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The phenomenon of overtourism, characterized by its multifaceted impacts on destinations, has emerged as a major concern in the tourism industry. This dissertation aims to explore the dynamics of overtourism, emphasizing the dual impacts of main-source tourism markets on destinations in terms of their economic, social, and environmental consequences. Unlike existing literature, which focuses primarily on the negative aspects of overtourism, the present study illustrates the nuanced interaction between tourism markets by highlighting both their potential benefits and disadvantages. This study offers an in-depth analysis of cost and benefit factors based on a priori and a posteriori segmentation methodologies, combined with time-series analysis and limited information maximum likelihood (LIML) methods. Based on three case studies—Hong Kong, Malta, and Barbados—from 1980 to 2021, this study demonstrates the heterogeneous nature of the impacts across destinations and the complexities of market aggregation and interaction. The study identifies gaps in the conventional narrative of overtourism and introduces an interdisciplinary approach to the investigation. Based on the symbiotic framework, coupled with the Portfolio Theory, market aggregations and interactions can be classified into mutualism, commensalism, and parasitism. Additionally, the ‘limits of acceptable change' (LAC) and the ‘level of analysis problem' (LAP) frameworks have been utilized to further examine dominant and non-dominant markets' aggregation effects and interaction dynamics, resulting in a more comprehensive understanding of overtourism's complexity. Key findings suggest tailoring strategies to address overtourism, emphasizing the balance between minimizing costs and optimizing benefits. Based on the findings of this study, policymakers and stakeholders must develop strategies that respond to the challenges associated with overtourism by integrating empirical measures with theoretical frameworks.

Made available in DSpace on 2016-12-12T20:22:53Z (GMT). No. of bitstreams: 1 LEANDERSON ANDRE.pdf: 2236080 bytes, checksum: a52e91a8b1a8e6a12497786254e94344 (MD5) Previous issue date: 2015-08-27 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Nature offers a wide range of phenomena that inspire the development of new technologies. The researchers from the area of Natural Computing abstracts the concept of optimization from various biological processes such as the evolution of species, the behavior of social groups, the search for food, among others. Such computer systems that have a similarity to natural biological systems are called biologically plausible. The development of biologically plausible algorithms gets interesting by the fact that biological systems are able to handle extremely complex problems. In this way, symbiotic relationships are one of several phenomena that can be observed in nature. These relationships consist of interactions that organisms carry out with each other resulting in benefit or disadvantage to those involved. In an optimization context, symbiotic relationships can be used to perform exchange of information between populations of candidate solutions to a given problem. Thus, this work highlights the concepts involving symbiotic relationships that may be important for the development of computer systems to solve complex problems. The main discussion presented in this study refers to the use of symbiotic relationships between populations of candidate solutions co-evolving in an ecological context. According to the analogy, populations interact with each other according to a specific symbiotic relationship in order to evolve their solutions. The proposed model is applied to several continuous benchmark functions with a high number of dimensions (D = 200) and in several benchmark instances of the multiple knapsack problem. The results obtained so far were promising concerning the application of symbiotic relationships. Finally, the conclusions are presented and some future directions for research are suggested. / A Natureza apresenta uma grande variedade de fenômenos que inspiram o desenvolvimento de novas tecnologias. Os pesquisadores da área de Computação Natural abstraem o conceito de otimização de vários processos biológicos, tais como a evolução das espécies, comportamento de grupos sociais, busca por comida, dentre outros. Tais sistemas computacionais que apresentam uma semelhança com os sistemas biológicos naturais são chamados de biologicamente plausíveis. O desenvolvimento de algoritmos biologicamente plausíveis se torna interessante pelo fato de que os sistemas biológicos são capazes de lidar com problemas extremamente complexos. As relações simbióticas são um dos vários fenômenos que podem ser observados na natureza. Essas relações consistem de interações que organismos realizam entre si resultando em benefícios ou prejuízos para os envolvidos. Em um contexto de otimização, as relações simbióticas podem ser utilizadas para realizar a troca de informação entre populações de soluções candidatas para um dado problema. Desta forma, este trabalho destaca os conceitos que envolvem as relações simbióticas que podem ser importantes para o desenvolvimento de sistemas computacionais para a resolução de problemas complexos. A principal discussão apresentada nesse trabalho refere-se a utilização de relações simbióticas entre populações de soluções candidatas, coevoluindo em um contexto ecológico. Com essa analogia, cada população interage com uma outra de acordo com uma relação simbiótica específica, com o objetivo de evoluir suas soluções. O modelo apresentado é aplicado a várias funções benchmark contínuas com um número alto de dimensões (D = 200) e várias instâncias benchmark do problema da mochila múltipla. Os resultados obtidos se mostraram promissores considerando a aplicação das relações simbióticas. Por fim, as conclusões são apresentadas e algumas direções para pesquisas futuras são sugeridas.

Different challenges arising from increasingly uncertain and unpredictable environmental and economicconditions have been shifting the focus of public governance and socio-economic development. Morerecently, empirical studies have demonstrated a transitional epoch in which humanity is currently in: TheAnthropocene, as well as its harmful effects that degrade the biosphere, and thus our economic, political,social well-being. The casual dynamics of climate change and its impacts on life-supporting ecosystemshas increasingly been recognized by a resilient approach which incorporates adaptive processes andschemes, allowing public governance to embrace the changes rather than control uncertainty. Thisresearch introduces the interwoven concepts of adaptive capacity, adaptive governance, and resiliencewithin a social and environmental framework. It provides a review of how these concepts support aparadigm shift to mitigating current and future challenges—understood through a multidisciplinaryapproach, and how scholars have sought to develop a blueprint to improve the need to foster and mobilizeadaptive capacity within the governance of the commons. In Sweden, key governmental and businessleaders have shown the ability to foster environmental governance that is capable of developing analternative form of planning, implementing, and managing public policy. Moreover, Sweden’s concertedmultilevel governance and public policy efforts have promoted an all-encompassing generational, mainlythrough: coordinated environmental policies and private, public, and civil society partnerships. Theseinitiatives have led to innovative technologies and projects (e.g. urban vertical farming technology) as wellas cross collaboration and integration of companies and industries in order to achieve economic, social,and environmentally symbiosis.