Big data dimensions' contribution to competitive advantage of firms in Kenya's communication service provider industry / Lule, Alan Nsubuga

By: Contributor(s): Publication details: Nairobi Strathmore University 2016Description: ix, 65pSubject(s): LOC classification:
  • HD30.2.L85 2016
Online resources: Summary: Research 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.
Reviews from LibraryThing.com:
Tags from this library: No tags from this library for this title. Log in to add tags.
Star ratings
    Average rating: 0.0 (0 votes)
Holdings
Item type Current library Call number Status Date due Barcode Item holds
Thesis Thesis Special Collection Reference Section HD30.2.L85 2016 Not for loan 99498
Total holds: 0

Research 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.

There are no comments on this title.

to post a comment.

© Strathmore University Library Madaraka Estate Ole, Sangale Road P. O. Box 59857 00200 City Square Nairobi Kenya
Tel.: (+254) (0)703 034000/(0)703 034200/(0)703 034300 Fax.: (+254) (0)20-607498