2018
DOI: 10.1007/978-3-319-75774-2_22
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Biogas and Biomethane Technologies: An AHP Model to Support the Policy Maker in Incentive Design in Italy

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Cited by 9 publications
(4 citation statements)
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“…Indeed, this value is evermore increasing when the positive externalities of renewable production are the driving force of the energy transition, and both energy providers and end-users are requested to take bold steps to align with the EU climate targets and put forward the transformation of the global economy from fossil-based to zero-carbon. Previous to the COVID-19 outbreak and the beginning of the war in Ukraine, it was widely acknowledged that to make prolonging the operation of existing biogas plants profitable, the introduction of a new incentive policy would have been necessary [94]. Our findings indeed confirm this sentiment.…”
Section: Resultssupporting
confidence: 77%
“…Indeed, this value is evermore increasing when the positive externalities of renewable production are the driving force of the energy transition, and both energy providers and end-users are requested to take bold steps to align with the EU climate targets and put forward the transformation of the global economy from fossil-based to zero-carbon. Previous to the COVID-19 outbreak and the beginning of the war in Ukraine, it was widely acknowledged that to make prolonging the operation of existing biogas plants profitable, the introduction of a new incentive policy would have been necessary [94]. Our findings indeed confirm this sentiment.…”
Section: Resultssupporting
confidence: 77%
“…As aforementioned, we organized a focus group to validate the hierarchy and the weights by dynamic discussion [61][62][63]. During the brainstorming, experts processed data and contributed to discussion according to their expertise, and a moderator helped discussion among experts and favored the process of reaching consensus on the final set of weights.…”
Section: Resultsmentioning
confidence: 99%
“…The AHP is based on the assumption that the decision-maker is always able to express a preference and judge the relative importance of (or preference for) the evaluation parameters [30][31][32]. In other words, it orders a finite number of actions Ai [12,33,34], by evaluating them with respect to a finite number k of attributes aj (j = 1, .…”
Section: Method: the Analytic Hierarchy Processmentioning
confidence: 99%