Innovation Management and Overall Business Performance: Exploratory Study in Chadian Context in the Two Logones
Bibliographic record
Abstract
Studies on innovation management, carried out so far, have clearly revealed its importance for the performance of companies. However, its control of overall performance combining organizational, social, economic, societal, and environmental dimensions remains little explored. Even research on its model combining integrated innovation projects, to explain the overall performance is few. To understand the relevance of conducting inclusive innovation projects, a study of companies in the agri-food sector was carried out. We have deployed the mixed methodology. Data production was conducted through 11 semi-structured interviews and 90 surveys per survey. The deconstruction approach of innovation management, from organizational innovation to environmental innovation, was used. The results showed that organizational innovation plays a decisive role in organizational, financial, and overall performance. De, technological and social innovations increase economic performance and contribute to the improvement of overall performance. On the other hand, societal and environmental innovations are less relevant for organizational and financial performance. However, they play a decisive role in the management of climate change and the reputation of the organization with society. But, above all, it is the combination of the four types of innovation that constitutes better actions for the overall performance of the company. The article is useful for researchers who will find renewed definitions of each configuration of innovation projects, performances, proven items, and that prove to be more relevant. While managers and consultants will find new performance factors to effectively improve and enhance the implementation of innovation projects. This article is part of resource theory and performance theory and suggests that there is a differentiated relational contingency to each of the factors.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".