2692-2967ISSN (Online)
2770-0216ISSN (Print)
Volume 14 , Issue 2 , PP: 37–47, 2026 | Cite this article as | XML | Html | PDF | Full Length Article
Shummaila Afzal 1 , Sidra Sohail 2 * , Sana Ullah 3
Doi: https://doi.org/10.54216/AJBOR.140204
The paper creates the business data analytics vision of how small and medium-sized enterprises (SMEs) of GCC travel and tourism ecosystems can mitigate the commercial disruption as the perceived cost, uncertainty, or inconvenience of air travel increases due to geopolitical friction in the region. Since there is a lack of public GCC micro-level booking and itinerary data, the research paper relies on a similar public dataset: the travel mode-choice dataset published under the name of statsmodels and initially based on the intercity mode-choice literature. The benchmark is operationalized as an analogue of disruption-sensitive travel demand reallocation and poses a managerial question, not a simply transport question: in the event of a shock that increases generalized cost and waiting frictions on the most exposed mode what are the most likely demand reallocations and how should SMEs respond? Empirical design transforms the data in the long-format alternative-choice form into an analytical platform that is business-facing and integrates multinomial logit, random forest, gradient boosting, and scenario stress testing into a single analytical framework. The findings indicate that the random forest model provides the best out of sample predictive performance (accuracy 0.981; macro-F1 0.973), whereas the multinomial logit model is useful in translating scenarios that can be understood. Average predicted air share decreases by 28.0 to 16.1 percent with simulated air-travel disruption, and train-like substitutes acquire most of the share. The results suggest that GCC travel, hospitality, and mobility SMEs cannot afford to trust one open channel when a period of geopolitical escalation occurs, but rather they should develop substitution-ready packages, flexible repricing guidelines, and portfolios of partnering that encompass low-friction options. The article adds a unique business analytics template of demand reallocation sensitive to crisis through the use of repeatable public information and underlines practical resilience solutions as opposed to self-forecasting wars.
Business data analytics , SMEs , GCC , Tourism resilience , Travel disruption , Scenario stress testing , Mode substitution
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