Strengthening effects of managerial innovativeness in promoting sustainable supply chain management in tourism business
Bibliographic record
Abstract
This paper aims to investigate sustainable tourism supply chains by examining the roles of environmental management, social support, and financial performance of tourist destination agencies. By placing the mediating role of innovativeness, this study developed a theoretical framework to explore the antecedents of tourism supply chain management. This research was conducted in a national park in Central Sulawesi, Indonesia, with 176 samples from tourism business actors. By using purposive sampling method, data analysis was performed using Partial Least Square-Structural Equation Modeling (PLS-SEM). The results of the analysis show a positive and significant influence of environmental management, social support, and financial performance on managerial innovation. These variables in the next analysis are estimated as antecedents of sustainable supply chain management (SSCM) in tourism, indicating positive and significant effects resulting from the analysis. In particular, the analysis also raises the important role of managerial innovation in improving the performance of sustainable supply chain management (SSCM) in tourism. Empirically, these findings underscore that the greater capabilities of the tourism organization in consolidating organizational resources, organizational performance and social support is more likely to increase the sustainability of SCM.
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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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.008 | 0.013 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".