4 maj 2023 presenterar doktoranden Evrim Oya Güner sitt arbete med titeln “Robotic Process Automation in Public Organizations: A Perspective of Technology as Routine Capability”. Halvtidsseminariet genomförs på Institutionen för data- och systemvetenskap (DSV) vid Stockholms universitet och kan även följas i Zoom.

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Respondent: Evrim Oya Güner, DSV
Expertgranskare: E. Burton Swanson, UCLA Anderson School of Management, USA
Interngranskare: Martin Henkel, DSV
Huvudhandledare: Shengnan Han, DSV
Handledare: Gustaf Juell-Skielse, Högskolan i Borås

Kontakta Evrim Oya Güner 

Bakgrund (på engelska)

Robotic Process Automation (hereafter RPA) is one of the technologies used to automate business processes by implementing configured software to perform the work previously done by humans (Willcocks et al., 2015). The configured software, a “software robot”, interacts with the information systems on the user interface like humans, based on pre-defined rules (Penttinen et al., 2018).

RPA is suitable for automating business processes composed of routine, repetitive, rule-based and high-volume tasks. The tasks performed by software robots include accessing management information systems, transferring and manipulating data, writing reports and sending emails (Aguirre and Rodriguez, 2017; Fernandez and Aman, 2018). Integrating artificial intelligence (AI) technologies with RPA allows more complicated tasks to be performed by software bots (Van der Aalst, 2018). For example, optical character recognition (OCR) integrated software bots can read and extract data from paper-based documents and enter them into a data processing system (Houy et al., 2019).

Both private and public organizations adopt RPA. According to Syed et al. (2020), RPA received significant attention from industries which are fast in new technology adoption with process-aware information systems, such as banking and insurance. Although the research in this field was initially performed in the private sector (i.e., Willcocks and Lacity, 2015), research in the public sector context has increased in the last few years in line with the increasing adoption of RPA among public organizations (Dias et al., 2019; Ranerup and Henriksen, 2019; 2020; Lindgren et al., 2022; Johansson and Söderström, 2022).

The literature indicates that adopting RPA improved public organizations’ practices in several ways (Güner et al., 2022). For example, Ranerup and Henriksen (2019) show that RPA-enabled decision-making practice reduced the cost of social assistance services and improved efficiency and transparency in public services. Dias et al. (2019), Denagama Vitharanage et al. (2020) and Ranerup and Henriksen (2020) reveal that transferring mundane work to RPA frees employees and provides favourable conditions to focus on more value-adding work. In addition, Lindgren (2020) argues that RPA initiatives in local government positively influence the course of digital government.

The extant literature significantly improved our knowledge of the implementations and implications of RPA (Houy et al., 2019; Ranerup and Henriksen, 2019; Lindgren et al., 2022); its stakeholders and ecosystem (Toll et al., 2022; Johansson and Söderström, 2022); its adoption (Juell-Skielse et al., 2021), and its deployment types and operating models (Asatiani et al., 2023).