Correlation of Big Data with Supply Chain Health Performance in Employees of the Tehran Intelligent Fuel System

Introduction: The dramatic growth of big data and its application in preventing waste of resources and increasing financial performance and supply chain health levels, need to be examined from different perspectives. This study aimed to determine the correlation between big data and supply chain health performance in employees of Tehran Intelligent Fuel System. Methods: In this descriptive correlational study, the statistical population includes 110 employees in the Tehran Intelligent Fuel System. Considering the total statistical population, and according to Morgan's table, 86 people were included, 35 managers and 51 experts were selected. Data collection tools included: a demographic questionnaire, "Chen et al's Big Data Questionnaire" and "Kumar & Raj Supply Chain Health Performance Questionnaire". The validity of the instruments was assessed using content validity ratio, construct validity by convergent validity method, reliability by internal consistency method by calculating Cronbach's alpha coefficient, and composite reliability. Data analysis was performed in SPSS. 25, LISREL 8, and Smart PLS. 2 software. Results: The T-statistic for big data had reported being 0.776. The use of big data in supply chain decisions to the health performance of supply chain is estimated at 129.86 and the path of using big data in decision making is reported to be 0.742, which is a positive value and shows the correlation between these two variables.  Conclusions: Big data has an effective correlation with supply chain health performance. Therefore, it is suggested that the authorities include online access to data and their management analysis in the organization to improve the health performance of the supply chain.