Staying Engaged During the Remote Work Revolution: An Integrated Job Crafting Perspective
Notice bibliographique
Résumé
Hybrid and remote workers now comprise nearly one-third of the working population in the U.S. and Canada (Barrero et al., 2021; StatCan, 2021), while employee engagement has dropped to its lowest point in a decade (Harter, 2023). It is now more crucial than ever to identify valuable strategies for individuals and organizations to increase engagement at work. Job crafting is a bottom-up approach to work design (Chen, 2022a, 2022b; Donaldson et al., 2021; Tims et al., 2012; Wrzesniewski & Dutton, 2001), extensively studied as a proactive employee behavior associated with increased engagement among other positive work outcomes (Lichtenthaler & Fischbach, 2019; Mukherjee & Dhar, 2022; Tims et al., 2012). However, job crafting can also be a “double-edged sword” (Harju et al., 2021), with promotion-focused (boundary expansion) behaviors contributing to engagement while prevention-focused (boundary reduction) behaviors detracting from engagement (Lichtenthaler & Fischbach, 2019). This dissertation is one of the first to investigate work engagement in the remote work context from an integrated promotion- and prevention-focused job crafting perspective (Tims et al., 2022). A sample of (n = 433) hybrid and remote workers were recruited for this cross-sectional study using CloudResearch Connect. Structural Equation Modeling (SEM) was utilized to determine whether promotion- and prevention-focused job crafting mediated the relationship between remote work resources/demands and work engagement. Hierarchical regression was run to understand the moderating role of perceived job crafting success on the relationship between job crafting and work engagement in gain cycles and loss spirals. Study findings supported the mediating role of promotion-focused job crafting on the relationship between remote work resources, demands, and engagement. Participants with high remote work resources and demands were found to engage in promotion-focused job crafting, while those with only high demands resorted to prevention-focused job crafting. Perceived job crafting success positively moderated the relationship between prevention-focused job crafting and work engagement. In conclusion, organizations can increase work engagement and the formation of gain cycles by providing adequate remote work resources, such as increased visibility and social support, to encourage promotion-focused job crafting. At the same time, hindering remote work demands, such as professional isolation and technology overload, should be minimized to avoid the preponderance of prevention-focused job crafting behaviors associated with decreased engagement. Managers can help employees break out of self-sabotaging loss spirals by facilitating short-term reductions in work boundaries and offering additional resources to offset hindering demands. Additional insights based on the study findings are provided for individuals and organizations navigating the sea of changes brought about by the remote work modality.
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Prédiction machine sur la base complète
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Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,006 | 0,005 |
| Communication savante | 0,008 | 0,005 |
| Science ouverte | 0,001 | 0,006 |
| Intégrité de la recherche | 0,001 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».