• Title/Summary/Keyword: Overseas Construction Order Forecasting

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Overseas Construction Order Forecasting Using Time Series Model (시계열 모형을 이용한 해외건설 수주 전망)

  • Kim, Woon Joong
    • Korean Journal of Construction Engineering and Management
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    • v.19 no.2
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    • pp.107-116
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    • 2018
  • Since 2010, Korea's overseas construction orders have seen dramatic fluctuations. I propose causes and remedies for the industry as a whole. Orders have recorded an annual average of $63.8 billion dollars from 2011 to 2014, reaching its highest at $71.6 billion dollars(2010) which marked the peak of Korea's overseas construction. However, due to a decline in international oil prices, starting in the last half of 2014, Korea's overseas construction orders have followed suit recording $46.1 billion dollar in 2014, $28.2 billion dollars in 2016, and $29.0 billion dollars in 2017. Facing uncertainty in Korea's overseas construction market, caused by continued slow growth of the global economy, Korean EPC contractors are at a critical point in regards to their award-winning capabilities. Together with declining oil prices, the challenges have never been bigger. To mitigate the challenges, I would suggest policy direction as a way to grow and develop the overseas construction industry. Proper counterplans are needed to foster Korea's overseas construction industry. Forecasting total order amount for overseas construction projects is essencial. Analyzing contract award & tender structure and its changing trends in both overseas and world construction markets should also be included. Korea has great potential and global competitiveness. These measures will serve to enhance Korea's overall export strategy in uncertain overseas markets and global economy.

Development of an Optimal Model for Forecasting Overseas Construction Orders (해외건설수주액 예측을 위한 최적모형 개발)

  • Lee, Kwangwon;Jo, Woonghyeon
    • 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.

COST PERFORMANCE PREDICTION FOR INTERNATIONAL CONSTRUCTION PROJECTS USING MULTIPLE REGRESSION ANALYSIS AND STRUCTURAL EQUATION MODEL: A COMPARATIVE STUDY

  • D.Y. Kim;S.H. Han;H. Kim;H. Park
    • International conference on construction engineering and project management
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    • 2007.03a
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    • pp.653-661
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    • 2007
  • Overseas construction projects tend to be more complex than domestic projects, being exposed to more external risks, such as politics, economy, society, and culture, as well as more internal risks from the project itself. It is crucial to have an early understanding of the project condition, in order to be well prepared in various phases of the project. This study compares a structural equation model and multiple regression analysis, in their capacity to predict cost performance of international construction projects. The structural equation model shows a more accurate prediction of cost performance than does regression analysis, due to its intrinsic capability of considering various cost factors in a systematic way.

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