Unboxing the temporal patterns of employee engagement: a daily and weekly analysis of needs satisfaction, work motivation and employee well-being
Bibliographic record
Abstract
Purpose This research used a temporal approach to operationalize employee engagement, capturing subjective/objective time of the day and day of the week to analyze the dynamic patterns of employees’ daily/weekly well-being, basic needs satisfaction, and situational work motivation under the integrated framework of self-determination theory. Design/methodology/approach Multi-level data was collected using the survey structure outlined under the day reconstruction methodology (DRM) with samples of Canadian part-time working undergraduate students and full-time US corporate employees (1980 work episodes reported by 321 participants). Findings Multi-level confirmatory factorial analysis results supported the measurement invariance for within-person variables in all the working episodes across the US and Canada samples. Structural equation modeling path analysis results, using the within-person variables, captured the daily temporal patterns that employees’ well-being (vitality and positive affect), basic psychological needs (autonomy and relatedness), and situational autonomous motivation started at a high level and decreased with both subjective and objective time of the day. Negative affect showed asymmetric daily and weekly temporal patterns compared to positive affect. A few indirect paths were found, including one from the subjective time of the day to employee well-being (vitality and affect) via situational autonomous motivation and another one from the day of the week to vitality and positive affect via relatedness needs satisfaction and situational autonomous motivation. Research limitations/implications The socio-cultural and business impacts of work scheduling practices and implications for theory-driven, evidence-based organizational development practices were discussed together with the research limitations. Practical implications Results on how the variations in self-regulation during the performance of different work tasks in a single work event help practitioners to connect repeated situational motivational change patterns to effective supervision. HR business partner can also utilize such findings to shape evidence-based practice to improve employee engagement. Originality/value This research is one of the few pioneer studies to look into how temporal factors, such as work scheduling, affect employees' well-being through the dynamic understanding of the mediated path model from time to employee well-being via psychological engagement conditions such as motivation and needs satisfaction.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| 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".