstrated using relative importance index method. Probability assessment model to analyze productivity was then developed by using Fuzzy Logic Toolbox of MATLAB. The applicability of the proposed model was tested in seven construction projects and the probability of impact of factors on productivity evaluated. The results of application of model in the construction firms infers that the most contributing factor groups for most of the projects were discerned to be manpower, motivation and time group.

• Proceedings of the Korean Society for Quality Management Conference
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• 2010.04a
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• pp.62-66
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• 2010

Company which produce the latest plastic products of survival dimension for competitive power security productivity elevation activity hard do. But enterprises is lacking value elevation activity that customer among product special quality is thinking heftily and isn't grasping well adjusted impact factors. So, addition quality failure cost is produced. In this research, investigated impact factor and factors influencing most heftily in quality for productivity elevation. As a result, present example that serve to control well importance benevolence.

• Knowledge Management Research
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• v.17 no.1
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• pp.49-72
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• 2016

Extant research on firm innovation productivity is limited in measuring the innovation productivity, in which they measured firm innovation productivity by using either inputs or outputs of innovation. The present study complemented the extant research by employing Data Envelopment Analysis (DEA) approach to measure firm innovation productivity. Furthermore, this paper examined the effects of firms' external knowledge search, as one of open innovation practices, on firm innovation productivity, for open innovation activities are regarded as an influencing factor on firm innovation productivity in the previous literatures. Using the data of the Korean Innovation Survey (KIS) of manufacturing industries conducted in 2008, this study developed hypotheses in which we considered not only two dimensions of external knowledge search (breadth and depth) but also two subtypes of external knowledge search (market-driven and science-driven). The results found that searching deeply and market-driven search are positively related to firm innovation productivity, but science-driven search is somewhat negatively related to firm innovation productivity. Furthermore, market-driven search can mitigate the negative effect of science-driven search on innovation productivity.

• Environmental and Resource Economics Review
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• v.23 no.4
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• pp.667-688
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• 2014

This research tested the EKC (Environment Kuznets Curve) Hypothesis using the $CO_2$ Emissions by region and GRDP. We built the panel data set on the 15 local government region from 1990 to 2010 for this analysis. GRDP, population and total factor productivity was considered as the factors influencing on the regional $CO_2$ Emissions. Analysis method in this research is panel GLS model as Lantz and Feng (2006). The results show that the EKC hypothesis did not hold in Korea but there is inverted U relationship between the $CO_2$ Emissions and total factor productivity. As the total factor productivity grows, the $CO_2$ increased but decreased after a certain level.

• Journal of Korean Society for Quality Management
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• v.30 no.4
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• pp.154-163
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• 2002

This study tries to analyze how TPM works in domestic manufacturing industry by estimating two-stage model. First stage tests the effects of five TPM-factor variables (TFV : (1) Small group activity & Autonomous maintenance, (2) Education & Training, (3) Planned maintenance, (4) improving effectiveness of each piece of facility (5) Safety & Environment) to two TPM-performance variables. Second stage tests how two TPVs affect the industry's productivity level. By combining these two stages, this study uses a model to explain how TPM, represented by TFVs, works to improve productivity via TPVs. Multivariate and univariate regression and correlation analyses were peformed. It is shown that five TFVs works in two different ways to improve the industry's productivity level. In the second stage, overall equipment effectiveness has relatively more significant effects to the productivity level.

• Korean Journal of Construction Engineering and Management
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• v.9 no.4
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• pp.92-100
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• 2008

Productivity is acknowledged as a very important factor for successful construction projects. Various data items collected daily form a construction site can be used for monitoring its productivity by analyzing them. However, no analytical methods for that purpose have been established in the domestic construction industry yet. Previous researches that utilized OLAP and data mining to analyze the factors that affect the productivity did not do well with predicting future cases with sufficient reliability. This research therefore proposes a new analytical process which is capable of figuring out the factors that would affect the productivity of future projects, through qualitative and quantitative analysis of the data collected from past projects.

• Journal of Preventive Medicine and Public Health
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• v.24 no.3 s.35
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• pp.400-413
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• 1991

The purpose of this paper is to identify factors affecting the optimum mix of required inputs and other relevant factors which account for the variation in physician's productivity in general hospitals, and to find out their implications for the efficient health planning and management. An extended version of Cobb-Douglas production function and cross sectional data of one day patient census from all general hospitals in Korea in 1988 were used in the analysis. Main results of the analysis and their implications could be summarized as follows : (1) The production function for physician's inpatient service shows the evidence of economies of scale, but the production function for physician's outpatient and adjusted-patient service, which combines both out- and in-patient service, shows that of dis-economies of scale. (2) The physician's role for production for all service is smaller than auxiliary personnel's, which imply that more intensive utilization of nurses, nursing aides and other auxiliary personnel is desirable for improving general hospital productivity (3) In case of physician's inpatient and adjusted-patient service, nurses' role is greater than nursing aides'. Therefore, more extensive utilization of nurses is recommended for the efficient operation of general hospitals. (4) The factor of hospital beds plays the leading role among required inputs in the production for physician's in- and adjusted-patient service. (5) The physician's productivity of general hospitals in rural area is lower than that in urban area. And the productivity of teaching hospitals is lower than that of the other hospitals. Further analysis was made in physician production function based upon the size of hospitals, namely those hospitals below 250 beds and those above. Explained variances by the factor of hospital beds was significantly increased in the case of those hospitals above 250. A more detailed and thorough investigation is needed for verifying factors influencing physician's productivity in general hospitals in Korea.

• The Journal of the Korea Contents Association
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• v.18 no.11
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• pp.571-580
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• 2018

The purpose of this study is to evaluate the productivity of elderly employees over 60 years old and to analyze factors that directly or indirectly affect the productivity of elderly employees, based on empirical facts of HR managers. As a result, the factors that have a positive effect on the productivity of elderly employees were attitude and professionalism. The decline in physical capacity due to aging was recognized as a key factor that negatively affected the productivity evaluation of elderly employees. Among the management strategies to improve the work performance, it has been shown that work placement or job redesign according to physical competency contributes to improving the productivity of elderly employees. Also, providing safety education and communication opportunities among workers has a positive effect on productivity improvement. The results of this study suggest that it is important to improve worker productivity by arranging older workers' work experience to be able to demonstrate their accumulated career and expertise and to create a working environment that takes into account physical competence.