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An extended research programme has examined over the past two decades how productivity in construction projects can be improved through the development of models for project monitoring and control, which process automatically collected data on the actual project performance. Tests that were conducted with these models demonstrate that this approach can help overcome some of the limitations of existing manual methods. However, they also indicate that certain manually obtained data are still required in addition to the automatically collected data. A framework for semi-automated project monitoring and control is proposed, in which both manually and automatically collected data can be incorporated. This framework integrates the monitoring of projects with their control by taking into account the impact on productivity of existing deviations from the planned performance, and of the controlling actions that are proposed to deal with these deviations.
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Stored only when both papers are in the corpus — 33 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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