Abstract
Strategic planning is one of the most popular strategy approaches across sectors and across the globe. Unsurprisingly, research on strategic planning crosses disciplines ranging from management and public administration to healthcare, urban planning and sustainability. This fragmentation has resulted in research silos, with little interaction between disciplines. Integration across disciplines is needed to understand the various purposes strategic planning can serve. This study uses topic modeling, a machine learning tool, to analyze 6361 articles on strategic planning. Ten topics are identified, which can be clustered into four categories: societal issues and challenges, processes and practices, street-level sectors, and corporate functions. Time trends analysis indicates a steep increase over time in research attention to strategic planning for the purpose of addressing societal issues and challenges. Combined with a qualitative meta-narrative review, these findings result in a purposeful strategic planning definition and conceptualization to guide theory, research and practice. © 2025 The Author(s).
| Original language | English |
|---|---|
| Article number | 102563 |
| Journal | Long Range Planning |
| Volume | 58 |
| Issue number | 4 |
| Online published | 6 Jul 2025 |
| DOIs | |
| Publication status | Published - Aug 2025 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 11 Sustainable Cities and Communities
Research Keywords
- Strategic planning
- Machine learning
- Topic modelling
- Meta-narrative review
- Mixed research synthesis
Publisher's Copyright Statement
- This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/
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