A measure of affordable loss in effectual decision-making
Bibliographic record
Abstract
The aim of this research study was to build a valid and parsimonious instrument to measure the entrepreneurial decision-making heuristic of affordable loss. The researcher argued that current scales measuring effectuation do not theoretically account for the affordable loss construct in a comprehensive way. Furthermore, existing scales hold shortcomings such as relying on retrospective accounts, a focus on only start-up phase, possible social desirability bias in items, and sampling from only a few industries. After extracting the core characteristics and conceptual domain from literature, a small qualitative engagement with expert entrepreneurs offered a deepened understanding of affordable loss. The main quantitative phase included three waves of data collection from 867 respondents across four countries, namely Canada, South Africa, United Kingdom, and United States. Through iterations of scale purification, a parsimonious and brief six-item and two-factor solution was generated. The study shows that affordable loss is constituted of a loss heuristic factor, as well as an experimental investing factor. Moreover, the newly developed scale operationalises affordable loss as a learned decision-making heuristic, whereby the agentic entrepreneur encounters uncertainty and emphasises downside risk potential, while still engaging in affordable and iterative investment experiments to overcome the uncertainty. Nomological validity was established, and measurement invariance upheld, for the new instrument. In terms of nomology, affordable loss was linked to well-established constructs – with entrepreneurial self-efficacy and loss aversion as antecedents and entrepreneurial bricolage as an outcome. The study contributes to theory in revealing two inextricably linked factors constituting affordable loss. Moreover, it empirically links the construct to two antecedents and one outcome for the first time with the new instrument. Methodologically, the study contributes the scale itself for scholars to employ in future research endeavours. Practically, the study offers practitioners a scale that may be used to assess entrepreneurs in development or incubation programmes, while offering teachers insight into the need to teach the two factors of affordable loss in unison. Finally, the study offers several suggested avenues for future research that may employ the scale.
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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 | 0.000 | 0.000 |
| 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".