Critical analysis of Big Data challenges and analytical methods
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In this article, the authors present a state-of-the-art review that presents a holistic view of the BD challenges and BDA methods theorized/proposed/employed by organizations to help others understand this landscape with the objective of making robust investment decisions.About:
This article is published in Journal of Business Research.The article was published on 2017-01-01 and is currently open access. It has received 1267 citations till now. The article focuses on the topics: Analytics & Big data.read more
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Green innovation and organizational performance: The influence of big data and the moderating role of management commitment and HR practices
TL;DR: In this article, the authors developed and tested a holistic model that depicts and examines the relationships among green innovation, its drivers, as well as factors that help overcome the technological challenges and influence the performance and competitive advantage of the firm.
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A survey towards an integration of big data analytics to big insights for value-creation
Mandeep Kaur Saggi,Sushma Jain +1 more
TL;DR: This article presents a comprehensive, well-informed examination, and realistic analysis of deploying big data analytics successfully in companies and presents a methodical analysis for the usage of Big Data Analytics in various applications such as agriculture, healthcare, cyber security, and smart city.
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Artificial intelligence and business models in the sustainable development goals perspective: A systematic literature review
TL;DR: In this article, the authors investigated the role of Artificial Intelligence (AI) in the construction of sustainable business models (SBMs) and provided a quantitative overview of the academic literature that constitutes the field.
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Big data analytics as an operational excellence approach to enhance sustainable supply chain performance
TL;DR: In this paper, the authors used dynamic capability theory as a foundation for evaluating the role of BDA capability as an operational excellence approach in improving sustainable supply chain performance, and identified two pathways that managers can use to improve sustainable supply-chain outcomes in the mining industry based on big data analytics capabilities.
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Role of institutional pressures and resources in the adoption of big data analytics powered artificial intelligence, sustainable manufacturing practices and circular economy capabilities
TL;DR: In this article, the authors employed institutional theory and resource-based view theory to elucidate the way in which automotive firms configure tangible resources and workforce skills to drive technological enablement and improve sustainable manufacturing practices and furthermore develop circular economy capabilities.
References
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A land use/land cover change geospatial cyberinfrastructure to integrate big data and temporal topology
Jin Xing,Renee Sieber +1 more
TL;DR: A LUCC-based geospatial cyberinfrastructure (GCI) that optimizes big data handling and analysis, in this case with raster data, and builds an optimization bridge among LUCC, ST modelling, and big data.
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Reflections on Big Data: ‘Just because it is accessible does not make it ethical’
TL;DR: In this paper, a reflection on boyd and Crawford's provocation on social problems related to Big Data, especially "Just because it is accessible does not make it ethnical" is presented.
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Large, high-dimensional, heterogeneous multi-sensor data analysis approach for process yield optimization in polymer film industry
Michael Kohlert,Andreas König +1 more
TL;DR: Novelty filtering, anomaly detection, and one-class classification (OCC) methods have been in the focus of the investigation, and a first prototype of an advanced novelty detection GUI for process monitoring was conceived, which supports the process monitoring by the responsible staff.
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DEMass: a new density estimator for big data
TL;DR: This work proposes the first density estimation method, having average case sub-linear time complexity and constant space complexity in the number of instances, that stretches this fundamental limit to an extent that dealing with millions of data can now be done easily and quickly.
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Constrained pattern mining in the new era
Andreia Silva,Cláudia Antunes +1 more
TL;DR: A new framework for constrained pattern mining is proposed, that allows us to organize and analyze existing algorithms and strategies, based on the different types and properties of constraints, and on the data sources they are able to handle.