Modeling carrying capacity and management for monuments condition in tourism regions Case study: Kangavar’s Anahita Temple

Abstract

Tourism locations are required to develop a general management plan that is consistent with visitor carrying capacities. This paper describes a carrying capacity modeling system that allows regions’ tourism managers to quantitatively determine whether the current state of a region’s tourism condition is in compliance with those standards or not. The modeling system uses an ex-post adaptive monuments management (AMM) model to determine whether the current state of a tourism region complies with the physical and social carrying capacities. Also the manager requires knowledge of the tourism carrying capacity, which in this article is determined by the use of physical, real and effective carrying capacities. The multiple attribute scoring test of capacity (MASTEC) identifies the best management action for achieving compliance. The AMM model addresses potential errors that can occur when inferring a monument state from resource/social conditions. The AMM model minimizes the likelihood of such decision errors by using Bayes’ rule to determine the state of tourism regions. The MASTEC method allows a manager to identify the best management action for bringing an incompliant monument into compliance with carrying capacities. Limits of Acceptable Change and Visitor Impact Management, and multiple attribute decision making maximizes the manager’s expected utility function subject to stochastic carrying capacity. Anahita Temple was selected to showcase the usage of these models. Several factors limit the ability of tourism regions to implement the carrying capacity modeling system. Using a spatial decision support tool to implement the modeling system lessens some of these limitations.

Keywords

• tourism carrying capacities
• adaptive ecosystem management
• bayes’ rule
• multiple attribute decision-making
• anahita temple