Int. J. Information Technology and Management, Vol. 16, No. 1, 2017 53 Copyright © 2017 Inderscience Enterprises Ltd. A situation awareness analysis scheme to identify deficiencies of complex man-machine interactions Ellemieke van Doorn*, Zoltán Rusák and Imre Horváth Faculty of Industrial Design Engineering, Delft University of Technology, 2628 CE Delft, the Netherlands Email: E.C.vanDoorn-1@tudelft.nl Email: Z.Rusak@tudelft.nl Email: I.Horvath@tudelft.nl *Corresponding author Abstract: This paper presents an analysis scheme which aims to support a systematic study of required situation awareness (RSA). This scheme supports identification of deficiencies of support for situation awareness (SA). Information needs are goal and task dependent and can be defined using existing cognitive task analysis (CTA) methods. RSA, however, is a subset of information needs and depends on the interaction between goals, tasks, system factors and individual factors. The analysis scheme has helped to identify that the current methods to define RSA do not support a distinction between information needs and RSA. The scheme was trialled in a nautical traffic management context as an extension to existing CTA methods. The research activities necessary to study RSA and to identify deficiencies of current support for SA in nautical traffic management context were applied. The study showed that the research set-up designed through application of the analysis scheme helped to define RSA, and that RSA is considerably context and operator dependent. Future research will focus on the potential for context-aware adaptable interface solutions to allow for RSA dependent information visualisation. Keywords: man-machine interactions; MMI; required situation awareness; information needs; situation awareness requirements; analysis scheme; deficiencies; nautical traffic management; information intensive task environment; informing. Reference to this paper should be made as follows: van Doorn, E., Rusák, Z. and Horváth, I. (2017) ‘A situation awareness analysis scheme to identify deficiencies of complex man-machine interactions’, Int. J. Information Technology and Management, Vol. 16, No. 1, pp.53–72. Biographical notes: Ellemieke van Doorn is currently a PhD candidate in the Cyber-Physical Systems Research Group at the Department of Design Engineering, Delft University of Technology, in the Netherlands. Concurrently, she works at Rijkswaterstaat, the Executive Body of the Dutch Ministry of Infrastructure and the Environment, where she is the Man-Machine Interactions Specialist of the Vessel Traffic Management of the Future Innovation Project. Her PhD research focuses on improving support for situation awareness in information intensive man-machine interactions context.