Vol: 14, Issue: 3 2024

Page: 45-51

Data-Driven Management Using Business Analytics: The Case Study of Data Sets for New Business in Tourism

Aarish Sachdeva

Received Date: 2024-05-21

Accepted Date: 2024-08-18

Published Date: 2024-08-22

http://doi.org/10.37648/ijtbm.v14i03.005

Tourism entrepreneurship has become increasingly data-intensive. This paper synthesizes peer-reviewed work from 2013–2023 to propose a practical, data-driven management playbook for a new tourism venture. We review major data sources (user-generated content, search and social signals, mobile positioning, OTA/airbnb supply & price data, and official statistics) and the analytics they enable (demand forecasting, location and product design, pricing, and reputation management). We then construct a case study for a hypothetical startup—TourStart—launching curated neighbourhood experiences in a beach destination. Using a portfolio of feasible, real-world data sets and methods (e.g., Google Trends for demand signals, TripAdvisor review mining for product features, Airbnb/OTA data for capacity & pricing, and—where available—mobile positioning for flows), we outline end-to-end decisions: market selection, seasonality calibration, micro-location choice, itinerary design, price setting, and marketing mix. Comparative analysis shows complementary strengths and biases across data sets: search data is timely but volatile; reviews are rich but biased toward vocal users; mobile data is granular but regulated; OTA/supply data captures competition but can contain systematic errors if not validated. We close with implementation guidance (data pipelines, KPIs, and experimentation), limitations (privacy, survivorship bias, platform shocks), and a research agenda. The contribution is a reproducible blueprint that aligns business analytics capability with entrepreneurial decisions in tourism.

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