Change Processes and Procedures in Service Oriented Virtual Organizations and Collaborative Network
Bibliographic record
Abstract
Business processes and services of Service Oriented Virtual Organizations are subject to change to meet the internal and external requirements of the competitive and rapidly changing environment they operate in. Efficient and practical change management solutions are needed to enable partners to gain insight on the procedures and the processes which can be used to facilitate the process of change. This paper presents a procedural change management framework to facilitate the process of change allowing the participating partners in a Virtual Organization to initiate, assess, collaborate, authorize, implement, evaluate and control changes in the SOVO. The solution consists of a multi-layered procedural framework, including the six layers of change processes, change actors, change control requirements and related management interfaces. It is derived from Information Technology Infrastructure Library (ITIL V3), Engineering Change Management (ECM) and European Collaborative Networked Organizations Leadership initiative (ECOLEAD) best practices and recommendations and customized to fit SOVO requirements and challenges. We present the implementation of six layers of changes processes using the IBM Business Process Manager (BPM) and the implementation architecture of the change management console to facilitate the process of change in SOVO.
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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 | 0.009 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.011 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".