Igor Sáez defends his doctoral thesis on RPA adoption in the insurance sector
Igor Sáez defends his doctoral thesis on RPA adoption in the insurance sector
Igor Sáez defends his doctoral thesis on RPA adoption in the insurance sector
On Monday, 22 June, Igor Sáez, a researcher at the Faculty of Business of Mondragon Unibertsitatea, defended his doctoral thesis at the Aula Magna of the Oñati Campus. The work, entitled “Organisational and Managerial Dimensions of Robotic Process Automation Adoption in Financial Services. A Case Study in Seguros Lagun Aro”, explores the organisational and managerial dimensions involved in the implementation of Robotic Process Automation (RPA) in the financial sector, using Seguros Lagun Aro as a case study
The research, supervised by Dr. Mónica Gago García, was evaluated by Hajo Alexander Reijers (Utrecht), Adela del Río Ortega (Sevilla), and Christophe Merlo (ESTIA, France).
Regarding the content of the research, here is the thesis abstract:
Robotic Process Automation (RPA) has emerged as a leading technology within organisations’ digital transformation agendas, offering rapid efficiency gains through the automation of rule-based, high-volume operational tasks. Despite its widespread adoption and sustained growth, a substantial proportion of RPA initiatives fail to deliver sustained value or to scale successfully. Existing literature has predominantly focused on technical implementation, while offering limited insight into the organisational and managerial factors that shape sustainable RPA adoption and performance. This thesis addresses this gap by examining RPA implementation through an organisational and managerial lens, positioning RPA as a socio-technical transformation rather than a purely technical solution.
The study adopts two complementary analytical perspectives. The organisational perspective investigates the socio-human dynamics that influence RPA adoption, with particular attention to change management, user behaviour, trust, and human–robot collaboration. The managerial perspective examines process selection, performance measurement, and maintenance challenges, emphasising the growing need for data-driven and predictive approaches powered by Artificial Intelligence for better governance and decision-making.
Methodologically, the thesis follows a single-case embedded design conducted within a mature RPA environment in the financial services sector, combining qualitative and quantitative methods across four interrelated empirical studies. From an organisational standpoint, the first study employs in-depth semi-structured interviews to analyse how communication, involvement, organisational culture, strategy, and incentives act as barriers or enablers of RPA adoption for business users. The findings demonstrate that effective change management and transparent communication are critical to mitigating resistance, increasing user trust, and sustaining human–robot collaboration. The second study adopts a mixed-methods approach to examine Business Exceptions as a key point of socio-technical friction, revealing how exception frequency erodes user trust and diminishes perceived automation value, while also identifying task characteristics that significantly reduce exception risk, enabling more robust and data-driven task selection decisions.
From a managerial perspective, the third study develops machine learning models to forecast business exceptions using operational RPA log data, demonstrating that predictive analytics can substantially improve exception management and support proactive governance. The fourth study extends this data-driven approach to RPA server activity forecasting, showing that advanced machine learning models outperform traditional time-series methods and enable more effective proactive maintenance and capacity planning in dynamic automation environments.
Collectively, the thesis makes several contributions. Theoretically, it advances the understanding of RPA as a socio-technical system by integrating organisational change and managerial perspectives. Practically, it provides actionable guidance for organisations seeking to improve RPA adoption and sustainability by aligning human-centred change management with data-driven managerial decision-making.
The defence took place at 11:00 a.m. and represents a further milestone in the research activity of the Faculty of Business, which continues to strengthen its commitment to generating knowledge applied to the business and technological environment. The Faculty extends its congratulations to Igor Sáez on this achievement and wishes him every success in his future professional and research career.