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176                   9. Life cycle decision support framework: Method and case study

                   To deal with the problem, multicriteria decision making (MCDM) methods were adopted
                 in the decision making process after LCSA results for several technologies, processes, or ser-
                 vices were provided, because MCDM methods can help to prioritize alternatives or to select
                 the best option based on data of multiple criteria provided (Yu et al., 2018; Ioppolo et al., 2019).
                 In addition, the hierarchical structure of LCSA results (with multiple indicators under three
                 pillars) fits the MCDM processing structure perfectly. Thus, the combination of LCSA and
                 MCDM compensates for the drawbacks of both LCSA and MCDM: improves the data quality
                 and provides a direct decision making result based on all-round sustainability assessment.
                 Many studies have applied MCDM combined with LCSA data and these methods have been
                 used in the construction industry (San-Jos  e Lombera and Cuadrado Rojo, 2010; Shahriar et al.,
                 2014), transportation (Bojkovi  c et al., 2010; Awasthi et al., 2011), energy generation (Zhang
                 et al., 2015; Zhao and Li, 2016), supply chain (Entezaminia et al., 2016; Luthra et al.,
                 2017a), and manufacturing (He et al., 2019).
                   In this chapter, the procedures and recent studies of LCSA are summarized in Section 9.2.
                 The MCDM methods used in competitive case studies based on LCSA results are also
                 reviewed and summarized in Section 9.2. A group Z-number best worst method (group
                 ZBWM) combined with the goal programming method is developed and introduced in
                 Section 9.3. The proposed method is adapted to analyze a case study regarding waste oil man-
                 agement technologies selection in Section 9.4, and the results and discussions are illustrated
                 afterward. The conclusions are summarized in Section 9.5.



                                              9.2 Literature reviews

                   The combination of LCSA and MCDM mutually compensates for the drawbacks of each
                 other. After the LCSA, decision makers find it hard to make the decisions because of inexistence
                 of the most superior alternative, which performs the best in every aspect. MCDM is a useful tool
                 to rank, or select multiple alternatives based on data of multiple criteria (Ishizaka and Siraj,
                 2018). Therefore, MCDM can help to determine the best alternative based on LCSA results,
                 while LCSA provides a scientific and reliable database for decision making, as shown in Fig. 9.1.
                   The MCDM method include four main steps: criteria system determination, decision mak-
                 ing matrix determination, criteria weighting, and aggregation (Ho et al., 2010).


                 9.2.1 Criteria system determination
                   The first step is to select criteria from LCSA indicators that can better describe the options.
                 Criteria in environmental, economic, and social perspectives are selected from LCA, LCC,
                 and LCSA, respectively, to analyze the target. The selection of criteria depends on the situa-
                 tion of industry and the knowledge from experts.


                 9.2.2 Decision making matrix determination
                   Prior to the weighting method, a decision-making matrix should be built summarizing all
                 information of alternatives with regard to criteria adapted from the criteria system. As for all
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