현금흐름 예측에 대한 많은 자료들은 실제 Tendering Stage(입찰단계) 혹은 Planning Stage(계획단계)의 Model들로서 Feasibility Study를 위한 Cash Flow Forecasting 주였다. 이 Model 들의 기법들은 하나의 Project를 통해서 Cash Flow를 예측하는 Model들이 대부분이고, 예측 방법은 주로 통계적인 접근 방법, 예들 들어 과거 Data를 통해서 Cash Flow 예측 곡선 Model 만들고 Project 유형별 상수나 변수 값을 부여함으로서 예측에 적용하였거나, Fuzzy Technique을 이용하여 Progress와 Cash Flow의 관계를 수식화 한 Model에 관리자의 경험과 판단에 의한 Forecasting Model도 제시되었다. 또한 Cash Flow가 아닌 기성 Flow 및 Cost Flow를 기준으로 한 표준화된 Model이 제시되었다 다른 한편으로는 Schedule과 Cost를 통합한 방법들, 즉, 간단한 주요 Activity와 Cost를 연결한 방법, Activity와 Cost Item과의 연결, 또는 Work Package를 이용한 방법, 마지막으로 좀더 정확도를 기하기 위한 Resource Level까지의 통합을 통해서 Project의 Cash Flow를 예측한 연구들이 이루어 졌다. 그러나 이러한 모든 예측 방법은 실제로 Planning Stage에 Forecasting한 Model로서 현재 진행중인 Project에 적용하기에는 그 정확도면에서 상당히 떨어지고, 대부분의 Model들은 Cash Flow 예측에 가장 중요한 Time lags를 고려하지 않았다. 또한Resource까지 연결은 현장 Engineer들의 많은 작업과 관리를 요구하게 된다. 본 연구는 시공단계에서의 Project의 현금흐름 예측에 관한 연구로서 매출계획과 건설회사의 실행 예산을 이용하여 현금흐름예측을 할 수 있는 Model을 제시하였다. 특히 건설공사의 현금흐름 예측의 중요한 요소인 Cash-Out에 대하여, 공사비 구성요소인 자재, 노무, 중기, 외주, 경비등 각 Resource의 보할(Weights)을 실 공사원가에 따른 보할의 변화와 Resource들의 Time Lag를 적용 기존 연구자의 Model과 다른 Model을 제시하였다. 또한 기존 연구자들의 Model과 비교하여 편리성, 정확도 및 신뢰성이 높은 Model임도 증명하였다.
현금흐름 예측에 대한 많은 자료들은 실제 Tendering Stage(입찰단계) 혹은 Planning Stage(계획단계)의 Model들로서 Feasibility Study를 위한 Cash Flow Forecasting 주였다. 이 Model 들의 기법들은 하나의 Project를 통해서 Cash Flow를 예측하는 Model들이 대부분이고, 예측 방법은 주로 통계적인 접근 방법, 예들 들어 과거 Data를 통해서 Cash Flow 예측 곡선 Model 만들고 Project 유형별 상수나 변수 값을 부여함으로서 예측에 적용하였거나, Fuzzy Technique을 이용하여 Progress와 Cash Flow의 관계를 수식화 한 Model에 관리자의 경험과 판단에 의한 Forecasting Model도 제시되었다. 또한 Cash Flow가 아닌 기성 Flow 및 Cost Flow를 기준으로 한 표준화된 Model이 제시되었다 다른 한편으로는 Schedule과 Cost를 통합한 방법들, 즉, 간단한 주요 Activity와 Cost를 연결한 방법, Activity와 Cost Item과의 연결, 또는 Work Package를 이용한 방법, 마지막으로 좀더 정확도를 기하기 위한 Resource Level까지의 통합을 통해서 Project의 Cash Flow를 예측한 연구들이 이루어 졌다. 그러나 이러한 모든 예측 방법은 실제로 Planning Stage에 Forecasting한 Model로서 현재 진행중인 Project에 적용하기에는 그 정확도면에서 상당히 떨어지고, 대부분의 Model들은 Cash Flow 예측에 가장 중요한 Time lags를 고려하지 않았다. 또한Resource까지 연결은 현장 Engineer들의 많은 작업과 관리를 요구하게 된다. 본 연구는 시공단계에서의 Project의 현금흐름 예측에 관한 연구로서 매출계획과 건설회사의 실행 예산을 이용하여 현금흐름예측을 할 수 있는 Model을 제시하였다. 특히 건설공사의 현금흐름 예측의 중요한 요소인 Cash-Out에 대하여, 공사비 구성요소인 자재, 노무, 중기, 외주, 경비등 각 Resource의 보할(Weights)을 실 공사원가에 따른 보할의 변화와 Resource들의 Time Lag를 적용 기존 연구자의 Model과 다른 Model을 제시하였다. 또한 기존 연구자들의 Model과 비교하여 편리성, 정확도 및 신뢰성이 높은 Model임도 증명하였다.
This research introduces the development of a project-level cash flow forecasting model in construction stage based on the planned earned value and the cost from a general contractors view on a jobsite. Most previous models have been developed to assist contractors in their pre-tendering or planning...
This research introduces the development of a project-level cash flow forecasting model in construction stage based on the planned earned value and the cost from a general contractors view on a jobsite. Most previous models have been developed to assist contractors in their pre-tendering or planning stage cash flow forecasts. The critical key to cash flow forecasting at the project level is how to build a cash-out model. The basic concept is to use moving weights of cost categories in a budget over project duration. The cost categories are classified to compile resources with almost the same time lags that are based on contracting payment conditions and credit times given by suppliers or venders. For cash-in, net planned monthly-earned values are simply transferred to the cash-in forecast, to be applied there with billing time and retention money. Validation of the model involves applying data from on-going 4 projects in progress for 12 months. Based on the results of the comparative analyses through the simulation of the proposed model and the existing models, the proposed model is more accurate, flexible and simpler than traditional models to the employee of construction jobsite who is not oriented financial knowledge.
This research introduces the development of a project-level cash flow forecasting model in construction stage based on the planned earned value and the cost from a general contractors view on a jobsite. Most previous models have been developed to assist contractors in their pre-tendering or planning stage cash flow forecasts. The critical key to cash flow forecasting at the project level is how to build a cash-out model. The basic concept is to use moving weights of cost categories in a budget over project duration. The cost categories are classified to compile resources with almost the same time lags that are based on contracting payment conditions and credit times given by suppliers or venders. For cash-in, net planned monthly-earned values are simply transferred to the cash-in forecast, to be applied there with billing time and retention money. Validation of the model involves applying data from on-going 4 projects in progress for 12 months. Based on the results of the comparative analyses through the simulation of the proposed model and the existing models, the proposed model is more accurate, flexible and simpler than traditional models to the employee of construction jobsite who is not oriented financial knowledge.
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가설 설정
2) Contract amount and budget changed over project duration.
제안 방법
Considering different time lags of cost categories, cash flow is calculated in 10-day increments. Fixed Weights Method (an existing model) applied fixed weights to cost categories over project duration, and Moving Weights Method (a new proposed model) applied different weights at each month using the new algorithm. The results of these two models were then compared to show the accuracy and consistency of the model.
, in order to compare the accuracy of forecasting cash flow. In addition, two types of simulations are performed on each project in order to compare the accuracy of forecasting models. Therefore, 208 total simulations were performed for four projects, which are 52 simulations per each project.
79% for 4 projects in type 2. In spite of considering errors in planning data, the result is a reasonable figure attained by applying the model for forecasting.
M) was developed to help general contractors on jobsites forecast cash flow during the construction stage. The model was based on the general procedure of construction jobsites and the nature of the general contractors budget. The model included new methodology that was not considered by previous researchers.
The simulations were conducted 13 times from start time (0 month) to 12 month per each method for individual projects and evaluated by the two methods, M.W.M and F.W.M., in order to compare the accuracy of forecasting cash flow. In addition, two types of simulations are performed on each project in order to compare the accuracy of forecasting models.
To simulate the dynamic cash flow forecasting, simulation experiments are composed of 10 simulation projects and 7 times, from after start month (0 month) to after 6th month, for each project so that a total 70 simulation experiments per each method are accomplished. As a result, since 2 types of 2 methods are applied, the experiment is simulated a total 280 times.
To verify the model, it is performed simulation using experimental data and four actual projects in progress. Comparative analyses of the simulation results based on the proposed model and existing models are performed.
성능/효과
Based on the results of M.A.D for simulations for 10 experiments that were run 50 times per model, M.W.M results are accurate, from 4.8% to 71%, than F.W.M. Eventually comparing M.W.M to F.W.M with M.A.D, M.W.M is on average 26.5% more accurate than F.W.M for experiments.
The error range of the forecasting is 0.23% to 0.6%, with an average of 0.38% for 4 projects in type 1, and 0.82% to 2.78%, with an average of 1.79% for 4 projects in type 2. In spite of considering errors in planning data, the result is a reasonable figure attained by applying the model for forecasting.
The result of accuracy tests in comparing the two models is that M.W.M is more accurate than F.W.M. In the type 1 the accuracy is 2.64% to 65.04%, with an average of 31.57%, higher than F.W.M in the ideal condition, where the planning is established well reflected on the construction jobsite, and continuously updated.
The result of the accuracy test comparing two models is that M.W.M is more accurate than F.W.M. In the type 2 the accuracy is 0.35% to 454%, an average of 1.75% higher. In this case, planning has remained for 1 year without any update of construction variations that change uncertainties into certainties.
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