Understanding Value Chain Participant Contribution to the Competitiveness of Sustainable Firms
Bibliographic record
Abstract
Historically, there have been trade-offs between the needs for profitability and sustainability in business strategy. This has been changing as the two needs have become interwoven in the pursuit of competitive advantage for many firms. This relatively new phenomenon of profitability being tied to sustainability has been examined from many perspectives, including internal and external pressures to be sustainable and competitive advantage from sustainable practices. Hence, using a model developed from an analysis of the literature, the relative importance of value chain participants and their respective contribution to the competitiveness of firms adopting sustainable practices will be investigated. The validity of the weight of each value chain participant was tested, using a deductive approach. Data collection was carried out through a questionnaire administered by Eco-Business, a large media company addressing ethical and sustainable business practices worldwide, and data analysis was done using multiple regression. Overall, the inclusion of Corporate Social Responsibility in a firm’s business strategy was the greatest influence for sustainability compared to its competitors. From primary activities of the value chain, the largest influence on a firm’s sustainability is its demand that suppliers have sustainable business practices. To further evaluate the relative importance of value chain participants for a global sample, different geographical regions and industry sectors have been analysed separately. While the results were fairly similar for each subsample, several disparities have arisen for certain geographical regions and industry sectors.
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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 | 0.009 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".