MétaCan
Menu
Back to cohort
Record W4406300739 · doi:10.1177/10944281241310574

Surveying the Upper Echelons: An Update to Cycyota and Harrison (2006) on Top Manager Response Rates and Recommendations for the Future

2025· article· en· W4406300739 on OpenAlexaff
Cameron J. Borgholthaus, Alaric Bourgoin, Peter D. Harms, Joshua V. White, Tyler N. A. Fezzey

Bibliographic record

VenueOrganizational Research Methods · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCustomer Service Quality and Loyalty
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsUpper echelonsPsychologySocial psychology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.059
metaresearch head score (Gemma)0.181
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.941
Threshold uncertainty score0.313

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0590.181
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0150.025
Science and technology studies0.0020.005
Scholarly communication0.0090.013
Open science0.0030.005
Research integrity0.0020.007
Insufficient payload (model declined to judge)0.0060.003

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.

Opus teacher head0.114
GPT teacher head0.488
Teacher spread0.374 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designObservational
DomainMethods
GenreEmpirical

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".

Quick stats

Citations7
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueOrganizational Research MethodsSame topicCustomer Service Quality and LoyaltyFrench-language works237,207