Recommendation agents and information sharing through social media for coronavirus outbreak

Nilashi, Mehrbakhsh; Asadi, Shahla; Minaei-Bidgoli, Behrouz; Abumalloh, Rabab Ali; Samad, Sarminah; Ghabban, Fahad; Ahani, Ali

doi:10.1016/j.tele.2021.101597

Cited by 52 publications

(37 citation statements)

References 81 publications

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“…The authors used TripAdvisor’s textual reviews and numerical ratings to reveal the customers' satisfaction in spa hotels. Nilashi et al (2021) used machine learning techniques to analyze the TripAdvisor online customers’ reviews for decision-making during the COVID-19 outbreak. They used LDA for data analysis.…”

Section: Previous Literature Of Online Customers’ Reviews and Ratingsmentioning

confidence: 99%

What is the impact of service quality on customers’ satisfaction during COVID-19 outbreak? New findings from online reviews analysis

Nilashi

Abumalloh

Alghamdi

et al. 2021

Telematics and Informatics

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Section: Previous Literature Of Online Customers’ Reviews and Ratingsmentioning

confidence: 99%

What is the impact of service quality on customers’ satisfaction during COVID-19 outbreak? New findings from online reviews analysis

Nilashi

Abumalloh

Alghamdi

et al. 2021

Telematics and Informatics

Self Cite

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“…According to Nilashi et al. [26] , during the COVID-19 pandemic, tourists are using electronic word of mouth (eWOM) more and more for travel planning. However, recommendation agents supported by applications of machine learning or soft computing techniques may be more effective.…”

Section: Literature Reviewmentioning

confidence: 99%

A calibrated piecewise-linear FGM approach for travel destination recommendation during the COVID-19 pandemic

Chen

Wang

2021

Applied Soft Computing

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After months of lockdown due to the COVID-19 pandemic, more people are planning regional trips because overseas travel is still not feasible. However, choosing a suitable travel destination during the COVID-19 pandemic is challenging because the factors critical to the selection process are very different from those usually considered. Furthermore, without sufficient literature or data for reference, existing methods based on psychological analyses or mining past experiences may not be applicable. Consequently, a fuzzy multi-criteria decision-making method – the calibrated piecewise-linear fuzzy geometric mean (FGM) approach – is proposed in this study for travel destination recommendation during the COVID-19 pandemic. The contribution of this research is twofold. First, the critical factors that affect the selection of a suitable travel destination during the COVID-19 pandemic are discussed. Second, the accuracy and efficiency using existing fuzzy analytic hierarchy process (FAHP) methods have been enhanced. The calibrated piecewise-linear FGM approach has been successfully applied to recommend suitable travel destinations to fifteen travelers for regional trips in Taiwan during the COVID-19 pandemic.

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“…Other studies include articles that focus on the use of electronic media for information sharing during the pandemic ( Nilashi, 2021 ), the use of virtual reality ( Schiopu et al, 2021 ), low consumption due to safety concerns ( Li et al, 2021 ), use of robot-staffs in room service ( Kim et al, 2021 ), post-COVID increase in local tourism ( Jeon & Yang, 2021 ) and quarantine lodging experience ( Wong & Yang, 2020 1). All the studies are related to understanding the consumer perspective of the hospitality and tourism sector.…”

Section: Resultsmentioning

confidence: 99%

Present and prospective research themes for tourism and hospitality education post-COVID19: A bibliometric analysis

Menon

Gunasekar

Dixit

et al. 2022

Journal of Hospitality, Leisure, Sport & Tourism Education

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Recommendation agents and information sharing through social media for coronavirus outbreak

Cited by 52 publications

References 81 publications

What is the impact of service quality on customers’ satisfaction during COVID-19 outbreak? New findings from online reviews analysis

What is the impact of service quality on customers’ satisfaction during COVID-19 outbreak? New findings from online reviews analysis

A calibrated piecewise-linear FGM approach for travel destination recommendation during the COVID-19 pandemic

Present and prospective research themes for tourism and hospitality education post-COVID19: A bibliometric analysis

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