# Blockchain Integrated IoT for Food Supply Chain: A Grey Based Delphi-DEMATEL Approach
## 4 Data Analysis and Results  
To finalise the CSFs of B-IoT adoption in FSC, a combination of a literature review and a grey Delphi approach is employed. Initially, a systematic literature review is done for the initial identification of CSFs for B-IoT in FSC. With the initial search of keywords in Scopus, the articles are identified for literature review. These keywords comprise \"food supply chain\", \"agri-food supply chain\", \"agri-supply chain\", \"blockchain\", \"internet of things\", \"IoT\", \"factors\", \"critical factors\" and \"critical success factors\". The search string is developed by combining these keywords through Boolean operators. After that, these strings are searched in the Scopus database that identifies the relevant articles. Furthermore, these articles are reviewed, and 14 CSFs of B-IoT are initially identified and shown in Table 3.  
After the initial identification of CSFs of B-IoT adoption in FSC, the grey Delphi method is applied with the help of experts. To achieve a balanced view, experts from academia and industry are selected [61]. A group of industrial professionals from the FSC and technology development sectors has been identified to collect data, and each has at least eight years of experience in FSC management. These academic experts work in the areas of FSC and technology management or technology transfer in reputed academic institutes. Their selection was based on their expertise and knowledge in the field of FSC. A structured questionnaire was created to apply the grey Delphi approach, in order to get the data. The experts were given copies of this questionnaire and requested to respond. The experts have evaluated these CSFs and provided their responses. In this manner, 10 valid responses are collected and shown in Table 4. \begin{table}
\begin{tabular}{c c c} \hline
**S. No** & **CSFs of B-IoT Adoption** & **Code** & **References** \\ \hline
1. & Top management support & IF1 & [2,75] \\
2. & Online platform cost & IF2 & [21,55] \\
3. & Theory associated with blockchain & IF3 & [76,77] \\
4. & Technology hardware readiness & IF4 & [18,78] \\
5. & Scalability & IF5 & [21,49] \\
6. & IoT and blockchain awareness & IF6 & [79] \\
7. & SC Responsiveness & IF7 & [75,78] \\
8. & Skilled personnel & IF8 & [18,80] \\
9. & Trust management & IF9 & [81] \\
10. & Knowledge management & IF10 & [81,82] \\
11. & Supply chain integration & IF11 & [2] \\
12. & High investment & IF12 & [18,83] \\
13. & Cyber attacks & IF13 & [84] \\
14. & Security \& privacy issues & IF14 & [13,85] \\ \hline \end{tabular}
\end{table} 
Table 3: Initial CSFs of B-IoT adoption in FSC. Following the expert group's responses, we transformed the linguistic value into grey numbers using Table 1. Table 5 shows the resulting grey value that is used for further process as grey Delphi steps. Further, Equation (7) is also used to calculate the overall grey weight. Whitening the grey weight (i.e., crisp number) is done using Equation (8). These crisp numbers are used to accept or reject the CSFs for analysis. Based on some studies such as [86; 87], 3.5 is the threshold value (\(\lambda\)) for crisp numbers. In other words, if the crisp value exceeds 3.5, then the CSF is considered relevant; otherwise, it is excluded. Table 6 shows the overall grey and crisp weights along with the decision. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Critical Factors** & **Overall Grey Weigh** & **Crisp Weigh** & **Decision** & **Rename** \\ \hline IF1 & [3.5,4.5] & 4 & Accept & F01 \\ IF2 & [1.8.2.8] & 2.3 & Reject & NA \\ IF3 & [1.1.2.1] & 1.6 & Reject & NA \\ IF4 & [3.4.4.4] & 3.9 & Accept & F02 \\ IF5 & [2.4,3.4] & 2.9 & Reject & NA \\ IF6 & [3.5,4.5] & 4 & Accept & F03 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Results of the grey Delphi method.