• International conference on construction engineering and project management
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• 2022.06a
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• pp.839-846
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• 2022

Traditionally, the construction industry has shown low labor productivity and productivity growth. To improve labor productivity, it must first be accurately measured. The existing method uses work-sampling techniques through observation of workers' activities at certain time intervals on site. However, a disadvantage of this method is that the results may differ depending on the observer's judgment and may be inaccurate in the case of a large number of missed scenarios. Therefore, this study proposes a model to automate labor productivity measurement by monitoring workers' actions using a deep learning-based pose estimation method. The results are expected to contribute to productivity improvement on construction sites.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.154-157
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• 2015

Construction industry still requires a lot of laborers to perform a project despite of advance in technologies, and improving labor productivity is an important strategy for successful project management. Since repetitive construction works exhibits learning effect, understanding laborers' learning phenomenon therefore allows managers to have improved labor productivity. In this context, previous research efforts quantified individual laborer's learning effect, though numerous construction works are performed in group. In other words, previous research about labor learning assumed that sum of individual's productivity is same as group productivity. Also, managers in construction sites need understanding about group learning behavior for dealing with labor performance problem. To address these issues, the authors investigate what variables affect laborers' group level learning process and develop conceptual model as a basic tool of productivity estimation regarding group learning. Based on the result of this research, it is possible to understand forming mechanism of learning within the group level. Further, this research may contribute to maximizing laborers' productivity in construction sites.

• Architectural research
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• v.7 no.2
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• pp.91-96
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• 2005

The purpose of this study is to clarify the reality of labor and capital productivity in the construction industry through an industry-level approach and to analyze the relationship between labor and capital productivity using a Cobb-Douglas production function. According to the research results, the construction industry has shown a very high capital productivity, while labor productivity has kept up a low level during the 1980s and 1990s. The reason was because of the lack of skillful construction workers and the decrease of capital. Meanwhile, the construction productivity has greatly increased since 2000 when there was no change in wages. This was because of a large inflow of low-wage foreign workers while the amount of value added has dramatically increased due to the liberalized sale price of apartment buildings. According to the analysis by the Cobb-Douglas production function, the elasticity coefficient of V/L to K/L in the construction industry had decreased from 1.1663 in the $1^{st}$ period(1971-1988) to 0.4465 in the $2^{nd}$ period(1989-1997), and to 0.1664 in the $3^{rd}$ period(1998-2003). Such a result means that the allocation of labor has gradually increased while the allocation of capital has decreased. Moreover there was a big increase in allocation of labor after 1998 due to the excessive deterioration of capital. In conclusion, in order to raise the construction productivity and to avoid labor-intensive production methods, investment for capital should be more increased. In particular, new machinery and equipment that can actually substitute human labor in construction sites should be more developed and applied to construction sites.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.968-973
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• 2005

The purpose of this study is to clarify the reality of labor and capital productivity in the construction industry through an industry-level approach and to analyze the relationship between labor and capital productivity using a Cobb-Douglas production function. According to the research results, the construction industry has shown a very high capital productivity, while labor productivity has kept up a low level during the 1980s and 1990s. The reason was because of the lack of skillful construction workers and the decrease of capital. Meanwhile, the construction productivity has greatly increased since 2000 when there was no change in wages. This was because of a large inflow of low-wage foreign workers while the amount of value added has dramatically increased due to the liberalized sale price of apartment buildings. According to the analysis by the Cobb-Douglas production function, the elasticity coefficient of V/L to K/L in the construction industry had decreased from 1.1663 in the 1^st period(1971-1988) to 0.4465 in the 2^nd period(1989-1997), and to 0.1664 in the 3^rd period(1998-2003). Such a result means that the allocation of labor has gradually increased while the allocation of capital has decreased. Moreover there was a big increase in allocation of labor after 1998 due to the excessive deterioration of capital. In conclusion, in order to raise the construction productivity and to avoid labor-intensive production methods, investment for capital should be more increased. In particular, new machinery and equipment that can actually substitute human labor in construction sites should be more developed and applied to construction sites.

• Journal of Korea Trade
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• v.25 no.1
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• pp.133-151
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• 2021

Purpose - This study examines the effects of expatriate transfer on foreign affiliate's labor productivity. Design/methodology - Using Korean-owned foreign affiliate-level data, we estimate the effect of expatriate transfer on foreign affiliate's labor productivity using the system generalized method of moments model. We also consider foreign affiliate- and host country-specific contingencies and test how they are associated with expatriates in enhancing foreign affiliate's labor productivity. Findings - We consider foreign production intensity and cultural distance between the home (i.e., South Korea) and host countries as key contingencies that influence the effect of expatriates on foreign affiliate's labor productivity. We find that expatriates are effective in enhancing the labor productivity of less production-intensive foreign affiliates. This effect is strengthened as expatriates are deployed to countries that share cultural similarities with the home country. Originality/value - Considering that previous studies provide mixed results on the effect of expatriates, our findings suggest that foreign affiliate-specific operational orientation and cultural distance should be considered jointly to understand the true effect of expatriate staffing on foreign affiliate performance.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2012.11a
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• pp.141-142
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• 2012

Estimating the productivity of labor has relied on the experience and intuition of an estimator, or productivity data, such as standard in practical estimation. However, when new technologies and new construction methods employed in the construction industry, Dependence of a quantity surveyor's intuition is increased. This is because of the lack of a systematic methodology which models, estimates, and measures the labor productivity, Due to the historical productivity data is unavailable. Even thought project history data contains information that is important to predict the performance of a project, It can not provide valuable information to model, estimate, and measure the labor productivity. This is because 1) the absence of the productivity measurement system with consistency, 2) the difficulty of reusability of historical data collected. Therefor, this study suggests a methodology which build a productivity model by measuring the productivity of labor and collecting the historical data systematically. In addition, this methology is applied to develop a productivity model of shop-drawing and manufacturing process using descrete event simulation.

• The Korean Journal of Health Service Management
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• v.5 no.1
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• pp.77-85
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• 2011

The study intends to conduct an analysis of relations between efficiency of investment to human resources and the operating margin in hospitals. The analyzed results are as follows: First, it is found out that an index related to labor productivity(the monthly value added per bed, the value added ratio to gross revenue), and an index for efficiency of human resources(value added to personnel expenses), do not have a significant difference by years. Second, labor productivity, indicating the efficiency of human resources, does not have a significant difference between regions and between hospital types. But there is a significant difference according to types of establishment: private hospitals have higher labor productivity(efficiency of human resources) than corporate hospitals. The hospital size is small have significantly higher labor productivity. As a result of a follow-up check, it is found out that there is separation between a group with more than 200 beds and a group with less than 200 beds. Third, at the relations between the indices related to value-added productivity and the operating margin that the higher the value added ratio to gross revenue and the higher labor productivity, the higher the operating margin. Especially, labor productivity(value added to personnel expenses), an index for the efficiency of human resources, out of all the indices related value added productivity, has the most significant influence on the operating margin.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2013.05a
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• pp.187-188
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• 2013

Meanwhile, the importance of managing factors affecting labor productivity has been recognized and emphasized. However, in the previous study, qualitative evaluation only took place for these factors. In this study, therefore, identified and quantified the priority of factors decreasing labor productivity, and established basic data.

• Journal of Construction Engineering and Project Management
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• v.1 no.1
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• pp.37-43
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• 2011

Labor productivity is a significant factor associated with controlling time, cost, and quality. Many researchers have developed models to define methods of measuring the relationship between productivity and various parameters such as the size of working area, maximum working hours, and the crew composition. Most of the previous research has focused on estimating productivity; however, this research concentrates on estimating labor productivity and developing time and cost data for repetitive concrete pouring activity. In Korea, "Standard Estimating" only entails the average productivity data of the construction industry, and it is difficult to predict the time and cost spent on any particular project. As a result, errors occur in estimating duration and cost for individual activities or projects. To address these issues, this research sought to collect data, measure productivity, and develop time and cost data using labor productivity based on field conditions from the collected data. A probabilistic approach is also proposed to develop data. A case study is performed to validate this process using actual data collected from construction sites. It is possible that the result will be used as the EVMS baseline of cost management and schedule management.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.256-261
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• 2011

Labor productivity is a significant factor related to control time, cost, and quality. Many researchers have developed models to define method of measuring the relationship between productivity and various constraints such as the size of working area, maximum working hours, and the crew composition. Most of the previous research has focused on estimating productivity; however, this research concentrates on estimating labor productivity and developing time and cost data for repetitive concrete pouring activity. In Korea, "Standard Estimating" only contains the average productivity data of the construction industry, and it is difficult to predict the time and cost of any particular project; hence, there are some errors in estimating duration and cost for individual activity and project. To address these issues, this research collects data, measures productivity, and develops time and cost data using labor productivity based on field conditions from the collected data. A probabilistic approach is also proposed to develop data. A case study is performed to validate this process using actual data collected from construction sites and it is possible that the result will be used as the EVMS baseline of cost management and schedule management.