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Spatial Decision Support System for Residential Solar Energy Adoption

  • Ahmed O. Alzahrani (Department of Information System and Technology, College of Computer Science and Engineering, University of Jeddah) ;
  • Hind Bitar (Department of Information Systems, King Abdulaziz University) ;
  • Abdulrahman Alzahrani (Department of Information System and Technology, College of Computer Science and Engineering, University of Jeddah) ;
  • Khalaf O. Alsalem (Department of Information System and Technology Department, Collage of Computer Science and Engineering, Jouf University)
  • Received : 2023.06.05
  • Published : 2023.06.30

Abstract

Renewable energy is not a new terminology. One of the fastest growing renewable energies is solar energy. The implementation of solar energy provides several advantages including the reduction of some of the environmental risks of fossil fuel consumption. This research elaborated the importance of the adaption of solar energy by developing a spatial decision support system (SDSS), while the Residential Solar Energy Adoption (RSEA) is an instantiation artifact in the form of an SDSS. As a GIS web-based application, RSEA allows stakeholders (e.g., utility companies, policymakers, service providers homeowners, and researchers) to navigate through locations on a map interactively. The maps highlight locations with high and low solar energy adoption potential that enables decision-makers (e.g., policymakers, solar firms, utility companies, and nonprofit organizations) to make decisions. A combined qualitative and quantitative methodological approach was used to evaluate the application's usability and user experience, and results affirmed the ability of the factors of utility, usefulness, and a positive user experience of the residential solar energy adoption of spatial decision support system (RSEA-SDSS). RSEA-SDSS in improving the decision-making process for potential various stakeholders, in utility, solar installations, policy making, and non-profit renewable energy domains.

Keywords

Acknowledgement

The authors extend their appreciation to the Deputyship for Research & innovation, Ministry of Education in Saudi Arabia for funding this research work through the project number MoE-IF-U-22-04100866-X

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