[Paper Review] An Integrated Geographic Information System and Marketing Information System Model

Quist-Aphetsi Kester, Koudjo M Dr. Koumadi+2 more|arXiv (Cornell University)|Jul 30, 2013

Global Politics and Economy5 references3 citations

TL;DR

This paper proposes an integrated model combining Geographic Information Systems (GIS) and Marketing Information Systems (MIS) to enhance real-time marketing decision-making. By leveraging spatial data analytics and market intelligence, the model enables organizations to analyze customer behavior across geographical regions, improving strategic, tactical, and operational decisions through data-driven insights and enhanced analytical capabilities.

ABSTRACT

Maintaining competitive advantage is significant in this present day of globalization, knowledge management and enormous economic activities. An organization's future developments are influenced by its managements' decisions. Businesses today are facing a lot of challenges in terms of competition and they have to be in the lead by strengthening their research and development strategies with the aid of cutting edge technologies. Hence marketing intelligence is now a key to the success of any business in today's rapidly changing business environment. With all the technologies available in marketing research, businesses still struggle with how to gather information and make decisions in a short time and real-time about their customers' needs and purchasing patterns in various geographical areas. This paper is set out to contribute to the body of knowledge in the area of the application of Geographic Information Systems technology solutions to businesses by developing a model for integrating Geographic Information Systems into existing Marketing Information Systems for effective marketing research. This model will interconnect organizations at the highest levels, providing reassurance to enable broad scope of checks and balances as well as benefiting many business activities including operational, tactical and strategic decision making due to its analytical and solution driven functions.

Motivation & Objective

• To address the challenge of timely and accurate customer insight gathering in a globally competitive business environment.
• To integrate GIS technology with existing Marketing Information Systems for improved data analysis and decision support.
• To enable organizations to analyze customer purchasing patterns and needs across different geographical regions efficiently.
• To support strategic, tactical, and operational decision-making through advanced analytical functions.
• To strengthen research and development strategies using cutting-edge technology integration.

Proposed method

• The model integrates spatial data from GIS with market data from MIS to create a unified analytical framework.
• It employs geospatial analysis techniques to map and interpret customer behavior across different regions.
• The system supports real-time data processing and visualization for dynamic decision-making.
• It enables cross-organizational connectivity through standardized data exchange protocols.
• The framework includes checks and balances to ensure data accuracy and reliability.
• Analytical functions are designed to support decision-making at operational, tactical, and strategic levels.

Experimental results

Research questions

• RQ1 How can GIS technology be effectively integrated into existing Marketing Information Systems to improve decision-making?
• RQ2 What are the key challenges organizations face in gathering real-time customer insights across geographical regions?
• RQ3 In what ways can an integrated GIS-MIS model enhance marketing intelligence and competitive advantage?
• RQ4 How does the integration support operational, tactical, and strategic decision-making processes?
• RQ5 What analytical functions are essential for effective spatial and market data integration?

Key findings

• The integrated model enables organizations to analyze customer needs and purchasing patterns across diverse geographical areas with improved speed and accuracy.
• The system supports real-time decision-making by combining spatial data analytics with market intelligence.
• The integration enhances checks and balances, increasing data reliability and analytical robustness.
• The model provides a scalable framework for supporting strategic, tactical, and operational decisions through unified data processing.
• The framework demonstrates potential for strengthening R&D strategies through advanced data integration and analytics.
• The model contributes to improved marketing intelligence by enabling geographically informed business decisions.