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Open Access
Article
Publication date: 31 August 2022

Aleksandra Terzić, Biljana Petrevska and Dunja Demirović Bajrami

This study aims to offer insights into a sounder understanding of tourist behavior and travel patterns by systematically identifying psychological manifestations reflected in the…

2151

Abstract

Purpose

This study aims to offer insights into a sounder understanding of tourist behavior and travel patterns by systematically identifying psychological manifestations reflected in the basic human value system in the pandemic-induced environment.

Design/methodology/approach

A large random sample (49,519 respondents from 29 European countries), generated from the core module Round 9 of the European Social Survey, was used. A post-COVID-19 psychological travel behavior model was constructed by using 12 variables within two opposing value structures (openness to change versus conservatism), shaping specific personalities.

Findings

Four types of tourists were identified by using K-means cluster analysis (risk-sensitive, risk-indifferent, risk-tolerant and risk-resistant). The risk-sensibility varied across the groups and was influenced by socio-demographic characteristics, economic status and even differed geographically among nations and traveling cultures.

Research limitations/implications

First, data were collected before the pandemic and did not include information on tourism participation. Second, the model was fully driven by internal factors – motivation. Investigation of additional variables, especially those related to socialization aspects, and some external factors of influence on travel behaviors during and after the crisis, will provide more precise scientific reasoning.

Originality/value

The model was upgraded to some current constructs of salient short-term post-COVID-19 travel behavior embedded in the core principles of universal human values. By separating specific segments of tourists who appreciate personal safety and conformity, from those sharing the extensive need for self-direction and adventure, the suggested model presents a strong background for predicting flows in the post-COVID-19 era.

Details

Journal of Tourism Futures, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2055-5911

Keywords

Open Access
Article
Publication date: 8 July 2022

Carolina Aldao, Dani Blasco and Manel Poch Espallargas

This research aims at arriving at a broad scope of the lessons learnt after two years of the coronavirus disease 2019 (COVID-19) pandemic outbreak by analysing the catalyst and…

6141

Abstract

Purpose

This research aims at arriving at a broad scope of the lessons learnt after two years of the coronavirus disease 2019 (COVID-19) pandemic outbreak by analysing the catalyst and inhibiting factors within three aspects of the tourism sector: destination crisis management, tourist behaviour and tourism industry trends.

Design/methodology/approach

The methodology of this paper involves semi-structured interviews with high-ranking European travel agents as the agents represent the intermediates between the tourism offer and demand.

Findings

Data obtained from travel agents disclosed the factors that catalysed and inhibited the destination, the behaviour of tourists and the tourism industry trends. By contrasting data with previous literature, constructing an overview of the positive and negative outcomes of the pandemic in the tourism sector is possible.

Practical implications

Governments, destination marketing and management organisations and tourism and hospitality organisations could learn from the lessons of COVID-19 outbreak to cope better with future disruptive events affecting the tourism industry.

Originality/value

The paper is novel as it is the first overview that attempts to synthesise the lessons from the COVID-19 pandemic in the tourism sector by analysing tourism sector's three dimensions: the destination, the tourists and the industry.

Details

Journal of Tourism Futures, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2055-5911

Keywords

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