Comments on: Recreation Behavior Modeling and Simulation http://liftlab.com/think/fabien/2008/03/17/recreation-behavior-modeling-and-simulation/ Fabien Girardin Mon, 07 Jul 2008 03:02:22 +0000 http://wordpress.org/?v=wordpress-mu-1.2.1 By: fabien http://liftlab.com/think/fabien/2008/03/17/recreation-behavior-modeling-and-simulation/#comment-332045 fabien Tue, 18 Mar 2008 02:28:56 +0000 http://liftlab.com/think/fabien/2008/03/17/recreation-behavior-modeling-and-simulation/#comment-332045 Thanks a lot for your comments and references Peter. I did not mean to undermine your work that I find fascinating. I used the word "sparse" because your dataset covers a certain area and probably a certain type of tourism. My experience with the city of Florence is that surveys do not capture certain tourists. The type of visitor who are in the city for the day and not leave traces in visiting museums nor in hotels. Of course by no mean I pretend that the flickr dataset encapsulates the large range of tourists. However, these user-generated information have a richness not carried by traditional tourist surveys. They provide individual and group digital traces of important aspects of a city during a visit. One aspect of my research is to find out more about the profile of people describing, uploading and georeferencing photos. In a second step I will not to valid these data with other datasets (such as the surveys you mention). Thanks a lot for your comments and references Peter. I did not mean to undermine your work that I find fascinating. I used the word “sparse” because your dataset covers a certain area and probably a certain type of tourism. My experience with the city of Florence is that surveys do not capture certain tourists. The type of visitor who are in the city for the day and not leave traces in visiting museums nor in hotels. Of course by no mean I pretend that the flickr dataset encapsulates the large range of tourists. However, these user-generated information have a richness not carried by traditional tourist surveys. They provide individual and group digital traces of important aspects of a city during a visit. One aspect of my research is to find out more about the profile of people describing, uploading and georeferencing photos. In a second step I will not to valid these data with other datasets (such as the surveys you mention).

]]> By: Peter Johnson http://liftlab.com/think/fabien/2008/03/17/recreation-behavior-modeling-and-simulation/#comment-332036 Peter Johnson Mon, 17 Mar 2008 21:52:49 +0000 http://liftlab.com/think/fabien/2008/03/17/recreation-behavior-modeling-and-simulation/#comment-332036 Fabien, Thanks for linking to my work (TourSim). Just to clarify; the page you linked to are surveys for tourism planners to evaluate TourSim as a way to determine the usefulness of this approach in the context of their tourism planning needs. This data is not used to inform the agent behaviour within the model. Rather, this behaviour is drawn from a range of large surveys that gather specific destinations, accommodations, activities, and characteristics of each tourist trip. These surveys are products of Statistics Canada (Canadian Travel Survey and International Travel Survey). These behaviours are then validated compared to the 2004 Nova Scotia Tourist Exit Survey. If you take a look at the metadata behind these surveys, I think you would have a hard time calling the range of variables, or number of cases "sparse"! I appreciate your perspective that flickr photos could be a useful source of data for determining places where tourists visit within a destination, but I'm not certain that this would encapsulate the true (very broad) range of tourist behaviours. I would think that there are numerous classes of tourist (and indeed people in society) who are not active on a site like flickr, or perhaps on the internet at all. If one were to parameterize agent behaviour based on this limited data source, I would hope that these behaviours were not ascribed to an entire body of tourists visiting a destination, but rather one tourist type ("the tech-savvy traveler" perhaps?). Your mention of Gimblett's work is a good one. He has come out with a recent edited book that details quite a bit about agent simulation for management within recreation areas; the caveat being that you can control the entry and exit of people within such a closed environment. This is one of the limitations of my work; in making a provincial-scale model, there is no way to truly control and track individuals, thus the reliance on survey data for agent parameterization. However, in discussion with tourism planners, the true utility of an ABM comes when looking at such large-scale dynamics, and how they play out over a competitive landscape. Most tourism planners I've spoken to seem content with their ability to manage and understand small-scale destinations using current methods. Anyways, I'll be interested to see how your work unfolds. I'd be interested to know what software platform you end up using to implement your model, and the type of feedback it receives. I've added a reference to some other articles you might find interesting. All the best, Peter A. Johnson, McGill University, Montreal, Canada Deadman et al. The Role of Goal-Oriented Autonomous Agents in Modeling People-Environment Interactions in Forest Recreation. Mathematical and Computer Modelling (1994) vol. 20 (8) pp. 121-133 O'Connor et al. Geo-temporal tracking and analysis of tourist movement. Mathematics and Computers in Simulation (2005) vol. 69 pp. 135-150 Fabien,

Thanks for linking to my work (TourSim). Just to clarify; the page you linked to are surveys for tourism planners to evaluate TourSim as a way to determine the usefulness of this approach in the context of their tourism planning needs. This data is not used to inform the agent behaviour within the model. Rather, this behaviour is drawn from a range of large surveys that gather specific destinations, accommodations, activities, and characteristics of each tourist trip. These surveys are products of Statistics Canada (Canadian Travel Survey and International Travel Survey). These behaviours are then validated compared to the 2004 Nova Scotia Tourist Exit Survey. If you take a look at the metadata behind these surveys, I think you would have a hard time calling the range of variables, or number of cases “sparse”!

I appreciate your perspective that flickr photos could be a useful source of data for determining places where tourists visit within a destination, but I’m not certain that this would encapsulate the true (very broad) range of tourist behaviours. I would think that there are numerous classes of tourist (and indeed people in society) who are not active on a site like flickr, or perhaps on the internet at all. If one were to parameterize agent behaviour based on this limited data source, I would hope that these behaviours were not ascribed to an entire body of tourists visiting a destination, but rather one tourist type (”the tech-savvy traveler” perhaps?).

Your mention of Gimblett’s work is a good one. He has come out with a recent edited book that details quite a bit about agent simulation for management within recreation areas; the caveat being that you can control the entry and exit of people within such a closed environment. This is one of the limitations of my work; in making a provincial-scale model, there is no way to truly control and track individuals, thus the reliance on survey data for agent parameterization. However, in discussion with tourism planners, the true utility of an ABM comes when looking at such large-scale dynamics, and how they play out over a competitive landscape. Most tourism planners I’ve spoken to seem content with their ability to manage and understand small-scale destinations using current methods.

Anyways, I’ll be interested to see how your work unfolds. I’d be interested to know what software platform you end up using to implement your model, and the type of feedback it receives. I’ve added a reference to some other articles you might find interesting.

All the best,

Peter A. Johnson,
McGill University,
Montreal, Canada

Deadman et al. The Role of Goal-Oriented Autonomous Agents in Modeling People-Environment Interactions in Forest Recreation. Mathematical and Computer Modelling (1994) vol. 20 (8) pp. 121-133

O’Connor et al. Geo-temporal tracking and analysis of tourist movement. Mathematics and Computers in Simulation (2005) vol. 69 pp. 135-150

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