(Big) Data Driven Strategic Decision-Making in Overtourism Management

Overtourism occurs when a destination exceeds its capacity to sustainably manage visitors: Overtourism has emerged as a significant challenge for numerous destinations worldwide, leading to detrimental effects on local communities, environments, cultures, and economies. How can one quantify the tipping point where tourism becomes unsustainable? Local, regional, and national authorities have implemented studies and policies aimed at mitigating overtourism, yet the challenge persists. The purpose of this paper is two-fold. First, we explore the transformative role of Big Data Analytics in the tourism and hospitality sectors as a powerful strategic tool for addressing overtourism. Big Data Analytics encompasses advanced techniques that streamline and interpret vast amounts of raw data, providing actionable insights that inform evidence-based decision-making. While predominantly applied in the fintech and information technology (IT), Big Data’s potential in tourism is just beginning to be realized. Second, we examine the application of descriptive, diagnostic, predictive, and prescriptive analytics to quantify and manage the pressures of overtourism, offering a data-driven approach to mitigate its negative impacts. Potentials, implications and challenges of using big data analytics as a strategic decision-making tool are discussed with the use of relevant case studies. The research positions Big Data Analytics as a critical instrument in bridging the gap between overtourism and sustainable tourism management strategies. Destinations and DMOs could greatly benefit from the implementation of big data analytics not only as a tool to mitigate overtourism proactively, but also as a useful developmental tool that will allow them to prevent the negative impacts of overtourism proactively.