The Tuscany Integrated Supply Chain Projects 2014–2022: A New Path to Support the Agri-Food Industry
Abstract
:1. Introduction
2. Materials and Methods
2.1. Background
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- Bottom-up approach: the integrated project starts from the needs of a group of actors who, having identified specific needs, outline a sectoral or territorial intervention strategy;
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- Cross-sectorality: the integrated project is a complex project that seeks to involve all those who participate in a production process or who live and operate in a given area, creating specific synergies and influencing economic and social relations;
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- Co-ordinated use of several intervention instruments: the integrated project must allow access to several RDP intervention measures, and possibly to other public policy instruments, in order to support all the interventions deemed useful for the envisaged strategy;
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- Presence of a specific development strategy: integration between several subjects must be supported by a specific strategy that outlines the specific features and justifies the actions undertaken within the project;
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- Creation of a structured partnership whose members are representative of the interests of the sectors and territories involved: the partnership must have precise responsibilities and guarantee the implementation of the project.
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- The variety of objectives to be integrated into an overall strategy;
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- The combination of support and incentive instruments at the service of the intervention strategy;
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- The aggregation of financial resources around a project idea;
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- The integration between the actors of the production chain (from raw materials to the marketing of the finished product);
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- The coordinated action, aimed at returning economic benefits to all stakeholders;
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- The use of all the different professional skills and competences needed to plan and implement the interventions.
2.2. The Tuscany Integrated Supply Chain Projects
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- Low qualification of operators that cannot be solved by technical assistance and services;
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- Low generational turnover, leading to a progressive ageing of operators and the reduction of stable employment replaced by temporary and less efficient employment;
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- Progressive reduction in the size of the agricultural sector, both in numerical terms and in terms of the size of enterprises;
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- Inadequate infrastructure for businesses and rural communities, particularly for the distribution and efficiency of water resources.
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- The identification of the sectors that need priority public support action;
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- The identification of measures that enable the financing of integrated design among other measures under the RDP;
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- Exploitation of synergies and complementarities;
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- Adoption of procedures that respect the principle of competition between economic operators.
2.3. The Statistical Analysis: The Dataset and Variables Used
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- Identifying the treated group: a panel dataset was defined (from 2018 to 2020) using the FADN regional dataset;
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- Identifying the control group using non-treated farms in the FADN regional dataset: the farms selected were those that did not join the integrated supply chain program (Tuscany RDP);
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- Providing statistical analysis to identify the differences between treated and non-treated farms by applying the Welch-t-test on main structural and economic variables;
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- Evaluating the results of treated and control Tuscany farms.
3. Results
3.1. Participation to Tuscany Rural Development
3.2. The Rural Production Chains Concerned
3.3. The Main Characteristics of the Sample
3.4. The Farm Characteristics and the Structural Variables
3.5. The Balance Sheet Variables
4. Discussion
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Code | Sub-Measures/Operations |
---|---|
1.2 | Support for demonstration activities and information actions |
3.1 | Support for new quality assurance schemes |
3.2 | Support for information and promotion activities carried out by producers’ associations in the internal market |
4.1.3 | Integrated Projects |
4.1.5 | Encouragement for the use of renewable energy in farms |
4.2.1 | Support for investments in the processing/marketing and/or development of agricultural products |
6.4.1 | Farm diversification |
6.4.2 | Energy deriving from renewable sources in rural areas |
8.5 | Investments aimed at increasing the resilience and environmental value of forest ecosystems |
8.6 | Support for investments in forestry technologies and in the processing, mobilization and marketing of forest products |
16.2 | Support for pilot and cooperation projects |
16.3 | Cooperation between small operators to organize joint work processes and share facilities and resources, as well for the development/marketing–tourism sector |
16.6 | Support for supply chain cooperation for the sustainable procurement of biomass to be used in production of food and energy and industrial processes |
16.8 | Support in drafting forest management plans or equivalent tools |
Sub-Measures/ Operations | Number of Applications | Distribution of Funds (Million Euro) | Distribution of Funds (%) |
---|---|---|---|
1.2 | 33 | 1.4 | 1.03 |
3.1 | 20 | 0.1 | 0.06 |
3.2 | 17 | 3.5 | 2.45 |
4.1.3 | 1210 | 73.4 | 51.25 |
4.1.5 | 75 | 1.9 | 1.32 |
4.2.1 | 128 | 31.8 | 22.61 |
6.4.1 | 50 | 3.9 | 2.76 |
6.4.2 | 14 | 0.9 | 0.64 |
8.5 | 4 | 0.5 | 0.35 |
8.6 | 75 | 5.1 | 3.64 |
16.2 | 369 | 16.7 | 11.86 |
16.3 | 17 | 0.9 | 0.62 |
16.6 | 3 | 0.6 | 0.41 |
16.8 | 1 | 0.2 | 0.14 |
Total | 2016 | 140.8 | 100 |
Control | Treated | |||
---|---|---|---|---|
Type of Farming | Value [%] | Number of Farms/Total Farms Considered | Value [%] | Number of Farms/Total Farms Considered |
Arable crops | 17.77 | 277/1559 | 13.43 | 18/134 |
Cereal crops | 5.26 | 82/1559 | 11.19 | 15/134 |
Granivores | 2.82 | 44/1559 | - | - |
Herbivores | 13.73 | 214/1559 | 11.19 | 15/134 |
Horticulture | 17.00 | 265/1559 | 8.95 | 12/134 |
Milk cattle | 0.45 | 7/1559 | 8.95 | 12/134 |
Mixed farms | 13.53 | 211/1559 | 14.93 | 20/134 |
Olive growing | 5.26 | 82/1559 | - | - |
Orchards | 5.58 | 87/1559 | 3.73 | 5/134 |
Viticulture | 18.60 | 290/1559 | 27.63 | 37/134 |
Control | Treated | |||
---|---|---|---|---|
Value [%] | Number of Farms/Total Farms Considered | Value [%] | Number of Farms/Total Farms Considered | |
Farm characteristics variables | ||||
Women-led farms | 23.54 | 367/1559 | 20.14 | 27/134 |
Youth-led farms | 10.07 | 157/1559 | 6.72 | 9/134 |
Diversified farms | 27.64 | 431/1559 | 47.76 | 64/134 |
Organic farms | 27.00 | 421/1559 | 47.76 | 64/134 |
Farms Location | ||||
Plain | 11.61 | 181/1559 | 11.19 | 15/134 |
Hill | 70.75 | 1103/1559 | 73.14 | 98/134 |
Mountain | 17.64 | 275/1559 | 15.67 | 21/134 |
Control | Treated | Statistical Analysis | |||
---|---|---|---|---|---|
Mean | Standard Deviation | Mean | Standard Deviation | Welch-t-Test | |
Farm Structural Variables | |||||
Total Area—Large Farms [ha] | 42.48 | 77.69 | 114.75 | 190.25 | **** |
UAA—[ha] | 32.34 | 53.05 | 81.57 | 117.93 | **** |
Labour Variables | |||||
Machine power expressed by KW per Utilised Agricultural Area [KW/UAA] | 22.20 | 59.33 | 11.58 | 17.26 | **** |
AWU | 2.00 | 1.87 | 3.89 | 6.37 | **** |
Control | Treated | Statistical Analysis | |||
---|---|---|---|---|---|
Mean | Standard Deviation | Mean | Standard Deviation | Welch-t-Test | |
Economic variables | |||||
Farm Net Value Added—[Euro] | 61,607.0 | 114,809.4 | 150,000.0 | 311,252.5 | *** |
Farm Net Value Added/UAA—[Euro/ha] | 9077.1 | 24,016.2 | 5476.0 | 13,787.6 | *** |
Farm Net Value Added/AWU—[Euro/AWU] | 24,678.6 | 21,459.3 | 32,753.3 | 25,359.1 | **** |
Net Income/UAA—[Euro/ha] | 5334.8 | 13,390.0 | 2752.2 | 7936.6 | **** |
Variables Costs/UAA—[Euro/ha] | 10,753.4 | 35,772.0 | 11,199.0 | 42,548.0 | ns |
Value Added/UAA—[Euro/ha] | 9727.4 | 25,323.2 | 5776.0 | 13,539.3 | *** |
Control | Treated | Statistical Analysis | |||
---|---|---|---|---|---|
Mean | Standard Deviation | Mean | Standard Deviation | Welch-t-Test | |
Patrimonial variables | |||||
Agricultural Capital/UAA—[Euro/ha] | 2841.6 | 8003.5 | 2289.4 | 2446.8 | ns |
Fixed Capital/UAA—[Euro/ha] | 35,757.4 | 59,326.0 | 27,899.3 | 54,691.6 | ns |
EU Help found—[Euro] | 9171.1 | 16,680.0 | 25,322.5 | 34,354.9 | **** |
EU Help found/UAA—[Euro/ha] | 319.5 | 854.6 | 331.0 | 466.3 | ns |
New Investments—[Euro] | 14,677.4 | 33,335.6 | 38,892.7 | 72,596.1 | *** |
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Cisilino, F.; Giampaolo, A.; Licciardo, F.; Orlando, M.; Tarangioli, S. The Tuscany Integrated Supply Chain Projects 2014–2022: A New Path to Support the Agri-Food Industry. Land 2023, 12, 1230. https://doi.org/10.3390/land12061230
Cisilino F, Giampaolo A, Licciardo F, Orlando M, Tarangioli S. The Tuscany Integrated Supply Chain Projects 2014–2022: A New Path to Support the Agri-Food Industry. Land. 2023; 12(6):1230. https://doi.org/10.3390/land12061230
Chicago/Turabian StyleCisilino, Federica, Antonio Giampaolo, Francesco Licciardo, Matteo Orlando, and Serena Tarangioli. 2023. "The Tuscany Integrated Supply Chain Projects 2014–2022: A New Path to Support the Agri-Food Industry" Land 12, no. 6: 1230. https://doi.org/10.3390/land12061230
APA StyleCisilino, F., Giampaolo, A., Licciardo, F., Orlando, M., & Tarangioli, S. (2023). The Tuscany Integrated Supply Chain Projects 2014–2022: A New Path to Support the Agri-Food Industry. Land, 12(6), 1230. https://doi.org/10.3390/land12061230