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Record W2602387211 · doi:10.5539/ass.v13n4p37

Aircraft Acquisition Conceptual Framework

2017· article· en· W2602387211 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAsian Social Science · 2017
Typearticle
Languageen
FieldEngineering
TopicTechnology Assessment and Management
Canadian institutionsnot available
FundersPublic Works and Government Services Canada
KeywordsAeronauticsChristian ministryOperations managementInefficiencyProcess managementOperations researchEngineeringBusinessPolitical science

Abstract

fetched live from OpenAlex

The Royal Malaysian Air Force (RMAF) has faced difficulties in achieving and sustaining at least 70% of its aircraft availability (Av) in order to support its operational requirements. The head start for this research is to discuss with a focus group (FG) which comprise of eight officers and one moderator and supported by observation on the field. The FG highlighted that the low Av was due to the ineffectiveness and inefficiency of the through life cycle support (TLCS) as a result of weaknesses in the acquisition conceptual framework (ACF). Three research questions were put forward; Q1: Why has the RMAF not achieved its aircraft Av as its desired objectives? Q2: How do the RMAF’s present acquisition practices given a significant impact to Av? And Q3: What is the recommended ACF to be used to ensure higher aircraft Av? The mix mode method (quantitative and qualitative) data collection was used. The literature review focused on critical success factors (CSFs) in terms of acquisition, terms and definition, and present practices in the Royal Malaysian Army (RMA), the Royal Malaysian Navy (RMN), the Malaysian public sector, the Department of Defence of the United States of America (DoD USA), the Ministry of Defence of United Kingdom (MoD UK) and the Australian Defence Force (ADF). Based on the CSFs from the literature review, a preliminary ACF I was developed. The RMAF case study had focused on Type A, Type B, Type C and Type D aircraft. Data on aircraft status for FY 2011 to 2015 was gathered from the Air Support Command Headquarters (ASHQ). The survey was achieved through 16 self-administered structured questionnaires which are close-ended involving 120 out of 150 respondents from the Worker Group (WG). The interviewer collected qualitative data using 21 semi-structured questionnaires with open-ended answers on 20 respondents from the Management Group (MG). The survey and interview results were presented in a matrix table and categorized in accordance with themes and their relationships. Based on the results of the case study, the preliminary ACF I was modified to ACF II. Then, ACF II was validated by four experts who comprise of two senior officers and two senior managers from the aviation industry. After validation, the ACF II was modified to ACF III (final) and was proposed for implementation. Three project objectives were put forward. Objective 1: To identify the cause of low Av.

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.

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)0.000
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.942
Threshold uncertainty score0.691

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.011
GPT teacher head0.279
Teacher spread0.268 · 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