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In this paper, we develop a novel discriminant framework, which allows to integrate the socio-economic determinants of the potential beneficiaries in the Social Innovation intothe discrimination process. Specifically, we formulate the socio-economic characteristics of all the participants to social events organized by the socia initivative as a variant two-stage discriminant framework to capture the users’ characteristics as well as their latent social connections.

Agroenergy, a relatively simple and mature technology to convert biomass into heat and electric energy, may represent a good opportunity to introduce the biorefinery schemes in rural areas. However, to guarantee the feasibility of new investments in this innovative sector, the commitment of all relevant players, and the sharing of their embedded knowledge of local conditions will play a crucial role. In this paper, we propose a modified neural network model to analyse the knowledge extracted from different groups of actors, in order to prevent the definition of strategic plans which may not be not fully consistent. We propose a methodology to support the strategic planning of the agroenergy innovation deployment in rural areas, based on the logical framework of the SWOT analysis, through which the most relevant factors affecting the expectations of local informed actors are identified. Subsequently, a modified multilayered feed-forward neural network is proposed to analyse the qualitative data, in order to verify their consistency. The results obtained from a case study in the province of Foggia (Italy) show that the level of consistency between the perceived factors affecting the deployment of the technology and the expectations towards the successful adoption of agroenergy at local level may vary depending on the degree of involvement and commitment of local players. This may represent a relevant issue for the definition of long-term strategic planning.

The Local Action Groups (LAGs) are supposed to contribute to the local development process through the enhancement of the territorial social capital. Stressing their aggregative role, the objective of this work is twofold: to find empirical evidence that LAGs’ operation can foster the social capital of the local partnerships, and to contribute to the methodological advancement in detecting social capital. The relational computational system here presented detects the contribution of LAGs on logical basis by comparing the relations actually existing and the relations created independently of the LAGs’ operation. The analysis reveals that the LAGs modified the morphology of their networks fostering the connectivity of their members and exalting the role of some actors as bridges among different polarities., Italian Review of Agricultural Economics, Vol 70 No 1 (2015)

In recent decades, one of the problems affecting the environment has been the increased use of plastics in agriculture, often illegally performed by open burning in the fields. The adoption of biodegradable products may represent an important opportunity to increase the environmental sustainability of agricultural sector. The goal of this study is to estimate the farmers’ willingness to pay for innovative biodegradable mulching films. A sample of 120 horticultural farms in the Province of Foggia (Apulia Region, Italy) has been surveyed by a questionnaire. The survey results demonstrate a substantial interest by farmers towards products made with innovative materials.

An emerging requirement for the evaluation of the rural development policy is the adoption of an objective method accounting for both material and immaterial achievements, and measuring the performance in order to understand the degree of accomplishment of policy objectives. In this paper we propose a Data Envelopment Analysis (DEA) approach capable of dealing with economic and social indicators, to measure the (relative) technical efficiency of a set of Local Action Groups (LAGs) operating within the LEADER programme. An evaluation exercise referred to eight LAGs located in Italy, is provided to demonstrate the effects of the inclusion of social capital indicator in the evaluation of the LAGs’ performances. In particular, the DEA allows to measure the relative efficiency of the LAGs and to identify the causes of the inefficiency. The outcomes of the analysis may represent a valuable information support for periodical policy review and for the enhancement of best practices.