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Mixed-methods evaluation demonstrates improved campaign efficiency and adaptive marketing modulation in ecotourism management, suggesting a viable framework for balancing promotion with conservation.
This study addresses the challenge of achieving sustainable marketing performance in fragile ecotourism destinations, where marketing activities must balance competitiveness with environmental preservation. A hybrid Smart Digital Marketing (SDM) framework that integrates Digital Six Sigma Marketing (DSSM) with fuzzy logic-based decision systems is developed and empirically evaluated to support adaptive decision-making under ecological constraints. Using an explanatory sequential mixed-methods design, the study combines survey data ( N = 250), stakeholder interviews ( N = 18), environmental observation scorecards, and computational modeling. The framework operationalizes three ecological and behavioral variables—environmental fragility, visitor load, and tourist satisfaction—as inputs to a Mamdani-type fuzzy inference system with 27 if–then rules, producing adaptive marketing intensity decisions aligned with carrying capacity. The pre–post analysis showed statistically significant observed improvements associated with framework implementation: campaign response time was reduced by 35.7%, process variance decreased by 39.4%, the process capability index increased from 0.94 to 1.42, and competitive positioning improved by 24.3%. The fuzzy inference system demonstrated adaptive modulation of marketing intensity from 0.80 under stable conditions to 0.19 under high ecological risk. The study contributes a practical, data-driven decision-support framework that enables organizations to align marketing strategies with ecological thresholds, extending Smart Digital Marketing as a dynamic capability within sustainability-sensitive tourism contexts. The framework provides a potentially transferable model for translating qualitative and ambiguous variables into structured, adaptive marketing decisions under environmental uncertainty.
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Nessreen El Said Mansour El Sharkawey (2026) studied this question.
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