Tourists' activity patterns result from complex interactions between time-space constraints and cognitive, social, cultural, and emotional factors. Accordingly, tourists' intradestination activity is studied today from multiple perspectives. Yet knowledge regarding the interrelationships between these factors is limited. The current research aims to contribute to the bridging of this gap, by studying tourists' activity patterns and the time-space resource allocation decisions they reflect. Using a smartphone application, 384 tourists' activity days in the cities of Tel-Aviv and Jerusalem were tracked and characterized in terms of resource allocation patterns, identifying three distinct behavioral patterns. The effects of various personal and external factors on group membership were then assessed. The results uncover complex relationships between various decision-making dimensions, where interdimensional interactions occur at multiple spatial scales and decision-making instances. These findings suggest that activity patterns emerge from a decision time-space in which effects are contingent upon each other across scales and behavioral dimensions.
While the direct physical effects of an urban catastrophe are relatively straightforward to assess, indirect and longterm impact on the urban system is more circumspect. A large-scale shock such as an earthquake derails the complex urban system from its equilibrium path onto an unknown trajectory. Consequently, assessing the effect of policy intervention that aims to mitigate this shock and increase urban resilience is fraught with complexity. This paper presents the implementation of dynamic agent-based simulation to test long-run effects of a hypothetical earthquake in Jerusalem, Israel. It focuses on investigating the effectiveness of policy choices aimed at restoring the urban equilibrium. Cities are found to have a self-organising market-based mechanism that strives to attain a new equilibrium. They therefore may not always bounce back -they may also bounce forward. Decision-makers, engineers, emergency and urban planners need to be cognizant of this tendency when designing policy interventions.Otherwise, well-intentioned efforts may inhibit urban rejuvenation and delay the onset of city recovery.
People share data in different ways. Many of them contribute on a voluntary basis, while others are unaware of their contribution. They have differing intentions, collaborate in different ways, and they contribute data about differing aspects. Shared Data Sources have been explored individually in the literature, in particular OpenStreetMap and Twitter, and some types of Shared Data Sources have widely been studied, such as Volunteered Geographic Information (VGI), Ambient Geographic Information (AGI), and Public Participation Geographic Information Systems (PPGIS). A thorough and systematic discussion of Shared Data Sources in their entirety is, however, still missing. For the purpose of establishing such a discussion, we introduce in this article a schema consisting of a number of dimensions for characterizing socially produced, maintained, and used ‘Shared Data Sources,’ as well as corresponding visualization techniques. Both the schema and the visualization techniques allow for a common characterization in order to set individual data sources into context and to identify clusters of Shared Data Sources with common characteristics. Among others, this makes possible choosing suitable Shared Data Sources for a given task and gaining an understanding of how to interpret them by drawing parallels between several Shared Data Sources.
Technological developments such as the Web 2.0, sensing technologies, and geographic information systems (GIS) greatly increase the accessibility of geo-information today, thus diminishing the divide between producers/experts and users. Accordingly, more populations engage today with digital mapping activities, leading to
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