An Empirical Analysis of Queuing Model and Queuing Behaviour in Relation to Customer Satisfaction at Jkuat Students Finance Office

Sammy Kariuki Mwangi; Thomas Mageto Ombuni

doi:doi:10.11648/j.ajtas.20150404.12

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An Empirical Analysis of Queuing Model and Queuing Behaviour in Relation to Customer Satisfaction at Jkuat Students Finance Office

Sammy Kariuki Mwangi, Thomas Mageto Ombuni

Published in American Journal of Theoretical and Applied Statistics (Volume 4, Issue 4)

Received: 14 May 2015 Accepted: 25 May 2015 Published: 2 June 2015

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Abstract

Over the years, the population of the university has increased with the introduction of double intake system which in turn has led to long waiting times and long queues in students finance department, due to few service stations, inefficiencies in the payment system used and students being disorderly. To enhance service delivery, a proper queuing system is needed. This is achieved by putting in place proper measures to ensure a good flow of students at the service counters. Focusing only on the main queue we collect data and do an empirical analysis of the model in use. Using queuing theory principles and formulas the study showed that on average 22 customers arrive every hour and the service rate is 23.7 customers per hour. The system utilization factor was 92.95%, the probability of zero customers waiting 7.05; average number of customers waiting is 12.252 and average waiting time 33.415 min. The study compared the single server model against multi-server model and concluded that M/M/1 model was not the best for the Finance department. Using a questionnaire of 384 respondents, the study found out that almost all customers are not satisfied about the nature of waiting lines and some students have turned away at regular occasions due to the long queues. The time students wait to be served should not be overlooked; constant check for their changing needs and improvement in the time spent when serving them has been emphasized by the study. In today’s competitive business environment, the modern society is progressively turning into a service dominating one. Customer satisfaction and service operation capabilities have given an organization a competitive advantage in the marketplace and this has consequently led to an increasing importance in service operations management. As a result, waiting has drawn great attention to all business operation management specialists.

Published in	American Journal of Theoretical and Applied Statistics (Volume 4, Issue 4)
DOI	10.11648/j.ajtas.20150404.12
Page(s)	233-246
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2015. Published by Science Publishing Group

Keywords

Queue, Behavior, Waiting Time, Logistic Model, Customer Satisfaction

References

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[2]	Amole Bilqis Bolanle ,(2011), “Application of Queuing theory to port congestion problem in Nigeria”,European Journal of Business and Management 3 (8), 2011 www.iiste.org ISSN 2222-1905 (Paper) ISSN 2222-2839
[3]	Azmat Nafees, (June 2007), Queuing theory and its application: analysis of the sales checkout operation in Ica supermarket, Department of Economics and Society ,M. Sc., University of Dalarna, Hogloskan Dalarna, Sweden
[4]	Banks, J.Carson, Nelson, B. L., Nicol, D. M. (2001), Discrete-Event System Simulation, Prentice Hall international series, 3 rd edition, p24–37
[5]	Daisi Famule Festus (2010), “Analysis Of M/M/1 Queuing Model With Applications To Waiting Time Of Customers In Banks”, Global Journal of Computer Science and Technology, 10 (13): (Ver. 1.0).
[6]	Davis M. M, Aquilano M. J. N, Chase B. R (2003), “Fundamentals of Operations Management”, Boston: McGrawHill Irwin, Fourth Edition.
[7]	Erlang A.K. (1948), “On the rational determination of the number of circuits”. In The life and works of A.K.Erlang. Brockmeyer E., Halstrom H.L. and Jensen A., eds. Copenhagen: The Copenhagen Telephone Company.
[8]	Gregory E. Opara-Nadi,(2005), “Electronic Self-checkout System Versus Cashier Operated System: A Performance Based Comparative Analysis”,Capella University, May, 2005.
[9]	Heizer, Render, (2004), “Operations Management -Waiting-Line Models Module D,” Prentice Hall, Inc, Upper Saddle River, N.J. USA.
[10]	János Sztrik, (January , 2010), “Queuing theory and its applications, A Personal View” , International Conference on Applied Informatics, Proceedings of the 8th conference,Vol.1.pp.9–30, Eger , Hungary
[11]	J.DeLayne Stroud,(December, 2014 ) “Basic sampling Strategies:Sample vs Population data ”,http: // www. isixsigma. com/tools-templates/sampling-data/ basic-sampling-strategies-sample-vs-population-data/
[12]	Jensen, Paul A. (2004), “Queuing models,” Operations Research Models and Methods, www.me.utexas.edu/~jensen/ORMM/models/unit/queue/index.html
[13]	J.S. (1997), “Regression Models for Categorical and Limited Dependent Variables”. Thousand Oaks, CA: Sage.
[14]	Kandemir-Caues, C and Cauas, L (2007), “An Application of Queuing Theory to the Relationship between Insulin Level and Number of Insulin Receptors”, Turkish Journal of Biochemistry, 32 (1): 32-38.
[15]	Muhammad Marsudi, Hani Shafeek,(January 7 – 9, 2014) “The Application of Queuing Theory in Multi-Stage Production Line”, Proceedings of the 2014 International Conference on Industrial Engineering and Operations Management Bali, Indonesia,
[16]	Obamiro, J.K. (2003), “Application of Queuing Model in Determining the Optimum number of Service Facility in Nigerian Hospitals”, M. Sc. Project submitted to Department of Business Administration, University of Ilorin, Nigeria
[17]	Palash Sahoo, (May, 2011),” The Monitoring of The Network Traffic Based on Queuing Theory.” M.Sc., National Institute of Technology, Orissa, India.
[18]	Prabhu, N. U. (1997), Foundations of Queuing Theory. Dordecht, Netherlands: Kluwer Academic Publishers Ritchie J and Lewis J (2003), ‘QualitativeResearch Practice: A Guide for Social Science Students and Researchers’. Sage publications, London.
[19]	S cotland, R., (1991), “Customer Service: A Waiting Game”, Marketing, pp 1-3.1991
[20]	Wellington Garikai Bonga, (January 2014),” An empirical analysis of the queuing theory and customer satisfaction: application in small and medium enterprises – a Case study of croc foods restaurant.” PhD, Atlantic International University, Zimbabwe.
[21]	Zhang Laifu Joel 1 , Wei Jonathan .,Tay S. C,(2000), “Discrete– Event Simulation Of Queuing Systems”,Proceedings of the Sixth Youth Science Conference, Ministry of Education, Singapore.(2000)

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APA Style

Sammy Kariuki Mwangi, Thomas Mageto Ombuni. (2015). An Empirical Analysis of Queuing Model and Queuing Behaviour in Relation to Customer Satisfaction at Jkuat Students Finance Office. American Journal of Theoretical and Applied Statistics, 4(4), 233-246. https://doi.org/10.11648/j.ajtas.20150404.12

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ACS Style

Sammy Kariuki Mwangi; Thomas Mageto Ombuni. An Empirical Analysis of Queuing Model and Queuing Behaviour in Relation to Customer Satisfaction at Jkuat Students Finance Office. Am. J. Theor. Appl. Stat. 2015, 4(4), 233-246. doi: 10.11648/j.ajtas.20150404.12

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AMA Style

Sammy Kariuki Mwangi, Thomas Mageto Ombuni. An Empirical Analysis of Queuing Model and Queuing Behaviour in Relation to Customer Satisfaction at Jkuat Students Finance Office. Am J Theor Appl Stat. 2015;4(4):233-246. doi: 10.11648/j.ajtas.20150404.12

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@article{10.11648/j.ajtas.20150404.12,
  author = {Sammy Kariuki Mwangi and Thomas Mageto Ombuni},
  title = {An Empirical Analysis of Queuing Model and Queuing Behaviour in Relation to Customer Satisfaction at Jkuat Students Finance Office},
  journal = {American Journal of Theoretical and Applied Statistics},
  volume = {4},
  number = {4},
  pages = {233-246},
  doi = {10.11648/j.ajtas.20150404.12},
  url = {https://doi.org/10.11648/j.ajtas.20150404.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20150404.12},
  abstract = {Over the years, the population of the university has increased with the introduction of double intake system which in turn has led to long waiting times and long queues in students finance department, due to few service stations, inefficiencies in the payment system used and students being disorderly. To enhance service delivery, a proper queuing system is needed. This is achieved by putting in place proper measures to ensure a good flow of students at the service counters. Focusing only on the main queue we collect data and do an empirical analysis of the model in use. Using queuing theory principles and formulas the study showed that on average 22 customers arrive every hour and the service rate is 23.7 customers per hour. The system utilization factor was 92.95%, the probability of zero customers waiting 7.05; average number of customers waiting is 12.252 and average waiting time 33.415 min. The study compared the single server model against multi-server model and concluded that M/M/1 model was not the best for the Finance department. Using a questionnaire of 384 respondents, the study found out that almost all customers are not satisfied about the nature of waiting lines and some students have turned away at regular occasions due to the long queues. The time students wait to be served should not be overlooked; constant check for their changing needs and improvement in the time spent when serving them has been emphasized by the study. In today’s competitive business environment, the modern society is progressively turning into a service dominating one. Customer satisfaction and service operation capabilities have given an organization a competitive advantage in the marketplace and this has consequently led to an increasing importance in service operations management. As a result, waiting has drawn great attention to all business operation management specialists.},
 year = {2015}
}

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TY  - JOUR
T1  - An Empirical Analysis of Queuing Model and Queuing Behaviour in Relation to Customer Satisfaction at Jkuat Students Finance Office
AU  - Sammy Kariuki Mwangi
AU  - Thomas Mageto Ombuni
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PY  - 2015
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DO  - 10.11648/j.ajtas.20150404.12
T2  - American Journal of Theoretical and Applied Statistics
JF  - American Journal of Theoretical and Applied Statistics
JO  - American Journal of Theoretical and Applied Statistics
SP  - 233
EP  - 246
PB  - Science Publishing Group
SN  - 2326-9006
UR  - https://doi.org/10.11648/j.ajtas.20150404.12
AB  - Over the years, the population of the university has increased with the introduction of double intake system which in turn has led to long waiting times and long queues in students finance department, due to few service stations, inefficiencies in the payment system used and students being disorderly. To enhance service delivery, a proper queuing system is needed. This is achieved by putting in place proper measures to ensure a good flow of students at the service counters. Focusing only on the main queue we collect data and do an empirical analysis of the model in use. Using queuing theory principles and formulas the study showed that on average 22 customers arrive every hour and the service rate is 23.7 customers per hour. The system utilization factor was 92.95%, the probability of zero customers waiting 7.05; average number of customers waiting is 12.252 and average waiting time 33.415 min. The study compared the single server model against multi-server model and concluded that M/M/1 model was not the best for the Finance department. Using a questionnaire of 384 respondents, the study found out that almost all customers are not satisfied about the nature of waiting lines and some students have turned away at regular occasions due to the long queues. The time students wait to be served should not be overlooked; constant check for their changing needs and improvement in the time spent when serving them has been emphasized by the study. In today’s competitive business environment, the modern society is progressively turning into a service dominating one. Customer satisfaction and service operation capabilities have given an organization a competitive advantage in the marketplace and this has consequently led to an increasing importance in service operations management. As a result, waiting has drawn great attention to all business operation management specialists.
VL  - 4
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Author Information

Sammy Kariuki Mwangi

Department of Statistics and Actuarial Sciences, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya
Thomas Mageto Ombuni

Department of Statistics and Actuarial Sciences, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya

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APA Style

Sammy Kariuki Mwangi, Thomas Mageto Ombuni. (2015). An Empirical Analysis of Queuing Model and Queuing Behaviour in Relation to Customer Satisfaction at Jkuat Students Finance Office. American Journal of Theoretical and Applied Statistics, 4(4), 233-246. https://doi.org/10.11648/j.ajtas.20150404.12

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ACS Style

Sammy Kariuki Mwangi; Thomas Mageto Ombuni. An Empirical Analysis of Queuing Model and Queuing Behaviour in Relation to Customer Satisfaction at Jkuat Students Finance Office. Am. J. Theor. Appl. Stat. 2015, 4(4), 233-246. doi: 10.11648/j.ajtas.20150404.12

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AMA Style

Sammy Kariuki Mwangi, Thomas Mageto Ombuni. An Empirical Analysis of Queuing Model and Queuing Behaviour in Relation to Customer Satisfaction at Jkuat Students Finance Office. Am J Theor Appl Stat. 2015;4(4):233-246. doi: 10.11648/j.ajtas.20150404.12

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@article{10.11648/j.ajtas.20150404.12,
  author = {Sammy Kariuki Mwangi and Thomas Mageto Ombuni},
  title = {An Empirical Analysis of Queuing Model and Queuing Behaviour in Relation to Customer Satisfaction at Jkuat Students Finance Office},
  journal = {American Journal of Theoretical and Applied Statistics},
  volume = {4},
  number = {4},
  pages = {233-246},
  doi = {10.11648/j.ajtas.20150404.12},
  url = {https://doi.org/10.11648/j.ajtas.20150404.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20150404.12},
  abstract = {Over the years, the population of the university has increased with the introduction of double intake system which in turn has led to long waiting times and long queues in students finance department, due to few service stations, inefficiencies in the payment system used and students being disorderly. To enhance service delivery, a proper queuing system is needed. This is achieved by putting in place proper measures to ensure a good flow of students at the service counters. Focusing only on the main queue we collect data and do an empirical analysis of the model in use. Using queuing theory principles and formulas the study showed that on average 22 customers arrive every hour and the service rate is 23.7 customers per hour. The system utilization factor was 92.95%, the probability of zero customers waiting 7.05; average number of customers waiting is 12.252 and average waiting time 33.415 min. The study compared the single server model against multi-server model and concluded that M/M/1 model was not the best for the Finance department. Using a questionnaire of 384 respondents, the study found out that almost all customers are not satisfied about the nature of waiting lines and some students have turned away at regular occasions due to the long queues. The time students wait to be served should not be overlooked; constant check for their changing needs and improvement in the time spent when serving them has been emphasized by the study. In today’s competitive business environment, the modern society is progressively turning into a service dominating one. Customer satisfaction and service operation capabilities have given an organization a competitive advantage in the marketplace and this has consequently led to an increasing importance in service operations management. As a result, waiting has drawn great attention to all business operation management specialists.},
 year = {2015}
}

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TY  - JOUR
T1  - An Empirical Analysis of Queuing Model and Queuing Behaviour in Relation to Customer Satisfaction at Jkuat Students Finance Office
AU  - Sammy Kariuki Mwangi
AU  - Thomas Mageto Ombuni
Y1  - 2015/06/02
PY  - 2015
N1  - https://doi.org/10.11648/j.ajtas.20150404.12
DO  - 10.11648/j.ajtas.20150404.12
T2  - American Journal of Theoretical and Applied Statistics
JF  - American Journal of Theoretical and Applied Statistics
JO  - American Journal of Theoretical and Applied Statistics
SP  - 233
EP  - 246
PB  - Science Publishing Group
SN  - 2326-9006
UR  - https://doi.org/10.11648/j.ajtas.20150404.12
AB  - Over the years, the population of the university has increased with the introduction of double intake system which in turn has led to long waiting times and long queues in students finance department, due to few service stations, inefficiencies in the payment system used and students being disorderly. To enhance service delivery, a proper queuing system is needed. This is achieved by putting in place proper measures to ensure a good flow of students at the service counters. Focusing only on the main queue we collect data and do an empirical analysis of the model in use. Using queuing theory principles and formulas the study showed that on average 22 customers arrive every hour and the service rate is 23.7 customers per hour. The system utilization factor was 92.95%, the probability of zero customers waiting 7.05; average number of customers waiting is 12.252 and average waiting time 33.415 min. The study compared the single server model against multi-server model and concluded that M/M/1 model was not the best for the Finance department. Using a questionnaire of 384 respondents, the study found out that almost all customers are not satisfied about the nature of waiting lines and some students have turned away at regular occasions due to the long queues. The time students wait to be served should not be overlooked; constant check for their changing needs and improvement in the time spent when serving them has been emphasized by the study. In today’s competitive business environment, the modern society is progressively turning into a service dominating one. Customer satisfaction and service operation capabilities have given an organization a competitive advantage in the marketplace and this has consequently led to an increasing importance in service operations management. As a result, waiting has drawn great attention to all business operation management specialists.
VL  - 4
IS  - 4
ER  -

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