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The impact of social media on the performance of microfinance institutions in developing countries : a quantitative approach

Over the last few decades, microfinance industry has played an essential role in alleviating poverty level and helping the underprivileged, by enabling access to myriads of financial services. Statistics from the World Bank reveals that, currently, only 4% of the underprivileged were served out of the 3 billion potential clients. Such results were due to several claims, particularly the operational and financial challenges faced by the MFIs in the constant flux, inviting more attentions towards its performance. While explicit focuses were given by many researchers towards mobile banking and Information Communication Technology (ICT) and online services in improving the MFIs performance, the study on how Social Media, as a rapidly growing online phenomenon, could affect the MFIs performance remain scarce. Hence, this study was aimed at investigating and clarifying the impact of social media on MFIs, based on four dimensional performance indicators: efficiency, financial sustainability, portfolio quality, and outreach. A model was developed utilising Resource Based-View (RBV) Theory, to test the relationship between social media application and organisational performance. A quantitative approach has been adopted employing from web-based questionnaires, to collect data from MFIs employees in developing countries such as Kenya, India and Jordan. Structured Equation Modelling (SEM) technique (i.e. SPSS and AMOS 20 software) was used as a tool to analyse the responses. Results revealed a significant influence of the social media over the MFIs performance, offering valuable insights to both researchers and practitioners in the domain of micro-finance, as well as social media – conforming that the adoption of social media as marketing, advertising and communication tools could significantly improve the MFIs performance. Keywords: Microfinance, Microfinance Institution Performance, Social Media, Resource Based View Theory.

Identiferoai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:715897
Date January 2016
CreatorsDaowd, Ahmad
ContributorsEldabi, T. A. ; Kamal, M.
PublisherBrunel University
Source SetsEthos UK
Detected LanguageEnglish
TypeElectronic Thesis or Dissertation
Sourcehttp://bura.brunel.ac.uk/handle/2438/14819

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