## 5 Conclusions and Future Work
### Future Work  
Combining expert perspectives has its advantages and disadvantages. Specifically, when multiple experts weigh in on a topic, the law of large numbers can lead to a more validated solution. However, conflicting views may negate each other and ultimately have no impact on the system. In order to address the latter, our method tackles the issue of conflicting expert opinions by modeling uncertainty and ambiguity through degrees of truth, falsity, and indeterminacy. This allows diverse opinions to coexist without canceling each other out. Furthermore, to enhance our method in this direction, a possible solution could be to assign weights to expert contributions based on their credibility, ensuring more reliable insights influence the final outcome. By visualizing these interactions, our method could provide a clearer, more robust decision-making process for assessing smart port performance. The presented framework needs further testing. One possible future endeavor could be to integrate our method with the sustainable balanced scorecard (SBSC) [84; 85; 86], a popular management tool. The SBSC employs performance metrics from financial, customer, business processes, technology, and socio-environmental perspectives, introducing a new performance measurement framework for smart ports. In such a hybrid method, the perspectives described in the SBSC model would act as the concepts in the NCMs. This would allow us to examine the relationship between the concepts and address the inherent vagueness and indeterminacy in decision-making due to human judgment. Scholars in [87] have already taken a step in this direction by proposing a hybrid method that integrates the neutrosophic AHP method with the SBSC model to assess smart port performance, albeit only theoretically. Several extensions of FCMs have been proposed by researchers in the last decade [88]. A potential future study could involve constructing a hybrid method based on grey system theory and NCMs. A similar work is described in [89], but it is applied to FCMs. We propose this extension to the aforementioned application because we believe that the theories of neutrosophic sets (NS) and grey systems are more consistent models of uncertainty. Thesemodels can provide significant advantages for decision-making compared to fuzzy sets, which are considered less reliable in demonstrating indeterminate relationships between concepts. Another extension that could be applied in NCMs is to incorporate the concept of time lag that may occur between the relationships of nodes. Causal strength over time units has not been previously studied in the field of NCMs. A preliminary attempt in the field of FCMs is discussed in [90], followed by related works in [91; 92; 93; 94] proposing advancements in \"traditional\" FCMs considering time. The concept of time could simulate the impact, in time units, of one presynaptic node on the postsynaptic node. From this perspective, we could analyze a system's behavior based on time by examining the change of causalities among factors over a discrete period t. A different approach is described in [36] where scholars utilize neutrosophic temporal logic in NCMs using Kripke structures to represent the nodes of the NCM. The accessibility relations in Kripke structures are modified to represent the degrees of indeterminacy or uncertainty between conceivable worlds, allowing for a comprehensive analysis of information flow and truth values across different worlds. Lastly, we mention prescriptive modeling, a category of business analytics that aims to prescribe operations within a system to achieve a specific goal [95]. It is an area that has garnered academic interest in recent years as it provides crucial support to decision-makers [96]. NCMs have previously been used to generate descriptive and predictive models.