Use of Entrepreneurial Marketing in Fostering Resellers’ Adoption of Smart Micro-Grid Technology
Bibliographic record
Abstract
This thesis investigates how entrepreneurial marketing (EM) can foster reseller's adoption of smart micro-grid (SMG) technology. Previous studies have emphasized the technical aspects of this new area of power systems industry. However, there is a need to understand the market adoption, especially that of resellers who act as intermediaries between suppliers and end-customers. An online survey based on the technology acceptance model (TAM) and EM literatures was used to gather data from 99 resellers. The data were analyzed using the partial least squares method to validate a model of the relationships between resellers' antecedents and intention to adopt SMG technology, and the role of suppliers' EM for the adoption. The results suggest that TAM can only partially be applied to the reseller context. Moreover, suppliers need to demonstrate EM, particularly entrepreneurial orientation, to increase resellers' performance expectancy and to decrease effort expectancy to foster the diffusion of novel SMG technology.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".