In-house development as an alternative for ERP adoption by SMEs: A critical case study
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.
Bibliographic record
Abstract
ERP systems are increasingly accessible to small and medium-sized enterprises (SMEs). If the\npotential benefits of these systems are significant, the same applies to the risk associated with their\nimplementation. The majority of ERP studies relate to software packages supplied by large vendors\nsuch as SAP and Oracle and by smaller vendors; but until now, few have studied the adoption of ERP\nsystems developed “in-house”. Furthermore, few studies have explicitly focused on minimizing the\nrisk of these systems at the adoption or pre-implementation stage. Presenting a critical case study\nwhich analyzes the adoption of an in-house ERP by a SME in the agri-food industry, this article\nproposes and tests a process framework of ERP systems adoption, based upon a literature review and\na conceptual framework centered on risk minimization. The study shows that 1) in-house ERP seems\nto represent a credible alternative for ERP adoption by SMEs, 2) to minimize risk at the adoption\nstage, a SME can proceed in a rather intuitive and unstructured manner, based however upon certain\nprinciples, policies and practices. The successful ERP implementation in this case indicates that it is\nnot always necessary to resort to formalized project management in order to minimize implementation\nrisk.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.007 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it