A multi-agent simulation approach to sustainability in tourism development

In the last decades the increasing facility in moving and the simultaneous fall of the transportation costs have strongly increased the tourist flows. As a consequence, different destinations, especially those which are rich of natural resources, unable or unready to sustain huge tourism flows, present serious problems of sustainability and Tourism Carrying Capacity (TCC). At the present, it is universally recognized that every tourist destination should plan effective and pro-reactive protection policies of its cultural, environmental and social resources. In order to facilitate policies definition it may be useful to measure the Tourist Carrying Capacity, but the literature has highlighted that this is not an easy task for different reasons: among the others, the complexity and the dynamicity of the concept, the absence of a universally accepted definition and the impossibility of assigning an objective scientific value and to apply a rigorous analysis. Thereby, more recently an alternative, or even complementary, interpretation of TCC has developed; it is called LAC, Limit of Acceptable Changes where the focus shifts from: “How much use an area can tolerate?†to “How much change is acceptable?â€, aiming at evaluating the costs and benefits from alternative management tourism actions. The aim of the paper is to present an innovative framework, based on the LAC approach - MABSiT, Mobile Agent Behavior Simulation in Tourism - developed by the authors, which is composed by five modules: elaboration data, DBMS, ad-hoc maps, agents and ontology. Its modular structure allows to easily study the interactions among the components in order to observe the behavior of the single agents. In an aggregate form, it is possible to define group dynamics, where one possible effect is the influence on the variation of agents’ satisfaction perception in comparison to the surroundings environment. The paper will be structured as follows: an introduction will be followed by a literature review; than the methodology and the framework will be presented and applied to a case study: Vieste, a known maritime destination of South of Italy, which is characterized by high problems of seasonality in the summer. Finally, some conclusions and policy recommendations will be drawn.

Evacuation modelling for wildland-urban interface fires in touristic areas

This technical note presents a brief overview of the models available for the simulation of fire evacuation at the wildland-urban interface in touristic areas. Depending on the scale of the scenarios under consideration and the evacuation mode considered, models are split into macroscopic vs microscopic tools and 1) pedestrian models, 2) traffic models, 3) coupled evacuation models, 4) modelling unconventional evacuation modes. The key findings of this review are: 1) When pedestrian movement is the main mode of evacuation transport, the scale of the analysis will have a strong impact on the choice of the most appropriate modelling approach although at building scale and not very large area size, the use of microscopic modelling based on a continuous approach seems to be a suitable method. 2) When multiple modes of transport are considered (e.g., pedestrian and traffic), the modeller should make a call into modelling explicitly or implicitly the pedestrian response and movement layer, 3) most evacuation models are currently not able to model explicitly unconventional means of evacuations such as displacement via sea or air. The scenario complexity and the uncertainty in the available input will affect the choice of modellers to represent evacuation modelling layers (e.g., pedestrian response, pedestrian movement, and traffic movement) and their interaction with the wildfire explicitly or implicitly

Recreational trip timing and duration prediction: A research note

This paper presents models that predict two recreational fishing trip parameters: the length of a trip and the timing of a trip within a year. A discrete choice (logit) model linking the choice of trip timing to calendar events, the demographic characteristics of anglers as well as the nature of the trip is econometrically estimated. A Tobit model is used to evaluate the relationship between fishing trip length and personal and trip characteristics. The results indicate that timing choice and trip length can be explained well in terms of observable personal and trip variables. Knowledge of these relationships is a useful input to tourism/recreational fishing management as well as to the development of tourism/fishing activity simulation models.recreational fishing, trip timing, length of recreational trips, tourism simulation, environmental impact management, Environmental Economics and Policy,

Urban tourism crowding dynamics: Carrying capacity and digital twinning

The increase in tourism activity globally has led to overcrowding, causing damage to local ecosystems and degradation of the tourism experience. To plan tourist activity it is necessary to define adequate indicators and understand the dynamics of tourist crowds. The main goals of this dissertation are the development of (1) an algorithm for assessing spatially fine-grained, physical carrying capacity (PCC) for a complex urban fabric, (2) an agent-based simulation model for the egress of participants in public open space tourism attraction events and (3) an agent-based simulation model using the PCC algorithm for tourism crowding stress analysis in urban fabric constrained scenarios. OpenStreetMap open-data was used throughout this research. The proposed PCC algorithm was tested in Santa Maria Maior parish in Lisbon that has a complex ancient urban fabric. The GAMA agent-based platform was used in the two simulation studies. The first compared two scenarios (normal and COVID-19) in three major public spaces in Lisbon and the second focused on the simulation of a real-time tourism crowding stress analysis scenario of visitors’ arrival at the Lisbon Cruise Terminal. The results show the proposed algorithm’s feasibility to determine the PCC of complex urban fabrics zones and its application as an initial reference value for the evaluation of real-time crowding stress, namely in simulations for assessing overtourism scenarios, both in public open spaces as in highly constrained urban fabrics.O aumento da atividade turística a nível global tem levado à superlotação, causando danos aos ecossistemas locais e degradação da experiência turística. Para planear a atividade turística é necessário definir indicadores adequados e entender as dinâmicas das multidões turísticas. Os principais objetivos desta dissertação são o desenvolvimento de (1) um algoritmo para avaliar a capacidade de carga física (CCF) de fino grão espacial para uma malha urbana complexa, (2) um modelo de simulação baseado em agentes para o escoamento de participantes em eventos de atração turística em espaços abertos e (3) um modelo de simulação baseado em agentes usando o algoritmo de CCF para análise do stress de aglomeração de turistas em cenários de malha urbana restritiva. Os dados abertos do OpenStreetMap foram usados nesta investigação. O algoritmo CCF proposto foi testado na freguesia de Santa Maria Maior, em Lisboa, que tem uma malha urbana antiga e complexo. A plataforma GAMA baseada em agentes foi usada nos dois estudos de simulação. O primeiro comparou dois cenários (normal e COVID-19) em três grandes espaços públicos de Lisboa e o segundo analisou o stress de aglomeração causado pela chegada de navios ao Terminal de Cruzeiros de Lisboa. Os resultados mostram a viabilidade do algoritmo proposto para determinar a CCF de zonas com tecidos urbanos complexos e a sua aplicação como valor de referência inicial para a avaliação do stress de superlotação em tempo real, nomeadamente na avaliação de cenários de aglomeração turística excessiva, tanto em espaços abertos, como em malhas urbanas intrincadas

Easing the adoption of agent-based modelling (ABM) in tourism research

Agent-based modelling (ABM) is an emerging approach in tourism research. Despite the natural fit between theories of tourism as a complex, interconnected system, and the generative approach supported in ABM, there has been only limited integration within mainstream tourism research. This research letter reports on a recent gathering of tourism ABM researchers to define the main challenges that face the adoption of ABM in tourism research. These include technical, communications, and novelty issues. In response to these challenges, three potential strategies to ease adoption are outlined: education, awareness, and interdisciplinary teams. These findings are framed as a call for increased attention to the fit of ABM within tourism research, and a framework for negotiating constraints to adoption of this technology.info:eu-repo/semantics/publishedVersio

Where to vacation? An agent-based approach to modelling tourist decision-making process

Agent-based models (ABMs) are becoming more relevant in social simulation due to the potential to model complex phenomena that emerge from individual interactions. In tourism research, complexity is a subject of growing interest and researchers start to analyse the tourism system as a complex phenomenon. However, there is little application of ABMs as a tool to explore and predict tourism patterns. The purpose of the paper is to develop an ABM that increases knowledge in tourism research by (i) considering the complexity of tourism phenomenon, (ii) providing tools to explore the complex relations between system components and (iii) giving insights on the functioning of the system and the tourist decision-making process. A theoretical ABM is developed to improve knowledge on tourist decision-making in the selection of a destination to vacation. Tourists’ behaviour, such as individual motivation, and social network influence in the vacation decision-making process are hereby discussed.info:eu-repo/semantics/publishedVersio

Crowd Dynamics, Management and Control at Tourist Attractions during Special Events: A Case Study at Souq Waqif Using Pedestride® Crowd Simulation Tool

"Large crowds can be expected at famous tourist attractions, e.g., Souq Waqif, during special events such as the FIFA World Cup 2022. A comprehensive understanding of crowd dynamics is extremely important in order to ensure safety of crowds and efficiency of crowd flows at large gathering spots. Pedestrian crowd simulation tools can be used to evaluate crowd flows and to verify crowd management and control strategies at public infrastructure. The objective of this study is to evaluate safety and efficiency of crowd flows at Souq Waqif, both under normal and emergency situations using Pedestride® Crowd Simulation tool developed at Melbourne University. This simulation model has been calibrated and validated using empirical data collected through controlled experiments and real-world observations. By simulating the increased visitor demand at Souq Waqif as a case study, we aim to highlight any required design modifications and to recommend and verify crowd management strategies in order to mitigate any unfavorable situations, such as stampede during any emergency. The study shows that at increased demands and during emergency evacuation, crowds tend to take similar route. Further, increased demands could elevate the maximum crowd density up to 6 p/m2 at gates and junctions. In order to mitigate such unfavorable situations, dynamic exit signs are needed to direct flows to other clear exits to avoid herding effect.