Abstract
The rising incidence and consequences of natural disasters, global economic crises, climate change, and socio-political upheavals have raised interest in resilience, particularly in small island economies. Their small size and high tourism-dependency make these small island states more vulnerable to such disruptions. Hence, understanding resilience or adaptive capacity to withstand shocks is fundamental to their sustainable development. The emerging literature uses the Adaptive Cycle Model to qualitatively analyse resilience through the evolution of tourism destinations. Nevertheless, the absence of quantitative studies using the Adaptive Cycle Model makes it a daunting task to adequately advise policymakers about the scope and scale of intervention necessary to facilitate the rebuilding of a stronger tourism industry. We, therefore, pioneer the use of Markov Switching Autoregressive Model to test the model’s applicability using four decades of data on tourist arrivals in two Caribbean destinations, Barbados and Grenada. The results reveal untapped opportunities for transformation and regeneration in both countries’ tourism industries, but highlight sharp contrast in their resilience capability. Grenada exhibits greater resilience as its adverse shocks, though deeper, are relatively transitory, while Barbados despite experiencing fewer external shocks faces prolonged repercussions from global recessions. For small islands, we conclude that the factors impacting lower resilience are the industry’s management deficiencies, inadequate cohesion among stakeholders, and lack of innovation. Overall, the findings present a modelling framework for tourism-dependent economies to determine how quickly they recover from major stress events, the associated strategies necessary to strengthen tourism resilience, and the potential to innovate in the tourism industry.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.