The Impact of Social Enterprises: A Bibliometric Analysis From 1991 to 2020
Bibliographic record
Abstract
The aim of this work is to provide, through a bibliometric analysis of the last 30 years of thematic literature, an overview on the contribution of social enterprises to the achievement of global goals.A bibliometric method has been used to analyze the characteristics, citation patterns and content of 3318 documents published in international academic journals, books review and chapters, editorial material and proceedings papers.Considering our findings, the bibliometric analysis has shown that there are journals that have had a greater production on the topic with an impact on research. Thanks to the work of the most impactful authors, it emerges that the case study is the most used method to demonstrate the centrality of social enterprises in social innovation. The analysis also shows that the centrality of the themes is linked to innovation, impact, management and performance, demonstrating the assumption that the driver of innovation in terms of social impact is given by these types of companies. The research also shows the keyword evolution through the years.Through the coding activity, it has also been possible to demonstrate that by transposing the global sustainability objectives to the local that the more in-depth ones are addressed on the issues of sustainable economy and fair, responsible and sustainable innovation, while there is much shortcoming regarding the achievement of gender equality, sustainable water management but even more on the reduction of inequality between nations. The latter is probably conditioned by the more global target and therefore not easily approachable to social enterprises.Research limitations/implications – The study shows a limitation, related to the adoption of the bibliometric method. However, it considers books review, chapters, papers published in international and academic journals, editorial materials, reviews and proceedings papers.Originality/value – This research shows that the interest on SDG and social enterprises has grown continuously in the last 30 years, especially in the last 5. The literature puts social enterprises at the center of social innovation by focusing on performance and management issues. Therefore, with the intention of mapping the studies that have been done in this regard, the study analyzed how research on local development coherence for global development has been addressed.
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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 | 0.006 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.089 | 0.121 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".