Organizational Implementation of Best Value Project Delivery: Impact of Value-Based Procurement, Preplanning, and Risk Management
Bibliographic record
Abstract
Many buyer organizations have attempted to implement new project delivery methods to increase performance on their contracting processes. Yet implementing new business practices can be difficult to accomplish successfully. An action research methodology was utilized to present a longitudinal case study of the University of Alberta’s implementation of the Best Value Business Model (BVBM). A key research objective was to document and present observations of the change management principles utilized during the implementation of organizational change at a large public organization. Other research objectives included quantification of project-level and organizational-level success indicators that reflect the progress of change implementation. Results are analyzed after more than two years of implementation of the BVBM on ten separate contracts. Direct cost savings on these projects as a result of the BVBM has been documented to be as much as $16 million when considering savings below budget and conducting comparisons against traditional project delivery methodologies. Other success factors include low rates of vendor and contractor change orders and high satisfaction among owner project managers with regards to the performance of contracted service providers. Contributions of this research include documentation how theoretical change management principles have been applied within an action research setting as well as the identification and documentation of success indicators for project- and organizational-level implementation of new project delivery methods.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".