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Marine Protected Areas (MPAs) shield ocean environments from hazardous human activities, including the extraction of marine resources and excessive urban development. Delimitation, zoning and governance structures are some of the environmental management tools that are provided by MPAs. These management tools may be contentious when human settlements exist within an MPAs' boundaries, since zoning affects existing human activities and potential developments, and managing structures overlap traditional governance arrangements. Varying perspectives emerge when each stakeholder is taken into consideration separately. Ideally all stakeholders with genuine interests in MPAs should take part in the delimitation, zoning and governance of these areas. However, governance is about reaching agreements amidst differences and is not just a matter of considering differences as singularities. In order to understand how multiple stakeholders would reach a shared environmental governance of an MPA, we took the Exuma Cays Land and Sea Park (ECLSP) in The Bahamas as a case study. The ECLSP, created in 1958, is co-managed by the Government of The Bahamas and the Bahamas National Trust (BNT), and contains within its boundaries uninhabited islands, islands occupied by local communities, and private islands mainly owned by foreigners or held in Bahamian trusts. In this study, we conducted an exercise with different stakeholders who were challenged to work together in redrawing the park's boundaries, zoning and governance structures. Their individual opinions mattered less than the discussion and outcomes of their joint work. We conclude that a shared environmental governance structure does not eliminate all the frictions among stakeholders, but rather it makes them all aware of the natural and social complexities involved in managing MPAs, which improves stewardship and enhances the ECLSP's legitimacy among stakeholders. [ABSTRACT FROM AUTHOR]

Amsterdam is a culturally rich city attracting millions of tourists. Popular activities in Amsterdam consist of museum visits and boat tours. By strategically combining them, this paper presents an innovative approach using waterborne autonomous vehicles (WAVs) to improve the museum visitation in Amsterdam. Multi-source urban data including I Amsterdam card data and Instagram hashtags are used to reveal museum characteristics such as offline and online popularity of museums and visitation patterns. A multi-objective model is proposed to optimize WAV routes by considering museum characteristics and travel experiences. An experiment in the Amsterdam Central area was conducted to evaluate the viability of employing WAVs. By comparing WAVs with land transportation, the results demonstrate that WAVs can enhance travel experience to cultural destinations. The presented innovative WAVs can be extended to a larger variety of points of interest in cities. These findings provide useful insights on embracing artificial intelligence in urban tourism. [ABSTRACT FROM AUTHOR]

Over the last 10 years, ride-hailing companies (such as Uber and Grab) have proliferated in cities around the world. While generally beneficial from an economic viewpoint, having a plurality of operators that serve a given demand for point-to-point trips might induce traffic inefficiencies due to the lack of coordination between operators when serving trips. In fact, the efficiency of vehicle fleet management depends, among other things, density of the demand in the city, and in this sense having multiple operators in the market can be seen as a disadvantage. There is thus a tension between having a plurality of operators in the market, and the overall traffic efficiency. To this date, there is no systematic analysis of this trade-off, which is fundamental to design the best future urban mobility landscape. In this paper, we present the first systematic, data-driven characterization of the cost of non-coordination in urban on-demand mobility markets by proposing a simple, yet realistic, model. This model uses trip density and average traffic speed in a city as its input, and provides an accurate estimate of the additional number of vehicles that should circulate due to the lack of coordination between operators—the cost of non-coordination. We plot such cost across different cities—Singapore, New York (limited to the borough of Manhattan in this work), San Francisco, Vienna and Curitiba—and show that due to non-coordination, each additional operator in the market can increase the total number of circulating vehicles by up to 67%. Our findings could support city policy makers to make data supported decisions when regulating urban on-demand mobility markets in their cities. At the same time, our results outline the need of a more proactive government participation and the need for new, innovative solutions that would enable a better coordination of on-demand mobility operators. [ABSTRACT FROM AUTHOR]