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Record W2150964232 · doi:10.5267/j.msl.2014.6.042

Investigating the effects of different factors on development of open source enterprise resources planning software packages

2014· article· en· W2150964232 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.

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

VenueManagement Science Letters · 2014
Typearticle
Languageen
FieldComputer Science
TopicOpen Source Software Innovations
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceSoftwareProcess managementEnterprise resource planningBusinessKnowledge managementSoftware developmentSoftware engineeringOperations managementEngineering managementOperating systemEngineering

Abstract

fetched live from OpenAlex

This paper investigates the effects of different factors on development of open source enterprise resources planning software packages. The study designs a questionnaire in Likert scale and distributes it among 210 experts in the field of open source software package development. Cronbach alpha has been calculated as 0.93, which is well above the minimum acceptable level. Using Pearson correlation as well as stepwise regression analysis, the study determines three most important factors including fundamental issues, during and after implementation of open source software development. The study also determines a positive and strong relationship between fundamental factors and after implementation factors (r=0.9006, Sig. = 0.000).

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.287
Threshold uncertainty score0.975

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0050.003
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 head0.017
GPT teacher head0.258
Teacher spread0.241 · 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