September 16, 2025 Thesis Open Access

Futasa Ermiyas

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  <identifier identifierType="DOI">10.20372/nadre:18447</identifier>
  <creators>
    <creator>
      <creatorName>Futasa Ermiyas</creatorName>
    </creator>
  </creators>
  <titles>
    <title>The Determinants of Loan Repayment Performance: Case Study of  Development Bank of Ethiopia, Nekemte District</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2025</publicationYear>
  <subjects>
    <subject>Loan Repayment Performance, Instability, Logit Model</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2025-09-16</date>
  </dates>
  <resourceType resourceTypeGeneral="Text">Thesis</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://nadre.ethernet.edu.et/record/18447</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.20372/nadre:18446</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://nadre.ethernet.edu.et/communities/ddu-business-economics</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="http://www.opendefinition.org/licenses/cc-by">Creative Commons Attribution</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;This study aims to identify the determinants of loan repayment performance in Development Bank of Ethiopia, Nekemte District western part of Ethiopia. To address the research objective, samples of 113 loans were taken from Development Bank of Ethiopia Nekemte District. Out of which 40 of them were performing and the rest 73 were non-performing loans. Stratified sampling method was used as per the indicative of the borrower&amp;rsquo;s loan status. Both primary and secondary data were used; the data gathered were analyzed using descriptive and inferential method of analysis. A descriptive statistics frequency table, t-test, chi-square test and bar graph were used and inferential statistics logistic regression (binary logit) was the particular model used to identify the determinants of the repayment performances. The logit result indicates; educational level of borrowers; credit experience of the customer, loan size permitted, equity, grace period, follow-up, weather and stability conditions determine the loan repayment performances positively and statistically significant factors. Other variable sector of the loan was negatively related and statistically significant factor affecting the loan repayment performances. The study recommends the bank to intensify its project monitoring and follow-up work in order to make responsive decisions and provide technical assistance for its financed projects, select more experienced customers/enhance the capacity of its customers through provision of continuous training, allocate sufficient loan amount up on the feasibility and increase debt-to- equity ratio. Finally, external factors such as weather and stability conditions should be under consideration in the credit policy of the bank before financing the loans to minimize risks of default&lt;/p&gt;</description>
  </descriptions>
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