Human-computer cloud for decision support in tourism: Approach and architecture

• Main Authors: Alexander Smirnov, Andrew Ponomarev, Tatiana Levashova, Nikolay Teslya
• Format: Article
• Language: English
• Published: FRUCT 2016-11-01
• Series: Proceedings of the XXth Conference of Open Innovations Association FRUCT
• Subjects: tourism; smart tourism; human factors; human computations; crowdsourcing; decision support
• Online Access: https://fruct.org/publications/fruct19/files/Smi.pdf
• ISSN: 2305-7254; 2343-0737

Tourism is one of the most dynamic and fastest-growing economic sectors, where on-the-fly information and decision support are more actual than ever. Tourist decision support systems today leverage a variety of technologies both machine-driven (GIS or knowledge-based inference) and human-driven (recommendation systems). This paper applies a novel concept of human-computer cloud as an architectural approach to building decision support systems in tourism (both from the tourist's perspective, and from destination management organization's perspective). This concept serves as a unifying basis for using human-based resources, allowing to virtualize them much like “ordinary” computing resources. Particularly, the paper identifies the list of typical decision support tasks in tourism domain, and then maps them to a multi-tiered conceptual architecture of cloud services. The proposed architecture is illustrated by the discussion of two scenarios - one for tourist perspective and one for destination management organization.