JOURNAL ARTICLE

The Influence of Rotating Savings and Credit Associations Dynamics on Local Trade Flows in Dar es Salaam, Tanzania.

  • Published In: Business Management Review (BMR), 2025, v. 28, n. 2. P. 110 1 of 3

  • Database: Business Source Ultimate 2 of 3

  • Authored By: Okangi, Fred P.; Busagara, Theresia E. 3 of 3

Abstract

This study examines the influence of Rotating Savings and Credit Associations (ROSCAs) on local trade flows in Dar es Salaam, Tanzania. Using a structured questionnaire, data were gathered from 107 ROSCA members to assess three key areas: the operational dynamics of ROSCAs, the socio-economic profiles of ROSCA members, and the accessibility of financial resources among ROSCA members. The findings reveal a significant positive relationship between the effective management of ROSCAs and increased local trade flows, underscoring that well-organized associations can facilitate smoother financial transactions. Furthermore, the diverse socio-economic profiles of ROSCA members were shown to promote knowledge-sharing and networking opportunities, which correlate strongly with enhanced trade activities in the local market. Lastly, the study recommends that ROSCAs strengthen their operational frameworks by focusing on effective management practices to sustain member satisfaction and facilitate trade growth. Promoting diversity within ROSCAs is vital, as it promotes richer business interactions and opportunities. Improving financial accessibility through more flexible contribution schedules and establishing emergency funds can also significantly support local trade activities. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Business Management Review (BMR). 2025/07, Vol. 28, Issue 2, p110
  • Document Type:Article
  • Subject Area:History
  • Publication Date:2025
  • ISSN:0856-2253
  • DOI:10.56279/bmrj.v28i2.6928
  • Accession Number:191554184
  • Copyright Statement:Copyright of Business Management Review (BMR) is the property of University of Dar es Salaam, Business School and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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