Corporate Social Responsibility and Entrepreneurial Ventures: A Conceptual Framework and Research Agenda
Bibliographic record
Abstract
Corporate social responsibility (CSR) and entrepreneurship are two essential topics in the current business landscape. However, despite the growing literature on these topics, there needs to be more comprehensive understanding of how they are related. In this conceptual article, we explore the linkages between CSR and entrepreneurship. First, we provide a definition and scope of entrepreneurship and then discuss the literature on CSR, highlighting different ways that businesses can engage in CSR. We argue that CSR and entrepreneurship are closely related, and propose a conceptual framework to understand how CSR can be integrated into the entrepreneurial process. Additionally, we identify three key areas of research in this emerging field: (1) the motivations for entrepreneurs to engage in CSR; (2) the impact of CSR on entrepreneurial ventures; and (3) the role of CSR in social entrepreneurship. We conclude with a discussion of our conceptual framework’s theoretical and practical implications, as well as future research directions for scholars and practitioners interested in CSR and Entrepreneurship.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.004 | 0.024 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".