Concept testing: the state of contemporary practice
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose The purpose of this paper is to better understand current concept testing practice and its role in the new product development process; identify the relationship, if any, between concept testing design and perceptions of its effectiveness; determine what evidence product managers or research consultants have for the reliability and validity of current concept testing. Design/methodology/approach A survey of new product managers collected detailed information on their organization's most recent traditional or conjoint concept testing project. In the study of marketing research consultants, 100 firms were asked to provide the publicly available information about the reliability and validity track record of their concept testing services. Findings There are differences between practices for incrementally and radically new concepts. Practitioners prefer to keep their information proprietary, so little has been learned about how concept tests should be designed, despite the thousands of concepts tested every year. Practical implications The paper identifies current concept testing practice, including which methods/models are used, what is known about their reliability and validity, and the perceived problems and desired improvements. Originality/value The paper identifies how concept testing is currently carried out and those issues most in need of future research.
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.
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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it