Integrating Green Logistics and Business Intelligence Models to Achieve Sustainable Development Goals
Year: 2025
Type: article
Study design: Observational Study
Abstract: This research article discusses the application of green logistics within the context of models of business intelligence (BI) as the basis for applying the Sustainable Development Goals (SDGs) within the realm of worldwide logistics firms, specifically in Jordan, Gulf countries, the UAE, Saudi Arabia, Kuwait, Qatar, and Oman.The total population surveyed comprised 368 respondents who were administered computerized online forms for administrative posts within large logistics sectors, specifically transportation, storage, and supply chain management.The application of SmartPLS 4 software was adopted to examine and validate the assumed structural equation models.In a concluding analysis, the efficient use of business intelligence software has a positive result on the application of green logistics, ensuring optimal resource management, better data-oriented decision-making, and lessened concerns with respect to the environment.The efficiency of such software leads to increased productivity, reduced expenses, reduced negative effects on the environment, and compliance with worldwide sustainability standards of sectors, with this research article providing support for models of sustainability facilitated by BI.Theoretically, this research supports further research on the relationship between digitized logistics practices and environmentally ideal behavior, providing a management perspective on application in developing models for sustainability.This research concludes that business intelligence is a significant factor within the strategic fulfillment of Sustainable Development Goals (SDGs).It provides such goals to provide intelligent, green logistical support, which improves overall organizational effectiveness alongside greater environmental accountability.
Institutions: Amman Arab University, Taibah University
Language: English
Subfield: Strategy and Management
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W7119081476