## 3 Methodology
### Total Interpretative Structural Modeling (TISM)
#### 3.1.2 Step 2: Initial Reachability Matrix (Representation of Enablers in Matrix Form)  
The second step aims to achieve a correlation matrix among the enablers for pair-wise comparison (initial reachability matrix). An online survey (questionnaire) was conducted, and ratings were taken from experts to find the interrelationships among enablers. The experts considered in this study were from three areas: academics, digital marketing experts, and perishable food-management experts. Experts utilized a Likert scale ranging from 1 to 5 to quantify the interdependencies of enablers with each other, as shown in Table 4.  
As per the experts' opinion, if there is an interrelationship among the enablers, the answer is Yes (Y), and an additional interpretation is required. Otherwise, the answer is considered No (N). The response rate was around 68 percent, which is sufficient for this type of survey [42]. The obtained responses from experts are represented in a matrix form, considering that Y is \"1\" and N is \"0\". Table 5 provides the responses collected from various experts.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Category** & **Rating** \\ \hline Very strong & 5 \\ \hline Strong & 4 \\ \hline Medium & 3 \\ \hline Weak & 2 \\ \hline Very weak & 1 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Quantification of the interdependencies of enablers (Likert 5-point scale).  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Enabler Number** & **1** & **2** & **3** & **4** & **5** & **6** & **7** & **8** & **9** & **10** & **11** & **12** & **13** & **14** & **15** \\ \hline
2 & 1 & 1 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\ \hline
3 & 1 & 0 & 1 & 0 & 0 & 0 & 1 & 1 & 0 & 1 & 0 & 0 \\ \hline
4 & 0 & 1 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 1 & 1 & 0 & 1 \\ \hline
5 & 0 & 1 & 1 & 1 & 1 & 1 & 1 & 0 & 0 & 0 & 1 & 0 & 1 \\ \hline
6 & 0 & 0 & 0 & 1 & 1 & 1 & 0 & 0 & 0 & 0 & 1 & 1 & 0 & 0 \\ \hline
7 & 0 & 0 & 0 & 0 & 1 & 1 & 1 & 1 & 0 & 0 & 0 & 0 & 0 & 0 \\ \hline
8 & 0 & 0 & 1 & 0 & 1 & 1 & 1 & 0 & 0 & 0 & 0 & 0 & 0 \\ \hline
9 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 \\ \hline
10 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 1 & 0 & 1 & 1 \\ \hline
11 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 1 & 0 & 1 \\ \hline
12 & 0 & 0 & 0 & 1 & 1 & 1 & 0 & 0 & 0 & 0 & 1 & 0 & 1 \\ \hline
13 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 1 & 0 \\ \hline
14 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 1 & 1 \\ \hline
15 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 1 & 0 & 1 & 1 & 1 \\ \hline \hline \end{tabular}
\end{table}
Table 5: Initial reachability matrix (IRM).  
1.3 Step 3: Final Reachability Matrix and Driving (D\({}_{\rm R}\)) and Dependence (D\({}_{\rm C}\)) Values  
After obtaining the initial reachability matrix from the experts' opinion, the transitivity rule of the matrix was checked (if E4-E7, E7-E10, then E4-E10). Each transitive connection was updated with 1* in the respective cell of the matrix. Table 6 shows the updated matrix with all the transitivity connections. The D\({}_{\rm R}\) and D\({}_{\rm C}\) values were calculated from the final reachability matrix by adding row and column values, respectively. The D\({}_{\rm R}\) and D\({}_{\rm C}\) values are shown in the last row and last column of Table 6.