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An integrated TOPSIS-MOORA-based performance evaluation methodology for the key service providers in sharing economy: case of Airbnb superhosts

An integrated TOPSIS-MOORA-based performance evaluation methodology for the key service providers... In the context of sharing economy, the superhost program of Airbnb emerges as a phenomenal success story that has transformed the tourism industry and garnered humongous popularity. Proper performance evaluation and classification of the superhosts are crucial to incentivize superhosts to maintain higher service quality. The main objective of this paper is to design an integrated multicriteria decision-making (MCDM) method-based performance evaluation and classification framework for the superhosts of Airbnb and to study the variation in various contextual factors such as price, number of listings and cancelation policy across the superhosts.Design/methodology/approachThis work considers three weighting techniques, mean, entropy and CRITIC-based methods to determine the weights of factors. For each of the weighting techniques, an integrated TOPSIS-MOORA-based performance evaluation method and classification framework have been developed. The proposed methodology has been applied for the performance evaluation of the superhosts (7,308) of New York City using real data from Airbnb.FindingsFrom the perspective of performance evaluation, the importance of devising an integrated methodology instead of adopting a single approach has been highlighted using a nonparametric Wilcoxon signed-rank test. As per the context-specific findings, it has been observed that the price and the number of listings are the highest for the superhosts in the topmost category.Practical implicationsThe proposed methodology facilitates the design of a leaderboard to motivate service providers to perform better. Also, it can be applicable in other accommodation-sharing economy platforms and ride-sharing platforms.Originality/valueThis is the first work that proposes a performance evaluation and classification framework for the service providers of the sharing economy in the context of tourism industry. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Benchmarking: An International Journal Emerald Publishing

An integrated TOPSIS-MOORA-based performance evaluation methodology for the key service providers in sharing economy: case of Airbnb superhosts

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Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
1463-5771
DOI
10.1108/bij-03-2020-0085
Publisher site
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Abstract

In the context of sharing economy, the superhost program of Airbnb emerges as a phenomenal success story that has transformed the tourism industry and garnered humongous popularity. Proper performance evaluation and classification of the superhosts are crucial to incentivize superhosts to maintain higher service quality. The main objective of this paper is to design an integrated multicriteria decision-making (MCDM) method-based performance evaluation and classification framework for the superhosts of Airbnb and to study the variation in various contextual factors such as price, number of listings and cancelation policy across the superhosts.Design/methodology/approachThis work considers three weighting techniques, mean, entropy and CRITIC-based methods to determine the weights of factors. For each of the weighting techniques, an integrated TOPSIS-MOORA-based performance evaluation method and classification framework have been developed. The proposed methodology has been applied for the performance evaluation of the superhosts (7,308) of New York City using real data from Airbnb.FindingsFrom the perspective of performance evaluation, the importance of devising an integrated methodology instead of adopting a single approach has been highlighted using a nonparametric Wilcoxon signed-rank test. As per the context-specific findings, it has been observed that the price and the number of listings are the highest for the superhosts in the topmost category.Practical implicationsThe proposed methodology facilitates the design of a leaderboard to motivate service providers to perform better. Also, it can be applicable in other accommodation-sharing economy platforms and ride-sharing platforms.Originality/valueThis is the first work that proposes a performance evaluation and classification framework for the service providers of the sharing economy in the context of tourism industry.

Journal

Benchmarking: An International Journal – Emerald Publishing

Published: Feb 8, 2021

Keywords: Tourism management; Performance measurement; Sharing economy; CRITIC; TOPSIS; MOORA

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