From Counters to Self-Checkouts: A Systematic Review of Factors Affecting Operational Efficiency in Retail Automation

Abstract— The Self-Checkout System (SCS) is a key element of retail automation, designed to improve operational efficiency and enhance customer convenience. This systematic literature review synthesizes insights from 16 peer-reviewed Q1/Q2 studies published between 2020 and 2025, leading to the identification of four critical factors influencing efficiency: technological design, user behavior, organizational preparedness, and workforce impact. The findings suggest that a combination of advanced perception technologies (e.g., AI vision, depth cameras), user-centered interface design, process reengineering, and comprehensive staff training, including cross-training for hybrid support roles, plays a pivotal role in shaping outcomes. Recent research also highlights emerging adoption drivers such as reduced stigma around sensitive purchases, increased privacy awareness, and shifting dynamics of customer empowerment. Efficiency is not an inherent attribute of the system alone, but rather the result of interactions among technology, users, and institutional contexts. Retailers and policymakers are encouraged to pursue integrated design approaches that holistically align technological innovation, store operations, and human labor.

Self-Checkout Systems (SCS), Retail Automation, Operational Efficiency, Systematic Literature Review

1. M. Blut, A. Y. L. Chong, Z. Tsigna, and V. Venkatesh, “Meta-Analysis of the Unified Theory of Acceptance and Use of Technology (UTAUT): Challenging its Validity and Charting a Research Agenda in the Red Ocean,” J. Assoc. Inf. Syst., vol. 23, no. 1, pp. 13–95, 2022, doi: 10.17705/1jais.00719. [Google Scholar] [Crossref]

2. H. Lee and K. K. Leonas, “Millennials’ Intention to Use Self-Checkout Technology in Different Fashion Retail Formats: Perceived Benefits and Risks,” Cloth. Text. Res. J., vol. 39, no. 4, pp. 264–280, Oct. 2021, doi: 10.1177/0887302X20926577. [Google Scholar] [Crossref]

3. C.-H. Hsiao and K.-Y. Tang, “Key Factors in the Continuance of Self-Service Technology and Its Mobile App Adoption—A Case Study of Convenience Stores in Taiwan,” Appl. Sci., vol. 15, no. 7, p. 3804, Mar. 2025, doi: 10.3390/app15073804. [Google Scholar] [Crossref]

4. A. Darmody and D. Zwick, “Theorizing the Costs of Self-Service Technologies and Co-Creation by Design,” J. Macromarketing, vol. 44, no. 1, pp. 6–13, Mar. 2024, doi: 10.1177/02761467231202017. [Google Scholar] [Crossref]

5. C. Bascur and C. Rusu, “Customer Experience in Retail: A Systematic Literature Review,” Appl. Sci., vol. 10, no. 21, p. 7644, Oct. 2020, doi: 10.3390/app10217644. [Google Scholar] [Crossref]

6. D. Marikyan, S. Papagiannidis, and G. Stewart, “Technology acceptance research: Meta-analysis,” J. Inf. Sci., p. 01655515231191177, Aug. 2023, doi: 10.1177/01655515231191177. [Google Scholar] [Crossref]

7. A. Milella, A. Petitti, R. Marani, G. Cicirelli, and T. D’orazio, “Towards Intelligent Retail: Automated on-Shelf Availability Estimation Using a Depth Camera,” IEEE Access, vol. 8, pp. 19353–19363, 2020, doi: 10.1109/ACCESS.2020.2968175. [Google Scholar] [Crossref]

8. L. Tan, S. Liu, J. Gao, X. Liu, L. Chu, and H. Jiang, “Enhanced Self-Checkout System for Retail Based on Improved YOLOv10,” J. Imaging, vol. 10, no. 10, p. 248, Oct. 2024, doi: 10.3390/jimaging10100248. [Google Scholar] [Crossref]

9. R. Wolniak, K. Stecuła, and B. Aydın, “Digital Transformation of Grocery In-Store Shopping-Scanners, Artificial Intelligence, Augmented Reality and Beyond: A Review,” Foods, vol. 13, no. 18, p. 2948, Sep. 2024, doi: 10.3390/foods13182948. [Google Scholar] [Crossref]

10. M. Blut and C. Wang, “Technology readiness: a meta-analysis of conceptualizations of the construct and its impact on technology usage,” J. Acad. Mark. Sci., vol. 48, no. 4, pp. 649–669, Jul. 2020, doi: 10.1007/s11747-019-00680-8. [Google Scholar] [Crossref]

11. R. Cardinali, L. Lusher, R. L. C. Taylor, and S. B. Villas-Boas, “Does automation reduce stigma? The effect of self-checkout register adoption on purchasing decisions,” J. Econ. Behav. Organ., vol. 237, p. 107126, Sep. 2025, doi: 10.1016/j.jebo.2025.107126. [Google Scholar] [Crossref]

12. C. D. Schultz and F. Paetz, “The way out – Customer benefits and self-service satisfaction in cashierless shopping systems,” J. Retail. Consum. Serv., vol. 85, p. 104280, Jul. 2025, doi: 10.1016/j.jretconser.2025.104280. [Google Scholar] [Crossref]

13. P. Duarte, S. C. Silva, M. A. Linardi, and B. Novais, “Understanding the implementation of retail self-service check-out technologies using necessary condition analysis,” Int. J. Retail Distrib. Manag., vol. 50, no. 13, pp. 140–163, Dec. 2022, doi: 10.1108/IJRDM-05-2022-0164. [Google Scholar] [Crossref]

14. R. Nicholls, “‘Consumption as Work’ - Questioning the Meaning of ‘Retirement’ in the Self-Service Economy,” J. Popul. Ageing, vol. 15, no. 2, pp. 493–513, Jun. 2022, doi: 10.1007/s12062-020-09317-z. [Google Scholar] [Crossref]

15. D. Vorobeva, Y. El Fassi, D. Costa Pinto, D. Hildebrand, M. M. Herter, and A. S. Mattila, “Thinking Skills Don’t Protect Service Workers from Replacement by Artificial Intelligence,” J. Serv. Res., vol. 25, no. 4, pp. 601–613, Nov. 2022, doi: 10.1177/10946705221104312 [Google Scholar] [Crossref]

• Competency and Challenges of BTLED-ICT Students in 2D Animation: An Analytical Study
• Slope Stability Assessment: A Case Study of Embankments Along OMU-Aran-Ilorin Road, Nigeria
• Advancements in Precursors, Materials, Deposition Techniques for Thin Film Research in Electronic Devices: A Mini Review
• “Empowering Indian Women through Entrepreneurship: A Study on Kolkata”
• Impact of Mental Mathematics Proficiency on Job Performance Among Seconadry Schools Teachers in Emohua and Port Hacourt City