**2.1 Interpretive structural modeling: a qualitative technique**

ISM methodology, as interpretive in judgment, can be used as a systematic means of recognizing the contextual relationships between the elements associated with an issue to be examined [9]. The ISM approach has been effectively utilized in diversified set of problems, for instance, risk management in supply chains [10] and energy conversation [11]. ISM can be illustrated in the following steps for the present study, as suggested by Sushil [8]:

Step 1: Identification of factors related to the problem or issue through literature review etc.

Step 2: Using domain information, fix contextual relationships between defined factors (e.g. V–row factor influences the column factor; A–column factor influences the row factor; O–no relationship between the row and column factors; or X–both direction relations from row to column and column to row factors).

Step 3: Construct a structural self-interaction matrix (SSIM) based on pair-wise comparison between factors of system which denotes direct relationship between two factors.

Step 4: SSIM is converted to initial reachability matrix, by replacing 1 or 0 for the original symbols–V, A, X and O as per the rules for transformation (see **Table 1**).

Step 5: The transitivity of initial reachability matrix is checked in order to develop the final reachability matrix. The transitive relationships mean that if variable "*x*" is associated with variable "*y*" and variable "*y*" is associated with variable "*z*", then variable "*x*" is certainly associated to variable "*z*".


*Elucidation of Seismic Soil Liquefaction Significant Factors DOI: http://dx.doi.org/10.5772/intechopen.97278*

#### **Table 1.**

identify important parameters of soil liquefaction. Dalvi et al. [1] used the Analytic Hierarchy Process and entropy methods to identify important parameters among 16 factors of soil liquefaction. Zhu [2] analyzed fifteen influencing factors of soil liquefaction by mathematical statistics method. Tang et al. [3] and Ahmad et al. [4] identified significant soil liquefaction factors by employing bibliometric and systematic literature review techniques based on standard penetration test respectively through interpretive structural modeling (ISM) approach. Most of these studies considered the quantification rather than the qualitative information of soil lique-

Seismic parameter, soil parameter and site conditions contain variety of factors that trigger liquefaction and discussed in detail in Section 3. As literature review search is the first step in the ISM technique to identify the important factors and their underlying relationships. Therefore, a systematic literature review (SLR) approach is used for this purpose which is described by Okoli and Schabram [5] and Tranfield et al. [6] is used. Warfield developed the ISM method between 1971 and 1974 [7], and it is based on the pair-wise comparison theory. ISM has seen some progress in terms of applications and techniques over the years [8]. Michel Godet and François Bourse introduced the Matrice d'impacts croisés multiplication appliqués à un classement (MICMAC) method. The creation of a graph that classifies factors based on driving power and dependency power is called

In this chapter, ISM and MICMAC methodologies are used to establish and analyze the structural hierarchical relationship and to examine the strength of the relationship between seismic soil liquefaction significant factors based on their

ISM methodology, as interpretive in judgment, can be used as a systematic means of recognizing the contextual relationships between the elements associated with an issue to be examined [9]. The ISM approach has been effectively utilized in diversified set of problems, for instance, risk management in supply chains [10] and energy conversation [11]. ISM can be illustrated in the following steps for the

Step 1: Identification of factors related to the problem or issue through literature

Step 2: Using domain information, fix contextual relationships between defined factors (e.g. V–row factor influences the column factor; A–column factor influences the row factor; O–no relationship between the row and column factors; or X–both

Step 3: Construct a structural self-interaction matrix (SSIM) based on pair-wise comparison between factors of system which denotes direct relationship between

Step 4: SSIM is converted to initial reachability matrix, by replacing 1 or 0 for

the original symbols–V, A, X and O as per the rules for transformation (see

Step 5: The transitivity of initial reachability matrix is checked in order to develop the final reachability matrix. The transitive relationships mean that if variable "*x*" is associated with variable "*y*" and variable "*y*" is associated with

**2.1 Interpretive structural modeling: a qualitative technique**

direction relations from row to column and column to row factors).

variable "*z*", then variable "*x*" is certainly associated to variable "*z*".

faction factors from scientific publications.

*Earthquakes - From Tectonics to Buildings*

driving power and dependence power.

present study, as suggested by Sushil [8]:

MICMAC.

**2. Methodology**

review etc.

two factors.

**Table 1**).

**164**

*Rules for transformation.*

Step 6: The reachability and antecedent sets of factors are developed from the final reachability matrix. The reachability set for a particular factor includes the factor itself and other factors which it may help to achieve, and antecedent set includes factor itself and other factors that can help in achieving it. Subsequently, the intersection of these sets is found for the entire factors. The factor for which reachability and intersection sets are identical is listed in the first level. This factor is then separated from other factors for the next iteration process. Repeat the same level of iteration process until all levels of each factor are established.

Step 7: Remove the transitivity links and draw a directed graph (digraph) from the final reachability matrix.

Step 8: Convert the digraph into an ISM-based hierarchical model by replacing the nodes with statements.

Step 9: The conceptual discrepancy of model is verified and improved for necessary modifications and corrections.
