There is a growing trend in the number of M&S studies that report on the use of Hybrid Simulation. However, the meaning and the usage of the term varies considerably. Indeed, the hybrid simulation panel during last year's conference (WSC2016) laid bare the strong views, from the panelists and audience alike, as to what constitutes a hybrid model and what is new? The ensuing debate set the scene for this year's paper, in which we discuss the various perspectives on hybrid simulation by focusing on three aspects: its definition, its purpose and its benefits. We hope this paper will pave the way for further studies on this subject, with the objective of achieving a convergence of the definition of hybrid simulation. 1 INTRODUCTION The Hybrid Simulation track at the WSC has continued to grow over the last four years. This is representative of the growing interest in this topic, and indeed, reflects the volume of publications accessible through scholarly outlets. However, the meaning and the usage of this term varies considerably, as the hybrid methodology is not precisely defined (Balaban, Hester, and Diallo 2014). Most of the studies refer to a pair-wise (e.g., Heath et al. 2011) or full combination (e.g., Djanatliev and German 2013) of the three most commonly applied simulation techniques, namely the Discrete-Event Simulation (DES), System Dynamics (SD), and Agent-Based Simulation (ABS). Furthermore, new terms have been introduced which, arguably, have the same meaning, e.g., multi-method simulation, multiparadigm modeling, cross-paradigm simulation, mixed-modeling and combined simulation. From the literature, we find numerous examples of "hybrid" models for specific use-cases. However, what makes those models "hybrid"? Is this only the application of two or more simulation paradigms? Why is hybridization necessary or useful in a certain case? What are the major steps to develop a hybrid model?
