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Negotiating Constraints to the Adoption of Agent-Based Modeling in Tourism Planning

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  • Peter A Johnson
  • Renee E Sieber

Abstract

Recent work exploring the use of agent-based models (ABMs) in a planning support role must be accompanied by an evaluation of the possible constraints that exist to the use of these models. This research presents an evaluation, from the perspective of professional tourism planners, of the potential for ABM of tourism dynamics to serve as a planning support system (PSS). Tourism is a phenomenon that is inherently individually based, with many interacting processes occurring at multiple scales, across space and time. This makes it a natural environment in which to test an ABM-based PSS. We conducted a series of interviews with tourism planners operating in the Canadian province of Nova Scotia, a region where tourism plays an important economic role. These interviews consisted of a general-needs overview, coupled with an assessment of a prototype model we developed, called TourSim. The interviews sought to uncover the specific planning tasks to which ABM would be best applied and identify areas of adoption constraint. The results of this research indicate that TourSim served as a scenario development tool, with a focus on data analysis and communication. Conversely, TourSim was reported to lack transparency, which affected the confidence that planners had in its results. This evaluation clarifies the path forward for developers looking to introduce ABM to planning practice.

Suggested Citation

  • Peter A Johnson & Renee E Sieber, 2011. "Negotiating Constraints to the Adoption of Agent-Based Modeling in Tourism Planning," Environment and Planning B, , vol. 38(2), pages 307-321, April.
    • Handle: RePEc:sae:envirb:v:38:y:2011:i:2:p:307-321
    DOI: 10.1068/b36109
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    1. Helen Couclelis, 2005. "“Where has the Future Gone?†Rethinking the Role of Integrated Land-Use Models in Spatial Planning," Environment and Planning A, , vol. 37(8), pages 1353-1371, August.
    2. Barnaud, Cécile & Bousquet, François & Trebuil, Guy, 2008. "Multi-agent simulations to explore rules for rural credit in a highland farming community of Northern Thailand," Ecological Economics, Elsevier, vol. 66(4), pages 615-627, July.
    3. Joshua M. Epstein & Robert L. Axtell, 1996. "Growing Artificial Societies: Social Science from the Bottom Up," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262550253, December.
    4. David O'Sullivan & Mordechai Haklay, 2000. "Agent-Based Models and Individualism: Is the World Agent-Based?," Environment and Planning A, , vol. 32(8), pages 1409-1425, August.
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    Cited by:

    1. Zhai, Xueting & Zhong, Dixi & Luo, Qiuju, 2019. "Turn it around in crisis communication: An ABM approach," Annals of Tourism Research, Elsevier, vol. 79(C).
    2. Crawford, Megan M., 2019. "A comprehensive scenario intervention typology," Technological Forecasting and Social Change, Elsevier, vol. 149(C).

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