# Data Conversion Strategies for Effective Aviation Technical Support as a Service
## 4 Discussion
### Future Research Directions  
Future research on ATSaaS should aim to address the limitations identified in this study and explore new dimensions to enhance its feasibility, scalability, and impact. One key direction is conducting empirical validations through pilot implementations in diverse operational contexts. This would involve collaborating with small airlines, maintenance providers, and regulatory bodies to gather real-world data and refine the theoretical models presented. Such practical applications would help uncover challenges related to stakeholder coordination, system integration, and the adoption of standardized data protocols. Existing studies on aviation technical support platforms (e.g., predictive maintenance systems such as Airbus Skywise and Boeing AHM) focus on large-scale operators, with limited consideration of scalable, cost-efficient service models for small airlines. Future research should involve pilot implementations of ATSaaS, allowing for data collection, performance assessment, and refinement of service models in diverse operational environments.  
Another critical area for exploration is the incorporation of advanced technologies such as artificial intelligence, blockchain, and the Internet of Things. These technologies could significantly enhance data processing, predictive maintenance, and cybersecurity in both centralized and decentralized ATSaaS architectures. Research should evaluate how these innovations can improve operational efficiency and reliability while maintaining cost-effectiveness.  
Future studies should also investigate hybrid architectural models that combine the strengths of centralized and decentralized approaches. For example, a hybrid model could centralize data validation while allowing decentralized data conversion at the stakeholder level, balancing flexibility and consistency. Additionally, sensitivity analyses could be expanded to account for variations in regulatory requirements, technological maturity, and economic conditions across different regions and airlines.  
Future studies should also investigate contractual and economic models for ATSaaS adoption. The cost-sharing mechanisms, service-level agreements, and regulatory compliance frameworks for ATSaaS have yet to be fully explored. Previous research on Software-as-a-Service (SaaS) models in aviation has demonstrated the benefits of subscription-based services but has not evaluated customized pricing models based on airline size, operational complexity, and real-time service demands. A more in-depth economic analysis would help determine the most viable business models for widespread industry adoption.  
The human and organizational factors influencing ATSaaS adoption warrant deeper examination as well. Research could explore the training needs, resistance to change, and collaborative dynamics among stakeholders within the ATSaaS ecosystem. Understanding these factors will be crucial for designing systems that are not only technically robust but also user-centric and widely adoptable.  
By addressing these areas, future research can further advance the ATSaaS framework, making it a transformative solution for small airlines and the broader aviation industry.