Triple Bottom Line in Indonesia Commercial Palm Oil Mill Business: Analytical Network Process Approach
Bibliographic record
Abstract
The latest trend in palm oil business is the emergence of independent commercial crude palm oil (CPO) mills, which emphasize processing FFB from smallholder plantations. The involvement of smallholders without mill in CPO operations shows that there is potential from the business for sustainable development. The purpose of this study to investigate the Indonesian commercial CPO mill business with a triple bottom line perspective. Moreover, this is to gain how much benefit the Commercial CPO mill business is in terms of profit, people and planet. This study applied the Analytic Network Process (ANP) with the criteria of profitability, social justice and environmental quality. This analytical technique uses a number of experts related to the palm oil business and sustainable development. The results of this study reveal that the critical success factors of priority Indonesian commercial CPO mills are the source of raw materials from small farmers (71.90%) and operational considerations of CPO mills (28.10%). While the benefits of this business can create shared value through quadruple helix analysis of academics, entrepreneurs, communities, and government which ranks profit (53.05%), people (23.75%) and planet (23.19%). The significant results of this study revealed that the Indonesia Commercial CPO mill is sustainable from triple bottom line point of view.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| 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".