Factors Affecting Leaders’ Adoption of Innovation:
Bibliographic record
Abstract
This study's focus is to determine why some leaders adopt an innovation, while others do not, through the case of high school athletic directors' digital ticket adoption. We explore the process through which sport managers evaluate an innovation as the best course of action. The purpose of this study was to identify critical factors influencing high school athletic directors' decisions to adopt digital ticketing as the best strategy for securing revenue and serving their event attendees. High school athletic directors (N = 628) completed an online survey measuring the effects that leaders' prior conditions and perceived characteristics of the innovation (i.e., independent variables) have on their decision to adopt or reject the technology (i.e., dependent variable). From a theoretical perspective, we extend the conceptual model proposed by Rogers' Diffusion of Innovation Theory, including two constructs specific to the situation considered (i.e., trust and cost). From a managerial standpoint, there appears to be a need to educate athletic directors on the free digital ticketing options available and its ease-of-use. Future research should explore the athletic directors' decision-making process across a more extensive timeline through a longitudinal study.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.010 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".