Student entrepreneurs with triple bottom line objectives: capabilities in creating viable business models
Bibliographic record
Abstract
Purpose The objective of this instrumental case study is to investigate issues impacting capability development/transformation with respect to student entrepreneurs’ aspirations to create a viable, evolving business model for their start-ups, namely, that are underpinned by goals featuring the “triple bottom line”. That is, instead of simply profits as an economic performance metric, there is also a consideration of wider social issues within the notion of “responsible leadership”, involving people and the planet. Design/methodology/approach Underpinned by a “capabilities lens”, the research setting focuses on the perceptions of student entrepreneurs together with other stakeholders in a Canadian university. The country context is pertinent, since to gain scalability, owners of start-up firms may need to internationalise to overcome limited domestic demand (despite the large geographic area); also, stakeholders’ support is sometimes needed to facilitate growth. Findings New insights demonstrate the need for appropriate stakeholders to facilitate effective transformative capability development amongst student entrepreneurs with triple bottom line objectives. Student entrepreneurs’ capability of validating facets of a viable evolving business model that address “all” and not “some” aspects of the triple bottom line is especially important. This is alongside the capability of being able to pivot product-market strategies where necessary, and this may feature the need to internationalise in the event there is limited domestic demand. A capability to develop soft skills is also likely to help student entrepreneurs communicate with stakeholders. In turn, such capabilities are likely to help move ideation, passed validation and through to commercialisation. Originality/value The utility of institutions and associated stakeholders offering education and training support to develop capabilities amongst students as aspiring entrepreneurs has featured in earlier studies. Likewise, issues associated with the notion of sustainability have also been previously considered. The originality of this instrumental case study is to offer a more nuanced investigation into salient issues associated with capability development amongst student entrepreneurs exhibiting triple bottom line objectives in their start-ups. That is, focusing on considerations related to validating their evolving business models and especially when facing limited domestic market demand.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".