Relationship between Logistics Cost and Relative Firm Efficiency in Indian Food Processing Sector
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Logistics plays an important role in determining the profits for a business enterprise through a dual influence on revenues and costs. Logistics are considered critical in the growth and performance of the food processing sector. The present study was undertaken to examine the relative performance of food processing units in India on the basis of logistics cost. Data Envelopment Analysis (DEA) was used to study the relative performance and the set considered for analysis consisted of 32 food processing units with the period of analysis covering 5 years from 2007-2011. Results indicate that no food processing unit was efficient throughout the period of analysis. Logistic regression results indicate that with a unit increase in logistics cost likelihood of the firm being efficient decreased 0.642 times. The results of the study underline the criticality of logistics management in the context of the food processing sector in India. For improving firm efficiency, it is imperative for Indian food processing companies to ensure efficiency in logistics operations.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it