An analytic network process‐based approach for location problems: the case of a new waste incinerator plant in the Province of Torino (Italy)

Starting from the topicality of the issues related to the location of undesirable facilities and on the basis of a brief review of the types of models that are currently being used in the Municipal Solid Waste Management context, the present paper proposes a multicriteria approach that is able to support decision makers in the choice of the best location for a waste incinerator plant in the Province of Torino (Italy). Three alternative sites have been compared through the use of the Analytic Network Process (ANP) method. The application allows the dependence relationships among the aspects and criteria to be assessed and the relative importance of all the elements that play an influence on the final choice to be elicitated. The decision-making process was developed through the identification of 31 environmental and socio-economic indicators that were grouped into clusters and organized in four subnetworks according to the Benefits, Opportunities, Costs and Risks (BOCR) model in order to compare the three alternatives by means of a holistic approach and to better highlight the tradeoffs between the aspects involved in the decision. The aim of this work is to analyse the contribution that the ANP technique offers in sustainability assessment of undesirable facilities, paying particular attention to the use of quantitative indicators in the evaluation process. The strengths and weaknesses of the ANP approach, combined with the use of measurable and verifiable indicators, are also discussed and three different sensitivity analyses have been performed in order to test the robustness of the proposed model and the stability of the results, exploring also rank reversal thresholds. The main findings of the present work have proved that the use of quantitative indicators as nodes of the ANP–BOCR structure significantly improves the internal coherence of the model and makes the decision process more traceable and reliable.