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dc.contributor.authorMitieka, Douglas Ombati
dc.date.accessioned2020-01-23T06:35:44Z
dc.date.available2020-01-23T06:35:44Z
dc.date.issued2019
dc.identifier.urihttp://erepository.uonbi.ac.ke/handle/11295/107722
dc.description.abstractBig Data Analytics is emerging as technology that re-defines how companies compete through development of capabilities and new business models. In the era of Big Data decisions can be automated in a way that guarantees speed, quality and flexibility. Despite this rush and the push to have enterprises embrace BDA, empirical evidence shows that majority of the firms have not been successful from their BDA initiatives. Those who have built their operational capabilities by developing their organizational knowledge and skills have shown some degree of success. The study applied knowledge based view to understand how firms build their capabilities necessary to operate in the presence of Big Data. An exploratory multiple case study research was conducted to establish how Big Data is used in making operations decisions. Data was collected using semi-structured interviews as the primary method and document review as the secondary method. The findings indicate that operations capabilities, skilled workforce, team cohesion, culture and cognitive capability have a role in shaping the use of Big Data Analytics for operations decisions. Overall the results point to the significance of operational capabilities, cognitive capabilities and team cohesion in designing operations that facilitate decisions that are of high quality, adaptable and fast. Keywords: Big Data Analytics, Operations Decisions, Team Cohesion, Operations Capability, Cognitive Capability.en_US
dc.language.isoenen_US
dc.publisherUoNen_US
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
dc.titleBig Data Analytics And Operations Decisions: A Case Study Of Banks In Kenyaen_US
dc.typeThesisen_US


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Attribution-NonCommercial-NoDerivs 3.0 United States
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 United States