The Moderating Role of Social Capital in the Relationship Between Green Supply Chain Management and Sustainable Business Performance: Evidence from Jordanian SMEs
Bibliographic record
Abstract
Today's businesses are very worried about environmental issues because many corporate activities could harm the environment.Green Supply Chain Management (GSCM) approaches have increased in popularity in this field.However, small and medium-sized businesses (SMEs) are often less inclined to adopt environmental practices compared to large companies.Although few earlier researchers investigated the direct impact of GSCM on Sustainable Business Performance (SBP), this study makes a unique contribution by offering a comprehensive view of assessing the moderating role of social capital (SC) in the influence of implementing two main GSCM practices (which are Internal-GSCM and External-GSCM) on sustainability performance.A survey method was used to collect data from 420 Jordanian SMEs, and the partial least squares (PLS) method is applied to test hypothesized relationships.The findings reveal that the practices of GSCM, significantly enhance SBP.Surprisingly, SC does not moderate the relationships between the GSCM practices and SBP.This study emphasizes the value of GSCM practices in enhancing SBP among Jordanian SMEs.It is implied that adopting GSCM practices help SMEs enhance the efficient consumption of resources and reduce production cost, improving SBP.Most importantly, the sustainable or GSCM plays a significant role in reducing waste and harmful emissions, thus, improving environmental quality.Hence, this study provides some insights into the type of GSCM practices the SMEs require to apply to improve the desired sustainability performance.This study adds new insights to the extant literature while providing significant new avenues for future research.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".