## 5 Conclusions
### Research Limitation and Future Plans  
In response to the reviewer's concerns, we have made a conscientious effort to identify and address the limitations within our study. We recognize that while our research provides a comprehensive exploration of integrating blockchain and smart contract technologies into 5G ceramic antenna manufacturing, it is not without its constraints. These reflections have been thoughtfully incorporated into the manuscript in Section 5.2, titled \"Research Limitation and Future Plans\", to provide a clear overview of the areas where our study may fall short and how we plan to address these in the context of future research directions. A primary limitation of our study is its focused research context, tailored specifically to a particular manufacturing environment. This specificity may limit the wider applicability of our findings across diverse manufacturing scenarios, each with its unique set of challenges. Consequently, the B-SER-M model, as it stands, may require adaptations to be effectively applied in different contexts. Another notable limitation is the subjective nature of the Analytic Hierarchy Process (AHP) analysis utilized in our study. Given that the AHP relies significantly on expert opinions, the potential variability in these opinions could introduce a level of inconsistency in our findings. This aspect is critical as it may affect the reliability and generalizability of our study's conclusions. To mitigate these concerns, future research endeavors could explore methods to quantify and reduce such subjectivity, possibly by incorporating a wider range of expert opinions or leveraging more objective data sources. Additionally, the rapidly evolving landscape of blockchain technology presents a dual-sided challenge: while it offers fresh opportunities, it also necessitates continuous research to keep our findings relevant and aligned with the latest technological advancements. Looking ahead, we identify several key areas for future investigation. Longitudinal studies will be pivotal in assessing the long-term impacts of blockchain integration within manufacturing processes, providing insights into its sustainability and the enduring benefits or challenges it presents. The need for empirical case studies examining the real-world implementation of the B-SER-M model is also pressing. Such studies will be instrumental in validating our theoretical propositions, offering practical insights, and examining the model's adaptability across various manufacturing environments. Moreover, future research could benefit from exploring how blockchain technology could be integrated with other emerging technologies, such as quantum computing and artificial intelligence, potentially leading to revolutionary advancements in manufacturing processes. Studies on the scalability of blockchain applications within larger and more complex manufacturing operations are equally critical. These investigations should aim to understand how blockchain technology can be scaled and integrated into expansive manufacturing systems without compromising efficiency or security. Furthermore, adopting a holistic perspective by incorporating views from a diverse array of stakeholders--including regulatory bodies, end consumers, and industry experts--will enrich our understanding of blockchain technology's impact on the manufacturing sector. This inclusive approach is vital for developing models that account for the needs and perspectives of all participants within the manufacturing ecosystem. Finally, the empirical validation and refinement of the B-SER-M model are essential. Real-world testing of the model to gather empirical data will be crucial for its refinement and enhancement, ensuring its applicability and effectiveness across various manufacturing contexts. By addressing these limitations and focusing our efforts on the outlined areas for future research, subsequent studies will continue to evolve decision-making models and significantly contribute to the advancement of 5G ceramic antenna production.