A STUDY OF QUEUING CHARACTERISTICS IN BANK ATM: ASSESSMENT OF SERVICE RATE AND UTILIZATION RATE
Chandramani Yadav
, Dr. Meenakshi Srivastava , Shubham Kumar Sharma
Bank ATM, Little’s theorem, M/M/I queuing model, Queue, Waiting lines
Queuing is the typical practice of consumers or individuals to receive the requested service; this may be handled or dispersed one person at a time. Bank ATMs would not lose business because of lengthy lineups. Every branch of the bank originally has one ATM available. However, when clients try to use another bank's ATM after withdrawing money to use one, it defeats the purpose of having one ATM. Therefore, in order to keep clients, the service time must always be improved. We talk about the advantages of doing queuing analysis on a busy ATM as we wrap up the paper. This paper aims to show that queuing theory satisfies the model when tested with a real-case scenario. The authors obtained the data from an ATM in Agra, Uttar Pradesh to derive the arrival rate, service rate, utilization rate, waiting time in the queue, and the probability of potential customers balking. The collected data is analyzed by using Little’s Theorem and M/M/1 queuing model. The arrival rate at ATM during its busiest period of the day is 0.44 customers per minute (cpm) while the service rate is 0.64 cpm during our study period. The average number of customers in the ATM is 2.2 and the utilization period is 0.687.
"A STUDY OF QUEUING CHARACTERISTICS IN BANK ATM: ASSESSMENT OF SERVICE RATE AND UTILIZATION RATE", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.5, Issue 12, page no.308 - 311, December-2020, Available :https://ijsdr.org/papers/IJSDR2012047.pdf
Volume 5
Issue 12,
December-2020
Pages : 308 - 311
Paper Reg. ID: IJSDR_209713
Published Paper Id: IJSDR2012047
Downloads: 000347200
Research Area: Other
Country: -, -, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
