  Travel Recommender Systems TRSs have been proposed to ease the burden of
choice in the travel domain by providing valuable suggestions based on user
preferences Despite the broad similarities in functionalities and data provided
by TRSs these systems are significantly influenced by the diverse and
heterogeneous contexts in which they operate This plays a crucial role in
determining the accuracy and appropriateness of the travel recommendations they
deliver For instance in contexts like smart cities and natural parks diverse
runtime informationsuch as traffic conditions and trail status
respectivelyshould be utilized to ensure the delivery of pertinent
recommendations aligned with user preferences within the specific context
However there is a trend to build TRSs from scratch for different contexts
rather than supporting developers with configuration approaches that promote
reuse minimize errors and accelerate timetomarket To illustrate this gap in
this paper we conduct a systematic mapping study to examine the extent to which
existing TRSs are configurable for different contexts The conducted analysis
reveals the lack of configuration support assisting TRSs providers in
developing TRSs closely tied to their operational context Our findings shed
light on uncovered challenges in the domain thus fostering future research
focused on providing new methodologies enabling providers to handle TRSs
configurations
