# A Novel Method for Technology Roadmapping: Nanorobots
## 2 Materials and Methods
### Literature Review
#### 2.1.2 Current Technology Roadmapping Method  
A technology roadmap can be viewed as a structured framework based on the dimension of time, and can be used for managing innovation strategies through layered thematic representations [40]. It explores the evolutionary relationships among technology, markets, and products, effectively aligning technological advancements with business objectives [41]. The structure of \"layers\" and \"sub-layers\" is crucial because it reflects the fundamental direction in which an organization addresses business issues. It facilitates communication between different business departments and integrates key business processes [42]. This layered structure is instrumental in fostering communication across various business departments and in the integration of essential business processes, thereby enhancing strategic coherence and operational efficiency [41]. Currently, there are three main methods for developing technology roadmaps: qualitative analyses, bibliometric analyses, and intelligent analyses. A qualitative analysis is the most widely applied method for creating technology roadmaps. Many scholars support and validate technology roadmap frameworks through qualitative case studies. Some scholars develop roadmaps through workshops, incorporating qualitative knowledge from various experts and continuously iterating the roadmap development process [43; 44; 45]. A bibliometric analysis, on the other hand, involves quantitatively parsing textual data to identify thematic elements in a field. It uses data metrics to identify the direction of technological research, further supporting the development of technology roadmaps through methods like network analyses and text mining [46; 47; 48]. For instance, [PERSON] et al. presented a pioneering approach that combines bibliometrics with a patent analysis to understand the technological trends and future directions of nanogenerators. By drawing data from the Web of Science and the Derwent World Patents Index, this study visualized the existing technological trajectory and identified key factors influencing the growth of the nano-generator industry. The authors highlighted how bibliometric and patent analyses serve as effective tools for tracking the development of new technologies and predicting their future applications [47]. Similarly, [PERSON] et al. introduced a novel framework for unveiling the evolutionary path of nanogenerator technology, emphasizing the use of multi-source data. Their methodology involves integrating bibliometrics and a patent citation analysis using sources like the Web of Science and the Derwent Innovation. This allows for a comprehensive exploration of both scientific and technological advancements. Their study particularly underscores the importance of text vectorization and clustering techniques in extracting thematic trends from large datasets, thereby enhancing the depth of bibliometric analyses [49]. Further expanding the scope of data sources, [PERSON] et al. proposed an advanced framework based on multi-source data to monitor the technology evolution pathways of nanogenerators. Their study incorporated data from academic papers, patents, and grants, sourced from the Web of Science, the Derwent Innovation Index, and the China Knowledge Centre for Engineering Science and Technology. The combination of these data sources offered a more detailed view of the progression from initial research (grants and papers) to technological applications (patents). This multi-source approach is critical for identifying the knowledge flow between academic research and technological innovation [50]. The traditional technology roadmapping method has been critiqued for its limitations, particularly in its ability to address complex, multifaceted systems, where the interdependencies and interactions across different technological layers are crucial.