[7] selected earthquake magnitude, soil type, shear wave velocity, and effective vertical stress using the support vector machine (SVM) method to assess LP. [PERSON] et al. [8] chose effective vertical stress, standard penetration test blow counts, earthquake magnitude, and peak ground acceleration using a genetic algorithm technique to predict LP. [PERSON] and [PERSON] [9] selected five significant factors: standard penetration test blow counts, mean grain size, groundwater table, and earthquake magnitude, using the fuzzy comprehensive evaluation method to evaluate LP. Most of the assessment methods include few factors affecting soil liquefaction, regardless of important factors or selection of indirect parameters, which may deviate from the actual situation of soil liquefaction assessment results. Limited research has been conducted in the past to identify important parameters for soil liquefaction. [PERSON] et al. [10] used the Analytic Hierarchy Process (AHP) and entropy methods to identify important parameters among 16 factors of soil liquefaction. [PERSON] [11] used rough set theory and AHP to find the subjective and objective weights of soil liquefaction factors by comparing the comprehensive weighting factors, and it was concluded that seismic parameters are more important than other factors. [PERSON] [12] analyzed fifteen influencing factors of soil liquefaction by mathematical statistics. [PERSON] et al. [13] identified twelve significant soil liquefaction factors by a bibliometric method and analyzed their structural relationship through an interpretive structural modeling (ISM) approach and these factors are earthquake magnitude, epicentral distance, duration of earthquake, fines content, particle size, grain composition, relative density, drainage condition, degree of consolidation, thickness of sand layer, depth of sand layer, and groundwater table. The soil liquefaction susceptibility mechanism has been understood well, however, estimating accurate and reliable liquefaction-induced hazards requires identification and benchmarking of the most important factors controlling liquefaction. Most of these studies considered the quantification rather than the qualitative information of soil liquefaction factors from scientific publications, without considering the underlying relationships among the important influencing parameters or the indirect parameters, resulting in deviations from the actual situation. Therefore, to accurately and reliably determine soil liquefaction susceptibility, it is necessary to identify and benchmark the important factors from the literature using a systematic literature review (SLR) approach, as described in [PERSON], 2010 and [PERSON] et al., 2003 [14; 15], and to clarify the relationships among them. ISM plays an essential role in such conditions and is a well-known methodology for understanding interactions between definite factors that describe a problem. The ISM method was developed by [PERSON], between 1971 and 1974 [16] and is based on the principle of pair-wise comparison. Over the years, ISM has received some development in its applications and techniques [17]. The MICMAC method was developed by [PERSON] and [PERSON] [18]. Matrice d'impacts croises multiplication appliquee a un classment (MICMAC) a cross-impact matrix multiplication applied to classification is a structural prospective analysis used to study indirect relationships [19]. In an indirect relationship, one can observe three variables and their direct effects: variable X affects Y, variable Y affects Z, X and Z have no direct effect, but their relationship with Y is a cross-correlation, where any change in X will affect Z. This analysis is also known as gray area exploration [20]. This analysis complements the ISM approach by exploring constraints that usually refer to the ISM method: it explores the relationship \"yes\" or \"no\" and ignores the so-called gray area between 0 and 1 [17]. MICMAC analysis involves the development of a graph that classifies factors based on driving power and dependence power.