Toward a Theory of Multi-Method Modeling and Simulation Approach

The representation via simulation models can easily lead to simulation models too simple for their intended purpose, or with too much detail, making them hard to understand. This problem is related to limitations of the modeling and simulation methods. A multi-method Modeling and Simulation (M&S) approach has the potential for improved representation by taking advantage of methods\u27 strengths and mitigating their weaknesses. Despite a high appeal for using multiple M&S methods, several related problems should be addressed first. The current level of theoretical, methodological, and pragmatic knowledge related to a multi-method M&S approach is limited. It is problematic that there is no clearly identified purpose and definition of the multi-method M&S approach. Theoretical and methodological advances are vital to enhancing the application of a multi-method M&S approach to address a broader range of scientific inquiries, improve quality of research, and enable finding common ground between scientific domains. This dissertation explored theoretical principles and research guidelines of a multi-method M&S approach. The analyzed literature offered perspectives related to the purpose, terms, and research guidelines of a multi-method M&S approach. A pragmatic philosophical stance was used to provide the basis for the choice of terms and definitions relevant to a multi-method M&S approach were proposed. The degrees of falsifiability are adapted to the M&S domain, which allowed for developing complementarity principles as the theoretical basis of a multi-method M&S approach. Next, a blueprint of a multi-method M&S approach called method formats was derived, because transitions toward formats must seek justifications in order to increase research objectivity and transparency. A sample set of methods was explored in the context of a proposed sample set of criteria. None of the methods were evaluated with the maximum score for every criterion, which implied that if all those characteristics were required within a research context, then, none of the methods could provide the highest possible score without combining methods. Finally, a case study that included a multi-method simulation model was developed, providing a data layer for evaluation of complementarity principles. The case study contributed to the credibility of complementarity principles as a reason to use a multi-method M&S approach and value of pseudo-triangulation as a mean of verification of a selected approach

Exploring the Use of Computer Simulations in Unraveling Research and Development Governance Problems

Understanding Research and Development (R&D) enterprise relationships and processes at a governance level is not a simple task, but valuable decision-making insight and evaluation capabilities can be gained from their exploration through computer simulations. This paper discusses current Modeling and Simulation (M&S) methods, addressing their applicability to R&D enterprise governance. Specifically, the authors analyze advantages and disadvantages of the four methodologies used most often by M&S practitioners: System Dynamics (SO), Discrete Event Simulation (DES), Agent Based Modeling (ABM), and formal Analytic Methods (AM) for modeling systems at the governance level. Moreover, the paper describes nesting models using a multi-method approach. Guidance is provided to those seeking to employ modeling techniques in an R&D enterprise for the purposes of understanding enterprise governance. Further, an example is modeled and explored for potential insight. The paper concludes with recommendations regarding opportunities for concentration of future work in modeling and simulating R&D governance relationships and processes