Enhancing Library User Experience through Queuing Theory: A Performance Analysis of OPAC Systems

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Manisha Naidu
Vinita Dewangan

Libraries have evolved from traditional repositories of books into complex service-oriented systems that cater to diverse user needs. With the growth of digital catalogues and electronic services, ensuring efficiency in user interactions has become increasingly important. Queuing theory, a mathematical approach to analyzing waiting lines and service congestion, provides a valuable framework for understanding and optimizing library processes. This paper examines the application of queuing theory in library management systems, with a special focus on Online Public Access Catalogue (OPAC) searching. By exploring theoretical models such as M/M/1 queues, Little’s Law, and system utilization measures, the research highlights how performance indices like average waiting time, queue length, and service rate can be leveraged to improve the user experience. Through case-based illustrations, this study demonstrates how queuing models can guide decision-making in resource allocation, technological upgrades, and service delivery. The findings suggest that a systematic application of queuing principles can reduce congestion, improve user satisfaction, and ensure sustainable service delivery in modern libraries.

Enhancing Library User Experience through Queuing Theory: A Performance Analysis of OPAC Systems. (2026). International Journal of Latest Technology in Engineering Management & Applied Science, 15(5), 2629-2636. https://doi.org/10.51583/IJLTEMAS.2026.150500211

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References

Acharya, U. H., & Ravindran, G. (1999). Application of queueing theory to libraries and information centers.

Erlang, A. K. (1909). The theory of probabilities and telephone conversations.

Gross, D., & Harris, C. M. (1998). Fundamentals of queueing theory (3rd ed.). Wiley.

Kendall, D. G. (1953). Stochastic processes occurring in the theory of queues and their analysis by the method of the imbedded Markov chain. The Annals of Mathematical Statistics, 24(3), 338–354.

Little, J. D. C. (1961). A proof for the queuing formula: L = λW. Operations Research, 9(3), 383–387.

Morse, P. M. (1968). Library effectiveness: A systems approach. MIT Press.

Shanmugasundaram, S., & Umarani, P. (2015). Queueing theory applied in everyday systems.

Somvanshi, T. V. S. S., et al. (2012). Application of queueing models in library management.

Warwick, J. P. (1994). A queueing network model for book circulation. Collection Management.

Warwick, J. P. (1998). Queueing theory model for book reservations and circulation. Collection Management.

Chen Jiang, Xilin Yuan, Li Liu (2017). “Research on the Configuration Model of Circulation Service Desk in University Library.” Library and Information Service 61(20): 97-104.

Yao Cui (2013). “Research on customer queuing problems of postal agency financial business hall--Taking Fanrong Street outlets as an example.” Guangxi: Industrial Engineering, Guilin University of Electronic Technology.

Sun, Y. P. Li, G. H. Huang (2012). “A queuing-theory-based interval-fuzzy robust two-stage programming model for environmental management under uncertainty.” Engineering Optimization 44(6):707-724.

CaoNgocNguyen, SoonwookHwang, Jik-SooKim(2017). “Making a case for the on-demand multiple distributed message queue system in a Hadoop cluster.” Cluster Computing 20(3):2095–2106.

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Enhancing Library User Experience through Queuing Theory: A Performance Analysis of OPAC Systems. (2026). International Journal of Latest Technology in Engineering Management & Applied Science, 15(5), 2629-2636. https://doi.org/10.51583/IJLTEMAS.2026.150500211