Application of a comprehensive methodology for the evaluation of social innovations in rural communities

open4noThis project has received funding from the European Union’s Horizon 2020 Research and Innovation Program under Grant Agreement No. 677622 (H2020 SIMRA–Social Innovation in Marginalised Rural Areas–Project).Despite the growing interest in social innovation (SI) in agriculture, the literature lacks validated tools for evaluating such initiatives. This paper provides an empirical application of the evaluation approach developed within the H2020 SIMRA project to a pilot experience conducted in a rural area of Southern Italy. The value added by this case study is the application of the five types of criteria used by the OECD for the evaluation of development programs, which are commonly referred to as REEIS: relevance, effectiveness, efficiency, impact, and sustainability. This experiment demonstrates the adequacy of the evaluation framework in identifying strengths and weaknesses of the initiative, according to a multifaceted perspective. The overall evaluation proves that most indicators fall under the high (48%) and medium categories (36%), and only few indicators are low (16%). The usefulness of the evaluation results is manifold. First, this evaluation highlights relevant arguments to support the communication strategy addressed at civil society, therefore reinforcing the civic engagement of the initiative, which is the distinctive feature of SI. Second, it supports project managers in addressing interventions to face emerging weaknesses. Finally, the evaluation provides factual evidence to policy makers to perform cost-effective analysis of rural development policies.openBaselice A.; Prosperi M.; Marini Govigli V.; Lopolito A.Baselice A.; Prosperi M.; Marini Govigli V.; Lopolito A

The networking dynamics of the Italian biofuel industry in time of crisis: Finding an effective instrument mix for fostering a sustainable energy transition

This paper aims to design the effective instrument mixes for fostering a sustainable energy transition in times of crises. We focus on a sufficiently developed green niche – namely the Italian biofuel sector – implementing a two-step investigation: 1) a social network analysis, to study the effects of the crisis on the basic niche development mechanisms, with the aim of eliciting its development needs; 2) a fuzzy inference simulation based on a causal-effect map drawn from experts' knowledge to identify the most effective instrument mix for the development of the niche studied. The major needs emerged in the case investigated are for an increase of actors' expectations towards the further development of the sector, and a need for a tailored networking activity, devoted to attracting specific knowledgeable actors. The results indicate that, among others, effective policy instruments are, in this case, the cooperation that has the best outcome in terms of networking, and the public procurement, which remarkably increases the level of expectation. The analysis presented constitutes a model to evaluate single policy drivers and their combinations to find adequate policy actions to promote the green energy transition in times of crisis

A Combined method to model policy interventions for local communities based on people knowledge

Policy interventions to promote innovative industries in peripheral regions are often hampered by lack of information on the functioning of the local socio-economic systems, due to their complexity. This might result in mismatches between policy objectives and the actual needs and capability of local communities. To overcome this drawback, it is crucial to obtain appropriate knowledge on the local system, which nevertheless is typically embedded in local actors’ minds in uncodified and tacit form. Fuzzy Cognitive Maps (FCMs) have been employed to decode this kind of knowledge in a reproducible manner. However, some problems remain as to how to integrate the necessary vagueness of local actors’ heuristic with experts’ knowledge into a rational framework. The following methodology customization is proposed: • Combine the FCMs with the Discourse Analysis to obtain relevant narratives (i.e. concepts, visions, insights, etc.) needed to define system boundaries and variables. • Employ individual interviews – rather than a participatory approach – to define the causal relations among system variables. • Integrate tacit and uncodified knowledge embedded in local actors within experts’ scientific knowledge

Life Cycle Management of Infrastructures

By definition, life cycle management (LCM) is a framework “of concepts, techniques, and procedures to address environmental, economic, technological, and social aspects of products and organizations in order to achieve continuous ‘sustainable’ improvement from a life cycle perspective” (Hunkeler et al.\ua02001). Thus, LCM theoretically integrates all sustainability dimensions, and strives to provide a holistic perspective. It also assists in the efficient and effective use of constrained natural and financial resources to reduce negative impacts on society (Sonnemann and Leeuw\ua02006; Adibi et al.\ua02015). The LCM of infrastructures is the adaptation of product life cycle management (PLM) as techniques to the design, construction, and management of infrastructures. Infrastructure life cycle management requires accurate and extensive information that might be generated through different kinds of intelligent and connected information workflows, such as building information modeling (BIM)

Designing Policy Mixes to Address the World’s Worst Devastation of a Rural Landscape Caused by Xylella Epidemic

The socio-economic consequences of the Xylella fastidiosa epidemic represent a global problem that can only be addressed through tailored, local solutions. The selection of public interventions is not a trivial task for policy makers, as they must weigh many different interests (e.g., private profit, ecosystem services, usability, preservation and growth of real estate value, amenities, and land protection). The present paper addresses this challenge by building participatory scenarios based on “fuzzy cognitive maps,” with the aim of identifying effective, acceptable, and efficient policy mixes to address the Xylella epidemic. The work investigates the case of southern Salento (Italy)–an olive production area at the epicentre of the global Xylella outbreak–to identify the most suitable actions for regenerating the landscape. To this end, the most efficient policy mixes are determined according to three possible policy perspectives, which provide different weights for effectiveness and acceptability. The results show that the proposed methodological approach may assist policy makers in coping with multifaceted policy challenges