Path to Sustainable Competitive Advantage with Use of Environmental, Social and Governance Principles
Bibliographic record
Abstract
Objective: This study aims to investigate the relationship between product innovation and strategic resource utilization in the Brazilian furniture industry from the perspective of sustainable competitive advantage. The objective is to identify the strategic resources that precede innovation and evaluate the influence of Environmental, Social, and Governance (ESG) principles on new product development. Method: A quantitative and descriptive research approach was employed, utilizing a survey instrument administered to 1067 companies in the Brazilian furniture industry. The survey gathered data on product innovation, strategic resource utilization, and adherence to ESG principles. Structural Equation Modeling (SEM) was employed to analyze the data, allowing for the examination of the complex relationships between variables. Results: The empirical analysis revealed a significant relationship between strategic resource utilization and product innovation, indicating that certain resources serve as antecedents to innovation. Furthermore, the study found that companies with access to strategic resources demonstrated an enhanced capacity for sustainable product innovation. Additionally, the influence of ESG principles on new product development was examined, providing insights into the role of sustainability in shaping innovation processes. Conclusions: The findings of this study underscore the critical importance of strategic resource management in driving sustainable product innovation in the Brazilian furniture industry. By identifying the resources that precede innovation, companies can strategically allocate resources to enhance their innovation capabilities and gain a competitive edge. Moreover, the integration of ESG principles into new product development processes can further bolster innovation efforts, aligning business practices with societal and environmental goals. Overall, this study contributes to advancing theoretical understanding and practical strategies for fostering sustainable innovation in the furniture industry and beyond.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 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".