Optimization model: the innovation and future of e-ecotourism for sustainability

Abstract

Purpose This study aims to find a dynamic model in an effort to optimize tourism performance in ecotourism destinations. The model structure is built based on competitive performance in geographic areas and the application of ecotourism elements that are integrated with big data innovation through artificial intelligence technology. Design/methodology/approach Data analysis is performed through dynamic system modeling. Simulations are carried out in three models: First, existing simulation models. Second, Scenario 1 is carried out by utilizing a causal loop through innovation of big data-based artificial intelligence technology to ecotourism elements. Third, Scenario 2 is carried out by utilizing a causal loop through big data-based artificial intelligence technology on aspects of ecotourism elements and destination competitiveness. Findings This study provides empirical insight into the competitiveness performance of destinations and the performance of implementing ecotourism elements if integrated with big data innovations that will be able to massively demonstrate the growth of sustainable tourism performance. Research limitations/implications This study does not use a primary database, but uses secondary data from official sources that can be accessed by the public. Practical implications The paper includes implications for the development of intelligent technology based on big data and also requires policy innovation. Social implications Sustainable tourism development. Originality/value This study finds the expansion of new theory competitiveness of ecotourism destinations.