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In recent years, the robotic process automation (RPA) technology has increasingly been used to automate business processes. While a lot of research has been published on the potential and benefits of the technology, only a few studies have conducted research on challenges related to RPA adoption. Hence, this study aims to identify and discuss challenges related to RPA implementation projects.

Following an inductive methodology, interviews have been conducted with consultants who were involved in multiple RPA implementation projects. Hence, their extensive experience and views contribute to a detailed and in-depth understanding of the phenomena under research.

The results suggest that there are various process-related, technical, resource-related, psychological and coordinative challenges that must be considered when conducting an RPA implementation project.

This paper contributes to knowledge by presenting a new typology of challenges, as well as providing an in-depth discussion of the individual challenges that organizations face.

Robotic process automation (RPA) is a rapidly emerging field of computer science. It refers to the use of software robots or similar virtual assistants, which are programmed to complete repetitive and labor-intensive tasks. It has been shown that RPA offers technologically advanced solutions to businesses around the world and can cut costs, raise levels of efficiency, and improve quality. In the effort to remain competitive in the market, RPA has become a powerful and competitive tool for companies spanning a range of different industries. In this chapter, the authors’ focus is on the role of RPA in the banking sector. In this chapter author will analyze the existing scientific research in this area, with a focus on the process requirements for implementing RPA in banks, RPA vendors, and the general benefits of robotization in banking. The chapter will provide additional value through a list of suggestions for the practical use of RPA in the banking industry.

Research of currently limited literature sees Robotic Process Automation (RPA) as an important tool at the tactical level. However, the literature has not considered its potential contribution to creating competitive advantages. This paper aims to link RPA and Resource-based view (RBV) literature, proposing a conceptual framework boosting RPA research as part of an organizational AI strategy.

This study applied a Systematic Literature Review (SRL), combining bibliometrics and content analysis. This study also built a new framework based on the updated RBV model that was transformed based on the RPA literature review results.

By bridging the two bodies of literature on RBV and RPA, this study manages to show the strategic side of the technology. Therefore, this study brought to light the most updated fundamental concepts of complementarity and scale-free fungible resources from RBV theory and AI technologies, applied to the domains of RPA, information systems and information technology (IS/IT) through the development of a new theoretical lens. Also, this study was able to elaborate on a new conceptual framework for AI strategy formulation to help organizations on their journey to AI utilization.

The authors did not find any research that has shown the strategic side of RPA, nor any that has used a theoretical lens based on the RBV theory to show this side. To the best of the author’s knowledge, this study seems to be the first to make the case for RPA's strategic potential.

This paper reviews existing research to understand when, how and with what results robotic process automation (RPA) is implemented by organizations.

The authors have identified 84 sources across eight databases and have analyzed them through the lens of a context–intervention–mechanism–outcomes framework (CIMO). The CIMO analysis maps the contextual drivers, intervention approaches and value related outcomes associated with RPA implementation.

The result of the analysis is the identification of four mechanisms explaining the approach organizations take to implement RPA: digitizing business processes, performing knowledge work together with humans, replacing outsourcing with RPA robots and developing a new business model. Therefore, in this paper, in order to reduce RPA literature fragmentation, the authors take into account the digital transformation (DT) perspective, by considering RPA as one example of digital technology.

This study sensitize organizational adopters to the different mechanisms they can deploy to conduct RPA implementations to achieve different desired outcomes in response to different drivers. Moreover, having a clear picture of the key enablers and associated barriers to the realization of these alternative paths serve as a useful map to guide the implementation process.

The findings contribute to DT research by conceptualizing these mechanisms through which organizations deploy automation tools—such as RPA.

Robotic process automation (RPA) has recently emerged as a technology focusing on the automation of repetitive, frequent, voluminous and rule-based tasks. Despite a few practical examples that document successful RPA deployments in organizations, evidence of its economic benefits has been mostly anecdotal. The purpose of this paper is to present a step-by-step method to RPA investment appraisal and a business case demonstrating how the steps can be applied to practice.

The methodology relies on design science research (DSR). The step-by-step method is a design artefact that builds on the mapping of processes and modelling of the associated costs. Due to the longitudinal nature of capital investments, modelling uses discounted cashflow and present value methods. Empirical grounding characteristic to DSR is achieved by field testing the artefact.

The step-by-step method is comprised of a preparatory step, three modelling steps and a concluding step. The modelling consists of compounding the interest rate, discounting the investment costs and establishing measures for comparison. These steps were applied to seven business processes to be automated by the case company, Estate Blend. The decision to deploy RPA was found to be trivial, not only based on the initial case data, but also based on multiple sensitivity analyses that showed how resistant RPA investments are to changing circumstances.

By following the provided step-by-step method, executives and managers can quantify the costs and benefits of RPA. The developed method enables any organization to directly compare investment alternatives against each other and against the probable status quo where many tasks in organizations are still carried out manually with little to no automation.

The paper addresses a growing new domain in the field of business process management by capitalizing on DSR and modelling-based approaches to RPA investment appraisal.

Robotic Process Automation (RPA) is a digital transformation tool that demonstrated tremendous growth in research output as well as its application in the past decade. This study attempts to identify essential research gaps and proposes future research agendas in the field by analyzing publishing trends, major stakeholders (authors, countries, affiliations, journals), key clusters and evolving themes by mapping the most recent research (2016–2022) in the field.

Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) was used to retrieve a total of 244 publications from the Web of Science (WOS) database for this analysis. The study then uses the open-source R program bibliometrix to conduct bibliometric analysis. A variety of tools and methods including collaboration network, word dynamics, co-occurrence network, thematic map and strategy map were utilized.

The analysis reveals the most influential stakeholders (country: the USA, author: Arai K, affiliation: Christ Deemed University), main clusters of intellectual structure (process mining, digital transformation, blockchain, information systems) and the evolution of themes (model innovation, artificial intelligence, big-data, design science and user acceptance) in the subject.

This study uses bibliometric analysis to provide a comprehensive overview of RPA literature which unravels the conceptual structure of the stream and proposes a research agenda for the future. Based on the growth of themes and the strategy map, this study may assist entrepreneurs and practitioners in determining field priorities for strategizing process innovation.

The study aimed to examine the robotic process automation (RPA) contextual (center of excellence and scalability) and the multidisciplinary (TOE) determinants of RPA adoption in service industries in the emerging economy.

Ten factors were identified through literature surveys and popular studies grounded in technology, organization and environment. SPSS AMOS SEM is used for scale measurement and hypotheses testing. A sample of 313 respondents was collected from middle to above middle management executives of service industries from India. The authors tested the hidden layers and non-linear relationships using artificial neural network (ANN) analysis.

The low complexity, center of excellence (CoE), and industry/business partner pressure were significant to the RPA adoption in service industries in emerging economies. Counterintuitively, the scalability showed a negative influence on the RPA adoption, and the process capability did not show influence. The results of SEM and ANN were consistent.

This research can unfold the RPA adoption scholarly debate to multiple services industries beyond the telecom sector in emerging economies.

RPA is a disruptive technology on the artificial intelligence (AI) continuum. It has the potential to change the ways of working and enable technology-driven transformation. However, despite having thriving service industries that can benefit from RPA, emerging economies lag in adoption compared to the developed nations.

The RPA and automation can bring transformation to human society. Large economies such as India and China have large-scale demand for services, and the waiting lines are a common issue struggled by society. RPA can address the scalability issues of several services.

This study is among the first to examine technology-organization-environment (TOE) with RPA, including RPA contextual variables such as the CoE and scalability. Literature reports TOE applications on several emerging technologies of Industry 4.0 such as cloud, blockchain, big data and 3 Dimensional Printing (3DP), but no or little reported studies around RPA in services industries in emerging markets.

Robotic process automation (RPA) has been widely implemented to automate digital tasks. The resulting new type of human–bot co-working environment, however, has been understudied. This paper investigated how the depth and breadth of RPA deployment impact employees' job autonomy and work intensification, as well as perceived RPA performance. It further examined how job autonomy, work intensification, and perceived RPA performance predict burnout and continuance intention to use RPA.

Using data collected from online survey of 128 RPA users, whose organizations have already gone live on RPA, partial least squares is used in the validation of the conceptual model and analysis.

The analytical results indicate that RPA deployment breadth and depth affect work intensification differently, and RPA deployment breadth and depth significantly predict perceived RPA performance. While work intensification increases burnout, job autonomy alleviates the burnout of employees. Finally, job autonomy and perceived RPA performance are both positive predictors of continuance intention to use RPA.

This study contributes to the literature by investigating how co-working affects employees' autonomy and quality of work. It also advances the research on technology deployment by showing how deployment breadth and depth differently affect employees' evaluations of work-related aspects. Third, it extends the applicability of job demand-resource model into technology deployment and continuance technology use literature, by illustrating the importance of a job resource such as job autonomy. Finally, it provides firms with RPA implementation strategies.

This research investigates Hong Kong academic librarians' attitudes toward robotic process automation (RPA) and their willingness to learn this technology.

This qualitative study collected data through one-on-one semi-structured interviews conducted with video conferencing software. After participants received basic RPA information and three existing library application cases, they answered questions based on the interview guide. This research used the inductive thematic analysis method to analyze the collected data.

Regarding Hong Kong academic librarians' attitudes towards RPA, 19 themes were identified. Although all participants did not have previous knowledge of RPA, most showed positive attitudes toward implementing RPA in their libraries and some willingness to learn it. Besides, among all identified themes, negative attitudes mainly comprised “Affect” and “Cognition” factors, hindering RPA deployment in academic libraries.

This research helps librarians and RPA vendors make better decisions or strategies for implementing RPA for libraries, which has not been explored, especially in East Asia.