Big data: The next frontier for innovation, competition, and productivity

Keywords

Big data, Underpinning, Competition (biology), Productivity, Frontier

References

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Cited by

• U.S. Productivity Growth: An Optimistic PerspectiveMartin Neil Baily, James Manyika, Shalabh Gupta — 2013
• Classification Systems, their Digitization and Consequences for Data-Driven Decision Making: Understanding Representational QualityMari‐Klara Stein, Sue Newell, Robert D. Galliers — 2013
• Real-Time and Data-Driven Operation Optimization and Knowledge Discovery for an Enterprise Information SystemQing Duan — 2014
• Information technology innovation: the power and perils of big data.Souichirou Aogaki, Hideki Kotaka, Ikuo Moritani — 2015
• Big Data Analytics in HealthcareRachel Lara Cohen — 2015
• Enterprise Data Analysis and Visualization: An Interview StudyDavid S. Miall — 2012
• Recent Development in Big Data Analytics for Business Operations and Risk Management雅美 糸魚川, 保 熊本, 義晴 中林 — 2017
• Practical Use of Robot Manipulators as Intelligent Manufacturing SystemsMagali Delmas — 2018
• What Do We Know About the Stewardship GapPamela Dee Pryfogle — 2018
• An Efficient Big Data Anonymization Algorithm Based on Chaos and Perturbation Techniques公仁 川添, 清見 植屋, 和彦 中村 — 2018
• Towards a Design Model for Interdisciplinary Information Systems curriculum Development, as exemplified by Big Data Analytics EducationFrieder Jacobi, Steffen Jähn, Robert Krawatzeck — 2014
• The Current State of Business Intelligence in AcademiaBarbara H. Wixom, Thilini Ariyachandra, Michael Goul — 2011
• About Big Data and its Challenges and Benefits in ManufacturingBogdan Nedelcu — 2013
• Acceptance of Operational Business Intelligence in Organisations - Developing a framework describing the context and powers at play involved in achieving OpBI acceptance in organisationsM.H.H. Oei — 2014
• Developing Innovative Services Based on Big Data: The Case of Go:SmartLeon Michael Caesarius, Niklas Johansson — 2013
• Data Mining for Tweet Sentiment ClassificationRowdy de Groot — 2012
• High density-focused uncertainty sampling for active learning over evolving stream dataDino Ienco, Bernhard Pfahringer, Indrė Žliobaitė — 2014
• Business Analytics: Converging ExpectationsLaura Katherine Burgin — 2014
• Multi-label feature selection with application to musical instrument recognitionTrudie Sandrock — 2013
• Nonparametric Bayesian Context Learning for Buried Threat DetectionChristopher R. Ratto — 2012

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