International Journal of Business and Economics Research
Volume 9, Issue 5, October 2020, Pages: 358-363
Received: Aug. 19, 2020;
Accepted: Sep. 1, 2020;
Published: Oct. 20, 2020
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Mohammad Asifur Rahman, Department of Information Technology, University of the Cumberlands, Williamsburg, Kentucky, USA
Atika Farzana Urmi, Department of Biostatistics, Virginia Commonwealth University, Richmond, Virginia, USA
The objective of the study was to propose a suitable probability model for supply chain management. As satisfactory service to the customers by different organization is a subject matter of supply chain management, attempt was made to observe the level of satisfaction of the customers visited the banks and mobile operators. Accordingly, data were collected from 560 customers throughout the banking hours in a day of different banks working in Bangladesh. The main questions to the customers were related to the satisfaction of the service rendered by the bank service providers and how much time the customers had to wait to get the service. A contagious probability distribution was fitted assuming the distribution of waiting time as exponential distribution with the assumption of number of customers waiting to follow the Poisson distribution. The percentage of satisfied customers with the service of the bank was 70.7. Satisfaction was noted in 55.1% visited customers of different mobile operator’s office. Level of satisfaction was significantly in declining trend with the increase in ages of the customers. This was true for both the service providing centers. Service satisfaction was in declining rate with the increase in waiting time. The sample data did not provide a suitable probability model according to the assumption.
Mohammad Asifur Rahman,
Atika Farzana Urmi,
On a Probability Distribution in Supply Chain Management, International Journal of Business and Economics Research.
Vol. 9, No. 5,
2020, pp. 358-363.
Copyright © 2020 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/
) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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