Data mining model for identifying project profitability variables

Andrew S. Chang, Sou Sen Leu

研究成果: Article同行評審

10 引文 斯高帕斯(Scopus)


Many engineering design companies collect data such as profits to manage projects. But the relationships between operational variables and performance are usually not thoroughly analyzed and interpreted. This paper proposes a data mining model and procedure to relate influence variables to project profitability. Data categories and variables are defined at the project input, process and output stages. The model proposed herein was tested by analyzing 548 projects of an engineering consulting company. The relationships between profitability and various input and process variables were identified and interpreted. For example, the effect of QA/QC on profitability is positive. Based on documented data and derived information, this model can help companies gain operational knowledge and thus further improve performance.

頁(從 - 到)199-206
期刊International Journal of Project Management
出版狀態Published - 2006 四月 1

All Science Journal Classification (ASJC) codes

  • Business and International Management
  • Management of Technology and Innovation

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