| Area: 6255 km2 | |
| Population: 198565 | |
| GDP at current prices (M EUR): : | |
| GDP per capita at current prices (EUR): 37382 | |
| % of National GDP: No information available. | |
| % of Unemployment: : | |
| Regional GERD (%): : |
| Name of strategy | Päijät-Häme Smart Specialisation Strategy |
| Type of strategy | Regional |
| Languages | FI |
| Strategy approved | Yes |
| Name | Position | Contact |
|---|---|---|
| Harri Kuusela | Regional Council of Päijät-Häme | harri.kuusela@paijat-hame.fi;toimisto@paijat-hame.fi |
Support the development of a Monitoring and Evaluation system
The targeted assignment for the Region of Päijät-Häme focuses on supporting its transition from traditional industry to a green, competency-based economy while addressing significant socio-economic and demographic challenges. One of the primary issues is the current Monitoring and Evaluation (M&E) system, which emphasizes funding without adequately capturing outcomes and impacts. To effectively tackle these challenges, the Regional Council of Päijät-Häme aims to enhance its M&E system by establishing feedback loops that provide clarity on how funding influences the region’s economy and social fabric. This assignment involves a thorough review of the existing M&E system to identify areas for improvement, culminating in the development of new indicators and analytical methods. The final deliverable includes a comprehensive set of indicators, an evaluation framework for interim and ex-post assessments of S3 activities, and detailed guidelines for implementing the upgraded M&E system.
| Aerospace & Defence ➝ | ||
| Agri-food ➝ | ||
| Construction ➝ | ||
| Creative & Cultural Industries ➝ | ||
| Digital ➝ | ||
| Electronics ➝ | ||
| Energy/Renewable Energy ➝ | ||
| Energy Intensive Industries ➝ |
| Healthcare ➝ | ||
| Mobility, Transport & Automotive ➝ | ||
| Proximity Economy ➝ | ||
| Retail ➝ | ||
| Social Economy ➝ | ||
| Textiles ➝ | ||
| Tourism ➝ |
These keywords, identified using AI and manually verified, highlight the key elements of each strategic priority as reflected in individual strategies.
These keywords, identified and associated through semantic AI algorithms and manually reviewed, support the search function by identifying topics related to each strategic priority. While a priority may not explicitly focus on these keywords, they provide meaningful connections. For exxample, agricultural terms might relate to circular economy priorities, such as biofuels or agricultural waste valorisation. Semantically associated keywords enable users to find regions with similar or related priorities, offering a starting point for deeper exploration of each specific strategy.
| Priority | Descriptive keywords | Semantic keywords |
|---|---|---|
| Sport | : | undefined |
| Food and beverage | : | undefined |
| Manufacturing | : | undefined |
| Sustainability | : | undefined |
| Economic classification (NACE section & division) | Scientific classification (NABS digit 1 & 2) | |
|---|---|---|
| Sport |
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| Food and beverage |
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| Manufacturing |
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| Sustainability |
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| Document type | Link |
|---|---|
| Webpage | No information available. |
| Webpage | Link to ERDF programmes database |
No information available.
No information available.
No information available.