Performance appraisal interval and employee exploratory innovation behavior: the curvilinear relationship and the boundary conditions
Bibliographic record
Abstract
Purpose Compressing project timelines represents a prevalent temporal tactic aimed at accelerating the innovation process. However, empirical evidence on the impact of such time constraints on innovation remains inconclusive. This study aims to investigate the relationship between a prevalent organizational time mechanism—Performance Appraisal Interval (PAI)—and employee exploratory innovation behavior. Additionally, we explore the boundary conditions that may influence this relationship: the moderating effects of future work self salience and supervisory developmental feedback. Design/methodology/approach Using online survey data collected in two waves from 426 employees working in hi-tech companies in China, we tested all the hypotheses. Findings (1) PAI demonstrates an inverted U-shaped influence on employees exploratory innovation behavior; (2) Employees’ future work self salience serves as a moderator that enhances the positive nature of this inverted U-shaped relationship; (3) Supervisory developmental feedback amplifies the moderating role of future work self salience, and the synergistic effect of PAI, future work self salience, and supervisory developmental feedback significantly enhances exploratory innovation behavior. Practical implications By providing insights that are attuned to the temporal aspects of performance appraisal, this study aids organizations in making more informed, strategic decisions that enhance both the effectiveness of performance assessments and the cultivation of an environment that encourages exploratory innovation. Additionally, it is recommended that organizational leaders incorporate future-oriented interventions and developmental feedback into their management practices to further promote employees' engagement in exploratory innovation. Originality/value Drawing on the interactive theory of performance, this study introduces a novel perspective on how an organizational temporal mechanism influences exploratory innovation and advances our understanding of the non-linear link between time constraints and employees' innovative behaviors.
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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 | 0.001 | 0.000 |
| 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 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".