# Towards a Comprehensive Metaverse Forensic Framework Based on Technology Task Fit Model
## 3 Results and Analysis
### Structural Model  
After ensuring the measurement model's requirements are met, the study investigates the inner relationships between independent and dependent variables. Standardized path coefficients, standard error, t-values, and \(p\)-values are among the critical metrics used to evaluate the relevance, direction, and strength of these associations. The study's direct correlations between variables may be understood and measured with the use of the structural model, shown in Figure 6. \begin{table}
\begin{tabular}{l l l l} \hline \hline
**Code** & **Cronbach’s Alpha** & **Composite Reliability (CR)** & **Average Variance Extracted (AVE)** \\ \hline COM & **0.55** & 0.760 & 0.516 \\ PEE & 0.774 & 0.847 & 0.591 \\ ROB & 0.736 & 0.851 & 0.657 \\ TAC & 0.704 & 0.815 & 0.533 \\ TEC & 0.788 & 0.875 & 0.701 \\ USA & 0.748 & 0.852 & 0.657 \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Reliability Analysis. Figure 6: Structural model. Hypothesis Testing  
This section presents the results of the hypothesis testing. These hypotheses (null) are further recapitulated thus:  
* H0: There is no statistically significant relationship between metaverse task characteristics and the perceived expectation of forensic examiners. * H1: There is no statistically significant relationship between metaverse technology characteristics and the perceived expectation of forensic examiners in identifying, extracting, and preserving potential digital evidence. The relationship between COM and PEE was not statistically significant (beta = \(-\)0.127, \(t\) = 0.451, \(p\) > 0.05), as shown in Table 8, which shows that the degree of comprehensiveness of the proposed framework is not capable of explaining the actual potential to use the proposed framework. Similarly, robustness (ROB) and performance expectation (PEE) did not exhibit a statistically significant relationship (beta = 0.363, \(t\) = 1.289, \(p\) > 0.05). Additionally, there was no evidence to support the relationship between task features and comprehensiveness (beta = 0.217, \(t\) = 0.664, \(p\) > 0.05). However, the results indicate that there is a positive and statistically significant relationship between task characteristics and robustness (beta = 0.719, \(t\) = 2.860, \(p\) < 0.05) as well as usability (beta = 0.566, \(t\) = 2.551, \(p\) < 0.05), respectively. Conversely, the \(p\)-value for each of the remaining direct relationships demonstrated a positive correlation, albeit statistically insignificant, with a \(p\)-value greater than 0.05. Attributively, this relatively poor significance can be linked to the limited number of responses. However, regarding the indirect effect, TAC and TEC to PEE, the result revealed a positive output, as shown in Table 9. Suffix to highlight that the defined null hypothesis of this study is hinged on this indirect relationship. Whilst the TAC showed a standardized beta coefficient of 0.498, the TEC had a much lower coefficient of 0.046 (negative relative relationship). Furthermore, the responses revealed that TAC has a statistically significant relationship with PEE (Beta coefficient = 0.498, \(p\) < 0.05) in contrast to TEC (Beta coefficient = \(-\)0.046, \(p\) > 0.05). In essence, the null hypothesis on the first hypothesis (H0) is rejected in favor of the alternate hypothesis. Conversely, the second null hypothesis (H1) is accepted. Therefore, the indirect relationship between task characteristics and performance expectancy shows that the respondents alluded that the proposed metaverse forensic framework can be used to conduct a digital forensic investigation in the metaverse platform. This further implies that the proposed framework addresses key factors and characteristics associated with the typical metaverse forensics processes.