Truly, madly, deeply: Strategic entrepreneuring and the aesthetic practices of craft entrepreneurs
Bibliographic record
Abstract
Abstract Research Summary Strategic entrepreneurship research has long focused on high growth and wealth maximization in the creation of primarily economic value. As such, it has largely overlooked craft entrepreneurs, who prioritize skill, materiality, and immersive action in creating broader forms of value. Deep engagement with materials, alongside daily aesthetic (sensory, tacit, embodied) practices are key to how craft entrepreneurs create unique value and strengthen competitive distinction. Drawing on ethnographic data from two craft‐based settings, we abductively generated three dimensions and associated tensions by which craft entrepreneurs leverage aesthetics for strategic entrepreneuring: materializing , enchanting , empathizing . Our key contribution is to unpack the embodied—and very human—processes by which craft entrepreneurs imagine and give life to unique offerings while creating distinctive value for both themselves and their stakeholders. Managerial Summary The focus of strategic entrepreneurship research is often on economic value creation, along with high growth and wealth maximization. By exploring the everyday practices of craft entrepreneurs, we unpack how creating broader forms of value (e.g., symbolic, artistic, social, cultural) through immersive and embodied actions contributes to stylistic and competitive distinction. For the craft entrepreneurs in our study, remaining competitive is about engaging in sensuous practices that result in meaningful and authentic offerings, for both themselves and their stakeholders. By capturing and exploring these daily practices, along with the tensions that undergird real‐time exchanges with stakeholders, we provide fresh insights into how craft entrepreneurs create unique value while delicately balancing tradition with innovation to strengthen competitive distinction.
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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 | 0.006 |
| 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 | 0.029 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".