Assessment of Factors Influencing Intent-to-Use Big Data Analytics in an Organization: Pilot Study

Big Data Analytics is a cross-section of big data, machine learning and modeling processes of examining large data sets to uncover hidden patterns, unknown correlations, trends and useful information for decision-making. Big Data Analytics is quickly becoming a critically important driver for business success. Many organizations are increasing IT budget on Big Data Analytics capabilities. The objective of this study is to assess the factors influencing the post-adoption intent-to-use of Big Data Analytics in an organization. A survey method was used for data collection using existing validated IS instruments. A total of 34 valid observations were collected. PLS-SEM was leveraged for data analysis because of the prediction focus of the study and the requirement to assess both reflective and formative measures in the same research model. The measurement and structural models were tested using the PLS algorithm. R-2, f(2), and Q(2) were used as the basis for the acceptable fit measurement. Based on the valid structural model and after running the bootstrapping procedure, Perceived Risk has no mediating effect on Trust-in-Technology on Intent-to-Use. Perceived Usefulness has a mediating effect on Trust-in-Technology on Intent-to-Use.