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Record W2122385593 · doi:10.37265/japiv.v5i1.82

Organizational Implementation of Best Value Project Delivery: Impact of Value-Based Procurement, Preplanning, and Risk Management

2013· article· en· W2122385593 on OpenAlexaboutno aff
Brian Lines, Kenneth Sullivan, Brian B. Stone

Bibliographic record

VenueJournal for the Advancement of Performance Information and Value · 2013
Typearticle
Languageen
FieldDecision Sciences
TopicConstruction Project Management and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsIntegrated project deliveryDocumentationVendorBusinessProcurementProcess managementProject management triangleProject managementOperations managementKnowledge managementComputer scienceMarketingEngineering

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.530
Threshold uncertainty score0.454

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.003
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.043
GPT teacher head0.376
Teacher spread0.333 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2013
Admission routes1
Has abstractyes

Explore more

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