Decision Framework for Engaging Cloud-Based Big Data Analytics Vendors

Emmanuel Wusuhon Yanibo Ayaburi (University of Texas Rio Grande Valley, USA), Michele Maasberg (Louisiana Tech University, USA) and Jaeung Lee (Louisiana Tech University, USA)
Copyright: © 2020 |Pages: 74
EISBN13: 9781799873907|DOI: 10.4018/JCIT.2020100104
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Abstract

Organizations face both opportunities and risks with big data analytics vendors, and the risks are now profound, as data has been likened to the oil of the digital era. The growing body of research at the nexus of big data analytics and cloud computing is examined from the economic perspective, based on agency theory (AT). A conceptual framework is developed for analyzing these opportunities and challenges regarding the use of big data analytics and cloud computing in e-business environments. This framework allows organizations to engage in contracts that target competitive parity with their service-oriented decision support system (SODSS) to achieve a competitive advantage related to their core business model. A unique contribution of this paper is its perspective on how to engage a vendor contractually to achieve this competitive advantage. The framework provides insights for a manager in selecting a vendor for cloud-based big data services.
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