Religious beliefs and the promotion of socially responsible entrepreneurship in the Indian agribusiness industry
Bibliographic record
Abstract
Purpose The purpose of this paper is to investigate the relationship between religious beliefs and socially responsible investment in the Indian agricultural industry. Design/methodology/approach Owners of small agribusiness firms from India were interviewed regarding their perceptions of religious beliefs and socially responsible investment in the agricultural industry. Findings The survey indicates that while religious beliefs and internal financing sources increase perceived socially responsible investment, the higher cost of debt capital decreases perceived socially responsible investment in the Indian agricultural industry. The higher level of internal financing sources, however, decreases the perceived cost of debt capital which may increase socially responsible investment in the Indian agricultural industry. Research limitations/implications This is a co-relational study that investigated the association between religious beliefs and socially responsible investment. There is not necessarily a causal relationship between the two. The findings of this study may only be generalized to firms similar to those that were included in this research. Originality/value This study contributes to the literature on the factors that increase socially responsible investment in the agricultural industry. The study also provides critical policy recommendations to minimize managerial implications. The findings may be useful for financial managers, agribusiness owners (farmers), investors, agribusiness management consultants, and other stakeholders.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".