Forecast, Foresight, and Adaptation: An Adaptive Strategy Framework for the Hospitality Industry Integrating Data-Driven Forecasting into Strategic Decision-Making

This dissertation advances a comprehensive framework for understanding how forecasting, foresight, and adaptive learning interact to shape strategic decision-making in the hospitality industry. It proposes the concept of an Adaptive Strategy Framework, in which organizations continuously move through a cyclical process of sensing, interpreting, and responding to change. Within this system, forecasting represents the predictive layer that transforms data into anticipatory insights; foresight serves as the interpretive layer that explores alternative futures and enhances strategic imagination; and adaptation functions as the transformative layer that converts learning into action, reinforcing organizational resilience and competitiveness.By integrating behavioural analytics, big data, and advanced statistical modelling, the study bridges the gap between operational forecasting and strategic foresight. It demonstrates that consumer digital behaviour, captured through web interactions and behavioural indicators such as trust, engagement, and purchase intention, provides a valuable predictive signal of market dynamics. Segmenting consumers through clustering and functional analysis reveals distinct behavioural archetypes that vary in loyalty, sensitivity to context, and temporal reactivity, highlighting the importance of tailored and time-sensitive strategies.The research also addresses the influence of environmental variability on demand, showing that climatic fluctuations and extreme events exert measurable effects on consumer choices and market performance. By combining behavioural and environmental dimensions within adaptive forecasting models, the study demonstrates how predictive accuracy can be enhanced when human decision-making processes are examined alongside exogenous shocks.From a theoretical standpoint, the dissertation contributes to strategic management by reframing forecasting as a process of learning and adaptation rather than prediction alone. It underscores that resilience in volatile markets depends on the integration of predictive precision, interpretive foresight, and adaptive capacity. From a managerial perspective, it offers a data-driven foundation for decision-making in hospitality, enabling managers to anticipate shifts in demand, optimize resource allocation, and design strategies that evolve with consumer and environmental dynamics.Ultimately, the work calls for a new generation of adaptive, data-informed organizations capable of transforming uncertainty into strategic opportunity through continuous sensing, foresight, and learning.