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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A framework for evaluating the business deployability of digital footprint based models for consumer credit
TL;DR: In this paper , the authors developed a framework for evaluating the business deployability of digital footprint-based models in consumer credit, which is composed of the following seven criteria: 1) data accessibility, 2) data timeliness, 3) data coverage, 4) data authenticity, 5) cost of deployment, 6) interpretability and 7) compliance.
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Modeling Big Data Enablers for Service Operations Management
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Foresights for big data across industries
TL;DR: In this paper , the authors explore the potential and growth of big data across several industries between 2016 and 2020 by using Google Trends to characterize the community's interest in big data, and identify areas with the greatest potential for future big data adoption.
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The Duality of Big Data in Explaining Decision-Making Quality
Maryam Ghasemaghaei,Ofir Turel +1 more
TL;DR: In this paper , the authors examine key conditions that help translating the availability of big data into improvements in decision-making quality and hence resolve existing tensions, and show that big data is a double-edged sword that can indirectly increase and reduce decision making quality; these effects depend in part on the levels of autonomy and employee skills.
Posted ContentDOI
Stochastic Neural Networks for Automatic Cell Tracking in Microscopy Image Sequences of Bacterial Colonies
Sorena Sarmadi,James J. Winkle,Razan N. Alnahhas,Matthew R. Bennett,Krešimir Josić,Andreas Mang,Robert Azencott +6 more
TL;DR: In this paper, an approach to frame-sequence tracking of deformable-cell motion by the automated minimization of a new, specific cost functional is proposed. But this method is not suitable for the detection of cell divisions, which is handled similarly by successive minimizations of two cost functions.
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Towards a Methodology for Developing Evidence-Informed Management Knowledge by Means of Systematic Review
TL;DR: The extent to which the process of systematic review can be applied to the management field in order to produce a reliable knowledge stock and enhanced practice by developing context-sensitive research is evaluated.
Journal ArticleDOI
Towards a Methodology for Developing Evidence-Informed Management Knowledge by Means of Systematic Review
TL;DR: In this article, the authors evaluate the process of systematic review used in the medical sciences to produce a reliable knowledge stock and enhanced practice by developing context-sensitive research and highlight the challenges in developing an appropriate methodology.
Journal ArticleDOI
Business intelligence and analytics: from big data to big impact
TL;DR: This introduction to the MIS Quarterly Special Issue on Business Intelligence Research first provides a framework that identifies the evolution, applications, and emerging research areas of BI&A, and introduces and characterized the six articles that comprise this special issue in terms of the proposed BI &A research framework.
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Critical questions for big data
danah boyd,Kate Crawford +1 more
TL;DR: The era of Big Data has begun as discussed by the authors, where diverse groups argue about the potential benefits and costs of analyzing genetic sequences, social media interactions, health records, phone logs, government records, and other digital traces left by people.
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Beyond the hype
Amir H. Gandomi,Murtaza Haider +1 more
TL;DR: The need to develop appropriate and efficient analytical methods to leverage massive volumes of heterogeneous data in unstructured text, audio, and video formats is highlighted and the need to devise new tools for predictive analytics for structured big data is reinforced.