Suchergebnisse

This research aims at examining impacts of ASEAN+6 trade agreements on the automobile industry in Vietnam. Vietnam's automobile industry competes with Thailand, Indonesia and the ASEAN countries as well as China, Korea, Japan and those covered by the ASEAN agreement. By 2018, the automobile import tariff from China, Korea and Japan will be reduced to 5%. In the context of multiple trade agreements, the study of the automobile industry has recently become an interesting topic, especially for policy debate.

Considering the features of GIs and organic production, Deliverable 5.2 analyses the relationships between Public Goods (PGs) and Food Quality Schemes (FQS). The deliverable evaluates the impacts of the cases study described in Deliverable 5.1 in terms of their contribution to rural development and territorial cohesion given by the capacity to generate positive externalities and hence PGs. The analysis focuses on: i) contribution to local economies; ii) generation of environmental, social and cultural externalities; iii) contribution of different governance mechanisms to ensure the valorisation of producers' know-how and local resources; iv) social cohesion in term of creation of social capital and social networks. Overall, the products that fall within the organic FQS category, contribute to the generation of environmental PGs more than the GI FQS. However, the latter contribute more to the generation of socio-economic PGs. In general, most FQS present a low capacity to generate Cultural Heritage PGs. This indicates that there is considerable space to improve the cultural dimension of these products for the benefit of producers and consumers. The analysis conducted by the Strength2Food methodology show that if there is political will on the part of producers, there is room for improvement in the generation of PGs. At the same time, the measurement of the capacity to produce PGs would further justify the greater economic value of these products to consumers.

Considering the features of GIs and organic production, Deliverable 5.2 analyses the relationships between Public Goods (PGs) and Food Quality Schemes (FQS). The deliverable evaluates the impacts of the cases study described in Deliverable 5.1 in terms of their contribution to rural development and territorial cohesion given by the capacity to generate positive externalities and hence PGs. The analysis focuses on: i) contribution to local economies; ii) generation of environmental, social and cultural externalities; iii) contribution of different governance mechanisms to ensure the valorisation of producers' know-how and local resources; iv) social cohesion in term of creation of social capital and social networks. Overall, the products that fall within the organic FQS category, contribute to the generation of environmental PGs more than the GI FQS. However, the latter contribute more to the generation of socio-economic PGs. In general, most FQS present a low capacity to generate Cultural Heritage PGs. This indicates that there is considerable space to improve the cultural dimension of these products for the benefit of producers and consumers. The analysis conducted by the Strength2Food methodology show that if there is political will on the part of producers, there is room for improvement in the generation of PGs. At the same time, the measurement of the capacity to produce PGs would further justify the greater economic value of these products to consumers.

Considering the features of GIs and organic production, Deliverable 5.2 analyses the relationships between Public Goods (PGs) and Food Quality Schemes (FQS). The deliverable evaluates the impacts of the cases study described in Deliverable 5.1 in terms of their contribution to rural development and territorial cohesion given by the capacity to generate positive externalities and hence PGs. The analysis focuses on: i) contribution to local economies; ii) generation of environmental, social and cultural externalities; iii) contribution of different governance mechanisms to ensure the valorisation of producers' know-how and local resources; iv) social cohesion in term of creation of social capital and social networks. Overall, the products that fall within the organic FQS category, contribute to the generation of environmental PGs more than the GI FQS. However, the latter contribute more to the generation of socio-economic PGs. In general, most FQS present a low capacity to generate Cultural Heritage PGs. This indicates that there is considerable space to improve the cultural dimension of these products for the benefit of producers and consumers. The analysis conducted by the Strength2Food methodology show that if there is political will on the part of producers, there is room for improvement in the generation of PGs. At the same time, the measurement of the capacity to produce PGs would further justify the greater economic value of these products to consumers.

Abstract
The dataset Sustainability performance of certified and non-certified food (https://www.doi.org/10.15454/OP51SJ) contains 25 indicators of economic, environmental, and social performance, estimated for 27 certified food value chains and their 27 conventional reference products. The indicators are estimated at different levels of the value chain: farm level, processing level, and retail level. It also contains the raw data based on which the indicators are estimated, its source, and the completed spreadsheet calculators for the following indicators: carbon footprint and food miles. This article describes the common method and indicators used to collect data for the twenty-seven certified products and their conventional counterparts. It presents the assumptions and choices, the process of data collection, and the indicator estimation methods designed to assess the three sustainability dimensions within a reasonable time constraint. That is: three person-months for each food quality scheme and its non-certified reference product. Several prioritisations were set regarding data collection (indicator, variable, value chain level) together with a level of representativeness specific to each variable and product type (country and sector). Technical details on how relatively common variables (e.g., number of animals per hectare) are combined into indicators (e.g., carbon footprint) are provided in the full documentation of the dataset.