Mediation of scenario planning on the reflection-performance relationship in new product development teams
Bibliographic record
Abstract
Purpose The purpose of this study is to reveal the mediating role of scenario planning between reflection and task performance in new product development (NPD) teams. Design/methodology/approach A cross-sectional research design was used to collect data from 78 NPD teams and 194 employees. The mediation analyses were conducted through the bootstrap PROCESS macro method. Findings The results of this study yielded support for two of three hypotheses. The authors found that the relationship of reflection with product development speed and new product success is mediated by scenario planning. There was no mediation of scenario planning between reflection and product development cost. Research limitations/implications These findings show how teams can capitalize on reflective thinking practices to increase NPD task performance through scenario planning. Practical implications This study provides useful guidelines for team leaders on how to accelerate product development processes and to increase the market success of a new product. Leaders should encourage their teams to review their previous performance metrics with ongoing changes in the business environments. Originality/value To the best of the authors’ knowledge, this study is the first to examine the mediating role of scenario planning on the reflection–task performance relationship in NPD teams.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 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".