Evolutionary Game Dynamics Applied to Strategic Adoption of Immersive Technologies in Cultural Heritage and Tourism

TL;DR

An evolutionary game model is employed to attempt to map possible scenarios and highlight potential decision-making trajectories in immersive technologies, highlighting how evolutionary dynamics lead to identifying a dominant long-term strategy that emerges from the complex system of coexistence among various stakeholders.

Abstract

Immersive technologies such as Metaverse, AR, and VR are at a crossroads, with many actors pondering their adoption and potential sectors interested in integration. The cultural and tourism industries are particularly impacted, facing significant pressure to make decisions that could shape their future landscapes. Stakeholders' perceptions play a crucial role in this process, influencing the speed and extent of technology adoption. As immersive technologies promise to revolutionize experiences, stakeholders in these fields weigh the benefits and challenges of embracing such innovations. The current choices will likely determine the trajectory of cultural preservation and tourism enhancement, potentially transforming how we engage with history, art, and travel. Starting from a decomposition of stakeholders' perceptions into principal components using Q-methodology, this article employs an evolutionary game model to attempt to map possible scenarios and highlight potential decision-making trajectories. The proposed approach highlights how evolutionary dynamics lead to identifying a dominant long-term strategy that emerges from the complex system of coexistence among various stakeholders.

Figures (7)

• Figure 1: Box-plot of the distributions of the values obtained for each statement (Fazio2024).
• Figure 2: Trend of the five variables $x_{qi}(t)$ over time, the asymptotic value show that Q-factor-1 dominates over others.
• Figure 3: Trend of the five variables $z_{qi}(t)$ over time, the asymptotic value determines the main sign of the loading of the various Q-factors. All Q-factors tend to positive values, except for Q-factor 3.
• Figure 4: Trends of the variables $y_{i}(t)$ related to the strategies where the Tool dimension takes the Traditional (T) option.
• Figure 5: Trends of the variables $y_{i}(t)$ related to the strategies where the Tool dimension takes the Standard digital (S) option.