Decisions about modeling and simulation (M&S) of real-world systems need to be evaluated prior to implementation. Discrete Event, System Dynamics, and Agent Based are three different modeling and simulation approaches widely applied to enhance decision-making of M&S of these systems. Combining and/or integrating these methods can provide solutions to a plethora of systems’ problems. However, current solutions and frameworks do not provide guidance for selecting and deploying M&S models. Hence, the aim of this work is to present a generic modeling framework for combining and/or integrating Discrete Event, System Dynamics, and Agent Based simulation approaches. The framework is termed multi-paradigm modeling framework (MPMF). In this paper, we describe the research methodology that was followed for the development of MPMF, the different phases of MPMF, and the generic relationships of forming and deploying multi-paradigm simulation models. Then we evaluate the framework by using it for the implementation of a universal task analysis simulation model (UTASiMo). The MPMF provided guidance on what methods need to be incorporated into the UTASiMo models, what information is exchanged among those models, and how these models are connected and interact with each other.

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This paper empirically examines the relationship between Foreign Direct Investment (FDI) and economic growth conducting a panel data analysis for a period of 20 years (1989~2008) in three different country groups: European Union member-countries, European Monetary Union member-countries, and countries in transition. These three country groups differ in many dimensions, one of which is their degree of economic integration. In contrast to the theoretical work that tends to suggest that FDI inflows have a positive effect on economic growth, we do not find a robust causality relationship between FDI and economic growth.

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