Leveraging Business Intelligence Solutions for Urban Parking Management

, , & (2024) Leveraging Business Intelligence Solutions for Urban Parking Management. City, Culture and Society, 37, Article number: 100579.

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Description

Efficient parking management is essential for enhancing customer experience, mobility, accessibility, and overall quality of life in urban areas. In recent years, parking analytics have emerged as valuable tools for understanding drivers’ behavior and developing data-driven management strategies. However, the application of these tools is often hindered by the complexity of data extraction, transformation, loading and analysis. Additionally, the implementation of these tools can be time-consuming and costly, further limiting their practical use for operators and urban authorities. To address this issue, this paper presents the development of a Business Intelligence tool specifically designed to facilitate parking management through the automated flow of transaction data between collection, processing, and analysis systems. The tool provides easy-to-use analytical capabilities that allow parking managers to analyze parking transaction data, identify trends and patterns, and make informed decisions about parking management quickly and easily. The cost-effective implementation of this tool presents a valuable solution for managing on-street parking in urban areas. This study highlights the potential of Business Intelligence tools for parking management and contributes to improving the effectiveness of parking management.

Impact and interest:

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ID Code: 248135
Item Type: Contribution to Journal (Journal Article)
Refereed: Yes
ORCID iD:
Ahmadian, Mehdiorcid.org/0000-0002-4601-4083
Baker, Douglasorcid.org/0000-0001-8812-8567
Paz, Alexanderorcid.org/0000-0002-1217-9808
Measurements or Duration: 10 pages
Keywords: On-street parking, visualization, business intelligence, urban analytics, parking occupancy, parking transactions
DOI: 10.1016/j.ccs.2024.100579
ISSN: 1877-9166
Pure ID: 167133429
Divisions: Current > QUT Faculties and Divisions > Faculty of Engineering
Current > Schools > School of Architecture & Built Environment
Current > Schools > School of Civil & Environmental Engineering
Funding Information: This research is funded by iMOVE CRC (project 3-025) and supported by the Cooperative Research Centers program, an Australian Government initiative.
Copyright Owner: Crown 2024
Copyright Statement: This work is covered by copyright. Unless the document is being made available under a Creative Commons Licence, you must assume that re-use is limited to personal use and that permission from the copyright owner must be obtained for all other uses. If the document is available under a Creative Commons License (or other specified license) then refer to the Licence for details of permitted re-use. It is a condition of access that users recognise and abide by the legal requirements associated with these rights. If you believe that this work infringes copyright please provide details by email to qut.copyright@qut.edu.au
Deposited On: 06 Jun 2024 23:32
Last Modified: 09 Jun 2024 21:04