Assessment of Participants’ Level of Interest in Accepting and Adopting Robotics Process Automation as a Technology Tool in the Finance and Insurance Sector: A Quantitative Correlational Study

Abstract

In the wake of the 2008 financial meltdown, financial organizations accelerated consolidation and transformation of business models in pursuit of turning the sector back to financial solvency (Paulet et al.,2015). The urgent need to transform and consolidate their position, exacerbated the rollout of new technologies which included robotic process automation. Robotic process automation offers a great and efficient way to alleviate human resource costs, other variable costs, provide reliant, consistent and responsive customer service offerings to both internal and external customers (Willcocks, Lacity, & Craig, 2017). The purpose of this study was to examine the level of interest by employees in adopting and using robotic process automation in the financial sector context. The study was conducted using the Unified Theory of Acceptance and Use of Technology (UTAUT2) framework by Vanketesh et al (2012). The UTAUT2 framework is commonly used to assess and evaluate the effects of performance and effort expectancy, social influence and facilitating conditions on the behavioral intention to use technology (Venkatesh et al., 2003). The framework’s overall fit, explanatory power, and the individual causal links it hypothesizes were evaluated by examining the acceptance of robotic process automation among employees in the financial sector. Performance expectancy, effort expectancy, social influence, and facilitating conditions were all found to be significant determinants of attitude and intention to adopt and use robotic process automation. The relatively high R-square of the model (R² = 0.78) indicating that approximately 78 percent of the variance in Behavioral Intention is explainable by Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Conditions suggests how well the model fits the observed data. An online survey collected data from 155 eligible financial sector employees from all 50 states. The response rate was 71 percent considering 63 respondents were rejected due to incomplete data, or other disqualifying factors.