Surveying the Upper Echelons: An Update to Cycyota and Harrison (2006) on Top Manager Response Rates and Recommendations for the Future
Bibliographic record
Abstract
Nearly 2 decades ago, Cycyota and Harrison (2006) documented a concerning trend of declining executive survey response rates and projected a continued decrease in the future. Their seminal work has significantly influenced the methodologies of upper echelons survey research. Our study examines the manner in which Cycyota and Harrison’s paper has impacted the existing upper echelons literature and replicates their study by analyzing peer-reviewed studies published post-2006. We reveal that executive response rates have largely stabilized since Cycyota and Harrison’s initial findings. Furthermore, we expand upon their research by identifying specific geographical contexts and contact methodologies associated with higher (and lower) response rates. Finally, we lend insight into the evolving landscape of executive survey research and offer practical implications for future methodological endeavors in the upper echelons.
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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 | 0.059 | 0.181 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.015 | 0.025 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.009 | 0.013 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".