How Does Age Moderate the Determinants of Crowdfunding Adoption by SMEs’s: Evidences from Morocco?
Bibliographic record
Abstract
In recent years, crowdfunding has emerged as a new fundraising technique for start-up ventures; however, Moroccan small and medium-sized businesses are still wary of this novel source of funding. This is confirmed by the low adoption rate of this financial innovation as well as the limited number of crowdfunding platforms in Morocco. This study aims to identify the impact of performance expectancy (PE), effort expectancy (EE), social influence (SI), facilitating conditions (FC), and perceived risk (PR) on SMEs’s intention to use crowdfunding platforms using a research model based on the Unified Theory of Acceptance and Use of Technology (UTAUT). Empirical data were collected from 241 respondents through a survey, and structural equation modelling was used to analyze the findings. The results show that performance expectancy (PE), effort expectancy (EE), and facilitating conditions (FE) affect SMEs’s intentions to use crowdfunding. However, social influences (SI) and perceived risk (PR) were not found to be significant determinants. Regarding the moderating effect of age, our study has highlighted that this variable has moderated the relationship between the three independents variables: performance expectancy, facilitating conditions and perceived risk. Finally, this paper offers recommendations for how to increase SMEs’s intention to use crowdfunding platforms.
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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 | 0.001 | 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 | 0.001 | 0.002 |
| 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".