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Record W2036063540 · doi:10.1002/pmj.21308

Learning from Project Management Implementation by Applying a Management Innovation Lens

2012· article· en· W2036063540 on OpenAlexaff
Janice Thomas, Svetlana Cicmil, Stella George

Bibliographic record

VenueProject Management Journal · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovation and Knowledge Management
Canadian institutionsAthabasca University
Fundersnot available
KeywordsOperationalizationInnovation managementScope (computer science)Project managementPaceKnowledge managementOPM3Process (computing)Innovation processProcess managementValue (mathematics)BusinessProject management triangleEngineeringComputer scienceMarketingWork in processSystems engineering

Abstract

fetched live from OpenAlex

Management innovation is a complex and dynamic process of organizational change that is not well understood. Drawing from the innovation and organizational change literatures, and using project management as an example of one particular form of management innovation, we operationalize this project management innovation process by identifying types of innovation events defined by the pace and scope of the change implemented. Linking innovation events into a journey, we map complex innovation journeys and provide empirically based insight into how value is created and destroyed through the selection and dynamics of innovation events that either support or detract from historical project management trajectories. We conclude by providing practical insights for those who contemplate undertaking such a journey.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.020
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.003
Science and technology studies0.0060.021
Scholarly communication0.0160.026
Open science0.0020.010
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0060.001

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 head0.300
Teacher spread0.257 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations16
Published2012
Admission routes1
Has abstractyes

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