Call for RPA Forum
Utrecht, the Netherlands, September 12 – 14, 2023
Call for Papers
Robotic Process Automation (RPA) is a maturing technology in the field of Business Process Management that enables the office automation of repetitive tasks. In essence, it relates to software agents (so-called software robots) that mimic how humans use computer applications when performing rule-based and well-structured tasks in a business process. Examples of those tasks include data transfer between applications, automated email query processing, and collation of payroll data from different sources.
However, RPA is much more than just technological innovation. It enables a digital taskforce and, what is more important, a control mechanism over it. Its objectives also extend beyond cutting costs: RPA directly addresses the digital transformation of companies by creating new value, improving the quality of services and products, reducing and controlling execution times, and improving work satisfaction by liberating employees from repetitive and tedious tasks.
At this point in time, RPA has reached a certain level of technological maturity and organizational adoption. This means that researchers now have the chance to look at RPA in a larger context. In particular, two aspects are emerging:
- Low-code automation: RPA is part of a development towards low-code automation aimed at building and automating processes with off-the-shelf software solutions that do not require extensive programming skills.
- RPA for smart automation: RPA can be combined with other technologies, such as process mining, AI, ML, OCR, or chatbots, with the goal of a more flexible, holistic process automation.
The capabilities and opportunities of RPA challenge a broad set of research communities. Computer scientists are attracted to its various technical aspects. Economists study the impact of RPA on labor and organizational effectiveness. Engineers are enabled to connect different data sources, improve the quality of the data and accelerate data analysis. RPA is particularly interesting for information systems scholars because it constitutes a technological innovation that impacts how individuals interact with software, it contributes to the digital transformation of organizations, and it has social implications since it may reduce work opportunities for those people who are carrying out simple, manual work.
This forum aims to bring together researchers from various communities and disciplines to discuss challenges, opportunities, and new ideas that relate to RPA and its application to business processes in private and public sectors. It is a unique setting where technical, business-oriented, and human-centered perspectives will come together. The forum will incorporate presentations of research papers and a panel discussion.
The forum solicits contributions related to RPA including, but not limited to, the following topics:
- Management of RPA and process automation in general, e.g., organizational expectations on RPA, RPA and digital transformation/innovation, organizational/social impact of RPA
- Technology for RPA-powered process automation, e.g., technological advances such as AI in combination with RPA, novel paradigms for employing RPA, RPA architectures and platforms
- Application of RPA-powered process automation, e.g., use cases in various industries or business functions
- Abstract submission:
May 23rd, 2023May 30th, 2023
- Paper submission:
May 30th, 2023June 6th, 2023
- Author notification:
June 30th, 2023July 8th, 2023
- Camera-ready submission:
July 14th, 2023July 18th, 2023
- Conference / RPA Forum: September 12th – 14th, 2023
Prospective authors are invited to submit original, unpublished papers on any of the topics of the forum. Papers must be written in English and must not simultaneously be submitted to another journal, conference, or workshop. We invite papers that (i) focus on technical aspects, (ii) describe new research positions or approaches (exploratory papers), or (iii) focus on evaluating existing problem situations (experience papers). The maximum length of the paper is 15 pages (including the title page, references, appendices, etc.). Shorter papers are explicitly welcomed.
Submissions must be prepared according to the format of Lecture Notes in Business Information Processing (LNBIP) specified by Springer. The title page must contain a short abstract and a list of keywords.
Papers must be submitted electronically in PDF format via the BPM 2023 EasyChair submission site (https://easychair.org/conferences/?conf=bpm2023). In order to facilitate a quick review process, authors are kindly asked to submit their (preliminary) abstract a week earlier.
Selected papers will be considered for a fast-track publication option in the EMISA Journal (https://emisa-journal.org).
RPA Forum Chairs
Ralf Plattfaut, University of Duisburg-Essen, Germany
Jana Rehse, Universität Mannheim, Germany
Simone Agostinelli, Sapienza University of Rome, Italy
Aleksandre Asatiani, University of Gothenburg, Sweden
Bernhard Axmann, Technical University of Ingolstadt
Adela del Río-Ortega, University of Seville, Spain
Carmelo Del Valle, University of Seville, Spain
Mathias Eggert, FH Aachen, Germany
Carsten Feldmann, FH Münster University of Applied Sciences, Germany
Peter Fettke, German Research Center for Artificial Intelligence (DFKI), and Saarland University, Germany
Christian Flechsig, Technische Universität Dresden, Germany
Norbert Frick, Hochschule der Deutschen Bundesbank, Germany
José González Enríquez, University of Seville, Spain
Lukas-Valentin Herm, Julius-Maximilians-Universität Würzburg, Germany
Hannu Jaakkola, University of Tampere, Finland
Christian Janiesch, TU Dortmund University, Germany
Andrés Jiménez Ramírez, University of Seville, Spain
Fabrizio Maria Maggi, Free University of Bozen-Bolzano, Italy
Andrea Marrella, Sapienza University of Rome
Massimo Mecella, Sapienza University of Rome, Italy
Dan O’Leary, University of Southern California, USA
Teijo Peltoniemi, University of Turku, Finland
Yara Rizk, IBM Research, USA
Rehan Syed, Queensland University of Technology, Australia
Maximilian Völker, Hasso Plattner Institut, Germany
Moe Wynn, Queensland University of Technology, Australia