Negotiating Construction Contracts through Practical Cash Flow Planning and Analysis Model

Research output: Contribution to journalArticlepeer-review

Abstract

Under-capitalization, difficulties in getting credit, substantial cost of getting financed, etc. cause contractors to complete projects with negative ending balances. Predictability and control of the cash flow through negotiating financial provisions of construction contracts mean differences between success and failure of a project or a contracting company. Despite many practical insights provided by professionals, structured procedures and tools are seldom used, and few contractors take advantage of the existing techniques which can enable them to identify the effects of their decisions on negotiating contract terms. In addition, commercial finance software is expensive and complicated. This paper presents the multi-period dynamic model on the project level which maximizes final cash balance through negotiating financial terms of contracts without time-consuming data collection and with reasonable accuracy. This allows industrial practitioners to define the cash flow planning horizon, as well as predict and maximize the final cash balance. Microsoft’s Excel spreadsheet software with its add-in optimization programs is used in solving these models. Through scenarios and sensitivity analysis on contract financial provisions, contractors can predict the impact on project cash inflows and outflows. The approximate solution of this deterministic model gives decision makers an excellent insight for making the optimal decisions.
Original languageAmerican English
Pages (from-to)23-33
Number of pages11
JournalThe International Journal of Construction Management
Volume12
Issue number2
DOIs
StatePublished - Jan 1 2012

Keywords

  • cash flow
  • construction contract negotiation
  • retained percentage
  • billing period
  • initial capital
  • multi-period dynamic optimization model

Disciplines

  • Economics
  • Operations and Supply Chain Management
  • Business Administration, Management, and Operations
  • Marketing
  • Statistics and Probability

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