An exploration study to find important factors influencing on enterprise resource planning
Bibliographic record
Abstract
Enterprise resource planning (ERP) has become a necessary in many organizations and many business units have been trying to emerge into an integrated system.There are many advantages on having an efficient ERP but many corporations fail to reach a full operational ERP for many reasons.In this paper, we present an empirical investigation to find important factors influencing ERP implementation in one of the biggest Iranian automakers named Iran Khodro.The proposed study designs a questionnaire in Likert scale consists of 46 questions, distributes it among some managers in this firm.Cronbach alpha is calculated as 0.802.In addition, Kaiser-Meyer-Olkin Measure of Sampling Adequacy and Approx.Chi-Square are 0.788 and 1677.307,respectively.Based on the results of our survey, we have derived eight factors including intelligence information, customer comfort, structure oriented, resource management, process oriented, customer oriented, flexible structure and knowledge management.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".