Bozana Zekan, Irem Önder, Ulrich Gunter
Airbnb is arguably the world’s most popular accommodation sharing platform. Its impact ondemand and supply within the tourism and hospitality industry is nowadays unquestionable.The present study delves into inspecting the efficiency of Airbnb listings of European cities, as,in spite of the success of Airbnb as a whole, it cannot be presupposed that all listings areequally successful. More specifically, data envelopment analysis (DEA) is employed in this firstcomprehensive benchmarking attempt within the domain of the sharing economy to date. Thisarticle also makes a contribution to robustness by introducing an interactivity note to thebase model, thus, inspecting the results for corroboration/discrepancies and going beyond thestatic analyses that are common in DEA modeling. Ultimately, this is done with the goal ofhighlighting opportunities for inefficient Airbnb listings to properly utilize their inputs andtherefore become more competitive
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