Big data dimensions’ contribution to competitive advantage of firms in Kenya’s Communication Service Provider industry

dc.contributor.authorNsubuga, Alan Lule
dc.descriptionA dissertation submitted for the fulfillment of the requirements for the Master of Business Administration, Strathmore Universityen_US
dc.description.abstractResearch has been done and thesis have been written in the field of competitive advantage by prominent authors such as Michael E. Porter, Allan Afuah, Douglas Laney, to name but a few, albeit nothing yet has been done to cover how the various dimensions of big data contribute to competitive advantage in Communication service provider (CSP) industry. Competitive advantage as defined by Michael E. Porter has two forms, namely, lower cost and differentiation. Competition through limit pricing in today’s competitive Kenyan market is only yielding low margin revenues and Communication service providers are keenly looking inside their organizations for new ways to differentiate themselves from their rivals. One way to gain competitive advantage, has been to utilize an already existing resource (big data) that is continually being collected in their systems. In this thesis, we evaluated how each big data dimension contributes to competitive advantage of a CSP by either bringing down cost or leading to differentiation of a CSP against its rivals. To achieve that, the study explored a couple of objectives, firstly, it determined the existence of dimensions of big data in the Communication service provider. Then, evaluated each dimension of big data and its contribution in gaining competitive advantage and finally, evaluated the benefits of big data and its analysis for CSP in Kenya. To answer the research questions that emerged from the study, a survey was carried out through oral interviews and questionnaires given to correspondents in the business analytics and finance, marketing and information technology departments of various CSPs. The data collected was then analyzed through the deployment of inferential statistics, factor analysis and principal component analysis, these methods of analysis were used to make an inference with regards to which dimension has the highest explanatory power on competitive advantage among CSPs. The study, through analysis found that volume was the big data dimension with the highest explanatory power on competitive advantage for a CSP in Kenya.en_US
dc.publisherStrathmore Universityen_US
dc.subjectData dimensionsen_US
dc.subjectCompetitive advantageen_US
dc.subjectCommunication Service Provider industryen_US
dc.titleBig data dimensions’ contribution to competitive advantage of firms in Kenya’s Communication Service Provider industryen_US