Investigating the influence of sustainable and smart supply chain practices on the entrepreneurial ecosystem of startup projects
Bibliographic record
Abstract
In the era of the digital world, supply chain systems and processes have changed in an unprecedented manner. Digital technologies and AI related applications have impacted the way in which supply chains are operated compared to traditional and linear supply chains in the previous era. Supply chains in this era are able to be agile, resilient and smarter. Some of the drawbacks of linear supply chains are addressed in the modern supply chains with the application of digital technologies. The future of supply chains now lies in focusing on achieving sustainability by leveraging the advantages provided by the technologies. Sustainability has gained increased focus both in the academic discipline as well as among industry practitioners especially after the development of Sustainable Development Goals (SDGs) by the United Nations. However, most of this development is limited to large scale enterprises and there is a need to improve it in Small and Medium Enterprises (SMEs) and Startups. In Particular, startups require a lot of support in developing their ecosystem in the initial days of their existence. Two major practices of supply chain are found to impact the entrepreneurial ecosystem of startups. The first one is smart supply chain related practices and the second one is sustainable supply chain related practices. This article focuses on the influence of these practices on the entrepreneurial ecosystem of startups. Both these supply chain practices are found to positively influence the development of the entrepreneurial ecosystem. An empirical survey was conducted using a structured questionnaire as a survey instrument in 85 pharmaceutical companies in India. The director of SMEs of Telangana state government was used to qualify the startups and SMEs based on different criteria. A total of 220 responses were received from these companies. Convenient cluster sampling technique was used to select the sample size. The responses were analysed using regression and ANOVA through SPSS. It is found that the smart and sustainable supply chain practices can foster the development of the entrepreneurial ecosystem of startups. The outcomes of this study provide high value-addition to researchers, academicians, students, policy makers, budding entrepreneurs and startup owners and employees.
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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 | 0.002 | 0.001 |
| 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 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".