• Journal of the Korea Institute of Building Construction
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• v.9 no.2
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• pp.31-38
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• 2009

In today's construction industry, buildings have been more complicated and higher, the demands of steel works have been increasingly concerned, which makes the schedule planning and management more significant. However, in actual construction sites, management is more based on a manager's construction experience than productivity data accumulated in previous projects. Moreover, most of the existing studies also featured a theoretical approach rather than an analysis of data straightforwardly collected in sites. In this study, a steel-erection site was visited to collect productivity data. The study found that there were significant disparities between aboveground work productivity and underground work; one tower crane operated work and two tower crane operated; and work productivity conducted in clear weather condition, cloud and rainy. However, the productivities of 'first node on ground' and 'second node on ground' were estimated similar. The productivity data collected and factors affecting the productivity will help managers to plan and control their similar steel-erection works. This study will also be beneficial for those performing related studies.

• Journal of Environmental Policy
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• v.9 no.3
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• pp.47-67
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• 2010

Carbon productivity is an efficiency concept, well suited to maximizing product/service(economic) value of firms and minimizing environmental impact($CO_2$ emissions). This study investigates the causal relationship between carbon productivity (eco-efficiency) and financial performance in Korean firms. The result shows that firms improving carbon productivity are able to gain superior financial performance. The analysis also show that changes in financial performance have a positive impact on the improvement of carbon productivity. However this study reports that carbon productivity does not have a long-run impact on financial performance and vice versa. Finally, the results also show that differences exist in the relationship between carbon productivity and financial performance when grouped by industry characteristics.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.492-499
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• 2022

A large number of employees shifted to Work from home (WFH) due to the COVID-19 pandemic, including the construction workforce. The changes in workload and productivity due to WFH impact the work performance and economic outputs of companies. However, there are mixed results about the impacts of WFH on workload and productivity. In particular, limited studies focused on specific types of work of different occupations in the construction workforce. This study aims to explore the impacts of WFH on workload and productivity considering different types of work for the construction workforce in the U.S. After identifying three main occupations and five types of work, an online survey (N = 69) was distributed. Descriptive analysis showed that participants had less workload (0.82 hours/week) and lower productivity (9.69%) during WFH. Three occupations had varied changes due to the different types of work. Analysis of Variance (ANOVA) indicated that there was no significant difference in workload, while productivity was decreased during WFH. In particular, the productivity of project-related work and communication and documentation decreased significantly. Overall, participants finished 2.85% less workload per week during WFH. The findings provide an insight into WFH in the construction workforce, which improves future remote or hybrid work arrangements in the construction industry.

• Journal of Labour Economics
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• v.32 no.2
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• pp.95-124
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• 2009

In this article, I were trying to analyze the listed manufacturing companies' trend of productivity and the corporate education & training effect after the financial crisis. According to the analysis, the listed manufacturing companies have decreased their productivity since financial crisis, and from such declining trend. jobless growth and a growth without physical and human capital investment has been observed. Furthermore, there is no efficient labor force coordination within the manufacturing industry; In order to analyze the effect of education & training investment on productivity more deeply, I have practiced the dynamic panel data analysis from constructing the micro panel data which consists of company level information 1997~2008. According to the consequences, dynamic panel data analysis solved the problem of the overestimating education & training effect fairly well.

• Journal of the Korea Institute of Building Construction
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• v.12 no.6
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• pp.636-647
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• 2012

Construction projects have become so large, complicated and incredibly high-tech that process management is currently considered one of the most important issues. Unlike typical manufacturing industries, most major construction activities are performed in the open air and thus are exposed to various environmental factors. Many studies have been conducted with the goal of establishing efficient techniques and tools for overcoming these limitations. Productivity analysis and prediction, one of the related research subjects, must be considered when evaluating approaches to reducing construction duration and costs. The aim of this research is to present a quantified impact analysis of construction delay factors on construction productivity of a steel staircase system, which has been widely applied to high rise building construction. It is also expected to improve the process by managing the factors, ultimately achieving an improvement in construction productivity. To achieve the research objectives, this paper analyzed different delay factors affecting construction duration by means of multiple regression analysis focusing on steel staircase systems, which have critical effects on the preceding and subsequent processes in structure construction. Statistical analysis on the multiple linear regression model indicated that the environment, labor and material delay factors were statistically significant, with 0.293, 0.491, and 0.203 as the respective quantified impacts on productivity.

• Journal of the Korea Institute of Building Construction
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• v.11 no.2
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• pp.100-107
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• 2011

As construction duration significantly influences the performance and the success of construction projects, it is necessary to appropriately manage the impact factors affecting construction duration. Recently, interest in the construction industry has been rising due to the recent change in the construction legal system, and the competition among the construction companies on construction time. However, the impact factors are extremely diverse. The existing productivity data on impact factors is not sufficient to properly identify the impact factor and measure the productivity from various perspectives, such as subcontractor, time, crew, work and so on. In this respect, a multidimensional analysis by a data warehouse is very helpful in order to view the manner in which productivity is affected by impact factors from various perspectives. Therefore, this research proposes a method that effectively takes the diverse productivity data of impact factors, and generates a multidimensional analysis. Decision tree analysis, a data mining technique, is also applied in this research in order to supply construction managers with appropriate productivity data on impact factors during the construction management process.

• Journal of Korea Port Economic Association
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• v.36 no.1
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• pp.183-196
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• 2020

Until now, there have been few studies analyzing the efficiency of the Port of Mokpo and comparing it with other seaports in the country to identify the future direction of development for the port. In this paper, we use the data envelopment analysis (DEA) model in combination with the Malmquist Productivity Index (MPI) to measure the efficiency and productivity of major ports in Korea, focusing on the Port of Mokpo. First, the study identifies which ports are efficient or inefficient based on technical or operational scale. Second, by using the MPI to overcome the shortfalls of the DEA model, the study can compare a port's performance across the years and evaluate the productivity of a port during the research period. Moreover, this study also applies fuzzy C-means (FCM) clustering to classify port groups based on the size of their infrastructure and their efficiency scores. Finally, it is possible to find ways to enhance the efficiency and future direction of development of the Port of Mokpo.

• Journal of Korea Port Economic Association
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• v.39 no.3
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• pp.21-32
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• 2023

The domestic automobile industry is growing due to favourable government policies and changing technological innovations. As the automobile industry becomes more active, the role of dedicated docks facilitating automobile exports is also becoming prominent which can be identified as a sector still requiring comprehensive research. Accordingly, a case analysis of domestic automobile port productivity was conducted using empirical data collected from Korean automobile ports to compare and analyze their productivity and to present implications based on the findings. In the case of productivity analysis, facility, labor, working time, and cost productivity were calculated from (the beginning of) 2021 to the second quarter of 2022. The results of the analysis revealed the port D to achieve the highest productivity during the study period, followed by the ports B, C, and A, respectively. Based on the current situation of each automobile dock revealed through the results, strategies for future development is derived.

• 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.

• Journal of Distribution Science
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• v.17 no.3
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• pp.31-39
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• 2019

Purpose - This study aims to investigate and analyze the factors that affect women's work productivity based on ethnic in the food and beverage industry. Also, it is also to determine whether there are differences in the productivity of female workers based on these ethnic groups. Research design, data, and Methodology - The approach of this research is quantitative by using multiple linear regression analysis and analysis of different tests using SPSS and tested on 114 samples of female workers in various small-scale, medium-sized food and beverage industry categories and large in Makassar City, Indonesia. Determination of samples based on proportional stratified sampling. Industry sampling criteria based on some workers, assets and wealth. Results and Conclusions - The results of this study state that health, years of service, work ethic, age, wages, and work environment have a significant effect on work productivity. While the level of education, the number of dependents does not have a considerable impact, the fact that there is a difference in the productivity index of female workers in a significant sector is compared to small and medium scale enterprises, including the variables of government policies related to pension insurance, work accident insurance and health insurance.