Vulnerability and resilience of the tourism sector in India: Effects of natural disasters and internal conflict

Barbhuiya, Mahfuzuar Rahman; Chatterjee, Devlina

doi:10.1016/j.tmp.2019.100616

Cited by 48 publications

(32 citation statements)

References 61 publications

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“…The results show that, on average, the tourism performance has been significantly devastating for the 16 analyzed cities since the first COVID-19 breakout. Thus, these results are aligned with previous literature demonstrating that the tourism industry is negatively impacted by unexpected events (Barbhuiya and Chatterjee, 2020;Bassil et al, 2019;McAleer et al, 2010;Neumayer and Plümper, 2016;Page et al, 2012;Rossell o et al, 2020;Seabra et al, 2020). Likewise, this paper is also connected to those previous attempts of documenting the relationship between the impacts of the COVID-19 on the tourism industry (Anguera-Torrell et al, 2020;Gössling et al, 2020;Hoque et al, 2020;Karim et al, 2020;Maneenop and Kotcharin, 2020;Sharma and Nicolau, 2020;Sobieralski, 2020).…”

Section: Discussionsupporting

confidence: 90%

“…The tourism industry is considered to be one of the most negatively impacted economic sectors when facing unexpected non-macroeconomic events such as terrorism, natural disasters or health crises. The occurrence of these unexpected events tends to be followed by a decrease on international tourists' arrivals (Barbhuiya and Chatterjee, 2020;Bassil et al, 2019;McAleer et al, 2010;Neumayer and Plü mper, 2016;Page et al, 2012;Rossell o et al, 2020;Seabra et al, 2020) and, consequently, with a negative economic impact for tourism firms. For instance, Chen et al (2005) demonstrate that non-macroeconomic forces, such as the 921 earthquake, the 9/11 terrorist attack or the SARS outbreak, significantly affect hotels' stock returns.…”

Section: Impacts Of Unexpected Events On Tourismmentioning

confidence: 99%

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Urban tourism performance index over the COVID-19 pandemic

Anguera-Torrell

Vives-Perez

Aznar-Alarcón

2021

IJTC

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Purpose This study aims to propose and estimate the urban tourism performance index (UTPI), an index that can measure and track the month-by-month tourism performance on main tourism cities since the initial outbreak of the COVID-19 pandemic. The UTPI is estimated for the following urban destinations: Bangkok, Paris, London, Dubai, Singapore, Kuala Lumpur, New York, Istanbul, Tokyo, Seoul, Osaka, Phuket, Milan, Barcelona, Bali and Hong Kong. Design/methodology/approach Monthly based data measuring the tourism industry’s performance for these urban destinations has been collected. This data includes airlines’ and hotels’ performance, as well as potential tourists’ online searches. The obtained data has been combined using a principal component analysis, generating the UTPI. Findings The UTPI shows that all urban areas analyzed in this study experienced a devastating negative impact because of the COVID-19 pandemic outbreak. However, the tourism recovery evolution follows heterogeneous patterns. Research limitations/implications The proposed index can be estimated using additional variables. Moreover, the index is only estimated for 16 tourism cities. Future studies can reproduce the methodology by incorporating further variables and amplifying the geographical coverage. Practical implications The UTPI might be useful for researchers and policymakers interested in using a measure of tourism performance during the COVID-19 pandemic in some of the most important urban destinations. Likewise, the UTPI index may serve as a suitable aggregated measure of tourism performance in a post-COVID-19 era or to monitor tourism during future crises. Originality/value This study analyzes the tourism performance during the COVID-19 pandemic from an urban perspective.

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Section: Discussionsupporting

confidence: 90%

Section: Impacts Of Unexpected Events On Tourismmentioning

confidence: 99%

Urban tourism performance index over the COVID-19 pandemic

Anguera-Torrell

Vives-Perez

Aznar-Alarcón

2021

IJTC

View full text Add to dashboard Cite

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“…Owing to this, IATA showed concern that the tourist numbers may not reach the level of 2019 until 2023-24 (IATA, 2020). Nevertheless, due to resilient characteristic of the tourism and hospitality industry (Biggs et al, 2012), it is believed that as cities start to unlock, the industry will rebound with better strategies to make travel safer (Barbhuiya & Chatterjee, 2020;.…”

Section: Covid-19 and Its Impact: An Overviewmentioning

confidence: 99%

Impacts of COVID-19 on tourism education: analysis and perspectives

Tiwari

Séraphin

Chowdhary

2020

Journal of Teaching in Travel & Tourism

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“…Several studies have identified tourism as a driver of the economic growth of any country (Badulescu et al, 2020;Mishra et al, 2011;Swangjang & Kornpiphat, 2021;Tang & Tan, 2015). Innumerable travelers visit different parts of the world to enjoy their leisure time or conduct business activities (Barbhuiya & Chatterjee, 2020;Bonham et al, 2006;Korstanje, 2011;Lepp & Gibson, 2003;Pforr, 2009). Despite the growth of the tourism industry worldwide, destination managers are increasingly getting concerned about the factors that create tourist hesitation toward traveling (Drimili et al, 2020;Pal et al, 2021;Pulido-Fernández et al, 2019;Wong & Yeh, 2009).…”

Section: Introductionmentioning

confidence: 99%

How does tourist perception lead to tourist hesitation? Empirical evidence from Bangladesh

Polas

Saha

Tabash

2021

Environ Dev Sustain

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The paper aims to identify the factors that cause prospective tourists’ hesitation to travel. The study also examines whether this relationship is mediated by the tourist perception in Bangladesh. The study is of quantitative design, and the relationships between tourist knowledge, tourist health risk, and destination personality with tourist hesitation were explored using a sample of 322 Bangladeshi prospective tourists. The three relationships were also examined through tourist perception. By using cross-sectional data, the researchers hypothesized that tourist knowledge, tourist health risk, and destination personality have a positive and significant effect on tourist hesitation. Besides, the researchers also hypothesized that tourist perception mediates the relationships between tourist knowledge, tourist health risk, and destination personality with tourist hesitation. In this respect, the Smart PLS 3.0 was employed to analyze the data. The results of the study confirm findings of previous related studies by not only highlighting the importance of tourist perception in shaping tourist hesitation but also indicating the way each dimension of tourism either enhances or inhibits the tourist hesitation. The results of the study also reveal a positive and significant relationship between tourist knowledge and tourist health risk with tourist hesitation. The analysis of data showed no conventional relationship between destination personality and tourist hesitation. Accordingly, this study identified the extent to which tourist perception mediates the relationship between tourist knowledge and destination personality with tourist hesitation. Meanwhile, the results of the study indicate the absence of any mediation role of tourist perception between tourist health risk and tourist hesitation. The study outcomes would encourage the government, policymakers, and tourism managements in creating a tailor-made responsiveness program by building a scenario that could offer more prominent sustainable tourism establishments. Besides, the results may assist stakeholders of tourist destinations in understanding tourist perception and the causes of tourist’s hesitation.

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Vulnerability and resilience of the tourism sector in India: Effects of natural disasters and internal conflict

Cited by 48 publications

References 61 publications

Urban tourism performance index over the COVID-19 pandemic

Urban tourism performance index over the COVID-19 pandemic

Impacts of COVID-19 on tourism education: analysis and perspectives

How does tourist perception lead to tourist hesitation? Empirical evidence from Bangladesh

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