Integrating Artificial Intelligence and Big Data Analytics into Enhance Decision Support Systems for Hotel Revenue Management

Abstract

The hospitality industry's decision-making processes have been revolutionized by the quick adoption of artificial intelligence (AI) and big data analytics (BDA), especially in hotel revenue management. Few studies have looked at how these technological capabilities work together to improve the efficacy of Decision Support Systems (DSS), despite the increased interest in digital transformation. This study examines how AI and big data analytics capabilities affect DSS effectiveness in hospitality firms. It is based on the Resource Based View (RBV). Data was gathered from 100 hospitality professionals in management and supervisory roles in hotels that have embraced digital technologies using a quantitative explanatory research design. Multiple linear regression was used to analyze the data. The results show that DSS effectiveness is positively and considerably impacted by both AI capability and big data analytics capability. The biggest predictor was found to be Big Data Analytics Capability, suggesting that companies with superior data integration, processing, and analysis capabilities are better able to support evidence-based managerial decisions. With significant explanatory power, the model accounts for 64.2% of the variance in DSS Effectiveness. By emphasizing DSS's function as a strategic organizational mechanism that converts digital resources into managerial value, the study expands on the Resource-Based View. For hotel managers looking to improve decision quality, operational responsiveness, and revenue performance through digital transformation programs, the findings offer useful insights.