Using historical data for forecasting s-curves at construction industry

M. T. Banki, Behzad Esmaeli

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Cash flow forecasting and control are essential to the survival of any contractor. The time available for a detailed pre-tender cash flow forecast is often limited. Therefore, contractors require simpler and quicker techniques which would enable them to forecast cash flow with reasonable accuracy. The paper is based on classifying projects into groups and producing a standard curve for each group simply by fitting one curve into the historical data A sample of data from 7 projects was collected which all of them were harbor construction project in Iran. S-curves were fitted into each using the logit transformation technique. Errors incurred when fitting these curves were measured and compared with those associates in fitting individual projects. Results showed that the difference between these errors was not significant. The results of the model developed in this paper were compared with previous models and evaluated. It is concluded that the model produced more accurate results than existing value and cost models

Original languageEnglish (US)
Title of host publication2008 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2008
Pages282-286
Number of pages5
DOIs
StatePublished - Dec 1 2008
Event2008 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2008 - Singapore, Singapore
Duration: Dec 8 2008Dec 11 2008

Publication series

Name2008 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2008

Other

Other2008 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2008
CountrySingapore
CitySingapore
Period12/8/0812/11/08

Fingerprint

Construction industry
Contractors
Curve fitting
Ports and harbors
S-curve
Cash flow
Costs

Keywords

  • Cash flow
  • Construction industry
  • Financial forecasting
  • Project management
  • S-curves

ASJC Scopus subject areas

  • Management Information Systems
  • Industrial and Manufacturing Engineering

Cite this

Banki, M. T., & Esmaeli, B. (2008). Using historical data for forecasting s-curves at construction industry. In 2008 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2008 (pp. 282-286). [4737875] (2008 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2008). https://doi.org/10.1109/IEEM.2008.4737875

Using historical data for forecasting s-curves at construction industry. / Banki, M. T.; Esmaeli, Behzad.

2008 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2008. 2008. p. 282-286 4737875 (2008 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2008).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Banki, MT & Esmaeli, B 2008, Using historical data for forecasting s-curves at construction industry. in 2008 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2008., 4737875, 2008 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2008, pp. 282-286, 2008 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2008, Singapore, Singapore, 12/8/08. https://doi.org/10.1109/IEEM.2008.4737875
Banki MT, Esmaeli B. Using historical data for forecasting s-curves at construction industry. In 2008 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2008. 2008. p. 282-286. 4737875. (2008 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2008). https://doi.org/10.1109/IEEM.2008.4737875
Banki, M. T. ; Esmaeli, Behzad. / Using historical data for forecasting s-curves at construction industry. 2008 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2008. 2008. pp. 282-286 (2008 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2008).
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