Table 1. SSCM risk factors This paper aims to identify and rank the risk factors that obstruct the operations of a sustainable supply chain in th Egyptian petrochemical sector. Figure 1 shows the approaches used to fulfill the research aim. Thirty-eight risk factors were identified by the literature, classified into three groups, the first group is risks affecting economic sustainability (14 factors), the second group is risks affecting social sustainability (12 factors) and the third is risks affecting environmental sustainability (12 factors). A survey was sent to experts in order to determine the risks relevant to the petrochemical sector, the most significant risks were determined by using the Content Validity Ratio method (CVR) (Vazifehdan and Darestani 2019). The CVR method represents as proportional level of experts' agreement in rating an item as essential (Hadzaman et al. 2018). Experts were asked to respond to each of the criteria and sub-criteria in the questionnaire as “necessary”, “useful but not necessary” and “not necessary”. Responses were calculated as follows: 3. Methods Table 1.(continued) SSCM risk factors Table 2. Saaty’s scale of relative importance The third step is organizing the pairwise comparison in a square matrix (i, j) that represents the different criteria reached in the first step. If the criterion on row i is more important than the criterion on column j, the element value is greater than one. The element value is | in case the criteria are equally important, and less than | if the criterion in column j is more important than the criterion in the row i (Bhushan and Rai 2004). Next, an AHP analysis was conducted in order to determine the most important risk factors in the petrochemical industry. AHP was developed in the ’70s by Thomas L. Saaty as a technique for decision-making. The AHP is one of the principal techniques of multi criteria decision making (MCDM) (Alshehri et al. 2022). It starts with decomposing a problem into a hierarchy of criteria to be easily analyzed and then conducting pairwise comparisons between criteria (Vargas 2010). The AHP procedure starts first by representing the problem in a hierarchal manner .The second step is the pairwise comparison which is done based on a nine-point scale as shown in table 2. Industry experts were invited to participate in assessing the importance of sustainability risk factors through responding to an AHP survey. Six experts participated in the survey representing the Egyptian petrochemical sector, there is a general consensus on the AHP method does not require a large sample size (Goral 2020) and according to Schmidt et al. (2015), sample sizes differing between four and nine have been used. Table 3. Random index values If the consistency ratio calculated for the comparison matrices is less than or equal to 0,1; the eigenvector “w” can be used as the weighted vector after the normalization. Otherwise, the comparison matrix needs to be revised (Deng et al. 2014; Uludag and Yazar 2019). In this research, CVR was calculated for each risk factor, according to Lawshe (1975) and the total number of participants, the min CVR value was 0.99 for this research. The accepted risk factors were included in the AHP survey distributed to experts in order to determine the importance of each factor. The final hierarchy of the problem reached based on the CVR values is illustrated in figure 2. A sample of the data entry sheet illustrating the inputs of ranking from each individual is shown in figure 3. Based on the weights, the most dominant risk factors were explosions, fires and chemical accidents under the environmental factors category. Explosions, fires and chemical accidents can be managed through effective emergency response which can lead to the reduction of life and property losses, prevention is a critical element whict can be achieved through safety management of equipment and safety training for employees (Zhu et al. 2020). Table 4. Local weights of sustainability risk factors and sub factors
