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Analysis of designed and emergent consequences of mobile banking usage by SME’s in Kenya using ethnographic decision tree modeling

Includes bibliographical references. / Evaluating the impact of Information and Communications Technologies for Development (ICT4D) has been a challenge both in terms of theoretical and methodological approaches. It has been pointed out in extant literature that ICT4D impact studies are few compared to those that investigate determinants of adoption. Knowledge of this scarcity and the theoretical and methodological limitations led to the conception of this study. This study set out to investigate the decision criteria evaluated by Kenyan micro, small and medium enterprises (MSMEs) when making the initial mobile banking adoption and usage decisions with a view to unearth the designed and emergent consequences. Ethnographic decision tree modelling (EDTM) which is a cognitive research methodology was feasibly employed to obtain the adoption and usage decision criteria from which quantifiable and non-quantifiable consequences were then inferred. Structuration theory was used as a theoretical lens to view the complex context in which mobile banking is embedded and adopted by MSMEs. The analysis of the empirical data obtained from the MSMEs led to the construction and testing of three decision models from which the study’s theory was developed. The derived theory demonstrates the existence of structurational interactions among decision criteria, antecedents of technology adoption, behavioural intention to adopt, and the designed and emergent consequences of actual usage. The study further reveals that contrary to popular belief and argument that adoption of mobile banking technology lowers financial services cost, Kenyan MSMEs adopt the technology not because of its affordability but because of other factors such as perceived usefulness, accessibility, safe custody of daily income, limited organizational capabilities, perceived ease of use, social capital and trust structures. The derived explanatory-predictive theory provides findings that may have significant implications for fiscal and monetary policymakers, development experts and mobile banking technology designers.

Identiferoai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:uct/oai:localhost:11427/12865
Date January 2014
CreatorsMwangi, James Boniface
ContributorsBrown, Irwin
PublisherUniversity of Cape Town, Faculty of Commerce, Department of Information Systems
Source SetsSouth African National ETD Portal
LanguageEnglish
Detected LanguageEnglish
TypeDoctoral Thesis, Doctoral, PhD
Formatapplication/pdf

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