ROBOTIC PROCESS AND ENTERPRISE PERFORMANCE: EVIDENCE FROM AN EMERGING ECONOMY
-
Oluwayomi Omotayo Olota(1*)
Department of Financial Intelligence, College of Accounting Sciences - University of South Africa
(*) Corresponding Author
Keywords:
Robotic Process, Enterprise Performance, Scalability, Accuracy of Data, Speed of Service
Abstract
The banking sector has been undergoing a broader digital revolution in recent years, including robotic process automation. Hence, this study examines the impact of the robotic processes on enterprise performance, emphasizing Access Bank of Nigeria as the study's focus. Specifically, the study examined (i) the effect of speed of service on employees' satisfaction. (ii) the influence of the accuracy of data processing on employees' work quality. (iii) the influence of scalability on employees' commitment. A descriptive research approach was adopted, and the staff of Access Bank of Nigeria served as the population. The sample size of 131, calculated through Taro Yamane's (1967) method, was used with simple random sampling to collect primary data from the respondents. A partial least squares structural equation model (PLS-SEM) was adopted to examine the causal relationship through SmartPLS 3.0. The results showed that all robotic process factors substantially predict enterprise performance; employees' satisfaction, employees' work quality, and employees' commitment all have R-squared values larger than 20%, which means that the model of robotic process (speed of service, accuracy of data processing, and scalability) accounts for a substantial amount of the volatility in these dependent variables. The study concluded that the robotic process significantly contributes to high performance in the banking industry in an emerging economy. Bank managers in emerging economies should promote scalability that may help ensure consistency in the outcome during the robotic process.
Keywords: Robotic Process; Enterprise Performance; Scalability; Accuracy of Data; Speed of Service
Downloads
Download data is not yet available.
References
Abiodun, T. O., Olusol, A. I., Oluwatoyi, O. A., Adeniran, A., Ibukun, F. O., & Temitope Gift Apata. (2025). The Role of Artificial Intelligence in Advancing Sustainable Banking and Service Efficiency in Nigerian Financial Institutions: An Assessment of Selected Quoted Banks. Journal of Sustainable Development Law and Policy (The), 16(1), 282–307. https://doi.org/10.4314/jsdlp.v16i1.15
Adwan, S., Goncharenko, G., & Liu, S. (2024). The impact of employee satisfaction on company’s labour investment efficiency. International Review of Financial Analysis, 96, 103570–103570. https://doi.org/10.1016/j.irfa.2024.103570
Aguirre, S., & Rodriguez, A. (2017). Automation of a Business Process Using Robotic Process Automation (RPA): A Case Study. Communications in Computer and Information Science, 742(1), 65–71. https://doi.org/10.1007/978-3-319-66963-2_7
Alassuli, A. (2025). Impact of artificial intelligence using the robotic process automation system on the efficiency of internal audit operations at Jordanian commercial banks. Banks and Bank Systems, 20(1), 122–135. https://doi.org/10.21511/bbs.20(1).2025.11
Asif, M., Wang, S., Shahzad, M. F., & Ashfaq, M. (2024). Data Privacy and Cybersecurity Challenges in the Digital Transformation of the Banking Sector. Computers & Security, 147(1), 104051–104051. https://doi.org/10.1016/j.cose.2024.104051
Atencio, E., Komarizadehasl, S., Lozano-Galant, J. A., & Aguilera, M. (2022). Using RPA for Performance Monitoring of Dynamic SHM Applications. Buildings, 12(8), 1140. https://doi.org/10.3390/buildings12081140
Bagherzadeh, M., Markovic, S., Cheng, J., & Vanhaverbeke, W. (2019). How Does Outside-In Open Innovation Influence Innovation Performance? Analyzing the Mediating Roles of Knowledge Sharing and Innovation Strategy. IEEE Transactions on Engineering Management, 1–14. https://doi.org/10.1109/tem.2018.2889538
Behrend, T. S., Ravid, D. M., & Rudolph, C. W. (2024). Technology and the changing nature of work. Journal of Vocational Behavior, 155, 104028. https://doi.org/10.1016/j.jvb.2024.104028
Boone, H. N., & Boone, D. A. (2012). Analyzing Likert data. Journal of Extension, 50(2), 48.
Cascio, W. F., & Montealegre, R. (2016). How technology is changing work and organizations. Annual Review of Organizational Psychology and Organizational Behavior, 3(1), 349-375. https://doi.org/10.1146/annurev-orgpsych-041015-062352
Chikte, S. D., & Deshmukh, S. D. (2022). Innovator's dilemma: To be the first or to be the best. Proceedings of the International Conference on Industrial Engineering and Operations Management, 2678-2686. https://doi.org/10.46254/eu05.20220522
Chin, W. W. (1998). The partial least squares approach to structural equation modeling. In G. A. Marcoulides (Ed.), Modern methods for business research (pp. 295-336). Lawrence Erlbaum Associates.
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum Associates.
Dhatchayani, K., Vezhaventhan, D., Sornamugi, P., T, Varsha., S, Priyadharshini., & T, Leha. (2025). Agile Decision-Making Framework using Hybrid Statistical and Predictive Models for Efficient Business Operations. 2025 6th International Conference on Mobile Computing and Sustainable Informatics (ICMCSI), 822–829. https://doi.org/10.1109/icmcsi64620.2025.10883071
Dhir, S., & Chakraborty, T. (2021). Does the perceived efficiency of the HR department matter in influencing satisfaction and employee performance? International Journal of Productivity and Performance Management, ahead-of-print(ahead-of-print). https://doi.org/10.1108/ijppm-01-2021-0047
Enriquez, J. G., Jimenez-Ramirez, A., Dominguez-Mayo, F. J., & Garcia-Garcia, J. A. (2020). Robotic Process Automation: A Scientific and Industrial Systematic Mapping Study. IEEE Access, 8, 39113–39129.
https://doi.org/10.1109/access.2020.2974934
Eulerich, M., Waddoups, N., Wagener, M., & Wood, D. A. (2023). The dark side of robotic process automation (RPA): Understanding risks and challenges with RPA. Accounting Horizons, 38(2), 1-10. https://doi.org/10.2308/horizons-2022-019
Farh, J. L., & Cheng, B. S. (1997). Modesty bias in self-rating in Taiwan: impact of item wording, modesty value, and self-esteem. Chinese Journal of Psychology.
Fernandez, D., & Aman, A. (2018). Impacts of robotic process automation on global accounting services. Asian Journal of Accounting & Governance, 9, 123-132. https://doi.org/10.17576/AJAG-2018-09-11
Field, A. (2013). Discovering statistics using IBM SPSS statistics (4th ed.). SAGE Publications.
Flechsig, C., Anslinger, F., & Lasch, R. (2021). Robotic process automation in purchasing and supply management: A multiple case study on potentials, barriers, and implementation. Journal of Purchasing and Supply Management, 28(1), 100718. https://doi.org/10.1016/j.pursup.2021.100718
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50. https://doi.org/10.1177/002224378101800104
Geyer-Klingeberg, J., Nakladal, J., Baldauf, F., & Veit, F. (2018). Process mining and robotic process automation: A perfect match. BPM (Dissertation/Demos/Industry), 2196, 124-131.
Guest, D. E. (2017). Human resource management and employee well‐being: Towards a new analytic framework. Human Resource Management Journal, 27(1), 22-38. https://doi.org/10.1111/1748-8583.12139
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (PLS-SEM) (2nd ed.). SAGE Publications.
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2-24. https://doi.org/10.1108/EBR-11-2018-0203
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115-135. https://doi.org/10.1007/s11747-014-0403-8
Hindle, J. Dr Lacity, M. Dr Willcocks, L & Dr Khan, S. (2017). Robotic Process Automation: Benchmarking the Client Experience [pdf], Robotic Process Automation Interim Executive Research Report. Available at:
https://www.blueprism.com/uploads/resources/whitepapers/BLUEPRISM_InterimReport.pdf [Accessed 6/3 2023].
Ji-fan Ren, S., Fosso Wamba, S., Akter, S., Dubey, R., & Childe, S. J. (2016). Modelling quality dynamics, business value and firm performance in a big data analytics environment. International Journal of Production Research, 55(17), 5011–5026. https://doi.org/10.1080/00207543.2016.1154209
K, Navaneetha., & Mohan, P. (2025). Technologies for Digital Disruption in Banking. South Asian Journal of Social Studies and Economics, 22(3), 22–34. https://doi.org/10.9734/sajsse/2025/v22i3966
Karvouniari, A., Karabetsos, D., Kleisiaris, C., Karavasileiadou, S., Baghdadi, N., Kyrarini, V., Kasagianni, E., Tsalkitzi, A., Malliarou, M., & Melas, C. (2024). Translation and Validation of Digital Competence Indicators in Greek for Health Professionals: A Cross-Sectional Study. Healthcare, 12.
https://doi.org/10.3390/healthcare12141370.
Klingeberg, J., Nakladal, J., Baldauf, F., & Veit, F. (2018). Process Mining and Robotic Process Automation: A Perfect Match. BPM (Dissertation/Demos/Industry), 2196, 124-131.
Kock, N., & Lynn, G. S. (2012). Lateral collinearity and misleading results in variance-based SEM: An illustration and recommendations. Journal of the Association for Information Systems, 13(7), 546-580. https://doi.org/10.17705/1jais.00302
Kollmann, T., Stöckmann, C., & Kensbock, J. M. (2017). Fear of failure as a mediator of the relationship between obstacles and nascent entrepreneurial activity—An experimental approach. Journal of Business Venturing, 32(3), 280-301. https://doi.org/10.1016/j.jbusvent.2017.02.002
Kotarba, M. (2017). Measuring digitalization–key metrics. URL: https://content. sciendo. com/downloadpdf/journals/fman/9/1/article-p123. pdf.
Kotarba, M. (2018). Digital transformation of business models. Foundations of management, 10(1), 123-142.
Lakshmi, D., Yadav, S., & Reddy, A. (2024). Robotic Process Automation in Banking for Better Customer Experience. International Research Journal on Advanced Engineering Hub (IRJAEH). https://doi.org/10.47392/irjaeh.2024.0276
Lamberton, C., Brigo, D., & Hoy, D. (2017). Impact of Robotics, RPA and AI on the insurance industry: challenges and opportunities. Journal of Financial Perspectives, 4(1).
Le Clair, C., Cullen, A., & King, M. (2017). The forrester wave™: Robotic process automation, q1 2017. Forrester Research, 770.
Li, C., Tang, J., Ma, T., Yang, X., & Luo, Y. (2020). Load balance based workflow job scheduling algorithm in distributed cloud. Journal of Network and Computer Applications, 152, 102518. https://doi.org/10.1016/j.jnca.2019.102518
Maček, A., Murg, M., & Čič, Ž. V. (2020). How robotic process automation is revolutionizing the banking sector. In Managing customer experiences in an omnichannel world: Melody of online and offline environments in the customer journey (pp. 271-286). Emerald Publishing Limited.
Marek, S. (2019). Dynamic business process management in the knowledge economy: Creating value from intellectual capital. Springer International Publishing. https://doi.org/10.1007/978-3-030-17566-8
Maslach, C., & Leiter, M. P. (2016). Understanding the burnout experience: Recent research and its implications for psychiatry. World Psychiatry, 15(2), 103-111. https://doi.org/10.1002/wps.20311
Metouol, M. Y. G. S., Ouya, S., & Mendy, G. (2023). Implementation of Robotic Process Automation To Decrease the Time Requires For KYC Onboarding Process. 2023 6th International Conference on Artificial Intelligence and Big Data (ICAIBD). https://doi.org/10.1109/icaibd57115.2023.10206136
Meyer, J. P., Bobocel, D. R., & Allen, N. J. (1991). Development of organizational commitment during the first year of employment: A longitudinal study of pre- and post-entry influences. Journal of Management, 17, 717-733
Mutenyo, J., Banga, M., Mayanja, J. B., Nakimu, R., Nsibirano, R., Massa, D., & Kalyowa, L. (2021). Determinants of enterprise performance in Uganda’s tourism sector: does gender matter. Int. J. Bus. Manag, 16(63), 10-5539.
Naqvi, A., & Munoz, J. M. (Eds.). (2020). Handbook of artificial intelligence and robotic process automation: Policy and government applications. Anthem Press.
Ng, S. C. H., Ho, G. T. S., & Wu, C. H. (2023). Blockchain-IIoT-big data aided process control and quality analytics. International Journal of Production Economics, 261, 108871. https://doi.org/10.1016/j.ijpe.2023.108871
None Abhaykumar Dalsaniya, Patel, N. K., & None Priya R Swaminarayan. (2025). Challenges and opportunities: Implementing RPA and AI in fraud detection in the banking sector. World Journal of Advanced Research and Reviews, 25(1), 296–308. https://doi.org/10.30574/wjarr.2025.25.1.0058
Oyeniyi, L. D., Ugochukwu, C. E., & Mhlongo, N. Z. (2024). Robotic process automation in routine accounting tasks: A review and efficiency analysis. World Journal of Advanced Research and Reviews, 22(1), 695–711.
https://doi.org/10.30574/wjarr.2024.22.1.1156
Patrício, L., Varela, L., & Silveira, Z. (2024). Literature review and proposal framework for assessing robotic process automation and artificial intelligence projects in healthcare services. Journal of Artificial Intelligence and Autonomous Intelligence, 1(1), 155-171. https://doi.org/10.54364/jaiai.2024.1111
Rashed, M., & Kassim, N. (2023). Factors influencing user’s intention to adopt AI-based cybersecurity systems in the UAE. Interdiscip. J. Inf. Knowl. Manag, 18, 459-486.
Ren, S. J., Fosso Wamba, S., Akter, S., Dubey, R., & Childe, S. J. (2016). Modelling quality dynamics, business value and firm performance in a big data analytics environment. International Journal of Production Research, 55(17), 5011-5026. https://doi.org/10.1080/00207543.2016.1154209
Robbins, S. P., & Judge, T. A. (2019). Organizational behaviour (18th ed.). Pearson Education.
Sabbagh, K., Friedrich, R., El-Darwiche, B., Singh, M., & Koster, A. (2013). Digitization for economic growth and job creation: Regional and industry perspectives. In S. Dutta & B. Bilbao-Osorio (Eds.), The global information technology report 2013 (pp. 35-42). World Economic Forum.
Samra, R. (2021). Robotic process automation and the power of automation in the workplace. Journal of AI, Robotics & Workplace Automation. https://doi.org/10.69554/virc1662
Sarstedt, M., Ringle, C. M., & Hair, J. F. (2017). Partial least squares structural equation modeling. In C. Homburg, M. Klarmann, & A. Vomberg (Eds.), Handbook of market research (pp. 1-40). Springer International Publishing. https://doi.org/10.1007/978-3-319-05542-8_15-1
Schueffel, P. (2017). Alternative distributed ledger technologies: Blockchain vs. Tangle vs. Hashgraph—A high-level overview and comparison. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3144241
Shet, S. V., Patil, S. V., & Chandawarkar, M. R. (2019). Competency based superior performance and organizational effectiveness. International Journal of Productivity and Performance Management, 68(4), 753–773. https://doi.org/10.1108/ijppm-03-2018-0128
Singh, S. (2003). Simple Random Sampling. , 71-136. https://doi.org/10.1007/978-94-007-0789-4_2.
Somda, M. M. Y. G., Ouya, S., & Mendy, G. (2023). Implementation of robotic process automation to decrease the time requires for KYC onboarding process. 2023 6th International Conference on Artificial Intelligence and Big Data (ICAIBD), 308-313. https://doi.org/10.1109/ICAIBD57115.2023.10206136
Szelągowski, M. (2019). Dynamic business process management. In Dynamic Business Process Management in the Knowledge Economy: Creating Value from Intellectual Capital (pp. 55-90). Cham: Springer International Publishing.
Thekkethil, M., Shukla, V., Beena, F., & Chopra, A. (2021). Robotic Process Automation in Banking and Finance Sector for Loan Processing and Fraud Detection. 2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO), 1-6.
https://doi.org/10.1109/icrito51393.2021.9596076.
Uklańska, A. (2023). Robotic process automation (RPA)–Bibliometric analysis and literature review. Foundations of management, 15(1), 129-140.
Van der Aalst, W. M., Bichler, M., & Heinzl, A. (2018). Robotic process automation. Business & information systems engineering, 60(4), 269-272.
Wenny, D. F. (2023). Strategy for Improving the Quality of Employee Work: Analysis of Training Implementation, Career Development and Team Work. Greenation International Journal of Economics and Accounting (GIJEA), 1(4), 550–559. https://doi.org/10.38035/gijea.v1i4.149
Zhu, Y. Q., & Kanjanamekanant, K. (2023). Human–bot co-working: job outcomes and employee responses. Industrial Management & Data Systems, 123(2), 515-533.
Adwan, S., Goncharenko, G., & Liu, S. (2024). The impact of employee satisfaction on company’s labour investment efficiency. International Review of Financial Analysis, 96, 103570–103570. https://doi.org/10.1016/j.irfa.2024.103570
Aguirre, S., & Rodriguez, A. (2017). Automation of a Business Process Using Robotic Process Automation (RPA): A Case Study. Communications in Computer and Information Science, 742(1), 65–71. https://doi.org/10.1007/978-3-319-66963-2_7
Alassuli, A. (2025). Impact of artificial intelligence using the robotic process automation system on the efficiency of internal audit operations at Jordanian commercial banks. Banks and Bank Systems, 20(1), 122–135. https://doi.org/10.21511/bbs.20(1).2025.11
Asif, M., Wang, S., Shahzad, M. F., & Ashfaq, M. (2024). Data Privacy and Cybersecurity Challenges in the Digital Transformation of the Banking Sector. Computers & Security, 147(1), 104051–104051. https://doi.org/10.1016/j.cose.2024.104051
Atencio, E., Komarizadehasl, S., Lozano-Galant, J. A., & Aguilera, M. (2022). Using RPA for Performance Monitoring of Dynamic SHM Applications. Buildings, 12(8), 1140. https://doi.org/10.3390/buildings12081140
Bagherzadeh, M., Markovic, S., Cheng, J., & Vanhaverbeke, W. (2019). How Does Outside-In Open Innovation Influence Innovation Performance? Analyzing the Mediating Roles of Knowledge Sharing and Innovation Strategy. IEEE Transactions on Engineering Management, 1–14. https://doi.org/10.1109/tem.2018.2889538
Behrend, T. S., Ravid, D. M., & Rudolph, C. W. (2024). Technology and the changing nature of work. Journal of Vocational Behavior, 155, 104028. https://doi.org/10.1016/j.jvb.2024.104028
Boone, H. N., & Boone, D. A. (2012). Analyzing Likert data. Journal of Extension, 50(2), 48.
Cascio, W. F., & Montealegre, R. (2016). How technology is changing work and organizations. Annual Review of Organizational Psychology and Organizational Behavior, 3(1), 349-375. https://doi.org/10.1146/annurev-orgpsych-041015-062352
Chikte, S. D., & Deshmukh, S. D. (2022). Innovator's dilemma: To be the first or to be the best. Proceedings of the International Conference on Industrial Engineering and Operations Management, 2678-2686. https://doi.org/10.46254/eu05.20220522
Chin, W. W. (1998). The partial least squares approach to structural equation modeling. In G. A. Marcoulides (Ed.), Modern methods for business research (pp. 295-336). Lawrence Erlbaum Associates.
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum Associates.
Dhatchayani, K., Vezhaventhan, D., Sornamugi, P., T, Varsha., S, Priyadharshini., & T, Leha. (2025). Agile Decision-Making Framework using Hybrid Statistical and Predictive Models for Efficient Business Operations. 2025 6th International Conference on Mobile Computing and Sustainable Informatics (ICMCSI), 822–829. https://doi.org/10.1109/icmcsi64620.2025.10883071
Dhir, S., & Chakraborty, T. (2021). Does the perceived efficiency of the HR department matter in influencing satisfaction and employee performance? International Journal of Productivity and Performance Management, ahead-of-print(ahead-of-print). https://doi.org/10.1108/ijppm-01-2021-0047
Enriquez, J. G., Jimenez-Ramirez, A., Dominguez-Mayo, F. J., & Garcia-Garcia, J. A. (2020). Robotic Process Automation: A Scientific and Industrial Systematic Mapping Study. IEEE Access, 8, 39113–39129.
https://doi.org/10.1109/access.2020.2974934
Eulerich, M., Waddoups, N., Wagener, M., & Wood, D. A. (2023). The dark side of robotic process automation (RPA): Understanding risks and challenges with RPA. Accounting Horizons, 38(2), 1-10. https://doi.org/10.2308/horizons-2022-019
Farh, J. L., & Cheng, B. S. (1997). Modesty bias in self-rating in Taiwan: impact of item wording, modesty value, and self-esteem. Chinese Journal of Psychology.
Fernandez, D., & Aman, A. (2018). Impacts of robotic process automation on global accounting services. Asian Journal of Accounting & Governance, 9, 123-132. https://doi.org/10.17576/AJAG-2018-09-11
Field, A. (2013). Discovering statistics using IBM SPSS statistics (4th ed.). SAGE Publications.
Flechsig, C., Anslinger, F., & Lasch, R. (2021). Robotic process automation in purchasing and supply management: A multiple case study on potentials, barriers, and implementation. Journal of Purchasing and Supply Management, 28(1), 100718. https://doi.org/10.1016/j.pursup.2021.100718
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50. https://doi.org/10.1177/002224378101800104
Geyer-Klingeberg, J., Nakladal, J., Baldauf, F., & Veit, F. (2018). Process mining and robotic process automation: A perfect match. BPM (Dissertation/Demos/Industry), 2196, 124-131.
Guest, D. E. (2017). Human resource management and employee well‐being: Towards a new analytic framework. Human Resource Management Journal, 27(1), 22-38. https://doi.org/10.1111/1748-8583.12139
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (PLS-SEM) (2nd ed.). SAGE Publications.
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2-24. https://doi.org/10.1108/EBR-11-2018-0203
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115-135. https://doi.org/10.1007/s11747-014-0403-8
Hindle, J. Dr Lacity, M. Dr Willcocks, L & Dr Khan, S. (2017). Robotic Process Automation: Benchmarking the Client Experience [pdf], Robotic Process Automation Interim Executive Research Report. Available at:
https://www.blueprism.com/uploads/resources/whitepapers/BLUEPRISM_InterimReport.pdf [Accessed 6/3 2023].
Ji-fan Ren, S., Fosso Wamba, S., Akter, S., Dubey, R., & Childe, S. J. (2016). Modelling quality dynamics, business value and firm performance in a big data analytics environment. International Journal of Production Research, 55(17), 5011–5026. https://doi.org/10.1080/00207543.2016.1154209
K, Navaneetha., & Mohan, P. (2025). Technologies for Digital Disruption in Banking. South Asian Journal of Social Studies and Economics, 22(3), 22–34. https://doi.org/10.9734/sajsse/2025/v22i3966
Karvouniari, A., Karabetsos, D., Kleisiaris, C., Karavasileiadou, S., Baghdadi, N., Kyrarini, V., Kasagianni, E., Tsalkitzi, A., Malliarou, M., & Melas, C. (2024). Translation and Validation of Digital Competence Indicators in Greek for Health Professionals: A Cross-Sectional Study. Healthcare, 12.
https://doi.org/10.3390/healthcare12141370.
Klingeberg, J., Nakladal, J., Baldauf, F., & Veit, F. (2018). Process Mining and Robotic Process Automation: A Perfect Match. BPM (Dissertation/Demos/Industry), 2196, 124-131.
Kock, N., & Lynn, G. S. (2012). Lateral collinearity and misleading results in variance-based SEM: An illustration and recommendations. Journal of the Association for Information Systems, 13(7), 546-580. https://doi.org/10.17705/1jais.00302
Kollmann, T., Stöckmann, C., & Kensbock, J. M. (2017). Fear of failure as a mediator of the relationship between obstacles and nascent entrepreneurial activity—An experimental approach. Journal of Business Venturing, 32(3), 280-301. https://doi.org/10.1016/j.jbusvent.2017.02.002
Kotarba, M. (2017). Measuring digitalization–key metrics. URL: https://content. sciendo. com/downloadpdf/journals/fman/9/1/article-p123. pdf.
Kotarba, M. (2018). Digital transformation of business models. Foundations of management, 10(1), 123-142.
Lakshmi, D., Yadav, S., & Reddy, A. (2024). Robotic Process Automation in Banking for Better Customer Experience. International Research Journal on Advanced Engineering Hub (IRJAEH). https://doi.org/10.47392/irjaeh.2024.0276
Lamberton, C., Brigo, D., & Hoy, D. (2017). Impact of Robotics, RPA and AI on the insurance industry: challenges and opportunities. Journal of Financial Perspectives, 4(1).
Le Clair, C., Cullen, A., & King, M. (2017). The forrester wave™: Robotic process automation, q1 2017. Forrester Research, 770.
Li, C., Tang, J., Ma, T., Yang, X., & Luo, Y. (2020). Load balance based workflow job scheduling algorithm in distributed cloud. Journal of Network and Computer Applications, 152, 102518. https://doi.org/10.1016/j.jnca.2019.102518
Maček, A., Murg, M., & Čič, Ž. V. (2020). How robotic process automation is revolutionizing the banking sector. In Managing customer experiences in an omnichannel world: Melody of online and offline environments in the customer journey (pp. 271-286). Emerald Publishing Limited.
Marek, S. (2019). Dynamic business process management in the knowledge economy: Creating value from intellectual capital. Springer International Publishing. https://doi.org/10.1007/978-3-030-17566-8
Maslach, C., & Leiter, M. P. (2016). Understanding the burnout experience: Recent research and its implications for psychiatry. World Psychiatry, 15(2), 103-111. https://doi.org/10.1002/wps.20311
Metouol, M. Y. G. S., Ouya, S., & Mendy, G. (2023). Implementation of Robotic Process Automation To Decrease the Time Requires For KYC Onboarding Process. 2023 6th International Conference on Artificial Intelligence and Big Data (ICAIBD). https://doi.org/10.1109/icaibd57115.2023.10206136
Meyer, J. P., Bobocel, D. R., & Allen, N. J. (1991). Development of organizational commitment during the first year of employment: A longitudinal study of pre- and post-entry influences. Journal of Management, 17, 717-733
Mutenyo, J., Banga, M., Mayanja, J. B., Nakimu, R., Nsibirano, R., Massa, D., & Kalyowa, L. (2021). Determinants of enterprise performance in Uganda’s tourism sector: does gender matter. Int. J. Bus. Manag, 16(63), 10-5539.
Naqvi, A., & Munoz, J. M. (Eds.). (2020). Handbook of artificial intelligence and robotic process automation: Policy and government applications. Anthem Press.
Ng, S. C. H., Ho, G. T. S., & Wu, C. H. (2023). Blockchain-IIoT-big data aided process control and quality analytics. International Journal of Production Economics, 261, 108871. https://doi.org/10.1016/j.ijpe.2023.108871
None Abhaykumar Dalsaniya, Patel, N. K., & None Priya R Swaminarayan. (2025). Challenges and opportunities: Implementing RPA and AI in fraud detection in the banking sector. World Journal of Advanced Research and Reviews, 25(1), 296–308. https://doi.org/10.30574/wjarr.2025.25.1.0058
Oyeniyi, L. D., Ugochukwu, C. E., & Mhlongo, N. Z. (2024). Robotic process automation in routine accounting tasks: A review and efficiency analysis. World Journal of Advanced Research and Reviews, 22(1), 695–711.
https://doi.org/10.30574/wjarr.2024.22.1.1156
Patrício, L., Varela, L., & Silveira, Z. (2024). Literature review and proposal framework for assessing robotic process automation and artificial intelligence projects in healthcare services. Journal of Artificial Intelligence and Autonomous Intelligence, 1(1), 155-171. https://doi.org/10.54364/jaiai.2024.1111
Rashed, M., & Kassim, N. (2023). Factors influencing user’s intention to adopt AI-based cybersecurity systems in the UAE. Interdiscip. J. Inf. Knowl. Manag, 18, 459-486.
Ren, S. J., Fosso Wamba, S., Akter, S., Dubey, R., & Childe, S. J. (2016). Modelling quality dynamics, business value and firm performance in a big data analytics environment. International Journal of Production Research, 55(17), 5011-5026. https://doi.org/10.1080/00207543.2016.1154209
Robbins, S. P., & Judge, T. A. (2019). Organizational behaviour (18th ed.). Pearson Education.
Sabbagh, K., Friedrich, R., El-Darwiche, B., Singh, M., & Koster, A. (2013). Digitization for economic growth and job creation: Regional and industry perspectives. In S. Dutta & B. Bilbao-Osorio (Eds.), The global information technology report 2013 (pp. 35-42). World Economic Forum.
Samra, R. (2021). Robotic process automation and the power of automation in the workplace. Journal of AI, Robotics & Workplace Automation. https://doi.org/10.69554/virc1662
Sarstedt, M., Ringle, C. M., & Hair, J. F. (2017). Partial least squares structural equation modeling. In C. Homburg, M. Klarmann, & A. Vomberg (Eds.), Handbook of market research (pp. 1-40). Springer International Publishing. https://doi.org/10.1007/978-3-319-05542-8_15-1
Schueffel, P. (2017). Alternative distributed ledger technologies: Blockchain vs. Tangle vs. Hashgraph—A high-level overview and comparison. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3144241
Shet, S. V., Patil, S. V., & Chandawarkar, M. R. (2019). Competency based superior performance and organizational effectiveness. International Journal of Productivity and Performance Management, 68(4), 753–773. https://doi.org/10.1108/ijppm-03-2018-0128
Singh, S. (2003). Simple Random Sampling. , 71-136. https://doi.org/10.1007/978-94-007-0789-4_2.
Somda, M. M. Y. G., Ouya, S., & Mendy, G. (2023). Implementation of robotic process automation to decrease the time requires for KYC onboarding process. 2023 6th International Conference on Artificial Intelligence and Big Data (ICAIBD), 308-313. https://doi.org/10.1109/ICAIBD57115.2023.10206136
Szelągowski, M. (2019). Dynamic business process management. In Dynamic Business Process Management in the Knowledge Economy: Creating Value from Intellectual Capital (pp. 55-90). Cham: Springer International Publishing.
Thekkethil, M., Shukla, V., Beena, F., & Chopra, A. (2021). Robotic Process Automation in Banking and Finance Sector for Loan Processing and Fraud Detection. 2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO), 1-6.
https://doi.org/10.1109/icrito51393.2021.9596076.
Uklańska, A. (2023). Robotic process automation (RPA)–Bibliometric analysis and literature review. Foundations of management, 15(1), 129-140.
Van der Aalst, W. M., Bichler, M., & Heinzl, A. (2018). Robotic process automation. Business & information systems engineering, 60(4), 269-272.
Wenny, D. F. (2023). Strategy for Improving the Quality of Employee Work: Analysis of Training Implementation, Career Development and Team Work. Greenation International Journal of Economics and Accounting (GIJEA), 1(4), 550–559. https://doi.org/10.38035/gijea.v1i4.149
Zhu, Y. Q., & Kanjanamekanant, K. (2023). Human–bot co-working: job outcomes and employee responses. Industrial Management & Data Systems, 123(2), 515-533.
Published
2026-03-01
How to Cite
Olota, O. (2026). ROBOTIC PROCESS AND ENTERPRISE PERFORMANCE: EVIDENCE FROM AN EMERGING ECONOMY. Journal of Management : Small and Medium Enterprises (SMEs), 19(1), 61-82. https://doi.org/10.35508/jom.v19i1.24644
Section
Articles
