The name is absent

The score for regional wealth

This score (regional wealth index, or IRR) measures the size and dynamism of the potential regional
market through the population, demographic growth, per capita income, economic growth and the effort
expended on innovation, with the help of spending on R&D.

This score is highly discriminatory as it runs from 3 to 18/20. The leading regions are located in France
(Rhône-Alpes, PACA), Spain (Cataluna, Andalusia) and Italy (Latium). They all have a large population
(more than 4 million inhabitants), a high income level (more than 20 K €/inhabitant) and a relatively high
technological intensity (R&D/GDP ratio greater than 1). On the contrary, regions with a low regional
richness index have a small population, GDP per capita below the average (19 K €) and mediocre
investment in innovation (less than 1%). However, economic growth (variation in GDP between 1999 and
2002) is more notable here than in the rich regions. These regions are located in Greece (Thessalia,
Makedonia), Portugal (Alentejo, Algarve), Spain (Aragon) and Italy (Calabria).

2. - Calculating the srvi in the context of 4 scenarios

Let us recall that the SRVI combines the 4 score functions analysed above (F&LF, F&LT, EC et IRR)
using the parameters:

IVR = 1/[ (FF&V) x α + (PF&V) x β + (MKO) x λ + (WRI) x θ]

As the 4 functions cover differing sectors and domains, we have developed simulations by modifying the
value of the parameters so as to present 4 scenarios characteristic of the components of the fruit and
vegetables supply chains¹¹:

- Scenario 1: strong agricultural production (the weighting coefficient relating to the fruit and
vegetable production sector, FF&V, is high)

- Scenario 2: strong downstream (the coefficients concerning the fruit and vegetable processing
industry, PF&V, and the wholesale companies¹², MKO, are high)

- Scenario 3: strong economic environment (high parameter for WRI)

- Scenario 4: balance between the 4 components of the SRVI

Tabl. 8: Parameters of the Score Functions Simulations

The scores have been calibrated in relation to 20 and the SRVI in relation to 10 in order to make it easier
to interpret the results of the calculations. The SRVI can, then, assume values ranging form 0 to 10.

The following table presents the scores obtained by the 30 regions in our sample for the 4 scenarios.

¹¹ On the Scenario method, see Godet (2001).

¹² For the 14 Greek regions, data for wholesalers was not available.

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