# Roadmap Modeling and Assessment Approach for Defense Technology System of Systems
## 2 Literature Review  
The traditional methodology of R&D management is now confronted with rocketing complexities stemming from the rapid emergence of novel innovations. The focal problem consists of two main components. The first originates from the diversity of basic scientific fields relating to applied technologies and the pluralism of technology interrelations, which are considered complexities of the nature of technology and the scale of system of systems, respectively. The second concerns the interactions among the significant stakeholders in the lifecycle procedure of R&D [8]. Drawing lessons from commercial enterprise management, the Department of Defense (DoD) developed a requisition management framework of weapon systems based on the multi-view theory [9]. Through collecting and integrating data, information, and expertise from different stakeholders, this framework can be used to calibrated comprehensive and accurate requirement models of defense requisition. Following this research methodology, other scholars discussed \"division and integration\" approaches for system of systems modeling. Moreover, these methods have been applied and validated in the requirement analyses of military capability [10], weapon systems [11], and defense technology [12]. Patent text is one of the focal data sources in R&D study due to its availability and semi-structured storage format. With text-mining tools, semantic and citation analysis [13; 14; 15; 16; 17; 18] can be used to measure technology relations through calculating the similarities among abstracted keyword vectors. Differing from the methods processing polysemous keyword vectors, citation analysis focuses on the accumulation and diffusion of innovation knowledge. In addition, it has the advantage of eliminating the ambiguities from authors' word choices and writing styles to measure the technology relations more objectively [19]. The centrality indices [16] were applied to identify core patents based on citation networks with the analytic network process (ANP) method [15]. Moreover, the division of technology areas in dynamic citation networks and the detection of those focal ones with higher development potential has been discussed through the integration of network analysis, time series models, and cluster analysis [17; 18]. Technology roadmaps have been widely applied in different domains of R&D planning, providing flexible information exchange platforms for the stakeholders including researchers, engineers, product managers, suppliers, and consumers [5]. This methodology can be used to identify vital information, including current and future customers' requirements and technology development opportunities, as well as to support decision-making in programing, executing, and inspecting the R&D schedules [5; 20]. Roadmap models involve various elements, such as technologies, products, services, and business/markets [6]. According to the related survey [5], the roadmaps drawing methods can be classified into expertise-based, computer/algorithm-based, and a hybrid category. Furthermore, different approaches of data analysis have been infused into and consummated this modeling framework. [PERSON] et al. [21] investigated a value-driven technology roadmap process focusing on customers' requirements, through integrating multiple related approaches, and demonstrated this methodology using the case study of software service business application. [PERSON] et al. [7] proposed an integrative approach combining technology roadmap and system dynamic simulation to improve the effectiveness of scenario planning. Aiming to cope with the rocketing data volume in drawing technology roadmaps, approaches of association rule mining (ARM) were used to abstract the relations among different elements [8]. In addition, the implementing process of a technology roadmap was demonstrated using applications in the energy service sector [22]. This empirical research was extended through discussing the differences of objectives in national, industry/sector, and organizational levels [20].