Building a Sustainable Manufacturing Industry: The Role of Innovativeness and Other Strategic Factors
Bibliographic record
Abstract
ABSTRACT Sustainable manufacturing is an effective way to improve organizational performance. In this sense, this research aims to analyze the determining factors of the success of the Brazilian manufacturing industry and evaluate innovativeness (Innovation Capacity) as a central point of sustainable manufacturing. The research was conducted through a survey to 1070 manufacturing industry companies from the Automotive Metal–Mechanical Clusters, Furniture Industry Cluster, and Garment Industry Cluster sectors. A structural equation modeling methodology and cluster analysis method were used to analyze the data. Among the results of this research, it is highlighted that Innovation Capacity is the central point of sustainable manufacturing, in which Innovativeness positively influences Sustainable Competitive Advantage and Organizational Performance. Among the contributions of this research is the framework validation for analyzing the factors that influence sustainable manufacturing. This study brings results that significantly contribute to the development of a sustainable manufacturing industry, which supports the achievement of Global Goals 9—Industry, Innovation, and Infrastructure.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".