Leveraging data visualisation for procurement decisions: a sequential mediation model

As data volume and complexity grow in today’s business environment, data visualisation (DV) assists procurement managers in making informed decisions. However, challenges such as information overload and limited data exchange remain. This study develops a conceptual model to examine whether the sequential mediating roles of business intelligence (BI) and information management capability (IMC) strengthen the effect of DV on procurement decision making (PDM) in the construction sector. To test the relationships, a quantitative approach was adopted using a questionnaire survey. Unstandardised β-coefficients were applied to examine the sequential mediation effects. Data were collected from Iranian construction companies and analysed through AMOS, SPSS, and the PROCESS macro. The direct effects of DV on PDM, as well as on BI and IMC, were supported. BI was found to mediate the relationship between DV and PDM, while IMC alone did not, suggesting that IMC by itself may be insufficient to improve DV’s effectiveness. However, when acting together, BI and IMC sequentially mediated the DV–PDM relationship, highlighting a pathway for achieving more accurate decisions. This study contributes to the literature by integrating dynamic capability theory with a sequential mediation framework, an empirical approach not previously applied within the construction sector of emerging economies.