Information inaccuracy: Implications for economic production scheduling

Thomas R. Rohleder, Gary D. Scudder

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


A number of articles have recently appeared proposing the use of NPV and similar economic scheduling performance measures. Much of this research has concentrated on developing methods to maximize NPV. However, it is assumed in almost all these studies that the cash flow information and cost rate parameters are all known with certainty. For confident use of NPV it would be beneficial to know the robustness of this measure to economic misspecification. This research study addresses the issue of economic information error by developing a simulation model of a jobshop that includes varying levels of information misspecification. The study considers a variety of time-based and economically oriented performance measures along with a number of classical and economic order-release and dispatch scheduling rules. Varying rates of shop utilization and due date tightness were also examined. The results show that NPV is relatively robust to information errors. Average errors must be of the magnitude of at least 40% before time-based measures such as mean flowtime and mean tardiness are financially preferable. At average error levels greater than 40%, the economic-based measures may be misguided by the poor economic information, making their schedules of less worth. However, with low utilization rates, many time-based measures are as good, or almost as good, as NPV in maximizing NPV with information error, even with low information error levels. Under such conditions, the use of the time-based measures may be preferable due to their simplicity.

Original languageEnglish (US)
Pages (from-to)51-66
Number of pages16
JournalInternational Journal of Production Economics
Issue number1
StatePublished - Nov 1995


  • Economics
  • Job-shop scheduling
  • Simulation

ASJC Scopus subject areas

  • Business, Management and Accounting(all)
  • Economics and Econometrics
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering


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