Examining The Influence of Various Big Data Capabilities on Tourism Firms in Saudi Arabia

The Saudi Vision 2030 promotes digital transformation initiatives, which in turn drive the Big Data Analytics market. Tourism companies with their extensive digital presence, especially on social media, create and capture massive amounts of data. Big Data Analytics (BDA) is are methods that enable large-scale data sets, supporting people management decisions, and cost-effectiveness evaluation. The ability to leverage data effectively has become a key differentiator for firms seeking to enhance their decision-making processes, optimize operations, and drive innovation. To effectively leverage data, companies need a set of related capabilities such as Data-Driven (DD), Technology capability (TECH), Technical Skills (TKSL), Managerial Skills (MSKL), and Data-Driven Culture (DDC). However, the body of knowledge scares studies that assess the impact of these capabilities on firm performance, especially in the Saudi Tourism context. In response, redrawing on the RBT and social materialism theories, the current paper examines the impact of key big data capabilities—Data-Driven (DD), Technology (TECH), Technical Skills (TKSL), Managerial Skills (MSKL), and Data-Driven Culture (DDC)—on firm performance (FP) within Saudi Arabia's tourism sector. By analyzing how these factors influence the effectiveness and success of tourism organizations, the study aims to provide insights into the strategic role of possessing big data analytics capabilities in enhancing competitiveness and driving growth in this rapidly evolving industry. The current study employed a self-administered questionnaire. The variable measurements were derived from previously published studies. The researcher collected 695 responses: 220 were incomplete, and four responses were outliers. The valid responses are 471. The direct impact of DD and TECH on FP shows that DD and TECH capabilities do not directly enhance firm performance. The insignificant roles of DD and TECH may be attributed to the maturity level or implementation quality issues. The direct impact of TSKL, MSKL, and DDC on FP is statistically significant, suggesting that TSKL, MSKL, and DDC capabilities can directly enhance firm performance. Therefore, the corresponding hypotheses H3, H4, and H5 are accepted. While the hypotheses H1 and H2 related to DD and TECH are rejected. Therefore, organizations need to adopt a maturity model of various capabilities to guide the gradual development and integration of analytics capabilities. For future work, it is recommended to investigate contextual factors under which DD and TECH capabilities significantly impact FP, such as complementary capabilities, organizational culture, and analytics maturity.