Purpose in practice: Mission implementation and employees’ psychosocial outcomes across organizational contexts
Publication date
2025-10-01ISBN
978-3-031-97608-7
Abstract
Amid shifting organizational landscapes, mission has gained prominence as a strategic mechanism for promoting alignment and shared purpose. Yet, declaration of mission alone rarely leads to meaningful impact unless it is understood, internalized, and enacted in employees’ daily work. This paper examines how effective mission implementation, defined as the consistency between mission content, practice, and motivation, relates to employee outcomes, including organizational commitment, prosocial behavior, and meaningful work. Study 1 draws on data from employees in organizations participating in the Driving Purpose and Mission Collaborative (DPMC), which actively engage in purpose-driven management practices. Study 2 includes employees from a broader range of organizations without formalized mission structures. Structural equation modeling was used in both studies. In Study 1, effective mission implementation directly predicted prosocial behavior and indirectly predicted meaningful work, mediated by organizational trust. In Study 2, mission implementation influenced outcomes only indirectly, with trust playing a central mediating role. These findings underscore the significance of mission implementation as a dynamic, context-sensitive process and demonstrate how alignment, trust, and prosocial motivation shape employees’ experience of purpose at work.
Document Type
Chapter or part of a book
Document version
Published version
Language
English
Subject (CDU)
65 - Communication and transport industries. Accountancy. Business management. Public relations
Keywords
Pages
Desconocido
Publisher
Springer
Recommended citation
Skhirtladze, E.; Selvam, R.; Rey, C. [et. al]. Purpose in practice: Mission implementation and employees’ psychosocial outcomes across organizational contexts. En: Integrating big data and IoT for enhanced decision-making systems in business. Studies in Big Data, Springer Cham, 2026, 177, pp. 299–308. Disponible en: <https://link.springer.com/chapter/10.1007/978-3-031-97609-4_25>. Fecha de acceso: 27 Mar 2026. ISBN: 978-3-031-97608-7. DOI: 10.1007/978-3-031-97609-4_25
This item appears in the following Collection(s)
- Capítols de llibre [52]
Rights
© 2026 The Author(s), under exclusive license to Springer Nature Switzerland AG

