Mathematics and Computer Science

Special Issue

One and Two Levels of Trade Credit Based on Discounted Cashflow and Inventory Inaccuracy and Other Modelling Related Topics

  • Submission Deadline: May 31, 2022
  • Status: Submission Closed
  • Lead Guest Editor: Christiana Ozokeraha
About This Special Issue
Inventory is the practice of stocking goods by manufacturers, retailers and wholesalers for future sale or use while trade credit is the purchasing of items without instantaneous payment due to offer of a credit period.
Deterministic models have to do with constant and known demand also in this case shortage will not be permitted and this can be associated with low setup costs.
Many deterministic inventory models have been formulated without trade credit or with one level of trade credit. In recent times, one of the problems of industrial and agro business is financial constraints. Government at different levels has intervened to reduce this problem by establishing industrial and agricultural banks that give loans to business men and women. However, many of those who need the loans do not have the necessary collateral security which the banks often ask for and many people find it difficult to keep the terms of agreements as regards the delay in time of payment.
From literature, it was observed that trade credit becomes an easier means of overcoming this problem hence this special issue will consider recent deterministic models in inventory under one and two levels of trade credit based on discounted cashflow and inventory inaccuracy since 1989. Finally, the significance and limitations of the study will be considered.
Aims and Scope:
  1. Inventory
  2. Deterministic inventory models
  3. One level trade credit
  4. Two levels trade credit
  5. Discounted cashflow
  6. Inventory inaccuracy
Lead Guest Editor
  • Christiana Ozokeraha

    Department of Statistics, School of Applied Sciences, Delta State Polytechnic, Oghara, Nigeria

Guest Editors
  • Happiness Obiora-Ilouno

    Department of Statistics, Nnamdi Azikiwe University, Awka, Nigeria

  • Andrew Tafamel

    Department of Business Administration, Faculty of Social Sciences University of Benin, Benin, Nigeria

  • Muhammad  Kaurangini

    Department of Mathematics, Faculty of Physical Sciences University of Science and Technology, Wudil, Nigeria

  • Mfon Etuk

    Department of Mathematics, Federal Polytechnic, Bida, Nigeria

  • Lucky  Igbinosun

    Department of Mathematics, Faculty of Physical Sciences University of Uyo, Uyo, Nigeria

  • Paul Ekoko

    Department of Mathematics, Faculty of Physical Sciences, University of Benin, Benin City, Ethiopia

  • Augustine Osagiede

    Department of Mathematics, Faculty of Physical Sciences, University of Benin, Benin City, Ethiopia

  • Sani Babangida

    Department of Mathematics, Faculty of Physical Sciences, Ahmadu Bello University, Zaria, Ethiopia

  • Julian Mbegbu

    Department of Statistics, Faculty of Physical Sciences, University of Benin, Benin City, Ethiopia

  • Henrietta Ojarikre

    Department of Mathematics, Faculty of Physical Sciences, Delta State University, Abraka, Ethiopia

  • Virtue Ekhosuehi

    Department of Mathematics, Faculty of Physical Sciences, University of Benin, Benin City, Ethiopia

Published Articles
  • Knowing Ahead Mathematical Determinant of Bank Customers Credit Worthiness: A Safe Strategy for Funding Loan in a Critical Economy

    Margaret Ose Asika

    Issue: Volume 6, Issue 1, January 2021
    Pages: 16-23
    Received: Jan. 29, 2020
    Accepted: Mar. 11, 2020
    Published: Mar. 10, 2021
    DOI: 10.11648/j.mcs.20210601.13
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    Abstract: The study was carried out to identify relevant attributes that signals the capacity of borrower to pay back the loan and determine the fit of mathematical scoring model to evaluate credit worthiness of a potential borrower. The data was taken from primary and secondary sources which was through the use of questionnaires (primary source) while the s... Show More