Geospatial analysis of Islamic business trends: Mapping global interest via google search query clustering

Asep Koswara

doi:10.59005/alkasb.v4i1.632

Authors

Asep Koswara IKOPIN University, Indonesia

DOI:

https://doi.org/10.59005/alkasb.v4i1.632

Keywords:

Geospatial Analysis, Global Islamic Economy, Google Search Query, Islamic Business Trends, Machine Learning in Economics

Abstract

The Islamic economy, encompassing sectors such as finance, halal food, tourism, and fintech, has expanded rapidly worldwide in recent years. Yet, global public interest trends in these sectors remain underexplored, particularly from a digital behavior standpoint. This study investigates Islamic business trends by analyzing and clustering Google search data (2020–2025) to uncover geographic and thematic interest patterns. Using geospatial mapping and unsupervised machine learning, it evaluates Google Trends data to reveal temporal and spatial shifts in engagement. Findings show Islamic finance interest is concentrated in regions with mature Shariah-compliant systems, while halal food attracts global attention beyond Muslim-majority demographics. Halal tourism and Sharia fintech, though niche, exhibit untapped growth potential. The study demonstrates how digital trace data can enhance real-time economic trend analysis, with regional variations reflecting cultural and institutional influences. By combining digital analytics, economic geography, and Islamic business research, this work provides actionable insights for policymakers and investors to identify market opportunities. Additionally, it introduces a pioneering framework integrating geospatial and machine learning methods to track global business trends, advocating for broader use of digital data in economic studies.

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