PurposeTravel interests of tourists during pandemics and outbreaks are reduced due to the prevalence of fear. It induces lifestyle changes, which may hinder efforts to recover the tourism value chain during post-COVID-19 lockdowns. Subscribing to domestic travel and domestic tourism is deemed to mitigate fear and gradually reopen the tourism industry. Although a crucial initiative, evaluating the perceived degree of exposure of tourists to COVID-19 in tourist sites operating under domestic tourism has not been fully explored in the emerging literature, which forms the main departure of this work.Design/methodology/approachThe problem domain is addressed by adopting multiple criteria sorting method – the VIKORSORT. To demonstrate such application, with 221 survey participants, 35 tourist sites in a province in the central Philippines struggling to revive the tourism industry are evaluated under six attributes that characterize tourists' exposure to COVID-19. To assess its efficacy, the performance of the VIKORSORT is compared to other distance-based multiple criteria sorting methods (i.e. TOPSIS-Sort and CODAS-SORT).FindingsResults show that proximity and volume of tourist arrivals are considered on top of the priority list of attributes. The use of VIKORSORT yields the assignment of 27 sites to the “moderate exposure” class, and eight under the “high exposure” class, with no tourist site assigned to the “low exposure” class. Sorting the tourist sites reveals some observations that tourists prefer sites (1) with open spaces, (2) with activities having limited group dynamics, (3) that are nature-based, and (4) with tourist arrivals that are not relatively high, with enough land area to practice social distancing. In addition, the assignments of the VIKORSORT with TOPSIS-Sort and CODAS-SORT are consistent at least 90% of the time, demonstrating its efficacy in addressing multiple criteria sorting problems.Originality/valueThis work provides an integrative approach in evaluating tourist sites in view of tourism recovery during pandemics. The findings offer crucial insights for the primary stakeholders (i.e. government, tourist operators, and tourists) in planning, resource allocation decisions, and policy formulation. Policy insights are offered, as well as avenues for future works.
Robust Ordinal Regression for Dominance-based Rough Set Approach to multiple criteria sorting
