Designing Strategies for Optimal ATM Placement Location Using Geospatial Methods and Consumer Transaction Behavior

The rapid development of Automated Teller Machines (ATMs) necessitates strategic placement to address customer needs, bank business goals, and evolving transaction trends. This study integrates geospatial methods and consumer transaction behavior to identify optimal ATM locations. Geographic Information System (GIS) technology, with overlay techniques, is employed to analyze spatial data, segment transactions, and evaluate geocentricity. Data collection involves tabulation (population density, city infrastructure) and spatial sources (BPS, OJK, Open Street Map), which are digitized and analyzed using methods such as Analytical Hierarchy Process (AHP), Voronoi, and hexagonal tessellation. The results indicate that city centers with high accessibility and comprehensive facilities are optimal locations for ATM placement. Consumer behavior analysis shows preferences for ATMs that are easy to access, open 24 hours, and equipped with complete facilities. By combining GIS and customer behavior data, the study provides actionable insights for efficient ATM placement. This approach enhances banking services, increases profitability, and ensures the sustainability of ATMs amidst digital wallet competition. The findings offer practical guidelines for banks to optimize ATM deployment while addressing customer needs and reducing operational costs. These insights also highlight GIS technology's pivotal role in modern banking asset management.

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Publication Details

Journal
Return Study of Management Economic and Bussines
Published
2024-11-23
DOI
https://doi.org/10.57096/return.v3i11.292
Primary Topic
Consumer Market Behavior and Pricing
Type
article
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article

Designing Strategies for Optimal ATM Placement Location Using Geospatial Methods and Consumer Transaction Behavior

Ari Setiawan, Achmad Ramdani
Return Study of Management Economic and Bussines
Consumer Market Behavior and Pricing
article

Designing Strategies for Optimal ATM Placement Location Using Geospatial Methods and Consumer Transaction Behavior

Ari Setiawan, Achmad Ramdani
article en

Abstract

The rapid development of Automated Teller Machines (ATMs) necessitates strategic placement to address customer needs, bank business goals, and evolving transaction trends. This study integrates geospatial methods and consumer transaction behavior to identify optimal ATM locations. Geographic Information System (GIS) technology, with overlay techniques, is employed to analyze spatial data, segment transactions, and evaluate geocentricity. Data collection involves tabulation (population density, city infrastructure) and spatial sources (BPS, OJK, Open Street Map), which are digitized and analyzed using methods such as Analytical Hierarchy Process (AHP), Voronoi, and hexagonal tessellation. The results indicate that city centers with high accessibility and comprehensive facilities are optimal locations for ATM placement. Consumer behavior analysis shows preferences for ATMs that are easy to access, open 24 hours, and equipped with complete facilities. By combining GIS and customer behavior data, the study provides actionable insights for efficient ATM placement. This approach enhances banking services, increases profitability, and ensures the sustainability of ATMs amidst digital wallet competition. The findings offer practical guidelines for banks to optimize ATM deployment while addressing customer needs and reducing operational costs. These insights also highlight GIS technology's pivotal role in modern banking asset management.

Return Study of Management Economic and BussinesVol. 3(11)
Harapan Bangsa Institute of Technology (ID), Universitas Patria Artha (ID)
Industry, innovation and infrastructure
Openalex Percentile: Top 70%
Consumer Market Behavior and Pricing
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Designing Strategies for Optimal ATM Placement Location Using Geospatial Methods and Consumer Transaction Behavior — Ari Setiawan, Achmad Ramdani · Return Study of Management Economic and Bussines (2024) | TGRS Research Map | TGRS