Abstract

Interpretive marine turtle tours in Cyprus yields an alluring ground to unfold the complex nature of pro-environmental behavior among travelers in nature-based destinations. Framing on Collins (2004) interaction ritual concept and the complexity theory, the current study proposes a configurational model and probes the interactional effect of visitors’ memorable experiences with environmental passion and their demographics to identify the causal recipes leading to travelers’ sustainable behaviors. Data was collected from tourists in the marine protected areas located in Cyprus. Such destinations are highly valuable not only for their function as an economic source for locals but also as a significant habitat for biodiversity preservation. Using fuzzy-set Qualitative Comparative Analysis (fsQCA), this empirical study revealed that three recipes predict the high score level of visitors’ environmentally friendly behavior. Additionally, an adaptive neuro-fuzzy inference system (ANFIS) method was applied to train and test the patterns of visitors’ pro-environmental behavior in a machine learning environment to come up with a model which can best predict the outcome variable. The unprecedented implications on the use of technology to simulate and encourage pro-environmental behaviors in sensitive protected areas are discussed accordingly.

摘要

在塞浦路斯进行的解释性海龟之旅提供了一个诱人的场所，可以揭示基于自然目的地的旅行者中环保行为的复杂性。在研究柯林斯（2004）互动仪式概念和复杂性理论的框架下，本研究提出了一种配置模型，并探讨了游客难忘经历与环境热情及其人口统计学的相互作用，以确定导致旅行者可持续行为的因果关系。数据是从位于塞浦路斯海洋保护区的游客那里收集的。这些目的地不仅具有作为当地人的经济来源的功能，而且还可以作为生物多样性保护的重要栖息地，因此具有很高的价值。使用模糊集定性比较分析（fsQCA），这项实证研究表明，三种配方可以预测游客的环保行为得分高。此外，在机器学习环境中，采用了一种自适应神经模糊推理系统（ANFIS）方法来训练和测试访问者的亲环境行为模式，从而得出可以最好地预测结果变量的模型。因此，讨论了在敏感保护区使用技术模拟和鼓励环保行为的空前意义。自适应神经模糊推理系统（ANFIS）方法被用来训练和测试机器学习环境中访问者的亲环境行为模式，从而得出可以最好地预测结果变量的模型。因此，讨论了在敏感保护区使用技术模拟和鼓励环保行为的空前意义。自适应神经模糊推理系统（ANFIS）方法被用来训练和测试机器学习环境中访问者的亲环境行为模式，从而得出可以最好地预测结果变量的模型。因此，讨论了在敏感保护区使用技术模拟和鼓励环保行为的空前意义。