• International conference on construction engineering and project management
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• 2022.06a
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• pp.188-195
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• 2022

Although issuing change orders is a common practice in the construction phase of any project, non-structural utility subcontractors are struggling and seek to find a way to reduce change orders. Therefore, this paper presents the analysis results on change orders to cultivate possible suggestions and solutions on how to reduce or minimize change orders in mechanical, electrical, and plumbing (MEP) works. Change orders in non-structural utility works are analyzed based on six categories such as rerouting and change of location, changes in weight, rejected design by Office of Statewide Health Planning and Development, District Structural Engineer, or the Structural Engineer of Record, unforeseen conditions, changed equipment, and owner-initiated change. The analysis findings showed that rerouting and changing location is the most significant cause, followed by unforeseen conditions. The results not only contribute to the existing body of knowledge on change order research area, but also help MEP contractors reduce the time and cost of change orders.

• Journal of Wetlands Research
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• v.7 no.4
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• pp.51-65
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• 2005

The insects and Benthic Macro-Invertebrates are very important for index of investigation. This reserch is executed a field investigation with a date analysis of the laboratory under such as above hypothesis and we have grasped the change of the creature according to the season through the executing of field investigation(We executed six times about the insects, seven times about the Benthic Macro-Inbertebrates each expending from Apr. to Oct. 2004). The result of summary in 2004 show that, we have grasped 12 orders 56 familys 116 species on 2001 and 10 orders 42 familys 78 species on 2002 through the investigation. Also we have grasped 13 orders 53 familys 114 species on 2003 and 12 orders 63 familys 121 speceies on 2004 through the investigation. In the case of enthic Macro-Invertebrates, we executed the analysis through the investigation result expending from 2003 to 2004 due to there is no literature investigation record from 2001 to 2002. We have grasped 8 orders 17 familys 24 species on 2003 and 7 orders 11 familys 24 species on Aug. 2004 through the investigation. We executed the analysis about an each condition due to it is difficult to compare the above result simply by the various variable at the investigation. We expect that it become the fundamental reference data to establish a efficient mode of life undo plan after grasped the inhabitation and movement route of creature inside the river through this reserch.

• Journal of the Korea Institute of Building Construction
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• v.13 no.3
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• pp.263-271
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• 2013

Change orders have been widespread in both the private and public construction sectors. In particular, in the case of G2B (Government to Business) contracts, adjustment of contract price and/or schedule extension is a frequent occurrence due to change orders. To uncover the causes of change orders and suggest an appropriate strategy, this study analyzed 296 cases of change orders in military facility construction projects from 2008 to 2010. The analysis revealed that the major causes of change orders are users' additional requirements (28.38%), a change of finishing materials (23.99%), and change of footing type (17.57%), in that order. Building on the results of this analysis, the authors suggest plans for practical improvements. Specific recommendations include 1) reflect user requirements at the early stage, 2) minimize the use of additional budget due to change orders, and 3) reduce the process and time for contract amendment, among others. The results of this study may provide significant implications to those involved in military construction projects, particularly project owners (i.e., the Ministry of Defense) and contractors.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.1283-1287
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• 2009

The Korean government implemented 259 road projects from 2004 to 2007, valued at $18.4 billion. Change orders of these road projects occurred 8,973 times and, subsequently, caused significant increases in the cost of the projects, approximately up to $4.2 billion (22.8% of the initial budget). These significant problems of huge change orders require a more workable control system for budget management whereas the effectiveness of the government's control is still not satisfied. However, previous approaches and studies mostly limited their analyses to simply classifying the causes of the change orders. This paper investigates the real frequency and cost impacts incurred by each cause of a change order, primarily based on 218 road projects in Korea. The paper then identifies the attributes of change orders through a survey of 204 project participants in that those sources were inevitable or avoided if properly managed. The causes of the change orders are further analyzed with analysis of variance (ANOVA) in connection with contract volume, bid award rate, the contractor's capacity to perform, and the design company's capacity. This study found that if the contract volume is smaller, then the possibility of change orders is higher. Interestingly, if the bid award rate is less than 67.5%, it signifies the highest rate of change orders. In addition, the contractors whose construction ability is assessed as the top-ranked group showed the lowest change order rates. With these results, this paper provides the preventive guidelines for reducing the likelihood of change orders.

• The Journal of the Korea Contents Association
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• v.17 no.9
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• pp.300-309
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• 2017

This paper examines the cyclical fluctuation of 'construction orders' and 'construction investment' using HP filter, Bandpass filter and Beveridge-Nelson decomposition methods. The main results are as follows. As a result of the analysis of the cyclical fluctuation of construction orders, it was analyzed that there were about 7 cyclical fluctuations from 1976 to the first quarter of 2017. Construction orders for cyclical fluctuations peaked in the second quarter of 2015 and turned to a downward trend. On the other hand, construction investment has experienced about 6 cycles of fluctuations during the same period, and it has been rising continuously since the bottom of 3Q12. This is consistent with the general theory that construction orders precede construction investments. In addition, the comparison of the construction orders, construction investment, and GDP amplitude shows that the GDP amplitude is the smallest and stable, and the construction orders have the greatest variation in amplitude. Therefore, construction orders should be adjusted by government policy depending on economic fluctuations.

• Korean Journal of Construction Engineering and Management
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• v.6 no.5 s.27
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• pp.69-77
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• 2005

Change is inevitable and is a reality of construction projects. Most construction contracts include change clauses and allowing contractors an equitable adjustment to the contract price and duration caused by change. However, the actions of a contractor can cause a loss of productivity and furthermore can result in disruption of the whole project because of a cumulative or ripple effect. Because of its complicated nature, it becomes a complex issue to determine the cumulative impact (ripple effect) caused by single or multiple change orders. Furthermore, owners and contractors do not always agree on the adjusted contract price for the cumulative Impact of the changes. A number of studies have attempted to quantify the impact of change orders on project costs and schedule. Many of these attempted to develop regression models to quantify the loss. However, regression analysis has shortcomings in dealing with many qualitative or noisy input data. This study develops ANN models to classify and quantify the labor productivity losses that are caused by the cumulative impact of change orders. The results skew that ANN models give significantly improved performance compared to traditional statistical models.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.281-283
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• 2006

In this paper, we consider the problem of batch processing of orders, where either a single order or a pair of orders which satisfies specific conditions may be grouped in the same batch. The objective of the problem is to minimize the number of batches formed to accommodate all orders. We prose an approach based on a Known algorithm proven to be optimal for special class of problems with tree structure and show the approach to have the worst case ratio of $2-{\frac{2}{n}}$

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.1
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• pp.193-202
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• 2015

This study suggests strategies business strategies of specialty contractors by interaction analysis between business performance indicators and construction business indicators depending on operation types. To analyzing this research, a database was analyze for construction orders and business performance indicators for specialty contractors with KRW 7 billion from 1997 to 2010 yr. For organized management oriented specialty contractors, the amount of construction orders is directly affecting the corporate stability and therefore decreasing orders can negatively affect the owner's equity ratio. However, considering that the turnover ratio of total liabilities and net worth is affecting the owner's equity, an asset management plan needs to be established in a way to increase sales to the owner's equity secured with increase in construction orders. For a single leader oriented specialty contractors, the owner's equity ratio is also significantly affected by change in the amount of construction orders and some countermeasure is required. But, as liability ratio is affecting the amount of construction orders, some sort of countermeasures to decrease liability ratio is required.

• Korean Journal of Construction Engineering and Management
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• v.21 no.4
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• pp.30-37
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• 2020

The purpose of this study is to compare and contrast the amount of overseas construction orders of South Korea and China by using various time series models that measure the overseas construction orders. Based on the analysis we propose better specification (model selection) with much more predictive power and prove the universality of the model developed by applying our findings with respect to the prediction power of overseas construction orders from other countries viewpoints (verification of generalization). The input variables include Dubai crude oil and exchange rates by country from 1981 to 2019. The VAR model is proposed based on the prediction power test, with respect to MAPE, RMSE, and MAE between the estimates and actual measurements from 2016 to 2019. We also conclude the results of the prediction of overseas construction orders time series of China are again consistent with the actual numbers. These analyses suggest the possibility of developing a comprehensive model that predict the potential construction orders of other countries.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.6
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• pp.1087-1093
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• 2017

The purpose of this study is to present an empirical analysis of determinants of the amount of orders received in construction technology engineering industry sector. Regression model was applied for 5 years from 2010 to 2014 to find out how the factors affecting the amount of orders received each year are different and what trends are observed. Although common significant variables were identified that there is a difference in the impact on their orders received. Specifically, the increase in the number of orders received while reducing the impact on orders received from 2010 to 2013, 2014 showed a slight tendency to increase. And increase in the number of employees shows that the influence of order received is higher in 2014 than in 2010. In addition, the gap between the metropolitan area and the non-metropolitan area has doubled in 2014 compared to 2010, but it is also confirmed that the metropolitan area is still strong. On the other hand, in the case of licensed technology, the only statistically significant variable was the negative correlation between the amount of orders received. Although the influence declined in 2014 compared to 2011, it still had a large impact on the amount of orders received.