Environmental Scanning Practices and Structure: An Empirical Study of Industrial Tunisian Group
Bibliographic record
Abstract
Background/Objectives: The main purpose of the research is to study the influence of the structural specificities on the environmental scanning practices of industrial Tunisian groups. This research presents the direct effect of structural specificity on environment scanning practices and verify the existence of linear relationships between centralization, formalization and complexity of the structure and the variables of the environmental scanning practices.Methods/Statistical. Methodological tools of the research methods were quantitative, a survey based on a questionnaire is conducted with a sample of the relevant population, namely, subsidiaries of Tunisian industrial groups. The number of managers to whom we sent the questionnaire amounted to 283, a total of 120 usable questionnaires were collected. The overall response rate was 42.4%. The collected questionnaires were then processed using specialized SPSS software. With regard to the purification of measuring instruments, exploratory factor analysis.Findings: The results of the hypothesis validation relating structure centralization and the environmental scanning practices mean that a weak centralization, a decentralization of decision-making. The second series of hypotheses concerning the link between structure formalization and environmental scanning practices, we were able to confirm the existence of all the relationships provided for between the formalization and the environmental scanning practices. The hypotheses concerning the relationship between the vertical complexity and the environmental scanning practices were rejected.Improvements/Applications: The contributions of scanning environment practices at the corporate level and at the level of group subsidiaries, and stimulate the efforts made by companies in the field of scanning environment.
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.
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 | 0.002 | 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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".